diff --git a/.readthedocs.yaml b/.readthedocs.yaml deleted file mode 100644 index 008aa7131..000000000 --- a/.readthedocs.yaml +++ /dev/null @@ -1,22 +0,0 @@ -# .readthedocs.yaml -# Read the Docs configuration file -# See https://docs.readthedocs.io/en/stable/config-file/v2.html for details - -# Required -version: 2 - -# Set the version of Python and other tools you might need -build: - os: ubuntu-22.04 - tools: - python: "3.10" - -sphinx: - configuration: docs/conf.py - -# Optionally declare the Python requirements required to build your docs -python: - install: - - requirements: docs/requirements.txt - - method: pip - path: . diff --git a/docs/.gitignore b/docs/.gitignore new file mode 100755 index 000000000..a68ef36f3 --- /dev/null +++ b/docs/.gitignore @@ -0,0 +1,25 @@ +# Dependencies +/node_modules + +# Production +/build + +# Generated files +.docusaurus +.cache-loader + +# Misc +.DS_Store +.env.local +.env.development.local +.env.test.local +.env.production.local + +npm-debug.log* +yarn-debug.log* +yarn-error.log* + +.idea +/bk + +.history \ No newline at end of file diff --git a/docs/Dockerfile b/docs/Dockerfile new file mode 100644 index 000000000..497b7773d --- /dev/null +++ b/docs/Dockerfile @@ -0,0 +1,12 @@ +FROM node:lts + +WORKDIR /app +COPY . /app + +RUN yarn install + +RUN npm run build + +EXPOSE 3000 + +CMD ["npm", "run", "serve"] diff --git a/docs/Makefile b/docs/Makefile deleted file mode 100644 index d4bb2cbb9..000000000 --- a/docs/Makefile +++ /dev/null @@ -1,20 +0,0 @@ -# Minimal makefile for Sphinx documentation -# - -# You can set these variables from the command line, and also -# from the environment for the first two. -SPHINXOPTS ?= -SPHINXBUILD ?= sphinx-build -SOURCEDIR = . -BUILDDIR = _build - -# Put it first so that "make" without argument is like "make help". -help: - @$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) - -.PHONY: help Makefile - -# Catch-all target: route all unknown targets to Sphinx using the new -# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS). -%: Makefile - @$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) diff --git a/docs/README.md b/docs/README.md new file mode 100755 index 000000000..a62857666 --- /dev/null +++ b/docs/README.md @@ -0,0 +1,25 @@ +# DB-GPT Website + +## Quick Start + +### Install dependencies +- Clone current project firstly! +- Install docusaurus dependencies, generate node_modules folder. + +``` +sudo yarn install +``` + +### launch +``` +yarn start +``` + +The default service starts on port `3000`, visit `localhost:3000` + +## Docker development + +```commandline +docker build -t dbgptweb . +docker run --restart=unless-stopped -d -p 3000:3000 dbgptweb +``` diff --git a/docs/_static/css/custom.css b/docs/_static/css/custom.css deleted file mode 100644 index f3bcfe7b5..000000000 --- a/docs/_static/css/custom.css +++ /dev/null @@ -1,928 +0,0 @@ -/* override default colors used in the Sphinx theme */ -:root { - --tabs-color-label-active: #0475DE; - --tabs-color-label-hover: #0475DE; - --buttons-color-blue: #0475DE; - --tabs-color-label-inactive: #9E9E9E; - --tabs-color-overline: #e0e0e0; - --tabs-color-underline: #e0e0e0; - --border-color-gray: #e0e0e0; - --background-color-light-gray:#fafafa; - --background-color-disabled: #9E9E9E; - --pst-color-link: 4, 117, 222; - --pst-color-primary: 4, 117, 222; - --pst-color-text-secondary: #616161; - --blue: #0475DE; - --sidebar-top: 5em; -} - -/* Remove flicker for announcement top bar replacement */ -.header-item.announcement { - background-color: white; - color: white; - padding: 0; -} - -/* Make the book theme secondary nav stick below the new main top nav */ -.header-article { - top: 58px; - z-index: 900 !important; -} - -.toctree-l1.has-children { - font-weight: bold; -} - -.toctree-l2 { - font-weight: normal; -} - -div.navbar-brand-box { - padding-top: 4em; -} - -td p { - margin-left: 0.75rem; -} - -table.longtable.table.autosummary { - table-layout: fixed; -} - -.table.autosummary td { - width: 100%; -} - -tr.row-odd { - background-color: #f9fafb; -} - -/* For Algolia search box - * overflow-y: to flow-over horizontally into main content - * height: to prevent topbar overlap -*/ -#site-navigation { - overflow-y: auto; - height: calc(100vh - var(--sidebar-top)); - position: sticky; - top: var(--sidebar-top) !important; -} - -/* Center the algolia search bar*/ -#search-input { - text-align: center; -} -.algolia-autocomplete { - width: 100%; - margin: auto; -} - -/* Hide confusing "<-" back arrow in navigation for larger displays */ -@media (min-width: 768px) { - #navbar-toggler { - display: none; - } -} - -/* Make navigation scrollable on mobile, by making algolia not overflow */ -@media (max-width: 768px) { - #site-navigation { - overflow-y: scroll; - } - - .algolia-autocomplete .ds-dropdown-menu{ - min-width: 250px; - } -} - -/* sphinx-panels overrides the content width to 1140 for large displays.*/ -@media (min-width: 1200px) { - .container, .container-lg, .container-md, .container-sm, .container-xl { - max-width: 1400px !important; - } -} - -.bottom-right-promo-banner { - position: fixed; - bottom: 100px; - right: 20px; - width: 270px; -} - -@media (max-width: 1500px) { - .bottom-right-promo-banner { - display: none; - } -} - -@media screen and (max-width: 767px) { - .remove-mobile { - display: none; - } - } - - @media screen and (max-width: 767px) { - .row-2-column { - flex-direction: column; - margin-top: 20px; - } - } - -/* Make Algolia search box scrollable */ -.algolia-autocomplete .ds-dropdown-menu { - height: 60vh !important; - overflow-y: scroll !important; -} - -.bd-sidebar__content { - overflow-y: unset !important; -} - -.bd-sidebar__top { - display: flex; - flex-direction: column; -} - -.bd-sidebar li { - position: relative; - word-wrap: break-word; -} - -nav.bd-links { - flex: 1; -} - -nav.bd-links::-webkit-scrollbar-thumb { - background-color: #ccc; -} - -nav.bd-links::-webkit-scrollbar { - width: 5px; -} - -dt:target, span.highlighted { - background-color: white; -} - -div.sphx-glr-bigcontainer { - display: inline-block; - width: 100%; -} - -td.tune-colab, -th.tune-colab { - border: 1px solid #dddddd; - text-align: left; - padding: 8px; -} - -/* Adjustment to Sphinx Book Theme */ -.table td { - /* Remove row spacing on the left */ - padding-left: 0; -} - -.table thead th { - /* Remove row spacing on the left */ - padding-left: 0; -} - -img.inline-figure { - /* Override the display: block for img */ - display: inherit !important; -} - -#version-warning-banner { - /* Make version warning clickable */ - z-index: 1; - margin-left: 0; - /* 20% is for ToC rightbar */ - /* 2 * 1.5625em is for horizontal margins */ - width: calc(100% - 20% - 2 * 1.5625em); -} - -/* allow scrollable images */ -.figure { - max-width: 100%; - overflow-x: auto; -} -img.horizontal-scroll { - max-width: none; -} - -.clear-both { - clear: both; - min-height: 100px; - margin-top: 15px; -} - -.buttons-float-left { - width: 150px; - float: left; -} - -.buttons-float-right { - width: 150px; - float: right; -} - -.card-body { - padding: 0.5rem !important; -} - -/* custom css for pre elements */ -pre { - /* Wrap code blocks instead of horizontal scrolling. */ - white-space: pre-wrap; - box-shadow: none; - border-color: var(--border-color-gray); - background-color: var(--background-color-light-gray); - border-radius:0.25em; -} - -/* notebook formatting */ -.cell .cell_output { - max-height: 250px; - overflow-y: auto; - font-weight: bold; -} - -/* Yellow doesn't render well on light background */ -.cell .cell_output pre .-Color-Yellow { - color: #785840; -} - -/* Newlines (\a) and spaces (\20) before each parameter */ -.sig-param::before { - content: "\a\20\20\20\20"; - white-space: pre; -} - -/* custom css for outlined buttons */ -.btn-outline-info:hover span, .btn-outline-primary:hover span { - color: #fff; -} - -.btn-outline-info, .btn-outline-primary{ - border-color: var(--buttons-color-blue); -} - -.btn-outline-info:hover, .btn-outline-primary:hover{ - border-color: var(--buttons-color-blue); - background-color: var(--buttons-color-blue); -} - -.btn-outline-info.active:not(:disabled):not(.disabled), .btn-outline-info:not(:disabled):not(.disabled):active, .show>.btn-outline-info.dropdown-toggle { - border-color: var(--buttons-color-blue); - background-color: var(--buttons-color-blue); - color: #fff; -} - -.btn-info, .btn-info:hover, .btn-info:focus { - border-color: var(--buttons-color-blue); - background-color: var(--buttons-color-blue); -} - -.btn-info:hover{ - opacity: 90%; -} - -.btn-info:disabled{ - border-color: var(--background-color-disabled); - background-color: var(--background-color-disabled); - opacity: 100%; -} - -.btn-info.active:not(:disabled):not(.disabled), .btn-info:not(:disabled):not(.disabled):active, .show>.btn-info.dropdown-toggle { - border-color: var(--buttons-color-blue); - background-color: var(--buttons-color-blue); -} - - -.topnav { - background-color: white; - border-bottom: 1px solid rgba(0, 0, 0, .1); - display: flex; - align-items: center; -} - -/* Content wrapper for the unified nav link / menus */ -.top-nav-content { - max-width: 1400px; - width: 100%; - margin-left: auto; - margin-right: auto; - padding: 0 1.5rem; - display: flex; - align-items: center; - justify-content: space-between; -} - -@media (max-width: 900px) { - /* If the window is too small, hide the custom sticky navigation bar at the top of the page. - Also make the pydata-sphinx-theme nav bar, which usually sits below the top nav bar, stick - to the top of the page. - */ - .top-nav-content { - display: none; - } - div.header-article.row.sticky-top.noprint { - position: sticky; - top: 0; - } -} - -/* Styling the links and menus in the top nav */ -.top-nav-content a { - text-decoration: none; - color: black; - font-size: 17px; -} - -.top-nav-content a:hover { - color: #007bff; -} - -/* The left part are the links and menus */ -.top-nav-content > .left { - display: flex; - white-space: nowrap; -} - -.top-nav-content .left > * { - margin-right: 8px; -} - -.top-nav-content .left > a, -.top-nav-content .left > .menu > a { - text-align: center; - padding: 14px 16px; - border-bottom: 2px solid white; -} - -.top-nav-content .menu:hover > a, -.top-nav-content .left > a:hover { - border-bottom: 2px solid #007bff; -} - -/* Special styling for the Ray logo */ -.top-nav-content .left > a.ray-logo { - width: 90px; - padding: 10px 0; -} -.top-nav-content .left > a.ray-logo:hover { - border-bottom: 2px solid white; -} - -/* Styling the dropdown menus */ -.top-nav-content .menu { - display: flex; -} -.top-nav-content .menu > a > .down-caret { - margin-left: 8px; -} -.top-nav-content .menu > ul { - display: none; -} - -.top-nav-content > button.try-anyscale > span { - margin: 0 12px; -} - -.top-nav-content .menu:hover > ul { - display: flex; - flex-direction: column; - align-items: flex-start; - box-shadow: 0 5px 15px 0 rgb(0 0 0 / 10%); - padding: 15px; - width: 330px; - position: absolute; - z-index: 2000; - background-color: white; - top: 58px; -} - -.top-nav-content .menu:hover > ul > li { - list-style: none; - padding: 5px 0; -} - -.top-nav-content .menu:hover > ul > li span { - display: block; -} - -.top-nav-content .menu:hover > ul > li span.secondary { - color: #787878; -} - -/* Styling the "Try Anyscale" button */ -.top-nav-content > button.try-anyscale { - float: right; - border-radius: 6px; - background-color: #e7f2fa; - padding-left: 12px; - padding-right: 12px; - margin-left: 12px; - height: 40px; - border: none; - white-space: nowrap; -} - -@media (max-width: 1000px) { - .top-nav-content > button.try-anyscale { - display: none; - } -} - -/* custom css for tabs*/ -.tabbed-set>label,.tabbed-set>label:hover { - border-bottom: 1px solid var(--border-color-gray); - color:var(--tabs-color-label-inactive); - font-weight: 500; -} - -.tabbed-set>input:checked+label{ - border-bottom: 0.125em solid; - color:var(--tabs-color-label-active); -} - - -.tabbed-label{ - margin-bottom:0; -} - -/* custom css for jupyter cells */ -div.cell div.cell_input{ - border: 1px var(--border-color-gray) solid; - background-color: var(--background-color-light-gray); - border-radius:0.25em; - border-left-color: var(--green); - border-left-width: medium; -} - -/* custom css for table */ -table { - border-color: var(--border-color-gray); -} - -/* custom css for topic component */ -div.topic{ - border: 1px solid var(--border-color-gray); - border-radius:0.25em; -} - -.topic { - background-color: var(--background-color-light-gray); -} - -/* custom css for card component */ -.card{ - border-color: var(--border-color-gray); -} - -.card-footer{ - background-color: var(--background-color-light-gray); - border-top-color: var(--border-color-gray); -} - -/* custom css for section navigation component */ -.bd-toc nav>.nav { - border-left-color: var(--border-color-gray); -} - -/* custom css for up and down arrows in collapsible cards */ -details.dropdown .summary-up, details.dropdown .summary-down { - top: 1em; -} - -/* remove focus border in collapsible admonition buttons */ -.toggle.admonition button.toggle-button:focus { - outline: none; -} - -/* custom css for shadow class */ -.shadow { - box-shadow: 0 0.2rem 0.5rem rgb(0 0 0 / 5%), 0 0 0.0625rem rgb(0 0 0 / 10%) !important; -} - -/* custom css for text area */ -textarea { - border-color: var(--border-color-gray); -} - -/* custom css for footer */ -footer { - margin-top: 1rem; - padding:1em 0; - border-top-color: var(--border-color-gray); -} - -.footer p{ - color: var(--pst-color-text-secondary); -} - -/* Make the hover color of tag/gallery buttons differ from "active" */ -.tag.btn-outline-primary:hover { - background-color: rgba(20, 99, 208, 0.62) !important; -} - -span.rst-current-version > span.fa.fa-book { - /* Move the book icon away from the top right - * corner of the version flyout menu */ - margin: 10px 0px 0px 5px; -} - - -/*Extends the docstring signature box.*/ -.rst-content dl:not(.docutils) dt { - display: block; - padding: 10px; - word-wrap: break-word; - padding-right: 100px; -} - -/*Lists in an admonition note do not have awkward whitespace below.*/ -.rst-content .admonition-note .section ul { - margin-bottom: 0; -} - -/*Properties become blue (classmethod, staticmethod, property)*/ -.rst-content dl dt em.property { - color: #2980b9; - text-transform: uppercase; -} - -.rst-content .section ol p, -.rst-content .section ul p { - margin-bottom: 0; -} - - -/* Adjustment to Version block */ -.rst-versions { - z-index: 1200 !important; -} - -.image-header { - display: flex; - flex-direction: row; - align-items: center; - padding-left: 16px; - padding-right:16px; - gap: 16px; -} - -.info-box { - box-shadow: 0px 4px 20px rgba(0, 0, 0, 0.05); - border-radius: 8px; - padding: 20px; -} - -.info-box:hover{ - box-shadow: 0px 4px 20px rgba(0, 0, 0, 0.1); -} - -.no-underline{ - text-decoration: none; -} -.no-underline:hover{ - text-decoration: none; -} - -.icon-hover:hover{ - height: 30px ; - width: 30px; -} - -.info-box-2 { - background-color: #F9FAFB; - border-radius: 8px; - padding-right: 16px; - padding-left: 16px; - padding-bottom: 24px; - padding-top: 4px; -} - - -.bold-link { - color: #000000 !important; - font-weight: 600; -} - -.community-box { - border: 1px solid #D2DCE6; - border-radius: 8px; - display: flex; - margin-bottom: 16px; -} - -.community-box:hover { - box-shadow: 0px 4px 20px rgba(0, 0, 0, 0.05); - text-decoration: none; -} - -.community-box p { - margin-top: 1rem !important; -} - -.tab-pane pre { - margin: 0; - padding: 0; - max-height: 252px; - overflow-y: auto; -} - -.grid-container { - display: grid; - grid-template-columns: repeat(auto-fit, minmax(300px,1fr)); - grid-gap: 16px; -} - -.grid-item { -padding: 20px; -} - - -.nav-pills { - background-color: #F9FAFB; - color: #000000; - padding: 8px; - border-bottom:none; - border-radius: 8px; -} - -.nav-pills .nav-link.active { - background-color: #FFFFFF !important; - box-shadow: 0px 3px 14px 2px rgba(3,28,74,0.12); - border-radius: 8px; - padding: 20px; - color: #000000; - font-weight: 500; -} - -.searchDiv { - width: 100%; - position: relative; - display: block; -} - -.searchTerm { - width: 80%; - border: 2px solid var(--blue); - padding: 5px; - height: 45px; - border-radius: 5px; - outline: none; -} - -.searchButton { - width: 40px; - height: 45px; - border: 1px solid var(--blue); - background: var(--blue); - color: #fff; - border-radius: 5px; - cursor: pointer; - font-size: 20px; -} - -/*Resize the wrap to see the search bar change!*/ -.searchWrap { - width: 100%; - position: relative; - margin: 15px; - top: 50%; - left: 50%; - transform: translate(-50%, -10%); - text-align: center; -} - -.sd-card { - border: none !important; -} - -.tag { - margin-bottom: 5px; - font-size: small; -} - -/* Override float positioning of next-prev buttons so that - they take up space normally, and we can put other stuff at - the bottom of the page. */ -.prev-next-area { - display: flex; - flex-direction: row; -} -.prev-next-area a.left-prev { - margin-right: auto; - width: fit-content; - float: none; -} -.prev-next-area a.right-next { - margin-left: auto; - width: fit-content; - float: none; -} - -/* CSAT widgets */ -#csat-inputs { - display: flex; - flex-direction: row; - align-items: center; -} - -.csat-hidden { - display: none !important; -} - -#csat-feedback-label { - color: #000; - font-weight: 500; -} - -.csat-button { - margin-left: 16px; - padding: 8px 16px 8px 16px; - border-radius: 4px; - border: 1px solid #D2DCE6; - background: #FFF; - display: flex; - flex-direction: row; - align-items: center; - justify-content: center; - cursor: pointer; - width: 85px; -} - -#csat-textarea-group { - display: flex; - flex-direction: column; -} - -#csat-submit { - margin-left: auto; - font-weight: 700; - border: none; - margin-top: 12px; - cursor: pointer; -} - -#csat-feedback-received { - display: flex; - flex-direction: row; - align-items: center; - justify-content: center; -} - -.csat-button-active { - border: 1px solid #000; -} - -.csat-icon { - margin-right: 4px; -} - -footer.col.footer { - display: flex; - flex-direction: row; -} - -footer.col.footer > p { - margin-left: auto; -} - -#csat { - min-width: 60%; -} - -#csat-textarea { - resize: none; -} - - -/* Ray Assistant */ - -.container-xl.blurred { - filter: blur(5px); -} - -.chat-widget { - position: fixed; - bottom: 10px; - right: 10px; - z-index: 1000; -} - -.chat-popup { - display: none; - position: fixed; - top: 20%; - left: 50%; - transform: translate(-50%, -20%); - width: 50%; - height: 70%; - background-color: white; - border: 1px solid #ccc; - border-radius: 10px; - box-shadow: 0 5px 10px rgba(0,0,0,0.1); - z-index: 1001; - max-height: 1000px; - overflow: hidden; - padding-bottom: 40px; -} - -.chatFooter { - position: absolute; - bottom: 0; - right: 0; - width: 100%; - background-color: #f8f9fa; -} - -#openChatBtn { - background-color: #000; - color: #fff; - width: 70px; - height: 70px; - border-radius: 10px; - border: none; - display: flex; - align-items: center; - justify-content: center; -} - -#closeChatBtn { - border: none; - background-color: transparent; - color: #000; - font-size: 1.2em; -} - -#closeChatBtn:hover { - color: #888; -} - -.chatHeader { - display: flex; - justify-content: space-between; - align-items: center; -} - -.chatContentContainer { - padding: 15px; - max-height: calc(100% - 80px); - overflow-y: auto; -} - -.chatContentContainer input { - margin-top: 10px; - margin-bottom: 10px; -} - -#result{ - padding: 15px; - border-radius: 10px; - margin-top: 10px; - margin-bottom: 10px; - background-color: #f8f9fa; - max-height: calc(100% - 20px); - overflow-y: auto; -} - -.chatContentContainer textarea { - flex-grow: 1; - min-width: 50px; - max-height: 40px; - resize: none; -} - -.searchBtn { - white-space: nowrap; -} - -.input-group { - display: flex; - align-items: stretch; -} - -/* Kapa Ask AI button */ -#kapa-widget-container figure { - padding: 0 !important; - } - - .mantine-Modal-root figure { - padding: 0 !important; - } - -@font-face { - font-family: "Linux Biolinum Keyboard"; - src: url(../fonts/LinBiolinum_Kah.ttf); -} - -.keys { - font-family: "Linux Biolinum Keyboard", sans-serif; -} - -.bd-article-container h1, .bd-article-container h2, .bd-article-container h3, .bd-article-container h4, .bd-article-container h5, .bd-article-container p.caption { - color: black; -} diff --git a/docs/_static/css/examples.css b/docs/_static/css/examples.css deleted file mode 100644 index d1f416d15..000000000 --- a/docs/_static/css/examples.css +++ /dev/null @@ -1,218 +0,0 @@ - -#site-navigation { - width: 330px !important; - border-right: none; - margin-left: 32px; - overflow-y: auto; - max-height: calc(100vh - var(--sidebar-top)); - position: sticky; - top: var(--sidebar-top) !important; - z-index: 1000; -} - -#site-navigation h5 { - font-size: 16px; - font-weight: 600; - color: #000; -} - -#site-navigation h6 { - font-size: 14px; - font-weight: 600; - color: #000; - text-transform: uppercase; -} - -/* Hide the default sidebar content */ -#site-navigation > div.bd-sidebar__content { - display: none; -} -#site-navigation > div.rtd-footer-container { - display: none; -} - -.searchDiv { - margin-bottom: 2em; -} - -#searchInput { - width: 100%; - color: #5F6469; - border: 1px solid #D2DCE6; - height: 50px; - border-radius: 4px; - background-color: #F9FAFB; - background-image: url("data:image/svg+xml,%3Csvg width='25' height='25' viewBox='0 0 25 25' fill='none' xmlns='http://www.w3.org/2000/svg'%3E%3Cg id='Systems / search-line' clip-path='url(%23clip0_1_150)'%3E%3Crect width='24' height='24' transform='translate(0.398529 0.0546875)' fill='%23F9FAFB'/%3E%3Cg id='Group'%3E%3Cpath id='Vector' d='M18.4295 16.6717L22.7125 20.9537L21.2975 22.3687L17.0155 18.0857C15.4223 19.3629 13.4405 20.0576 11.3985 20.0547C6.43053 20.0547 2.39853 16.0227 2.39853 11.0547C2.39853 6.08669 6.43053 2.05469 11.3985 2.05469C16.3665 2.05469 20.3985 6.08669 20.3985 11.0547C20.4014 13.0967 19.7068 15.0784 18.4295 16.6717ZM16.4235 15.9297C17.6926 14.6246 18.4014 12.8751 18.3985 11.0547C18.3985 7.18669 15.2655 4.05469 11.3985 4.05469C7.53053 4.05469 4.39853 7.18669 4.39853 11.0547C4.39853 14.9217 7.53053 18.0547 11.3985 18.0547C13.219 18.0576 14.9684 17.3488 16.2735 16.0797L16.4235 15.9297V15.9297Z' fill='%238C9196'/%3E%3C/g%3E%3C/g%3E%3Cdefs%3E%3CclipPath id='clip0_1_150'%3E%3Crect width='24' height='24' fill='white' transform='translate(0.398529 0.0546875)'/%3E%3C/clipPath%3E%3C/defs%3E%3C/svg%3E%0A"); - background-repeat: no-repeat; - background-position-x: 0.5em; - background-position-y: center; - background-size: 1.5em; - padding-left: 3em; -} - -#searchInput::placeholder { - color: #5F6469; - opacity: 1; -} - -.tag { - margin-bottom: 5px; - font-size: small; - color: #000000; - border: 1px solid #D2DCE6; - border-radius: 14px; - display: flex; - flex-direction: row; - align-items: center; - width: fit-content; - gap: 1em; -} - -.tag.btn-outline-primary { - color: #000000; - padding: 3px 12px 3px 12px; - line-height: 20px; -} - -.tag-btn-wrapper { - display: flex; - flex-direction: row; - flex-wrap: wrap; - gap: 1em; -} - -div.sd-container-fluid.docutils > div { - gap: var(--ray-example-gallery-gap-y) var(--ray-example-gallery-gap-x); - display: grid; - grid-template-columns: 1fr; -} - -/* Reflow to a 2-column format for normal screens */ -@media screen and (min-width: 768px) { - div.sd-container-fluid.docutils > div { - grid-template-columns: 1fr 1fr; - } -} - -div.gallery-item { - width: auto; -} - -div.gallery-item > div.sd-card { - border-radius: 8px; - box-shadow: 0px 4px 10px 0px rgba(0, 0, 0, 0.05) !important; -} - -/* Example gallery "Tutorial" title */ -div.sd-card-title > span.sd-bg-success.sd-bg-text-success { - color: #2F80ED !important; - font-weight: 500; - background: linear-gradient(180deg, rgba(25, 177, 226, 0.2) 0%, rgba(0, 109, 255, 0.2) 100%); - background-color: initial !important; -} - -/* Example gallery "Code example" title */ -div.sd-card-title > span.sd-bg-secondary.sd-bg-text-secondary { - color: #219653 !important; - font-weight: 500; - background: linear-gradient(180deg, rgba(29, 151, 108, 0.2) 0%, rgba(0, 226, 147, 0.2) 100%); - background-color: initial !important; -} - -/* Example gallery "Blog" title */ -div.sd-card-title > span.sd-bg-primary.sd-bg-text-primary { - color: #F2994A !important; - font-weight: 500; - background: linear-gradient(180deg, rgba(255, 230, 5, 0.2) 0%, rgba(255, 185, 80, 0.2) 100%); - background-color: initial !important; -} - -/* Example gallery "Video" title */ -div.sd-card-title > span.sd-bg-warning.sd-bg-text-warning { - color: #EB5757 !important; - font-weight: 500; - background: linear-gradient(180deg, rgba(150, 7, 7, 0.2) 0%, rgba(255, 115, 115, 0.2) 100%); - background-color: initial !important; -} - -/* Example gallery "Course" title */ -div.sd-card-title > span.sd-bg-info.sd-bg-text-info { - color: #7A64FF !important; - font-weight: 500; - background: linear-gradient(180deg, rgba(53, 25, 226, 0.2) 0%, rgba(183, 149, 255, 0.2) 100%); - background-color: initial !important; -} - -div.sd-card-body > p.sd-card-text > a { - text-align: initial; -} - -div.sd-card-body > p.sd-card-text > a > span { - color: rgb(81, 81, 81); -} - -#main-content { - max-width: 100%; -} - -#noMatches { - display: flex; - flex-direction: column; - align-items: center; - justify-content: center; -} - -#noMatchesInnerContent { - display: flex; - flex-direction: column; - align-items: center; - justify-content: center; -} - -#noMatches.hidden,.gallery-item.hidden { - display: none !important; -} - -.btn-primary { - color: #004293; - background: rgba(61, 138, 233, 0.20); - padding: 3px 12px 3px 12px; - border: 1px solid #D2DCE6; -} - -button.try-anyscale { - background-color: initial !important; - width: fit-content; - padding: 0 !important; - margin-left: auto !important; - float: initial !important; -} - -button.try-anyscale > svg { - display: none; -} - -button.try-anyscale > i { - display: none; -} - -button.try-anyscale > span { - margin: 0; - text-decoration-line: underline; - font-weight: 500; - color: #000; -} - -.top-nav-content { - justify-content: initial; -} - -/* Hide nav bar that has github, fullscreen, and print icons */ -div.header-article.row.sticky-top.noprint { - display: none !important; -} - -/* Hide the footer with 'prev article' and 'next article' buttons */ -.footer-article.hidden { - display: none !important; -} diff --git a/docs/_static/css/termynal.css b/docs/_static/css/termynal.css deleted file mode 100644 index 391a48078..000000000 --- a/docs/_static/css/termynal.css +++ /dev/null @@ -1,108 +0,0 @@ -/** - * termynal.js - * - * @author Ines Montani - * @version 0.0.1 - * @license MIT - */ - - :root { - --color-bg: #252a33; - --color-text: #eee; - --color-text-subtle: #a2a2a2; -} - -[data-termynal] { - width: auto; - max-width: 100%; - background: var(--color-bg); - color: var(--color-text); - font-size: 18px; - font-family: 'Fira Mono', Consolas, Menlo, Monaco, 'Courier New', Courier, monospace; - border-radius: 4px; - padding: 75px 45px 35px; - position: relative; - -webkit-box-sizing: border-box; - box-sizing: border-box; -} - -[data-termynal]:before { - content: ''; - position: absolute; - top: 15px; - left: 15px; - display: inline-block; - width: 15px; - height: 15px; - border-radius: 50%; - /* A little hack to display the window buttons in one pseudo element. */ - background: #d9515d; - -webkit-box-shadow: 25px 0 0 #f4c025, 50px 0 0 #3ec930; - box-shadow: 25px 0 0 #f4c025, 50px 0 0 #3ec930; -} - -[data-termynal]:after { - content: 'bash'; - position: absolute; - color: var(--color-text-subtle); - top: 5px; - left: 0; - width: 100%; - text-align: center; -} - -[data-ty] { - display: block; - line-height: 2; -} - -[data-ty]:before { - /* Set up defaults and ensure empty lines are displayed. */ - content: ''; - display: inline-block; - vertical-align: middle; -} - -[data-ty="input"]:before, -[data-ty-prompt]:before { - margin-right: 0.75em; - color: var(--color-text-subtle); -} - -[data-ty="input"]:before { - content: '$'; -} - -[data-ty][data-ty-prompt]:before { - content: attr(data-ty-prompt); -} - -[data-ty-cursor]:after { - content: attr(data-ty-cursor); - font-family: monospace; - margin-left: 0.5em; - -webkit-animation: blink 1s infinite; - animation: blink 1s infinite; -} - -a[data-terminal-control] { - text-align: right; - display: block; - color: #aebbff; -} - - -/* Cursor animation */ - -@-webkit-keyframes blink { - 50% { - opacity: 0; - } -} - -@keyframes blink { - 50% { - opacity: 0; - } -} - diff --git a/docs/_static/css/use_cases.css b/docs/_static/css/use_cases.css deleted file mode 100644 index 5678d2245..000000000 --- a/docs/_static/css/use_cases.css +++ /dev/null @@ -1,23 +0,0 @@ -.query-param-ref-wrapper { - display: flex; - justify-content: center; - align-items: center; - border: 1px solid #8C9196; - border-radius: 8px; -} - -.example-gallery-link { - padding: 1em 2em 1em 2em; - text-decoration: none !important; - color: black !important; - display: flex; - align-items: center; -} - -/* Shooting star icon next to gallery links */ -a.example-gallery-link::before { - content: url("data:image/svg+xml,%3Csvg width='24' height='24' viewBox='0 0 24 24' fill='none' xmlns='http://www.w3.org/2000/svg'%3E%3Cg id='Group'%3E%3Cpath id='Vector' d='M15.199 9.945C14.7653 9.53412 14.4863 8.98641 14.409 8.394L14.006 5.311L11.276 6.797C10.7511 7.08302 10.1436 7.17943 9.55597 7.07L6.49997 6.5L7.06997 9.556C7.1794 10.1437 7.08299 10.7511 6.79697 11.276L5.31097 14.006L8.39397 14.409C8.98603 14.4865 9.53335 14.7655 9.94397 15.199L12.082 17.456L13.418 14.649C13.6744 14.1096 14.1087 13.6749 14.648 13.418L17.456 12.082L15.199 9.945ZM15.224 15.508L13.011 20.158C12.9691 20.2459 12.9065 20.3223 12.8285 20.3806C12.7505 20.4389 12.6594 20.4774 12.5633 20.4926C12.4671 20.5079 12.3686 20.4995 12.2764 20.4682C12.1842 20.4369 12.101 20.3836 12.034 20.313L8.49197 16.574C8.39735 16.4742 8.27131 16.41 8.13497 16.392L3.02797 15.724C2.93149 15.7113 2.83954 15.6753 2.76006 15.6191C2.68058 15.563 2.61596 15.4883 2.57177 15.4016C2.52758 15.3149 2.50514 15.2187 2.5064 15.1214C2.50765 15.0241 2.53256 14.9285 2.57897 14.843L5.04097 10.319C5.10642 10.198 5.12831 10.0582 5.10297 9.923L4.15997 4.86C4.14207 4.76417 4.14778 4.66541 4.17662 4.57229C4.20546 4.47916 4.25656 4.39446 4.3255 4.32553C4.39444 4.25659 4.47913 4.20549 4.57226 4.17665C4.66539 4.14781 4.76414 4.14209 4.85997 4.16L9.92297 5.103C10.0582 5.12834 10.198 5.10645 10.319 5.041L14.843 2.579C14.9286 2.53257 15.0242 2.50769 15.1216 2.50648C15.219 2.50528 15.3152 2.52781 15.4019 2.57211C15.4887 2.61641 15.5633 2.68116 15.6194 2.76076C15.6755 2.84036 15.7114 2.93242 15.724 3.029L16.392 8.135C16.4099 8.27134 16.4742 8.39737 16.574 8.492L20.313 12.034C20.3836 12.101 20.4369 12.1842 20.4682 12.2765C20.4995 12.3687 20.5079 12.4671 20.4926 12.5633C20.4774 12.6595 20.4389 12.7505 20.3806 12.8285C20.3223 12.9065 20.2459 12.9691 20.158 13.011L15.508 15.224C15.3835 15.2832 15.2832 15.3835 15.224 15.508ZM16.021 17.435L17.435 16.021L21.678 20.263L20.263 21.678L16.021 17.435Z' fill='black'/%3E%3C/g%3E%3C/svg%3E%0A"); - display: flex; - align-items: center; - margin-right: 0.5em; -} diff --git a/docs/_static/img/muti-model-cluster-overview.png b/docs/_static/img/muti-model-cluster-overview.png deleted file mode 100644 index 934cbfa47..000000000 Binary files a/docs/_static/img/muti-model-cluster-overview.png and /dev/null differ diff --git a/docs/babel.config.js b/docs/babel.config.js new file mode 100755 index 000000000..e00595dae --- /dev/null +++ b/docs/babel.config.js @@ -0,0 +1,3 @@ +module.exports = { + presets: [require.resolve('@docusaurus/core/lib/babel/preset')], +}; diff --git a/docs/blog/authors.yml b/docs/blog/authors.yml new file mode 100755 index 000000000..38115f2ba --- /dev/null +++ b/docs/blog/authors.yml @@ -0,0 +1,67 @@ +csunny: + name: csunny + title: Owner + url: https://github.com/csunny + image_url: https://github.com/csunny.png + +Aries-ckt: + name: Aries-ckt + title: Developer + url: https://github.com/Aries-ckt + image_url: https://github.com/Aries-ckt.png + +yhjun1026: + name: yhjun1026 + title: Developer + url: https://github.com/yhjun1026 + image_url: https://github.com/yhjun1026.png + +xuyuan23: + name: Shinexy + title: Developer + url: https://github.com/xuyuan23 + image_url: https://github.com/xuyuan23.png + +yihong0618: + name: yihong0618 + title: Developer + url: https://github.com/yihong0618 + image_url: https://github.com/yihong0618.png + +zhanghy-sketchzh: + name: zhanghy-sketchzh + title: Developer + url: https://github.com/zhanghy-sketchzh + image_url: https://github.com/zhanghy-sketchzh.png + +fangyinc: + name: fangyinc + title: Developer + url: https://github.com/fangyinc + image_url: https://github.com/fangyinc.png + +wangzaistone: + name: wangzaistone + title: Developer + url: https://github.com/wangzaistone + image_url: https://github.com/wangzaistone.png + +qutcat1997: + name: qutcat1997 + title: Developer + url: https://github.com/qutcat1997 + image_url: https://github.com/qutcat1997.png + + +Aralhi: + name: Aralhi + title: Developer + url: https://github.com/Aralhi + image_url: https://github.com/Aralhi.png + + +Ifffff: + name: Ifffff + title: Developer + url: https://github.com/Ifffff + image_url: https://github.com/Ifffff.png diff --git a/docs/blog/welcome/index.md b/docs/blog/welcome/index.md new file mode 100755 index 000000000..2cfe41435 --- /dev/null +++ b/docs/blog/welcome/index.md @@ -0,0 +1,8 @@ +--- +slug: welcome +title: Welcome +authors: [csunny, Aries-ckt, yhjun1026, xuyuan23, yihong0618, zhanghy-sketchzh, fangyinc, wangzaistone, qutcat1997, Aralhi, Ifffff] +tags: [eosphoros-ai, DB-GPT, github] +--- + +[DB-GPT](https://github.com/eosphoros-ai/DB-GPT) is an experimental open-source project that uses localized GPT large models to interact with your data and environment. With this solution, you can be assured that there is no risk of data leakage, and your data is 100% private and secure. diff --git a/docs/conf.py b/docs/conf.py deleted file mode 100644 index 1fe4747f5..000000000 --- a/docs/conf.py +++ /dev/null @@ -1,84 +0,0 @@ -# Configuration file for the Sphinx documentation builder. -# -# For the full list of built-in configuration values, see the documentation: -# https://www.sphinx-doc.org/en/master/usage/configuration.html - -# -- Project information ----------------------------------------------------- -# https://www.sphinx-doc.org/en/master/usage/configuration.html#project-information - -import toml -import os -import sys - -project = "DB-GPT" -copyright = "2023, csunny" -author = "csunny" - -version = "👏👏 0.4.2" -html_title = project + " " + version - -# -- General configuration --------------------------------------------------- -# https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration - -extensions = [ - "sphinx.ext.autodoc", - "sphinx.ext.autodoc.typehints", - "sphinx.ext.autosummary", - "sphinx.ext.napoleon", - "sphinx.ext.viewcode", - # "sphinxcontrib.autodoc_pydantic", - "myst_nb", - "sphinx_copybutton", - "sphinx_panels", - "sphinx_tabs.tabs", - "IPython.sphinxext.ipython_console_highlighting", - "sphinx.ext.autosectionlabel", -] -source_suffix = [".ipynb", ".html", ".md", ".rst"] - - -myst_enable_extensions = [ - "dollarmath", - "amsmath", - "deflist", - "html_admonition", - "html_image", - "colon_fence", - "smartquotes", - "replacements", -] - -# autodoc_pydantic_model_show_json = False -# autodoc_pydantic_field_list_validators = False -# autodoc_pydantic_config_members = False -# autodoc_pydantic_model_show_config_summary = False -# autodoc_pydantic_model_show_validator_members = False -# autodoc_pydantic_model_show_field_summary = False -# autodoc_pydantic_model_members = False -# autodoc_pydantic_model_undoc_members = False - -templates_path = ["_templates"] -exclude_patterns = ["_build", "Thumbs.db", ".DS_Store"] - - -# multi language config -language = "en" # ['en', 'zh_CN'] # -locales_dirs = ["./locales/"] -gettext_compact = False -gettext_uuid = True - - -def setup(app): - app.add_css_file("css/custom.css") - app.add_css_file("css/examples.css") - app.add_css_file("css/termynal.css") - # app.add_css_file("css/use_cases.css") - - -# -- Options for HTML output ------------------------------------------------- -# https://www.sphinx-doc.org/en/master/usage/configuration.html#options-for-html-output - -html_theme = "sphinx_book_theme" - - -html_static_path = ["_static"] diff --git a/docs/docs/awel.md b/docs/docs/awel.md new file mode 100644 index 000000000..c54f9ad5f --- /dev/null +++ b/docs/docs/awel.md @@ -0,0 +1,135 @@ +# AWEL(Agentic Workflow Expression Language) + +Agentic Workflow Expression Language(AWEL) is a set of intelligent agent workflow expression language specially designed for large model application +development. It provides great functionality and flexibility. Through the AWEL API, you can focus on the development of business logic for LLMs applications +without paying attention to cumbersome model and environment details. + +AWEL adopts a layered API design. AWEL's layered API design architecture is shown in the figure below. + + +

+ +

+ +## AWEL Design + +AWEL is divided into three levels in deign, namely the operator layer, AgentFream layer and DSL layer. The following is a brief introduction +to the three levels. + +- **Operator layer** +The operator layer refers to the most basic operation atoms in the LLM application development process, +such as when developing a RAG application. Retrieval, vectorization, model interaction, prompt processing, etc. +are all basic operators. In the subsequent development, the framework will further abstract and standardize the design of operators. +A set of operators can be quickly implemented based on standard APIs + +- **AgentFream layer** +The AgentFream layer further encapsulates operators and can perform chain calculations based on operators. +This layer of chain computing also supports distribution, supporting a set of chain computing operations such as filter, join, map, reduce, etc. More calculation logic will be supported in the future. + +- **DSL layer** +The DSL layer provides a set of standard structured representation languages, which can complete the operations of AgentFream and operators by writing DSL statements, making it more deterministic to write large model applications around data, avoiding the uncertainty of writing in natural language, and making it easier to write around data. Application programming with large models becomes deterministic application programming. + +## Examples +The preliminary version of AWEL has alse been released, and we have provided some built-in usage examples. + +## Operators + +### Example of API-RAG +You can find [source code](https://github.com/eosphoros-ai/DB-GPT/blob/main/examples/awel/simple_rag_example.py) from `examples/awel/simple_rag_example.py` +```python +with DAG("simple_rag_example") as dag: + trigger_task = HttpTrigger( + "/examples/simple_rag", methods="POST", request_body=ConversationVo + ) + req_parse_task = RequestParseOperator() + # TODO should register prompt template first + prompt_task = PromptManagerOperator() + history_storage_task = ChatHistoryStorageOperator() + history_task = ChatHistoryOperator() + embedding_task = EmbeddingEngingOperator() + chat_task = BaseChatOperator() + model_task = ModelOperator() + output_parser_task = MapOperator(lambda out: out.to_dict()["text"]) + + ( + trigger_task + >> req_parse_task + >> prompt_task + >> history_storage_task + >> history_task + >> embedding_task + >> chat_task + >> model_task + >> output_parser_task + ) + +``` +Bit operations will arrange the entire process in the form of DAG + +

+ +

+ +#### Example of LLM + cache + +

+ +

+ + +### AgentFream Example +```python +af = AgentFream(HttpSource("/examples/run_code", method = "post")) +result = ( + af + .text2vec(model="text2vec") + .filter(vstore, store = "chromadb", db="default") + .llm(model="vicuna-13b", temperature=0.7) + .map(code_parse_func) + .map(run_sql_func) + .reduce(lambda a, b: a + b) +) +result.write_to_sink(type='source_slink') +``` + +### DSL Example + +``` python +CREATE WORKFLOW RAG AS +BEGIN + DATA requestData = RECEIVE REQUEST FROM + http_source("/examples/rags", method = "post"); + + DATA processedData = TRANSFORM requestData USING embedding(model = "text2vec"); + DATA retrievedData = RETRIEVE DATA + FROM vstore(database = "chromadb", key = processedData) + ON ERROR FAIL; + + DATA modelResult = APPLY LLM "vicuna-13b" + WITH DATA retrievedData AND PARAMETERS (temperature = 0.7) + ON ERROR RETRY 2 TIMES; + + RESPOND TO http_source WITH modelResult + ON ERROR LOG "Failed to respond to request"; +END; +``` + +## Currently supported operators +- **Basic Operators** + - BaseOperator + - JoinOperator + - ReduceOperator + - MapOperator + - BranchOperator + - InputOperator + - TriggerOperator +- ** Stream Operators** + - StreamifyAbsOperator + - UnstreamifyAbsOperator + - TransformStreamAbsOperator + +## Executable environment +- Stand-alone environment +- Ray environment + + diff --git a/docs/docs/changelog/doc.md b/docs/docs/changelog/doc.md new file mode 100644 index 000000000..3629dcdc1 --- /dev/null +++ b/docs/docs/changelog/doc.md @@ -0,0 +1 @@ +# Documentation Description \ No newline at end of file diff --git a/docs/docs/faq.md b/docs/docs/faq.md new file mode 100644 index 000000000..429a49e0d --- /dev/null +++ b/docs/docs/faq.md @@ -0,0 +1,2 @@ +# FAQ +If you encounter any problems, you can submit an [issue](https://github.com/eosphoros-ai/DB-GPT/issues) on Github. \ No newline at end of file diff --git a/docs/docs/installation/advanced_usage/OpenAI_SDK_call.md b/docs/docs/installation/advanced_usage/OpenAI_SDK_call.md new file mode 100644 index 000000000..25dad39b2 --- /dev/null +++ b/docs/docs/installation/advanced_usage/OpenAI_SDK_call.md @@ -0,0 +1,60 @@ +# OpenAI SDK Calls Local Multi-model +The call of multi-model services is compatible with the OpenAI interface, and the models deployed in DB-GPT can be directly called through the OpenAI SDK. + +:::info note + +⚠️ Before using this project, you must first deploy the model service, which can be deployed through the [cluster deployment tutorial](/docs/installation/model_service/cluster). +::: + + +## Start apiserver + +After deploying the model service, you need to start the API Server. By default, the model API Server uses port `8100` to start. +```python +dbgpt start apiserver --controller_addr http://127.0.0.1:8000 --api_keys EMPTY + +``` + + +## Verify + +### cURL validation +After the apiserver is started, the service call can be verified. First, let's look at verification through curl. + + +:::tip +List models +::: +```python +curl http://127.0.0.1:8100/api/v1/models \ +-H "Authorization: Bearer EMPTY" \ +-H "Content-Type: application/json" +``` + +:::tip +Chat +::: +```python +curl http://127.0.0.1:8100/api/v1/chat/completions \ +-H "Authorization: Bearer EMPTY" \ +-H "Content-Type: application/json" \ +-d '{"model": "vicuna-13b-v1.5", "messages": [{"role": "user", "content": "hello"}]}' +``` + + +## Verify via OpenAI SDK + +```python +import openai +openai.api_key = "EMPTY" +openai.api_base = "http://127.0.0.1:8100/api/v1" +model = "vicuna-13b-v1.5" + +completion = openai.ChatCompletion.create( + model=model, + messages=[{"role": "user", "content": "hello"}] +) +# print the completion +print(completion.choices[0].message.content) +``` + diff --git a/docs/docs/installation/advanced_usage/vLLM_inference.md b/docs/docs/installation/advanced_usage/vLLM_inference.md new file mode 100644 index 000000000..205235169 --- /dev/null +++ b/docs/docs/installation/advanced_usage/vLLM_inference.md @@ -0,0 +1,19 @@ +# vLLM Inference +DB-GPT supports [vLLM](https://github.com/vllm-project/vllm) inference, a fast and easy-to-use LLM inference and service library. + +## Install dependencies +`vLLM` is an optional dependency in DB-GPT. You can install it manually through the following command. + +```python +$ pip install -e ".[vllm]" +``` + +## Modify configuration file +In the `.env` configuration file, modify the inference type of the model to start `vllm` inference. +```python +LLM_MODEL=vicuna-13b-v1.5 +MODEL_TYPE=vllm +``` + +For more information about the list of models supported by `vLLM`, please refer to the [vLLM supported model document](https://docs.vllm.ai/en/latest/models/supported_models.html#supported-models). + diff --git a/docs/docs/installation/docker.md b/docs/docs/installation/docker.md new file mode 100644 index 000000000..2bdc52d2b --- /dev/null +++ b/docs/docs/installation/docker.md @@ -0,0 +1,112 @@ +# Docker Deployment + +## Docker image preparation + +There are two ways to prepare a Docker image. 1. Pull from the official image 2. Build locally. You can **choose any one** during actual use. + +1.Pulled from the official image repository, [Eosphoros AI Docker Hub](https://hub.docker.com/u/eosphorosai) +```python +docker pull eosphorosai/dbgpt:latest +``` +2.local build(optional) +```python +bash docker/build_all_images.sh +``` +Check the Docker image +```python +# command +docker images | grep "eosphorosai/dbgpt" + +# result +-------------------------------------------------------------------------------------- +eosphorosai/dbgpt-allinone latest 349d49726588 27 seconds ago 15.1GB +eosphorosai/dbgpt latest eb3cdc5b4ead About a minute ago 14.5GB +``` +`eosphorosai/dbgpt` is the base image, which contains project dependencies and the sqlite database. The `eosphorosai/dbgpt-allinone` image is built from `eosphorosai/dbgpt`, which contains a MySQL database. Of course, in addition to pulling the Docker image, the project also provides Dockerfile files, which can be built directly through scripts in DB-GPT. Here are the build commands: + +```python +bash docker/build_all_images.sh +``` +When using it, you need to specify specific parameters. The following is an example of specifying parameter construction: + +```python +bash docker/build_all_images.sh \ +--base-image nvidia/cuda:11.8.0-runtime-ubuntu22.04 \ +--pip-index-url https://pypi.tuna.tsinghua.edu.cn/simple \ +--language zh +``` +You can view the specific usage through the command `bash docker/build_all_images.sh --help` + +## Run Docker container + +### Run through Sqlite database + + +```python +docker run --ipc host --gpus all -d \ +-p 5000:5000 \ +-e LOCAL_DB_TYPE=sqlite \ +-e LOCAL_DB_PATH=data/default_sqlite.db \ +-e LLM_MODEL=vicuna-13b-v1.5 \ +-e LANGUAGE=zh \ +-v /data/models:/app/models \ +--name dbgpt \ +eosphorosai/dbgpt +``` +Open the browser and visit [http://localhost:5000](http://localhost:5000) + +- `-e LLM_MODEL=vicuna-13b-v1.5`, which means the base model uses `vicuna-13b-v1.5`. For more model usage, you can view the configuration in `/pilot/configs/model_config.LLM_MODEL_CONFIG`. +- `-v /data/models:/app/models`, specifies the model file to be mounted. The directory `/data/models` is mounted in `/app/models` of the container. Of course, it can be replaced with other paths. + +After the container is started, you can view the logs through the following command +```python +docker logs dbgpt -f +``` + +### Run through MySQL database + +```python +docker run --ipc host --gpus all -d -p 3306:3306 \ +-p 5000:5000 \ +-e LOCAL_DB_HOST=127.0.0.1 \ +-e LOCAL_DB_PASSWORD=aa123456 \ +-e MYSQL_ROOT_PASSWORD=aa123456 \ +-e LLM_MODEL=vicuna-13b-v1.5 \ +-e LANGUAGE=zh \ +-v /data/models:/app/models \ +--name db-gpt-allinone \ +db-gpt-allinone +``` +Open the browser and visit [http://localhost:5000](http://localhost:5000) + +- `-e LLM_MODEL=vicuna-13b-v1.5`, which means the base model uses `vicuna-13b-v1.5`. For more model usage, you can view the configuration in `/pilot/configs/model_config.LLM_MODEL_CONFIG`. +- `-v /data/models:/app/models`, specifies the model file to be mounted. The directory `/data/models` is mounted in `/app/models` of the container. Of course, it can be replaced with other paths. + +After the container is started, you can view the logs through the following command +```python +docker logs db-gpt-allinone -f +``` + +### Run through the OpenAI proxy model +```python +PROXY_API_KEY="You api key" +PROXY_SERVER_URL="https://api.openai.com/v1/chat/completions" +docker run --gpus all -d -p 3306:3306 \ +-p 5000:5000 \ +-e LOCAL_DB_HOST=127.0.0.1 \ +-e LOCAL_DB_PASSWORD=aa123456 \ +-e MYSQL_ROOT_PASSWORD=aa123456 \ +-e LLM_MODEL=proxyllm \ +-e PROXY_API_KEY=$PROXY_API_KEY \ +-e PROXY_SERVER_URL=$PROXY_SERVER_URL \ +-e LANGUAGE=zh \ +-v /data/models/text2vec-large-chinese:/app/models/text2vec-large-chinese \ +--name db-gpt-allinone \ +db-gpt-allinone +``` +- `-e LLM_MODEL=proxyllm`, set the model to serve the third-party model service API, which can be openai or fastchat interface. +- `-v /data/models/text2vec-large-chinese:/app/models/text2vec-large-chinese`, sets the knowledge base embedding model to `text2vec` + +Open the browser and visit [http://localhost:5000](http://localhost:5000) + + diff --git a/docs/docs/installation/docker_compose.md b/docs/docs/installation/docker_compose.md new file mode 100644 index 000000000..61bc81987 --- /dev/null +++ b/docs/docs/installation/docker_compose.md @@ -0,0 +1,26 @@ +# Docker-Compose Deployment + +## Run via Docker-Compose +```python +$ docker compose up -d +------------------------------------------ +[+] Building 0.0s (0/0) +[+] Running 2/2 +✔ Container db-gpt-db-1 Started 0.4s +✔ Container db-gpt-webserver-1 Started +``` + + +## View log +```python +$ docker logs db-gpt-webserver-1 -f +``` + +:::info note + +For more configuration content, you can view the `docker-compose.yml` file +::: + + +## Visit +Open the browser and visit [http://localhost:5000](http://localhost:5000) diff --git a/docs/getting_started/install/cluster/vms/index.md b/docs/docs/installation/model_service/cluster.md similarity index 69% rename from docs/getting_started/install/cluster/vms/index.md rename to docs/docs/installation/model_service/cluster.md index fc06e3d60..13919495d 100644 --- a/docs/getting_started/install/cluster/vms/index.md +++ b/docs/docs/installation/model_service/cluster.md @@ -1,65 +1,79 @@ -Cluster Deployment -================================== -(local-cluster-index)= -## Model cluster deployment +# Cluster Deployment +## Install command line tools +All the following operations are completed through the `dbgpt` command. To use the `dbgpt` command, you first need to install the `DB-GPT` project. You can install it through the following command -**Installing Command-Line Tool** - -All operations below are performed using the `dbgpt` command. To use the `dbgpt` command, you need to install the DB-GPT project with `pip install -e ".[default]"`. Alternatively, you can use `python pilot/scripts/cli_scripts.py` as a substitute for the `dbgpt` command. - -### Launch Model Controller - -```bash -dbgpt start controller +```python +$ pip install -e ".[default]" +``` +It can also be used in script mode +```python +$ python pilot/scripts/cli_scripts.py ``` -By default, the Model Controller starts on port 8000. +## Start Model Controller +```python +$ dbgpt start controller +``` +## View log +```python +$ docker logs db-gpt-webserver-1 -f +``` +By default, `Model Server` will start on port `8000` -### Launch LLM Model Worker +## Start Model Worker -If you are starting `chatglm2-6b`: +:::tip +Start `chatglm2-6b` model Worker +::: -```bash +```python dbgpt start worker --model_name chatglm2-6b \ --model_path /app/models/chatglm2-6b \ --port 8001 \ --controller_addr http://127.0.0.1:8000 ``` -If you are starting `vicuna-13b-v1.5`: -```bash +:::tip +Start `vicuna-13b-v1.5` model Worker +::: + +```python dbgpt start worker --model_name vicuna-13b-v1.5 \ --model_path /app/models/vicuna-13b-v1.5 \ --port 8002 \ --controller_addr http://127.0.0.1:8000 ``` +:::info note +⚠️ Make sure to use your own model name and model path. -Note: Be sure to use your own model name and model path. +::: -### Launch Embedding Model Worker -```bash +## Start the embedding model service +```python dbgpt start worker --model_name text2vec \ --model_path /app/models/text2vec-large-chinese \ --worker_type text2vec \ --port 8003 \ --controller_addr http://127.0.0.1:8000 ``` +:::info note +⚠️ Make sure to use your own model name and model path. -Note: Be sure to use your own model name and model path. +::: -Check your model: +:::tip +View and inspect deployed models +::: -```bash -dbgpt model list -``` -You will see the following output: -``` +```python +$ dbgpt model list + +-----------------+------------+------------+------+---------+---------+-----------------+----------------------------+ | Model Name | Model Type | Host | Port | Healthy | Enabled | Prompt Template | Last Heartbeat | +-----------------+------------+------------+------+---------+---------+-----------------+----------------------------+ @@ -72,43 +86,42 @@ You will see the following output: +-----------------+------------+------------+------+---------+---------+-----------------+----------------------------+ ``` -### Connect to the model service in the webserver (dbgpt_server) -**First, modify the `.env` file to change the model name and the Model Controller connection address.** +## Use model serving -```bash +The model service deployed as above can be used through dbgpt_server. First modify the `.env` configuration file to change the connection model address + +```python +dbgpt start webserver --light +``` + +## Start Webserver + +```python LLM_MODEL=vicuna-13b-v1.5 # The current default MODEL_SERVER address is the address of the Model Controller MODEL_SERVER=http://127.0.0.1:8000 ``` +`--light` means not to start the embedded model service. -#### Start the webserver -```bash -dbgpt start webserver --light -``` - -`--light` indicates not to start the embedded model service. - -Alternatively, you can prepend the command with `LLM_MODEL=chatglm2-6b` to start: - -```bash +Or it can be started directly by command to formulate the model. +```python LLM_MODEL=chatglm2-6b dbgpt start webserver --light ``` +## Command line usage +For more information about the use of the command line, you can view the command line help. The following is a reference example. -### More Command-Line Usages -You can view more command-line usages through the help command. +:::tip +View dbgpt help `dbgpt --help` +::: -**View the `dbgpt` help** -```bash +```python dbgpt --help -``` -You will see the basic command parameters and usage: - -``` +Already connect 'dbgpt' Usage: dbgpt [OPTIONS] COMMAND [ARGS]... Options: @@ -122,17 +135,18 @@ Commands: model Clients that manage model serving start Start specific server. stop Start specific server. + trace Analyze and visualize trace spans. ``` -**View the `dbgpt start` help** -```bash +:::tip +Check the dbgpt start command `dbgpt start --help` +::: + +```python dbgpt start --help -``` -Here you can see the related commands and usage for start: - -``` +Already connect 'dbgpt' Usage: dbgpt start [OPTIONS] COMMAND [ARGS]... Start specific server. @@ -141,21 +155,21 @@ Options: --help Show this message and exit. Commands: - apiserver Start apiserver(TODO) + apiserver Start apiserver controller Start model controller webserver Start webserver(dbgpt_server.py) worker Start model worker +(dbgpt_env) magic@B-4TMH9N3X-2120 ~ % ``` -**View the `dbgpt start worker`help** +:::tip +View the dbgpt start model service help command `dbgpt start worker --help` +::: -```bash +```python dbgpt start worker --help -``` -Here you can see the parameters to start Model Worker: - -``` +Already connect 'dbgpt' Usage: dbgpt start worker [OPTIONS] Start model worker @@ -166,6 +180,8 @@ Options: --worker_type TEXT Worker type --worker_class TEXT Model worker class, pilot.model.cluster.DefaultModelWorker + --model_type TEXT Model type: huggingface, llama.cpp, proxy + and vllm [default: huggingface] --host TEXT Model worker deploy host [default: 0.0.0.0] --port INTEGER Model worker deploy port [default: 8001] --daemon Run Model Worker in background @@ -183,14 +199,21 @@ Options: [default: True] --heartbeat_interval INTEGER The interval for sending heartbeats (seconds) [default: 20] + --log_level TEXT Logging level + --log_file TEXT The filename to store log [default: + dbgpt_model_worker_manager.log] + --tracer_file TEXT The filename to store tracer span records + [default: + dbgpt_model_worker_manager_tracer.jsonl] + --tracer_storage_cls TEXT The storage class to storage tracer span + records --device TEXT Device to run model. If None, the device is automatically determined - --model_type TEXT Model type, huggingface, llama.cpp and proxy - [default: huggingface] --prompt_template TEXT Prompt template. If None, the prompt template is automatically determined from model path, supported template: zero_shot,vi - cuna_v1.1,llama-2,alpaca,baichuan-chat + cuna_v1.1,llama-2,codellama,alpaca,baichuan- + chat,internlm-chat --max_context_size INTEGER Maximum context size [default: 4096] --num_gpus INTEGER The number of gpus you expect to use, if it is empty, use all of them as much as @@ -209,18 +232,18 @@ Options: --compute_dtype TEXT Model compute type --trust_remote_code Trust remote code [default: True] --verbose Show verbose output. - --help Show this message and exit. + --help Show this message and exit. ``` -**View the `dbgpt model`help** +:::tip +View dbgpt model service related commands `dbgpt model --help` +::: -```bash +```python dbgpt model --help -``` -The `dbgpt model ` command can connect to the Model Controller via the Model Controller address and then manage a remote model: -``` +Already connect 'dbgpt' Usage: dbgpt model [OPTIONS] COMMAND [ARGS]... Clients that manage model serving @@ -238,4 +261,7 @@ Commands: restart Restart model instances start Start model instances stop Stop model instances -``` \ No newline at end of file +``` + + + diff --git a/docs/docs/installation/model_service/stand_alone.md b/docs/docs/installation/model_service/stand_alone.md new file mode 100644 index 000000000..911c9aa92 --- /dev/null +++ b/docs/docs/installation/model_service/stand_alone.md @@ -0,0 +1,123 @@ +# Stand-alone Deployment + +## Preparation +```python +# download source code +$ git clone https://github.com/eosphoros-ai/DB-GPT.git + +$ cd DB-GPT +``` + +## Environment installation + +```python +# create a virtual environment +$ conda create -n dbgpt_env python=3.10 + +# activate virtual environment +$ conda activate dbgpt_env +``` + +## Install dependencies + +```python +pip install -e ".[default]" +``` + +## Model download + +Download LLM and Embedding model + +:::info note + +⚠️ If there are no GPU resources, it is recommended to use the proxy model, such as OpenAI, Qwen, ERNIE Bot, etc. +::: + + +```python +$ mkdir models && cd models + +# download embedding model, eg: text2vec-large-chinese +$ git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese +``` + +:::tip + +Set up proxy API and modify `.env`configuration +::: + +```python +#set LLM_MODEL TYPE +LLM_MODEL=proxyllm +#set your Proxy Api key and Proxy Server url +PROXY_API_KEY={your-openai-sk} +PROXY_SERVER_URL=https://api.openai.com/v1/chat/completions +``` + +:::info note +⚠️ If you have GPU resources, you can use local models to deploy +::: + +```python +$ mkdir models && cd models + +# # download embedding model, eg: vicuna-13b-v1.5 or +$ git clone https://huggingface.co/lmsys/vicuna-13b-v1.5 + +# download embedding model, eg: text2vec-large-chinese +$ git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese + +$ popd + +``` + +## Command line startup + +```python +LLM_MODEL=vicuna-13b-v1.5 +dbgpt start webserver --port 6006 +``` +By default, the `dbgpt start webserver command` will start the `webserver`, `model controller`, and `model worker` through a single Python process. In the above command, port `6006` is specified. + + + +## View and verify model serving + +:::tip +view and display all model services +::: +```python +dbgpt model list +``` + +```python +# result ++-----------------+------------+------------+------+---------+---------+-----------------+----------------------------+ +| Model Name | Model Type | Host | Port | Healthy | Enabled | Prompt Template | Last Heartbeat | ++-----------------+------------+------------+------+---------+---------+-----------------+----------------------------+ +| vicuna-13b-v1.5 | llm | 172.17.0.9 | 6006 | True | True | | 2023-10-16T19:49:59.201313 | +| WorkerManager | service | 172.17.0.9 | 6006 | True | True | | 2023-10-16T19:49:59.246756 | ++-----------------+------------+------------+------+---------+---------+-----------------+----------------------------+ + +``` +Where `WorkerManager` is the management process of `Model Workers` + +:::tip +check and verify model serving +::: +```python +dbgpt model chat --model_name vicuna-13b-v1.5 +``` + +The above command will launch an interactive page that allows you to talk to the model through the terminal. + +```python +Chatbot started with model vicuna-13b-v1.5. Type 'exit' to leave the chat. + + +You: Hello +Bot: Hello! How can I assist you today? + +You: +``` + diff --git a/docs/docs/installation/sourcecode.md b/docs/docs/installation/sourcecode.md new file mode 100644 index 000000000..4ceeb9cf7 --- /dev/null +++ b/docs/docs/installation/sourcecode.md @@ -0,0 +1,380 @@ +# Source Code Deployment + +## Environmental requirements + +| Startup Mode | CPU * MEM | GPU | Remark | +|:--------------------:|:------------:|:--------------:|:---------------:| +| Proxy model | 4C * 8G | None | Proxy model does not rely on GPU | +| Local model | 8C * 32G | 24G | It is best to start locally with a GPU of 24G or above | + + + + + + +### Download source code + +:::tip +Download DB-GPT +::: + + + +```python +git clone https://github.com/eosphoros-ai/DB-GPT.git +``` + +### Miniconda environment installation + +- The default database uses SQLite, so there is no need to install a database in the default startup mode. If you need to use other databases, you can read the [advanced tutorials](/docs/operation_manual/advanced_tutorial) below. We recommend installing the Python virtual environment through the conda virtual environment. For the installation of Miniconda environment, please refer to the [Miniconda installation tutorial](https://docs.conda.io/projects/miniconda/en/latest/). + +:::tip +Create a Python virtual environment +::: + +```python +python >= 3.10 +conda create -n dbgpt_env python=3.10 +conda activate dbgpt_env + +# it will take some minutes +pip install -e ".[default]" +``` + +:::tip +Copy environment variables +::: +```python +cp .env.template .env +``` + + +## Model deployment + +DB-GPT can be deployed on servers with lower hardware through proxy model, or as a private local model under the GPU environment. If your hardware configuration is low, you can use third-party large language model API services, such as OpenAI, Azure, Qwen, ERNIE Bot, etc. + +:::info note + +⚠️ You need to ensure that git-lfs is installed +```python +● CentOS installation: yum install git-lfs +● Ubuntu installation: apt-get install git-lfs +● MacOS installation: brew install git-lfs +``` +::: +### Proxy model + +import Tabs from '@theme/Tabs'; +import TabItem from '@theme/TabItem'; + + + + Install dependencies + +```python +pip install -e ".[openai]" +``` + +Download embedding model + +```python +cd DB-GPT +mkdir models and cd models +git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese +``` + +Configure the proxy and modify LLM_MODEL, PROXY_API_URL and API_KEY in the `.env`file + +```python +# .env +LLM_MODEL=chatgpt_proxyllm +PROXY_API_KEY={your-openai-sk} +PROXY_SERVER_URL=https://api.openai.com/v1/chat/completions +``` + + +Install dependencies + +```python +pip install dashscope +``` + +Download embedding model + +```python +cd DB-GPT +mkdir models and cd models + +# embedding model +git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese +or +git clone https://huggingface.co/moka-ai/m3e-large +``` + +Configure the proxy and modify LLM_MODEL, PROXY_API_URL and API_KEY in the `.env`file + +```python +# .env +# Aliyun tongyiqianwen +LLM_MODEL=tongyi_proxyllm +TONGYI_PROXY_API_KEY={your-tongyi-sk} +PROXY_SERVER_URL={your_service_url} +``` + + +Install dependencies + +```python +pip install zhipuai +``` + +Download embedding model + +```python +cd DB-GPT +mkdir models and cd models + +# embedding model +git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese +or +git clone https://huggingface.co/moka-ai/m3e-large +``` + +Configure the proxy and modify LLM_MODEL, PROXY_API_URL and API_KEY in the `.env`file + +```python +# .env +LLM_MODEL=zhipu_proxyllm +PROXY_SERVER_URL={your_service_url} +ZHIPU_MODEL_VERSION={version} +ZHIPU_PROXY_API_KEY={your-zhipu-sk} +``` + + + + +Download embedding model + +```python +cd DB-GPT +mkdir models and cd models + +# embedding model +git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese +or +git clone https://huggingface.co/moka-ai/m3e-large +``` + +Configure the proxy and modify LLM_MODEL, PROXY_API_URL and API_KEY in the `.env`file + +```python +# .env +LLM_MODEL=wenxin_proxyllm +PROXY_SERVER_URL={your_service_url} +WEN_XIN_MODEL_VERSION={version} +WEN_XIN_API_KEY={your-wenxin-sk} +WEN_XIN_SECRET_KEY={your-wenxin-sct} +``` + + + + +:::info note + +⚠️ Be careful not to overwrite the contents of the `.env` configuration file +::: + + +### Local model + + + +##### Hardware requirements description +| Model | Quantize | VRAM Size | +|------------------ |--------------|----------------| +|Vicuna-7b-1.5 | 4-bit | 8GB | +|Vicuna-7b-1.5 | 8-bit | 12GB | +|Vicuna-13b-v1.5 | 4-bit | 12GB | +|Vicuna-13b-v1.5 | 8-bit | 24GB | + +##### Download LLM + +```python +cd DB-GPT +mkdir models and cd models + +# embedding model +git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese +或者 +git clone https://huggingface.co/moka-ai/m3e-large + +# llm model, if you use openai or Azure or tongyi llm api service, you don't need to download llm model +git clone https://huggingface.co/lmsys/vicuna-13b-v1.5 + +``` +##### Environment variable configuration, configure the LLM_MODEL parameter in the `.env` file +```python +# .env +LLM_MODEL=vicuna-13b-v1.5 +``` + + + + +##### Hardware requirements description +| Model | Quantize | VRAM Size | +|------------------ |--------------|----------------| +|Baichuan-7b | 4-bit | 8GB | +|Baichuan-7b | 8-bit | 12GB | +|Baichuan-13b | 4-bit | 12GB | +|Baichuan-13b | 8-bit | 20GB | + +##### Download LLM + + +```python +cd DB-GPT +mkdir models and cd models + +# embedding model +git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese +or +git clone https://huggingface.co/moka-ai/m3e-large + +# llm model +git clone https://huggingface.co/baichuan-inc/Baichuan2-7B-Chat +or +git clone https://huggingface.co/baichuan-inc/Baichuan2-13B-Chat + +``` +##### Environment variable configuration, configure the LLM_MODEL parameter in the `.env` file +```python +# .env +LLM_MODEL=baichuan2-13b +``` + + + + +##### Hardware requirements description +| Model | Quantize | VRAM Size | +|------------------ |--------------|----------------| +|ChatGLM-6b | 4-bit | 7GB | +|ChatGLM-6b | 8-bit | 9GB | +|ChatGLM-6b | FP16 | 14GB | + + +##### Download LLM + +```python +cd DB-GPT +mkdir models and cd models + +# embedding model +git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese +or +git clone https://huggingface.co/moka-ai/m3e-large + +# llm model +git clone https://huggingface.co/THUDM/chatglm2-6b + +``` +##### Environment variable configuration, configure the LLM_MODEL parameter in the `.env` file +```python +# .env +LLM_MODEL=chatglm2-6b +``` + + + + + +### llama.cpp(CPU) +:::info note +⚠️ llama.cpp can be run on Mac M1 or Mac M2 +::: + +DB-GPT also supports the lower-cost inference framework llama.cpp, which can be used through llama-cpp-python. + + +#### Document preparation +Before using llama.cpp, you first need to prepare the model file in gguf format. There are two ways to obtain it. You can choose one method to obtain the corresponding file. + +:::tip +Method 1: Download the converted model +::: + +If you want to use [Vicuna-13b-v1.5](https://huggingface.co/lmsys/vicuna-13b-v1.5), you can download the converted file [TheBloke/vicuna-13B-v1.5-GGUF](https://huggingface.co/TheBloke/vicuna-13B-v1.5-GGUF), only this one file is needed. Download the file and put it in the model path. You need to rename the model to: `ggml-model-q4_0.gguf`. +```python +wget https://huggingface.co/TheBloke/vicuna-13B-v1.5-GGUF/resolve/main/vicuna-13b-v1.5.Q4_K_M.gguf -O models/ggml-model-q4_0.gguf +``` + +:::tip +Method 2: Convert files yourself +::: +During use, you can also convert the model file yourself according to the instructions in [llama.cpp#prepare-data–run](https://github.com/ggerganov/llama.cpp#prepare-data--run), and place the converted file in the models directory and name it `ggml-model-q4_0.gguf`. + + +#### Install dependencies +llama.cpp is an optional installation item in DB-GPT. You can install it with the following command. + +```python +pip install -e ".[llama_cpp]" +``` + +#### Modify configuration file +Modify the `.env` file to use llama.cpp, and then you can start the service by running the [command](/docs/quickstart.mdx) + + +#### More descriptions + +| environment variables | default value | description | +|-------------------------------------|------------------|-----------------------| +| `llama_cpp_prompt_template` | None | Prompt template now supports `zero_shot, vicuna_v1.1,alpaca,llama-2,baichuan-chat,internlm-chat`. If it is None, the model Prompt template can be automatically obtained according to the model path. | +| `llama_cpp_model_path` | None | model path | +| `llama_cpp_n_gpu_layers` | 1000000000 | How many network layers to transfer to the GPU, set this to 1000000000 to transfer all layers to the GPU. If your GPU is low on memory, you can set a lower number, for example: 10. | +| `llama_cpp_n_threads` | None | The number of threads to use. If None, the number of threads will be determined automatically. | +| `llama_cpp_n_batch` | 512 | The maximum number of prompt tokens to be batched together when calling llama_eval | +| `llama_cpp_n_gqa` | None | For the llama-2 70B model, Grouped-query attention must be 8. | +| `llama_cpp_rms_norm_eps` | 5e-06 | For the llama-2 model, 5e-6 is a good value. | +| `llama_cpp_cache_capacity` | None | Maximum model cache size. For example: 2000MiB, 2GiB | +| `llama_cpp_prefer_cpu` | False | If a GPU is available, the GPU will be used first by default unless prefer_cpu=False is configured. | + + + + +## Test data (optional) +The DB-GPT project has a part of test data built-in by default, which can be loaded into the local database for testing through the following command +- **Linux** + +```python +bash ./scripts/examples/load_examples.sh + +``` +- **Windows** + +```python +.\scripts\examples\load_examples.bat +``` + +## Run service +The DB-GPT service is packaged into a server, and the entire DB-GPT service can be started through the following command. +```python +python pilot/server/dbgpt_server.py +``` + +## Visit website +Open the browser and visit [`http://localhost:5000`](http://localhost:5000) \ No newline at end of file diff --git a/docs/docs/modules/agent.md b/docs/docs/modules/agent.md new file mode 100644 index 000000000..cef4f7b29 --- /dev/null +++ b/docs/docs/modules/agent.md @@ -0,0 +1,2 @@ +# DD-Agents +Data Driven Multi-Agents(DD-Agents) \ No newline at end of file diff --git a/docs/docs/modules/connections.md b/docs/docs/modules/connections.md new file mode 100644 index 000000000..3c2aac866 --- /dev/null +++ b/docs/docs/modules/connections.md @@ -0,0 +1,2 @@ +# Connections +The connections module supports connecting to various structured, semi-structured, and unstructured data storage engines. Bring multi-dimensional data into the framework and realize the interaction between natural language and multi-dimensional data \ No newline at end of file diff --git a/docs/docs/modules/eval.md b/docs/docs/modules/eval.md new file mode 100644 index 000000000..94d1c8957 --- /dev/null +++ b/docs/docs/modules/eval.md @@ -0,0 +1,3 @@ +# Evaluation + +Model effect and framework performance evaluation. \ No newline at end of file diff --git a/docs/docs/modules/fine_tuning.md b/docs/docs/modules/fine_tuning.md new file mode 100644 index 000000000..887b9b00d --- /dev/null +++ b/docs/docs/modules/fine_tuning.md @@ -0,0 +1,2 @@ +# Fine-Tuning +Text2SQL and Text2API(DSL) fine-tune to enhance model performance. \ No newline at end of file diff --git a/docs/docs/modules/rag.md b/docs/docs/modules/rag.md new file mode 100644 index 000000000..9746543d6 --- /dev/null +++ b/docs/docs/modules/rag.md @@ -0,0 +1,2 @@ +# MS-RAG +Multi-Source Enhanced Retrieval-Augmented Generation Framework(MS-RAG) \ No newline at end of file diff --git a/docs/docs/modules/smmf.md b/docs/docs/modules/smmf.md new file mode 100644 index 000000000..03aaafe1a --- /dev/null +++ b/docs/docs/modules/smmf.md @@ -0,0 +1,7 @@ +# SMMF +Service-oriented Multi-model Management Framework(SMMF) + + +

+ +

\ No newline at end of file diff --git a/docs/docs/modules/visual.md b/docs/docs/modules/visual.md new file mode 100644 index 000000000..89873875e --- /dev/null +++ b/docs/docs/modules/visual.md @@ -0,0 +1,2 @@ +# Visualization +DB-GPT provides rich visualization capabilities, which are developed independently as reusable modules in the [GPT-Vis](https://github.com/eosphoros-ai/GPT-Vis) project \ No newline at end of file diff --git a/docs/getting_started/observability.md b/docs/docs/operation_manual/advanced_tutorial/debugging.md similarity index 94% rename from docs/getting_started/observability.md rename to docs/docs/operation_manual/advanced_tutorial/debugging.md index 33b2a4017..1a4cc1317 100644 --- a/docs/getting_started/observability.md +++ b/docs/docs/operation_manual/advanced_tutorial/debugging.md @@ -1,29 +1,28 @@ # Debugging -------------- +DB-GPT provides a series of tools to help developers troubleshoot and solve some problems they may encounter. -DB-GPT provides a set of tools to help you troubleshoot and resolve some of the issues you may encounter. +## Trace log +DB-GPT writes some key system runtime information to trace logs. By default, they are located in `logs/dbgpt*.jsonl`. -## Trace Logs - -DB-GPT writes some critical system runtime information to trace logs. By default, these are located in `logs/dbgpt*.jsonl`. - -DB-GPT also offers a command-line tool, `dbgpt trace`, to help you analyze these trace logs. You can see its specific usage with the command `dbgpt trace --help`. +DB-GPT also provides a command line tool `dbgpt trace` to help analyze these trace logs. You can check the specific usage through the following command: -## Viewing Chat Details +```python +dbgpt trace --help +``` -You can use the `dbgpt trace chat` command to view chat details. By default, it will display the latest chat message. +## View chat details +You can view chat details through the `dbgpt trace chat` command. By default, the latest conversation information is displayed. -### Viewing Service Runtime Information -```bash +## View service runtime information +```python dbgpt trace chat --hide_conv ``` -You will see an output like: - -``` +The output is as follows: +```python +------------------------+--------------------------+-----------------------------+------------------------------------+ | Config Key (Webserver) | Config Value (Webserver) | Config Key (EmbeddingModel) | Config Value (EmbeddingModel) | +------------------------+--------------------------+-----------------------------+------------------------------------+ @@ -57,15 +56,12 @@ You will see an output like: +--------------------------+-----------------------------+----------------------------+------------------------------+ ``` -### Viewing the Latest Chat Message - -```bash +## View latest conversation information +```python dbgpt trace chat --hide_run_params ``` - -You will see an output like: - -``` +The output is as follows: +```python +-------------------------------------------------------------------------------------------------------------------------------------------+ | Chat Trace Details | +----------------+--------------------------------------------------------------------------------------------------------------------------+ @@ -88,16 +84,12 @@ You will see an output like: +----------------+--------------------------------------------------------------------------------------------------------------------------+ ``` - -### Viewing Chat Details and Call Chain - -```bash +## View chat details and call chain +```python dbgpt trace chat --hide_run_params --tree ``` - -You will see an output like: - -``` +The output is as follows: +```python Invoke Trace Tree: @@ -137,15 +129,13 @@ Operation: DB-GPT-Web-Entry (Start: 2023-10-12 03:06:43.180, End: 2023-10-12 03: +----------------+--------------------------------------------------------------------------------------------------------------------------+ ``` -### Viewing Chat Details Based on trace_id +## View chat details based on trace_id -```bash +```python dbgpt trace chat --hide_run_params --trace_id ec30d733-7b35-4d61-b02e-2832fd2e29ff ``` - -You will see an output like: - -``` +The output is as follows: +```python +-------------------------------------------------------------------------------------------------------------------------------------------+ | Chat Trace Details | +----------------+--------------------------------------------------------------------------------------------------------------------------+ @@ -169,13 +159,13 @@ You will see an output like: +----------------+--------------------------------------------------------------------------------------------------------------------------+ ``` -### More `chat` Usage +## More chat command usage -```bash +```python +# command dbgpt trace chat --help -``` -``` +# output Usage: dbgpt trace chat [OPTIONS] [FILES]... Show conversation details @@ -191,15 +181,12 @@ Options: --help Show this message and exit. ``` -## Viewing Call Tree Based on `trace_id` - -```bash -dbgpt trace tree --trace_id ec30d733-7b35-4d61-b02e-2832fd2e29ff -``` - -You will see an output like: - +## View the call tree based on trace_id +```python +dbgpt trace chat --help ``` +The output is as follows: +```python Operation: DB-GPT-Web-Entry (Start: 2023-10-12 03:22:10.592, End: None) Operation: get_chat_instance (Start: 2023-10-12 03:22:10.594, End: None) Operation: get_chat_instance (Start: 2023-10-12 03:22:10.594, End: 2023-10-12 03:22:10.658) @@ -217,17 +204,14 @@ Operation: DB-GPT-Web-Entry (Start: 2023-10-12 03:22:10.592, End: 2023-10-12 03: ``` -## Listing Trace Information - -### Listing All Trace Information - - -```bash +## List trace information +List all Trace information +```python dbgpt trace list ``` +The output is as follows: -You will see an output like: -``` +```python +--------------------------------------+---------------------------------------------------------------------------+-----------------------------------+------------------+ | Trace ID | Span ID | Operation Name | Conversation UID | +--------------------------------------+---------------------------------------------------------------------------+-----------------------------------+------------------+ @@ -240,14 +224,10 @@ You will see an output like: +--------------------------------------+---------------------------------------------------------------------------+-----------------------------------+------------------+ ``` -### Listing Trace Information by Trace Type - -```bash +## View trace information based on trace type +```python dbgpt trace list --span_type chat -``` -You will see an output like: -``` +--------------------------------------+---------------------------------------------------------------------------+-------------------+--------------------------------------+ | Trace ID | Span ID | Operation Name | Conversation UID | +--------------------------------------+---------------------------------------------------------------------------+-------------------+--------------------------------------+ @@ -258,14 +238,11 @@ You will see an output like: +--------------------------------------+---------------------------------------------------------------------------+-------------------+--------------------------------------+ ``` -### Searching Trace Information +## Search trace information -```bash +```python dbgpt trace list --search Hello -``` -You will see an output like: -``` +--------------------------------------+---------------------------------------------------------------------------+----------------------------------------------+--------------------------------------+ | Trace ID | Span ID | Operation Name | Conversation UID | +--------------------------------------+---------------------------------------------------------------------------+----------------------------------------------+--------------------------------------+ @@ -278,13 +255,12 @@ You will see an output like: +--------------------------------------+---------------------------------------------------------------------------+----------------------------------------------+--------------------------------------+ ``` -### More `list` Usage -```bash +## More list related command usage + +```python dbgpt trace list --help -``` -``` Usage: dbgpt trace list [OPTIONS] [FILES]... List your trace spans diff --git a/docs/docs/operation_manual/advanced_tutorial/rag.md b/docs/docs/operation_manual/advanced_tutorial/rag.md new file mode 100644 index 000000000..49fb831f7 --- /dev/null +++ b/docs/docs/operation_manual/advanced_tutorial/rag.md @@ -0,0 +1 @@ +# RAG Parameter Adjustment \ No newline at end of file diff --git a/docs/docs/operation_manual/advanced_tutorial/smmf.md b/docs/docs/operation_manual/advanced_tutorial/smmf.md new file mode 100644 index 000000000..192ad21b1 --- /dev/null +++ b/docs/docs/operation_manual/advanced_tutorial/smmf.md @@ -0,0 +1 @@ +# SMMF \ No newline at end of file diff --git a/docs/docs/operation_manual/fine_tuning_manual/text_to_sql.md b/docs/docs/operation_manual/fine_tuning_manual/text_to_sql.md new file mode 100644 index 000000000..1f3397686 --- /dev/null +++ b/docs/docs/operation_manual/fine_tuning_manual/text_to_sql.md @@ -0,0 +1,193 @@ +# Text2SQL Fine-Tuning +We have split the Text2SQL-related fine-tuning code into the `DB-GPT-Hub `sub-project, and you can also view the source code directly. + +## Fine-tune pipline + +Text2SQL pipline mainly includes the following processes: +- [Build environment](#build-environment) +- [Data processing](#data-processing) +- [Model train](#model-train) +- [Model merge](#model-merge) +- [Model predict](#model-predict) +- [Model evaluation](#model-evaluation) + + +## Build environment +We recommend using the conda virtual environment to build a Text2SQL fine-tuning environment + +```python +git clone https://github.com/eosphoros-ai/DB-GPT-Hub.git +cd DB-GPT-Hub +conda create -n dbgpt_hub python=3.10 +conda activate dbgpt_hub +conda install -c conda-forge poetry>=1.4.0 +poetry install +``` + +The current project supports multiple LLMs and can be downloaded on demand. In this tutorial, we use `CodeLlama-13b-Instruct-hf` as the base model. The model can be downloaded from platforms such as [HuggingFace](https://huggingface.co/) and [Modelscope](https://modelscope.cn/models). Taking HuggingFace as an example, the download command is: +```python +cd Your_model_dir +git lfs install +git clone git@hf.co:codellama/CodeLlama-13b-Instruct-hf +``` + +## Data processing + +### Data collection +The case data of this tutorial mainly uses the `Spider` dataset as an example: +- introduction: the `Spider` dataset is recognized as the most difficult large-scale cross-domain evaluation list in the industry. It contains 10,181 natural language questions and 5,693 SQL statements, involving more than 200 databases in 138 different fields. +- download: [download](https://drive.google.com/uc?export=download&id=1TqleXec_OykOYFREKKtschzY29dUcVAQ) the data set to the project directory, which is located in `dbgpt_hub/data/spider`. + +### Data processing +The project uses the information matching generation method for data preparation, that is, the `SQL + Repository` generation method that combines table information. This method combines the data table information to better understand the structure and relationship of the data table, and to better generate SQL that meets the needs. + +The project has encapsulated the relevant processing code in the corresponding script. You can directly run the script command with one click. The generated training sets `example_text2sql_train.json` and `example_text2sql_dev.json` will be obtained in the `dbgpt_hub/data/` directory. + +```python +# Generate train data and dev(eval) data +sh dbgpt_hub/scripts/gen_train_eval_data.sh +``` +There are `8659` items in the training set and `1034` items in the dev set. The generated training set data format is as follows: +```json +{ + "db_id": "department_management", + "instruction": "I want you to act as a SQL terminal in front of an example database, you need only to return the sql command to me.Below is an instruction that describes a task, Write a response that appropriately completes the request.\n\"\n##Instruction:\ndepartment_management contains tables such as department, head, management. Table department has columns such as Department_ID, Name, Creation, Ranking, Budget_in_Billions, Num_Employees. Department_ID is the primary key.\nTable head has columns such as head_ID, name, born_state, age. head_ID is the primary key.\nTable management has columns such as department_ID, head_ID, temporary_acting. department_ID is the primary key.\nThe head_ID of management is the foreign key of head_ID of head.\nThe department_ID of management is the foreign key of Department_ID of department.\n\n", + "input": "###Input:\nHow many heads of the departments are older than 56 ?\n\n###Response:", + "output": "SELECT count(*) FROM head WHERE age > 56", + "history": [] +} +``` + +Configure the training data file in `dbgpt_hub/data/dataset_info.json`. The value of the corresponding key in the json file defaults to `example_text2sql`. This value is the value that needs to be passed in for the parameter `--dataset` in the subsequent training script train_sft. The `file_name` in json The value is the file name of the training set. + + +### Code interpretation +The core code of data processing is mainly in `dbgpt_hub/data_process/sql_data_process.py`. The core processing class is `ProcessSqlData()`, and the core processing function is `decode_json_file()`. + +`decode_json_file()` first processes the table information in the `Spider` data into a dictionary format. The `key` and `value` are respectively the `db_id` and the `table` and `column` information corresponding to the `db_id` into the required format, for example: +```json +{ + "department_management": department_management contains tables such as department, head, management. Table department has columns such as Department_ID, Name, Creation, Ranking, Budget_in_Billions, Num_Employees. Department_ID is the primary key.\nTable head has columns such as head_ID, name, born_state, age. head_ID is the primary key.\nTable management has columns such as department_ID, head_ID, temporary_acting. department_ID is the primary key.\nThe head_ID of management is the foreign key of head_ID of head.\nThe department_ID of management is the foreign key of Department_ID of department. +} +``` +Then fill the `{}` part of `INSTRUCTION_PROMPT` in the config file with the above text to form the final instruction. `INSTRUCTION_PROMPT` is as follows: +```json +INSTRUCTION_PROMPT = "I want you to act as a SQL terminal in front of an example database, you need only to return the sql command to me.Below is an instruction that describes a task, Write a response that appropriately completes the request.\n ##Instruction:\n{}\n" +``` + +Finally, the question and query corresponding to each `db_id`in the training set and validation set are processed into the format required for model SFT training, that is, the data format shown in the execution part of the data processing code above. + + +:::info note +If you want to collect more data for training yourself, you can use the relevant code of this project to process it according to the above logic. +::: + + +## Model train +For the sake of simplicity, this reproduction tutorial uses LoRA fine-tuning to run directly as an example, but project fine-tuning can support not only `LoRA` but also `QLoRA` and [deepspeed](https://github.com/microsoft/DeepSpeed) acceleration. The detailed parameters of the training script `dbgpt_hub/scripts/train_sft.sh` are as follows: + +```json +CUDA_VISIBLE_DEVICES=0 python dbgpt_hub/train/sft_train.py \ + --model_name_or_path Your_download_CodeLlama-13b-Instruct-hf_path \ + --do_train \ + --dataset example_text2sql_train \ + --max_source_length 2048 \ + --max_target_length 512 \ + --finetuning_type lora \ + --lora_target q_proj,v_proj \ + --template llama2 \ + --lora_rank 64 \ + --lora_alpha 32 \ + --output_dir dbgpt_hub/output/adapter/code_llama-13b-2048_epoch8_lora \ + --overwrite_cache \ + --overwrite_output_dir \ + --per_device_train_batch_size 1 \ + --gradient_accumulation_steps 16 \ + --lr_scheduler_type cosine_with_restarts \ + --logging_steps 50 \ + --save_steps 2000 \ + --learning_rate 2e-4 \ + --num_train_epochs 8 \ + --plot_loss \ + --bf16 +``` + +Introduction to key parameters and meanings in train_sft.sh: +- `model_name_or_path` : Path to the LLM model used. +- `dataset`: The value is the configuration name of the training data set, corresponding to the outer key value in `dbgpt_hub/data/dataset_info.json`, such as `example_text2sql`. +- `max_source_length`: Enter the text length of the model. The effect parameter of this tutorial is `2048`, which is the optimal length after multiple experiments and analysis. +- `max_target_length`: The sql content length of the output model, set to `512`. +- `template`: The lora part of different model fine-tuning in the project settings. For the Llama2 series models, it is set to `llama2`. +- `lora_target`: The network parameter changing part during LoRA fine-tuning. +- `finetuning_type`: Finetuning type, the value is `[ptuning, lora, freeze, full]`, etc. +- `lora_rank`: Rank size in LoRA fine-tuning. +- `lora_alpha`: scaling factor in LoRA fine-tuning. +- `output_dir`: The path output by the Peft module during SFT fine-tuning. The default setting is under the `dbgpt_hub/output/adapter/` path. +- `per_device_train_batch_size`: The batch of training samples on each GPU. If the computing resources support it, it can be set to larger. The default is `1`. +- `gradient_accumulation_steps`: The accumulated steps value of gradient update. +- `lr_scheduler_type`: learning rate type. +- `logging_steps`: steps interval for log saving. +- `save_steps`: The steps size value of ckpt saved by the model. +- `num_train_epochs`: The number of epochs of training data. +- `learning_rate`: learning rate, the recommended learning rate is `2e-4`. + +If you want to train based on `QLoRA`, you can add the parameter quantization_bit to the script to indicate whether to quantize. The value is `[4 or 8]` to enable quantization. +If you want to fine-tune different LLMs, the key parameters `lora_target` and `template` corresponding to different models can be changed by referring to the relevant content in the project's `README.md`. + +## Model merge + + +## Model predict +After the model training is completed, to predict the trained model, you can directly run `predict_sft.sh` in the project script directory. + +Prediction run command: +```python +sh ./dbgpt_hub/scripts/predict_sft.sh +``` + +In the project directory `./dbgpt_hub/output/pred/`, this file path is the location of the default output of the model prediction results (if it does not exist, it needs to be created). The detailed parameters in `predict_sft.sh` for this tutorial are as follows: +```python + +echo " predict Start time: $(date)" +## predict +CUDA_VISIBLE_DEVICES=0 python dbgpt_hub/predict/predict.py \ + --model_name_or_path Your_download_CodeLlama-13b-Instruct-hf_path \ + --template llama2 \ + --finetuning_type lora \ + --checkpoint_dir Your_last_peft_checkpoint-4000 \ + --predicted_out_filename Your_model_pred.sql + +echo "predict End time: $(date)" +``` +The value of the parameter `--predicted_out_filename` is the file name of the result predicted by the model, and the results can be found in the `dbgpt_hub/output/pred` directory. + + +## Model evaluation +For the evaluation of the model's effect on the dataset, the default is on the `Spider` dataset. Run the following command: + +```python +python dbgpt_hub/eval/evaluation.py --plug_value --input Your_model_pred.sql +``` + +The results generated by large models have a certain degree of randomness because they are closely related to parameters such as `temperature` (can be adjusted in `GeneratingArguments` in `/dbgpt_hub/configs/model_args.py`). By default, the execution accuracy of our multiple evaluations is `0.789` and above. We have placed some of the experimental and evaluation results in the project `docs/eval_llm_result.md` for reference only. + + +`DB-GPT-Hub` uses `LoRA` to fine-tune the weight file on `Spider`'s training set based on the LLM of `CodeLlama-13b-Instruct-hf`. The weight file has been released. Currently, it has achieved an execution accuracy of about `0.789` on the `Spider`'s evaluation set. The weight file `CodeLlama-13b-sql-lora` is available on [HuggingFace](https://huggingface.co/eosphoros). + + +## Appendix +The experimental environment of this article is based on a graphics card server with `A100 (40G)`, and the total training time is about 12 hours. If your machine resources are insufficient, you can give priority to reducing the value of the parameter `gradient_accumulation_steps`. In addition, you can consider using `QLoRA` to fine-tune (add `--quantization_bit 4` to the training script `dbgpt_hub/scripts/train_sft.sh`). From our experience, `QLoRA` At `8` epochs, the results are not much different from the `LoRA` fine-tuning results. + +# test + + +The output is as follows: + + +```python +dbgpt trace --help +``` + +:::info note + +::: diff --git a/docs/docs/operation_manual/started_tutorial/agent.md b/docs/docs/operation_manual/started_tutorial/agent.md new file mode 100644 index 000000000..173617e6d --- /dev/null +++ b/docs/docs/operation_manual/started_tutorial/agent.md @@ -0,0 +1,62 @@ +# Data Agent + +Regarding the use of plugin(data agent), the current project supports basic plugin warehouses and plugin expansion capabilities. The project currently has a built-in search plugin. Let's experience the basic usage of the plugin. + +## Steps +The use of the default plugin mainly includes the following steps. For more advanced features, you can follow the subsequent advanced tutorials. +- 1.Enter the plugin market +- 2.View the list of plugins in the GitHub repository +- 3.Download the plugin +- 4.Select Data Agent +- 5.Start chat + +### View plugin list +First, you can click the `Update GitHub plugin` button, and the plugin list in the [GitHub plugin repository](https://github.com/eosphoros-ai/DB-GPT-Plugins) will automatically be displayed here. + + +

+ +

+ +### Download plugin + +Click the `download` button to download the plugin locally + +

+ +

+ +After the download is successful, you can see the plugin list in the my plugin interface. Of course, it also supports uploading models through local upload. + +

+ +

+ + +### Select `Data Agent` +Select the plugin dialog to enable plugin use. + +

+ +

+ + +### Configure cookies + +Before starting to use the default search plugin, you need to configure cookies. For detailed configuration tutorials, see the [plugin description](https://github.com/eosphoros-ai/DB-GPT-Plugins/tree/main/src/dbgpt_plugins/search_engine). + +Specify the corresponding cookie configuration items in the `.env` file to complete the configuration. + + +### Start chat +After configuring cookies, we can start using the plugin. + +

+ +

+ + +:::info note + +For more plugin expansion and advanced gameplay, welcome to [communicate](https://github.com/eosphoros-ai/DB-GPT/issues) with us. +::: diff --git a/docs/docs/operation_manual/started_tutorial/chat_dashboard.md b/docs/docs/operation_manual/started_tutorial/chat_dashboard.md new file mode 100644 index 000000000..af4f2ecff --- /dev/null +++ b/docs/docs/operation_manual/started_tutorial/chat_dashboard.md @@ -0,0 +1,64 @@ +# Chat Dashboard + +Report analysis corresponds to the `Chat Dashboard` scenario in DB-GPT, and intelligent report generation and analysis can be performed through natural language. It is one of the basic capabilities of generative BI (GBI). Let's take a look at how to use the report analysis capabilities. + +## Steps +The following are the steps for using report analysis: +- 1.Data preparation +- 2.Add data source +- 3.Select Chat Dashboard +- 4.Start chat + + +### Data preparation + +In order to better experience the report analysis capabilities, we have built some test data into the code. To use this test data, we first need to create a test library. +```SQL +CREATE DATABASE IF NOT EXISTS dbgpt_test CHARACTER SET utf8; +``` + +After the test library is created, you can initialize the test data with one click through the script. + +```python +python docker/examples/dashboard/test_case_mysql_data.py +``` + +### Add data source + +The steps to add a data source are the same as [Chat Data](/docs/operation_manual/started_tutorial/chat_data.mdx). Select the corresponding database type in the data source management tab, then create it. Fill in the necessary information to complete the creation. + +

+ +

+ + + +### Select Chat Dashboard + +After the data source is added, select `Chat Dashboard` on the home scene page to perform report analysis. + +

+ +

+ + + +### Start chat +Enter specific questions in the dialog box on the right to start a data conversation. + +

+ +

+ + + +:::info note + +⚠️ Data dialogue has relatively high requirements on model capabilities, and `ChatGPT/GPT-4` has a high success rate. Other open source models you can try `Vicuna-13B` +::: + +Of course, in addition to `preview mode`, `editor mode` is also provided. In editor mode, SQL can be edited and modified. You can see the changes in the chart synchronously. + +

+ +

diff --git a/docs/docs/operation_manual/started_tutorial/chat_data.md b/docs/docs/operation_manual/started_tutorial/chat_data.md new file mode 100644 index 000000000..a283b2048 --- /dev/null +++ b/docs/docs/operation_manual/started_tutorial/chat_data.md @@ -0,0 +1,64 @@ +# Chat Data +Chat data capability is to dialogue with data through natural language. Currently, it is mainly dialogue between structured and semi-structured data, which can assist in data analysis and insight. + +:::info note + +Before starting the data conversation, we first need to add the data source +::: + +## steps + +To start a data conversation, you need to go through the following steps: +- 1.Add data source +- 2.Select ChatData +- 3.Select the corresponding database +- 4.Start a conversation + + +### Add data source + +First, select the `data source` on the left to add and add a database. Currently, DB-GPT supports multiple database types. Just select the corresponding database type to add. Here we choose MySQL as a demonstration. For the test data of the demonstration, see the [test sample](https://github.com/eosphoros-ai/DB-GPT/tree/main/docker/examples/sqls). + + +

+ +

+ + + +### Choose ChatData + +

+ +

+ +### Start a conversation + + +:::info note + +⚠️ Pay attention to selecting the corresponding model and database during the dialogue. At the same time, DB-GPT also provides preview mode and editing mode. +::: + + +:::tip + +preview mode +::: + + +

+ +

+ + + +:::tip + +editing mode +::: + +

+ +

+ diff --git a/docs/docs/operation_manual/started_tutorial/chat_db.md b/docs/docs/operation_manual/started_tutorial/chat_db.md new file mode 100644 index 000000000..c4656ff47 --- /dev/null +++ b/docs/docs/operation_manual/started_tutorial/chat_db.md @@ -0,0 +1,82 @@ +# Chat DB + +The purpose of `Chat DB` is to create professional database experts, positioned as LLM As DBA, who can complete database performance analysis, optimization and other work by talking to the database. Currently, ChatDB only has some basic capabilities, which will be gradually enhanced with the iteration of the community. + + +## Steps + +The Chat DB usage process mainly includes the following steps: +- 1.Select Chat DB +- 2.Add data source (talk to data) +- 3.Select the basic model and database +- 4.Start chat + +### Select Chat DB + +

+ +

+ + + +### Select DataBase + +

+ +

+ + +### Start Chat + +:::tip + +Single table query +::: + +

+ +

+ +:::tip + +Multi-table query +::: + +

+ +

+ +:::tip + +Index optimization suggestions +::: + +

+ +

+ + +:::tip + +Database problem diagnosis +::: + +

+ +

+ + +:::tip + +Troubleshoot slow queries +::: + +

+ +

+ + +:::danger Note + +⚠️ The examples provided above are for demonstration only. The model output results are from open source models and ChatGPT agents. They have not been fine-tuned or targeted optimized. They are for reference only and are not guaranteed to be absolutely correct. +::: diff --git a/docs/docs/operation_manual/started_tutorial/chat_excel.md b/docs/docs/operation_manual/started_tutorial/chat_excel.md new file mode 100644 index 000000000..cb1a2ccaf --- /dev/null +++ b/docs/docs/operation_manual/started_tutorial/chat_excel.md @@ -0,0 +1,56 @@ +# Chat Excel + +Chat Excel means that you can interpret and analyze Excel data through natural language dialogue. + + +

+ +

+ + +## Steps + +The steps to use Chat Excel are relatively simple and are mainly divided into the following steps: +- 1.Select Chat Excel dialogue scene +- 2.Upload Excel document +- 3.Start chat + +### Select `Chat Excel` + + +

+ +

+ +### Upload Excel document + + +:::info note + +⚠️ the Excel file format is converted to `.csv` format +::: + +

+ +

+ +After the upload is successful, the content will be summarized by default and some questioning strategies will be recommended. + +

+ +

+ +### Start chat + +You can then start a conversation based on the uploaded file. + +

+ +

+ + +Use open source models + +

+ +

diff --git a/docs/docs/operation_manual/started_tutorial/chat_knowledge.md b/docs/docs/operation_manual/started_tutorial/chat_knowledge.md new file mode 100644 index 000000000..6dae5b03f --- /dev/null +++ b/docs/docs/operation_manual/started_tutorial/chat_knowledge.md @@ -0,0 +1,76 @@ +# Chat Knowledge + +`Chat knowledge` provides the ability to question and answer questions based on private domain knowledge, and can build intelligent question and answer systems, reading assistants and other products based on the `knowledge base`. `RAG` technology is also used in DB-GPT to enhance knowledge retrieval. + + +## Noun explanation + + +:::info note + +`Knowledge Space`: is a document space that manages a type of knowledge. Document knowledge of the same type can be uploaded to a knowledge space. +::: + + +## Steps +The knowledge base operation process is relatively simple and is mainly divided into the following steps. +- 1.Create knowledge space +- 2.Upload documents +- 3.Wait for document vectorization +- 4.Knowledge base chat + + +### Create knowledge space + +Select the knowledge base, click the `Create` button, and fill in the necessary information to complete the creation of the knowledge space. + + + +

+ +

+ + +### Upload documents + +Document addition currently supports multiple types, such as plain text, URL crawling, and various document types such as PDF, Word, and Markdown. Select a specific document to `upload`. + +

+ +

+ + +Select the corresponding document and click `Finish`. + + +

+ +

+ + +### Waiting for document vectorization + +Click on the `knowledge space` and observe the document `slicing` + `vectorization` status in the lower left corner. When the status reaches `FINISHED`, you can start a knowledge base conversation. + + +

+ +

+ + +### Knowledge base chat + +Click the `Chat`button to start a conversation with the knowledge base. + + +

+ +

+ + +### Reading assistant +In addition to the above capabilities, you can also upload documents directly in the knowledge base dialogue window, and the document will be summarized by default. This capability can be used as a `reading assistant` to assist document reading. + +

+ +

\ No newline at end of file diff --git a/docs/docs/overview.md b/docs/docs/overview.md new file mode 100644 index 000000000..d0e84c766 --- /dev/null +++ b/docs/docs/overview.md @@ -0,0 +1,85 @@ +--- +sidebar_position: 0 +--- + +# Overview +DB-GPT is an **open-source framework for large language models(LLMs) in the databases fields**. It's purpose is to build infrastructure for the domain of large language models, making it easier and more convenient to develop applications around databases by developing various technical capabilities such as: + +- **SMMF(Service-oriented Multi-model Management Framework)** +- **Text2SQL Fine-tuning** +- **RAG(Retrieval Augmented Generation) Framework and Optimization** +- **Data-Driven Agents Framework Collaboration** + +In the Data 3.0 era, enterprises/developers can build their own exclusive applications with less code based on LLMs and databases. + +

+ +

+ + +## Features + +##### Private Domain Q&A & Data Processing & RAG +- Supports custom construction of knowledge bases through methods such as built-in, multi-file format uploads, and plugin-based web scraping. Enables unified vector storage and retrieval of massive structured and unstructured data. + +##### Multi-Data Source & GBI(Generative Business Intelligence) +- Supports interaction between natural language and various data sources such as Excel, databases, and data warehouses. Also supports analysis reporting. + +##### SMMF(Service-oriented Multi-model Management Framework) +- Supports a wide range of models, including dozens of large language models such as open-source models and API proxies. Examples include LLaMA/LLaMA2, Baichuan, ChatGLM, ERNIE Bot, Qwen, Spark, etc. + +##### Automated Fine-tuning +- Supports Text2SQL fine-tuning. Provides a lightweight automatic fine-tuning framework around the fields of LLM and Text2SQL, supporting methods such as LoRA/QLoRA/P-turning, making Text2SQL fine-tuning as convenient as a production line. +##### Data-Driven Multi-Agents & Plugins +- Supports executing tasks through custom plugins and natively supports the Auto-GPT plugin model. [Agents protocol](https://agentprotocol.ai/) follows the Agent Protocol standard. + +##### Privacy and Security +- Supports data privacy protection. Ensures data privacy and security through techniques such as privatizing large language models and proxy de-identification. + +## Getting Started + + - [Quickstart](/docs/quickstart) + - [Installation](/docs/installation) + + +## Terminology + +| terminology | Description | +|----------------------|---------------------------------------------------------------| +|
`DB-GPT`
| DataBase Generative Pre-trained Transformer, an open source framework around databases and large language models | +|
`Text2SQL/NL2SQL`
| Text to SQL uses large language model capabilities to generate SQL statements based on natural language, or provide explanations based on SQL statements | +|
`KBQA`
| Knowledge-Based Q&A system | +|
`GBI`
| Generative Business Intelligence, based on large language models and data analysis, provides business intelligence analysis and decision-making through dialogue | +|
`LLMOps`
| A large language model operation framework that provides a standard end-to-end workflow for training, tuning, deploying, and monitoring LLM to accelerate application deployment of generated AI models | +|
`Embedding`
| Methods to convert text, audio, video and other materials into vectors | +|
`RAG`
| Retrieval Augmented Generation | + +## Use Cases + +- [Use Cases](/docs/use_cases) + +## Modules + +#### [SMMF](/docs/modules/smmf) +Service-oriented Multi-model Management Framework + +#### [Retrieval](/docs/modules/rag) +Multi-Knowledge Enhanced Retrieval-Augmented Generation Framework + +#### [Agents](/docs/modules/agent) +Data Driven Multi-Agents + +#### [Fine-tuning](/docs/modules/fine_tuning) +Fine-tuning module for Text2SQL/Text2DSL + + +## More + +- [Connections](/docs/modules/connections) +Connect various data sources + +- [Obvervablity](/docs/operation_manual/advanced_tutorial/debugging) +Observing & monitoring + +- [Evaluation](/docs/modules/eval) +Evaluate framework performance and accuracy \ No newline at end of file diff --git a/docs/docs/quickstart.md b/docs/docs/quickstart.md new file mode 100644 index 000000000..cb2cad58a --- /dev/null +++ b/docs/docs/quickstart.md @@ -0,0 +1,156 @@ +--- +sidebar_position: 0 +--- + +# Quickstart +DB-GPT supports the installation and use of a variety of open source and closed models. Different models have different requirements for environment and resources. If localized model deployment is required, GPU resources are required for deployment. The API proxy model requires relatively few resources and can be deployed and started on a CPU machine. + + +:::info note +- Detailed installation and deployment tutorials can be found in [Installation](/docs/installation). +- This page only introduces deployment based on ChatGPT proxy and local Vicuna model. +::: + +## Environmental preparation + +### Download source code + +:::tip +Download DB-GPT +::: + + + +```python +git clone https://github.com/eosphoros-ai/DB-GPT.git +``` + +### Miniconda environment installation + +- The default database uses SQLite, so there is no need to install a database in the default startup mode. If you need to use other databases, you can read the [advanced tutorials](/docs/operation_manual/advanced_tutorial/rag) below. We recommend installing the Python virtual environment through the conda virtual environment. For the installation of Miniconda environment, please refer to the [Miniconda installation tutorial](https://docs.conda.io/projects/miniconda/en/latest/). + +:::tip +Create a Python virtual environment +::: + +```python +python >= 3.10 +conda create -n dbgpt_env python=3.10 +conda activate dbgpt_env + +# it will take some minutes +pip install -e ".[default]" +``` + +:::tip +Copy environment variables +::: +```python +cp .env.template .env +``` + +## Model deployment + +:::info note + +Provide two deployment methods to quickly start experiencing DB-GPT. + +::: + +### Method 1. OpenAI agent mode deployment +:::info note + +⚠️ You need to ensure that git-lfs is installed +```python +● CentOS installation: yum install git-lfs +● Ubuntu installation: apt-get install git-lfs +● MacOS installation: brew install git-lfs +``` +::: + +#### Install dependencies + +```python +pip install -e ".[openai]" +``` + +#### Download embedding model + +```python +cd DB-GPT +mkdir models and cd models +git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese +``` + +#### Configure the proxy and modify LLM_MODEL, PROXY_API_URL and API_KEY in the `.env`file + +```python +# .env +LLM_MODEL=chatgpt_proxyllm +PROXY_API_KEY={your-openai-sk} +PROXY_SERVER_URL=https://api.openai.com/v1/chat/completions +``` + + +### Method 2. Vicuna local deployment + +#### Hardware requirements description +| Model | Quantize | VRAM Size | +|:----------------------------------------:|--------------:|---------------| +|Baichuan-7b | 4-bit | 8GB | +|Baichuan-7b | 8-bit | 12GB | +|Baichuan-13b | 4-bit | 12GB | +|Baichuan-13b | 8-bit | 20GB | + +#### Download LLM + +```python +cd DB-GPT +mkdir models and cd models + +# embedding model +git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese +or +git clone https://huggingface.co/moka-ai/m3e-large + +# llm model, if you use openai or Azure or tongyi llm api service, you don't need to download llm model +git clone https://huggingface.co/lmsys/vicuna-13b-v1.5 + +``` +#### Environment variable configuration, configure the LLM_MODEL parameter in the `.env` file +```python +# .env +LLM_MODEL=vicuna-13b-v1.5 +``` + + +## Test data (optional) +Load default test data into SQLite database +- **Linux** + +```python +bash ./scripts/examples/load_examples.sh +``` +- **Windows** + +```python +.\scripts\examples\load_examples.bat +``` + +## Run service + +```python +python pilot/server/dbgpt_server.py +``` + + +## Visit website +Open the browser and visit [`http://localhost:5000`](http://localhost:5000) + + + + + + + + diff --git a/docs/docs/use_cases.md b/docs/docs/use_cases.md new file mode 100644 index 000000000..9ec7aa212 --- /dev/null +++ b/docs/docs/use_cases.md @@ -0,0 +1 @@ +# Use Cases \ No newline at end of file diff --git a/docs/docusaurus.config.js b/docs/docusaurus.config.js new file mode 100755 index 000000000..c3eff6384 --- /dev/null +++ b/docs/docusaurus.config.js @@ -0,0 +1,247 @@ +// @ts-check +// Note: type annotations allow type checking and IDEs autocompletion + +const { ProvidePlugin } = require("webpack"); +const path = require("path"); +const lightCodeTheme = require('prism-react-renderer/themes/github'); +const darkCodeTheme = require('prism-react-renderer/themes/dracula'); + +/** @type {import('@docusaurus/types').Config} */ +const config = { + title: 'DB-GPT', + tagline: 'Revolutionizing Database Interactions with Private LLM Technology', + favicon: 'img/eosphoros.jpeg', + + // Set the production url of your site here + url: 'http://docs.dbgpt.site', + // Set the // pathname under which your site is served + // For GitHub pages deployment, it is often '//' + baseUrl: '/', + + // GitHub pages deployment config. + // If you aren't using GitHub pages, you don't need these. + organizationName: 'eosphoros-ai', // Usually your GitHub org/user name. + projectName: 'DB-GPT', // Usually your repo name. + + onBrokenLinks: 'warn', + onBrokenMarkdownLinks: 'warn', + + // Even if you don't use internalization, you can use this field to set useful + // metadata like html lang. For example, if your site is Chinese, you may want + // to replace "en" with "zh-Hans". + i18n: { + defaultLocale: 'en', + locales: ['en', 'zh-CN'], + }, + + scripts: [ + { + src: '/redirect.js', + async: true, + }, + ], + + plugins: [ + () => ({ + name: "custom-webpack-config", + configureWebpack: () => ({ + plugins: [ + new ProvidePlugin({ + process: require.resolve("process/browser"), + }), + ], + resolve: { + fallback: { + path: false, + url: false, + }, + }, + module: { + rules: [ + { + test: /\.m?js/, + resolve: { + fullySpecified: false, + }, + }, + { + test: /\.py$/, + loader: "raw-loader", + resolve: { + fullySpecified: false, + }, + }, + { + test: /\.ipynb$/, + loader: "raw-loader", + resolve: { + fullySpecified: false, + }, + }, + ], + }, + }), + }), + ], + + presets: [ + [ + 'classic', + /** @type {import('@docusaurus/preset-classic').Options} */ + ({ + docs: { + sidebarPath: require.resolve('./sidebars.js'), + remarkPlugins: [ + [require("@docusaurus/remark-plugin-npm2yarn"), { sync: true }], + ], + + async sidebarItemsGenerator({ + defaultSidebarItemsGenerator, + ...args + }){ + const sidebarItems = await defaultSidebarItemsGenerator(args); + sidebarItems.forEach((subItem) => { + // This allows breaking long sidebar labels into multiple lines + // by inserting a zero-width space after each slash. + if ( + "label" in subItem && + subItem.label && + subItem.label.includes("/") + ){ + subItem.label = subItem.label.replace("/\//g", "\u200B"); + } + }); + return sidebarItems; + } + // Please change this to your repo. + // Remove this to remove the "edit this page" links. + }, + + pages: { + remarkPlugins: [require("@docusaurus/remark-plugin-npm2yarn")], + }, + + theme: { + customCss: require.resolve('./src/css/custom.css'), + }, + }), + ], + ], + + themeConfig: + /** @type {import('@docusaurus/preset-classic').ThemeConfig} */ + ({ + defaultClassicDocs: '/docs/get_started', + // Replace with your project's social card + navbar: { + logo: { + alt: 'DB-GPT Logo', + src: 'img/dbgpt_logo.png', + srcDark: 'img/DB-GPT_LOGO_White.png', + href: "/docs/overview" + }, + + items: [ + { + type: 'docSidebar', + sidebarId: 'tutorialSidebar', + position: 'left', + label: 'Docs', + to: "/docs/overview", + }, + { + type: 'docSidebar', + sidebarId: 'tutorialSidebar', + position: 'left', + label: 'Tutorials', + to: "/docs/tutorials", + }, + // { + // type: 'docSidebar', + // sidebarId: 'tutorialSidebar', + // position: 'left', + // label: 'Community', + // to: "/docs/tutorials", + // }, + { + href: 'https://github.com/eosphoros-ai/community', + position: 'left', + label: "Community", + className: 'header-community-link', + }, + { + href: 'https://github.com/eosphoros-ai/DB-GPT', + position: 'right', + className: 'header-github-link', + }, + { + href: 'https://huggingface.co/eosphoros', + position: 'right', + label: "HuggingFace", + className: 'header-huggingface-link', + }, + { + href: 'https://www.yuque.com/eosphoros/dbgpt-docs/bex30nsv60ru0fmx', + position: 'left', + label: "中文文档", + }, + ], + }, + footer: { + style: 'light', + links: [ + { + title: 'Community', + items: [ + { + label: 'Discord', + href: 'https://discord.gg/erwfqcMP', + }, + { + label: "Dockerhub", + href: "https://hub.docker.com/u/eosphorosai", + }, + ], + }, + { + title: "Github", + items: [ + { + label: 'Github', + href: 'https://github.com/eosphoros-ai/DB-GPT', + }, + { + label: "HuggingFace", + href: "https://huggingface.co/eosphoros" + } + ] + }, + { + title: 'More', + items: [ + { + label: 'Hacker News', + href: 'https://news.ycombinator.com/item?id=36038815', + }, + { + label: 'Twitter', + href: 'https://twitter.com/DbGpt80100', + }, + ], + }, + ], + copyright: `Copyright © ${new Date().getFullYear()} DB-GPT`, + }, + prism: { + theme: lightCodeTheme, + darkTheme: darkCodeTheme, + }, + colorMode: { + defaultMode: 'light', + disableSwitch: false, + respectPrefersColorScheme: false, + }, + }), +}; + +module.exports = config; diff --git a/docs/ecosystem.md b/docs/ecosystem.md deleted file mode 100644 index 9d6bd4150..000000000 --- a/docs/ecosystem.md +++ /dev/null @@ -1 +0,0 @@ -# Ecosystem \ No newline at end of file diff --git a/docs/faq.md b/docs/faq.md deleted file mode 100644 index ddd60bd43..000000000 --- a/docs/faq.md +++ /dev/null @@ -1,138 +0,0 @@ -# FAQ -##### Q1: text2vec-large-chinese not found - -##### A1: make sure you have download text2vec-large-chinese embedding model in right way - -```tip -centos:yum install git-lfs -ubuntu:apt-get install git-lfs -y -macos:brew install git-lfs -``` -```bash -cd models -git lfs clone https://huggingface.co/GanymedeNil/text2vec-large-chinese -``` - -##### Q2: execute `pip install -r requirements.txt` error, found some package cannot find correct version. - - -##### A2: change the pip source. - -```bash -# pypi -$ pip install -r requirements.txt -i https://pypi.python.org/simple -``` - -or - -```bash -# tsinghua -$ pip install -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple/ -``` - -or - -```bash -# aliyun -$ pip install -r requirements.txt -i http://mirrors.aliyun.com/pypi/simple/ -``` - - -##### Q3:Access denied for user 'root@localhost'(using password :NO) - -##### A3: make sure you have installed mysql instance in right way - -Docker: -```bash -docker run --name=mysql -p 3306:3306 -e MYSQL_ROOT_PASSWORD=aa12345678 -dit mysql:latest -``` -Normal: -[download mysql instance](https://dev.mysql.com/downloads/mysql/) - -##### Q4:When I use openai(MODEL_SERVER=proxyllm) to chat -

- -

- -##### A4: make sure your openapi API_KEY is available - -##### Q5:When I Chat Data and Chat Meta Data, I found the error -

- -

![chatdataerror](https://github.com/eosphoros-ai/DB-GPT/assets/13723926/991dbaf5-da42-4c63-a65c-9aa9e174da59) -]() - - -##### A5: you have not create your database and table -1.create your database. -```bash -mysql> create database {$your_name} -mysql> use {$your_name} -``` - -2.create table {$your_table} and insert your data. -eg: -```bash -mysql>CREATE TABLE `users` ( - `id` int NOT NULL AUTO_INCREMENT, - `username` varchar(50) NOT NULL COMMENT '用户名', - `password` varchar(50) NOT NULL COMMENT '密码', - `email` varchar(50) NOT NULL COMMENT '邮箱', - `phone` varchar(20) DEFAULT NULL COMMENT '电话', - PRIMARY KEY (`id`), - KEY `idx_username` (`username`) COMMENT '索引：按用户名查询' -) ENGINE=InnoDB AUTO_INCREMENT=101 DEFAULT CHARSET=utf8mb4 COMMENT='聊天用户表' -``` - -##### Q6:How to change Vector DB Type in DB-GPT. - -##### A6: Update .env file and set VECTOR_STORE_TYPE. -DB-GPT currently support Chroma(Default), Milvus(>2.1), Weaviate vector database. -If you want to change vector db, Update your .env, set your vector store type, VECTOR_STORE_TYPE=Chroma (now only support Chroma and Milvus(>2.1), if you set Milvus, please set MILVUS_URL and MILVUS_PORT) -If you want to support more vector db, you can integrate yourself.[how to integrate](https://db-gpt.readthedocs.io/en/latest/modules/vector.html) -```commandline -#*******************************************************************# -#** VECTOR STORE SETTINGS **# -#*******************************************************************# -VECTOR_STORE_TYPE=Chroma -#MILVUS_URL=127.0.0.1 -#MILVUS_PORT=19530 -#MILVUS_USERNAME -#MILVUS_PASSWORD -#MILVUS_SECURE= - -#WEAVIATE_URL=https://kt-region-m8hcy0wc.weaviate.network -``` -##### Q7:When I use vicuna-13b, found some illegal character like this. -

- -

- -##### A7: set KNOWLEDGE_SEARCH_TOP_SIZE smaller or set KNOWLEDGE_CHUNK_SIZE smaller, and reboot server. - -##### Q8:space add error (pymysql.err.OperationalError) (1054, "Unknown column 'knowledge_space.context' in 'field list'") - - -##### A8: -1.shutdown dbgpt_server(ctrl c) - -2.add column context for table knowledge_space -```commandline -mysql -h127.0.0.1 -uroot -paa12345678 -``` -3.execute sql ddl -```commandline -mysql> use knowledge_management; -mysql> ALTER TABLE knowledge_space ADD COLUMN context TEXT COMMENT "arguments context"; -``` -4.restart dbgpt server - - - - - - - - - diff --git a/docs/getting_started/application.rst b/docs/getting_started/application.rst deleted file mode 100644 index 9af9644dd..000000000 --- a/docs/getting_started/application.rst +++ /dev/null @@ -1,24 +0,0 @@ -Applications -================================== -DB-GPT product is a Web application that you can chat database, chat knowledge, text2dashboard. - -.. image:: https://github.com/eosphoros-ai/DB-GPT/assets/13723926/f6564da2-bed3-43ad-9659-d00e0eeb255b - - -- Chat DB -- Chat Knowledge -- Dashboard -- Plugins - -.. toctree:: - :maxdepth: 2 - :caption: Application - :name: chatdb - :hidden: - - ./application/chatdb/chatdb.md - ./application/kbqa/kbqa.md - ./application/dashboard/dashboard.md - ./application/chatexcel/chatexcel.md - ./application/model/model.md - ./application/chatagent/chatagent.md \ No newline at end of file diff --git a/docs/getting_started/application/chatagent/chatagent.md b/docs/getting_started/application/chatagent/chatagent.md deleted file mode 100644 index 13e1ede73..000000000 --- a/docs/getting_started/application/chatagent/chatagent.md +++ /dev/null @@ -1,28 +0,0 @@ -ChatAgent -================================== -ChatAgent can automatically select the right tool to answer and solve user problems through LLM. -![chat_agent0](https://github.com/eosphoros-ai/DB-GPT/assets/13723926/f6a88ab8-9352-444d-80a3-2d5456cd4286) - -### 1.Update Plugins From Git -Update the latest plug-in information from the DB-GPT official plug-in repository. -Address:https://github.com/eosphoros-ai/DB-GPT-Plugins/tree/main/src/dbgpt_plugins/search_engine - -![agent_hub_1](https://github.com/eosphoros-ai/DB-GPT/assets/13723926/1ae406e2-840d-4e82-92f5-716cf69367e2) - -### 2.Install Plugin -Install the plugin you want to use from the list of agent hub plugins. - -Address:https://github.com/eosphoros-ai/DB-GPT-Plugins/tree/main/src/dbgpt_plugins/search_engine -![agent_hub_1](https://github.com/eosphoros-ai/DB-GPT/assets/13723926/1ae406e2-840d-4e82-92f5-716cf69367e2) - -### 3.Upload My Local Plugin File -If you want to use a private plug-in developed by yourself, you can upload the plug-in first and then use it. - -### 4.Select installed plug-ins dialog -Select an installed plugin to have a conversation. -![chat_agent1](https://github.com/eosphoros-ai/DB-GPT/assets/13723926/f0b94bea-23ab-4ae3-8b45-195e1edafed5) -![chat_agent2](https://github.com/eosphoros-ai/DB-GPT/assets/13723926/eae566ff-2105-4553-9125-9e9cab687377) - -### 5.Uninstall My Plugin -Uninstall plugins you no longer need. -![agent_hub_2](https://github.com/eosphoros-ai/DB-GPT/assets/13723926/1989a9d1-5b52-4c31-8f07-4d676a26ef75) diff --git a/docs/getting_started/application/chatdb/chatdb.md b/docs/getting_started/application/chatdb/chatdb.md deleted file mode 100644 index 12a6aa8b6..000000000 --- a/docs/getting_started/application/chatdb/chatdb.md +++ /dev/null @@ -1,62 +0,0 @@ -ChatData & ChatDB -================================== -ChatData generates SQL from natural language and executes it. ChatDB involves conversing with metadata from the -Database, including metadata about databases, tables, and -fields.![db plugins demonstration](https://github.com/eosphoros-ai/DB-GPT/assets/13723926/d8bfeee9-e982-465e-a2b8-1164b673847e) - -```{admonition} The LLM (Language Model) suitable for the ChatData scene is -* chatgpt3.5. -* chatgpt4. -* Vicuna-v1.5. -``` - -### 1.Choose Datasource - -If you are using DB-GPT for the first time, you need to add a data source and set the relevant connection information -for the data source. - -```{tip} -there are some example data in DB-GPT-NEW/DB-GPT/docker/examples - -you can execute sql script to generate data. -``` - -#### 1.1 Datasource management - -![db plugins demonstration](https://github.com/eosphoros-ai/DB-GPT/assets/13723926/7678f07e-9eee-40a9-b980-5b3978a0ed52) - -#### 1.2 Connection management - -![db plugins demonstration](https://github.com/eosphoros-ai/DB-GPT/assets/13723926/25b8f5a9-d322-459e-a8b2-bfe8cb42bdd6) - -#### 1.3 Add Datasource - -![db plugins demonstration](https://github.com/eosphoros-ai/DB-GPT/assets/13723926/19ce31a7-4061-4da8-a9cb-efca396cc085) - -```{note} -now DB-GPT support Datasource Type - -* Mysql -* Sqlite -* DuckDB -* Clickhouse -* Mssql -* Spark -``` - -### 2.ChatData -##### Preview Mode -After successfully setting up the data source, you can start conversing with the database. You can ask it to generate -SQL for you or inquire about relevant information on the database's metadata. -![db plugins demonstration](https://github.com/eosphoros-ai/DB-GPT/assets/13723926/8acf6a42-e511-48ff-aabf-3d9037485c1c) - -##### Editor Mode -In Editor Mode, you can edit your sql and execute it. -![db plugins demonstration](https://github.com/eosphoros-ai/DB-GPT/assets/13723926/1a896dc1-7c0e-4354-8629-30357ffd8d7f) - - -### 3.ChatDB - -![db plugins demonstration](https://github.com/eosphoros-ai/DB-GPT/assets/13723926/e04bc1b1-2c58-4b33-af62-97e89098ace7) - - diff --git a/docs/getting_started/application/chatdb/img.png b/docs/getting_started/application/chatdb/img.png deleted file mode 100644 index b6a3afc5e..000000000 Binary files a/docs/getting_started/application/chatdb/img.png and /dev/null differ diff --git a/docs/getting_started/application/chatexcel/chatexcel.md b/docs/getting_started/application/chatexcel/chatexcel.md deleted file mode 100644 index 3df00c720..000000000 --- a/docs/getting_started/application/chatexcel/chatexcel.md +++ /dev/null @@ -1,32 +0,0 @@ -ChatExcel -================================== -![db plugins demonstration](https://github.com/eosphoros-ai/DB-GPT/assets/13723926/4113ac15-83c2-4350-86c0-5fc795677abd) -ChatExcel uses natural language to analyze and query Excel data.![db plugins demonstration](../../../../assets/chat_excel/chat_excel_1.png) - -```{admonition} The LLM (Language Model) suitable for the ChatExcel scene is -* chatgpt3.5. -* chatgpt4. -``` - -### 1.Select And Upload Excel or CSV File -Select your excel or csv file to upload and start the conversation. -```{tip} -ChatExcel - -The ChatExcel function supports Excel and CSV format files, select the corresponding file to use. -``` -![db plugins demonstration](../../../../assets/chat_excel/chat_excel_2.png) -![db plugins demonstration](../../../../assets/chat_excel/chat_excel_3.png) - -### 2.Wait for Data Processing -After the data is uploaded, it will first learn and process the data structure and field meaning. -![db plugins demonstration](../../../../assets/chat_excel/chat_excel_4.png) - -### 3.Use Data Analysis Calculation -Now you can use natural language to analyze and query data in the dialog box. -![db plugins demonstration](../../../../assets/chat_excel/chat_excel_5.png) -![db plugins demonstration](../../../../assets/chat_excel/chat_excel_6.png) -![db plugins demonstration](../../../../assets/chat_excel/chat_excel_7.png) - - - diff --git a/docs/getting_started/application/dashboard/dashboard.md b/docs/getting_started/application/dashboard/dashboard.md deleted file mode 100644 index a233d0f24..000000000 --- a/docs/getting_started/application/dashboard/dashboard.md +++ /dev/null @@ -1,41 +0,0 @@ -Dashboard -================================== -The purpose of the DB-GPT Dashboard is to empower data analysts with efficiency. DB-GPT provides intelligent reporting -technology, allowing business analysts to perform self-service analysis directly using natural language and gain -insights into their respective areas of business. - -```{admonition} The LLM (Language Model) suitable for the Dashboard scene is -* chatgpt3.5. -* chatgpt4. -``` - -```{note} Dashboard now support Datasource Type -* Mysql -* Sqlite -* DuckDB -``` - -## Steps to Dashboard In DB-GPT - -#### 1 add datasource - -If you are using Dashboard for the first time, you need to mock some data to test. DB-GPT provide some dashboard test -data in pilot/mock_datas/, you should follow the steps. -![add_datasource](https://github.com/eosphoros-ai/DB-GPT/assets/13723926/0afc72ea-83c8-45ff-8c36-213b1c6fb5dd) - -#### 2.Choose Dashboard Mode - -![create_space](https://github.com/eosphoros-ai/DB-GPT/assets/13723926/5e888880-0e97-4b60-8e5c-b7e7224197f0) - -#### 3.Select Datasource - -![document](https://github.com/eosphoros-ai/DB-GPT/assets/13723926/da2ac8b5-eca4-48ef-938f-f9dc1ca711b3) - -#### 4.Input your analysis goals - -![document](https://github.com/eosphoros-ai/DB-GPT/assets/13723926/3f427350-5bd5-4675-8f89-1bd5c63ff2c6) -![db plugins demonstration](../../../../assets/chat_dashboard/chat_dashboard_1.png) - -#### 5.Adjust and modify your report -![db plugins demonstration](../../../../assets/chat_dashboard/chat_dashboard_2.png) - diff --git a/docs/getting_started/application/kbqa/kbqa.md b/docs/getting_started/application/kbqa/kbqa.md deleted file mode 100644 index ec04b2101..000000000 --- a/docs/getting_started/application/kbqa/kbqa.md +++ /dev/null @@ -1,297 +0,0 @@ -KBQA -================================== -![chat_knowledge](https://github.com/eosphoros-ai/DB-GPT/assets/13723926/bc343c94-df3e-41e5-90d5-23b68c768c59) - -DB-GPT supports a knowledge question-answering module, which aims to create an intelligent expert in the field of databases and provide professional knowledge-based answers to database practitioners. - -![chat_knowledge](https://github.com/eosphoros-ai/DB-GPT/assets/13723926/6e55f2e5-94f7-4906-aed6-097db5c6c721) - -## KBQA abilities - - -```{admonition} KBQA abilities -* Knowledge Space. -* Multi Source Knowledge Source Embedding. -* Embedding Argument Adjust -* Chat Knowledge -* Multi Vector DB -``` - -```{note} -If your DB type is Sqlite, there is nothing to do to build KBQA service database schema. - -If your DB type is Mysql or other DBTYPE, you will build kbqa service database schema. - -### Mysql -$ mysql -h127.0.0.1 -uroot -paa12345678 < ./assets/schema/knowledge_management.sql - -or - -execute DBGPT/assets/schema/knowledge_management.sql -``` - -## Steps to KBQA In DB-GPT - -#### 1.Create Knowledge Space -If you are using Knowledge Space for the first time, you need to create a Knowledge Space and set your name, owner, description. -![create_space](https://github.com/eosphoros-ai/DB-GPT/assets/13723926/a93e597b-c392-465f-89d5-b55621d068a8) - - - -#### 2.Create Knowledge Document -DB-GPT now support Multi Knowledge Source, including Text, WebUrl, and Document(PDF, Markdown, Word, PPT, HTML and CSV). -After successfully uploading a document for translation, the backend system will automatically read and split and chunk the document, and then import it into the vector database. Alternatively, you can manually synchronize the document. You can also click on details to view the specific document slicing content. -##### 2.1 Choose Knowledge Type: -![document](https://github.com/eosphoros-ai/DB-GPT/assets/13723926/5b8173da-f444-4607-9d12-14bcab8179d0) - -##### 2.2 Upload Document: -![upload](https://github.com/eosphoros-ai/DB-GPT/assets/13723926/91b338fc-d3b2-476e-9396-3f6b4f16a890) - - -#### 3.Chat With Knowledge -![upload](https://github.com/eosphoros-ai/DB-GPT/assets/13723926/a8281be7-1454-467d-81c9-15ef108aac10) - -#### 4.Adjust Space arguments -Each knowledge space supports argument customization, including the relevant arguments for vector retrieval and the arguments for knowledge question-answering prompts. -##### 4.1 Embedding -Embedding Argument -![upload](https://github.com/eosphoros-ai/DB-GPT/assets/13723926/f1221bd5-d049-4ceb-96e6-8709e76e502e) - -```{tip} Embedding arguments -* topk:the top k vectors based on similarity score. -* recall_score:set a threshold score for the retrieval of similar vectors. -* recall_type:recall type. -* model:A model used to create vector representations of text or other data. -* chunk_size:The size of the data chunks used in processing. -* chunk_overlap:The amount of overlap between adjacent data chunks. -``` - -##### 4.2 Prompt -Prompt Argument -![upload](https://github.com/eosphoros-ai/DB-GPT/assets/13723926/9918c9c3-ed64-4804-9e05-fa7d7d177bec) - -```{tip} Prompt arguments -* scene:A contextual parameter used to define the setting or environment in which the prompt is being used. -* template:A pre-defined structure or format for the prompt, which can help ensure that the AI system generates responses that are consistent with the desired style or tone. -* max_token:The maximum number of tokens or words allowed in a prompt. -``` - -#### 5.Change Vector Database - -```{admonition} Vector Store SETTINGS -#### Chroma -* VECTOR_STORE_TYPE=Chroma -#### MILVUS -* VECTOR_STORE_TYPE=Milvus -* MILVUS_URL=127.0.0.1 -* MILVUS_PORT=19530 -* MILVUS_USERNAME -* MILVUS_PASSWORD -* MILVUS_SECURE= - -#### WEAVIATE -* WEAVIATE_URL=https://kt-region-m8hcy0wc.weaviate.network -``` - -## KBQA command line - -### Load your local documents to DB-GPT - -```bash -dbgpt knowledge load --space_name my_kbqa_space --local_doc_path ./pilot/datasets --vector_store_type Chroma -``` - -- `--space_name`: Your knowledge space name, default: `default` -- `--local_doc_path`: Your document directory or document file path, default: `./pilot/datasets` -- `--vector_store_type`: Vector store type, default: `Chroma` - -**View the `dbgpt knowledge load --help`help** - -``` -dbgpt knowledge load --help -``` - -Here you can see the parameters: - -``` -Usage: dbgpt knowledge load [OPTIONS] - - Load your local knowledge to DB-GPT - -Options: - --space_name TEXT Your knowledge space name [default: default] - --vector_store_type TEXT Vector store type. [default: Chroma] - --local_doc_path TEXT Your document directory or document file path. - [default: ./pilot/datasets] - --skip_wrong_doc Skip wrong document. - --overwrite Overwrite existing document(they has same name). - --max_workers INTEGER The maximum number of threads that can be used to - upload document. - --pre_separator TEXT Preseparator, this separator is used for pre- - splitting before the document is actually split by - the text splitter. Preseparator are not included - in the vectorized text. - --separator TEXT This is the document separator. Currently, only - one separator is supported. - --chunk_size INTEGER Maximum size of chunks to split. - --chunk_overlap INTEGER Overlap in characters between chunks. - --help Show this message and exit. -``` - -### List knowledge space - -#### List knowledge space - -``` -dbgpt knowledge list -``` - -Output should look something like the following: -``` -+------------------------------------------------------------------+ -| All knowledge spaces | -+----------+-------------+-------------+-------------+-------------+ -| Space ID | Space Name | Vector Type | Owner | Description | -+----------+-------------+-------------+-------------+-------------+ -| 6 | n1 | Chroma | DB-GPT | DB-GPT cli | -| 5 | default_2 | Chroma | DB-GPT | DB-GPT cli | -| 4 | default_1 | Chroma | DB-GPT | DB-GPT cli | -| 3 | default | Chroma | DB-GPT | DB-GPT cli | -+----------+-------------+-------------+-------------+-------------+ -``` - -#### List documents in knowledge space - -``` -dbgpt knowledge list --space_name default -``` - -Output should look something like the following: -``` -+------------------------------------------------------------------------+ -| Space default description | -+------------+-----------------+--------------+--------------+-----------+ -| Space Name | Total Documents | Current Page | Current Size | Page Size | -+------------+-----------------+--------------+--------------+-----------+ -| default | 1 | 1 | 1 | 20 | -+------------+-----------------+--------------+--------------+-----------+ - -+-----------------------------------------------------------------------------------------------------------------------------------+ -| Documents of space default | -+------------+-------------+---------------+----------+--------+----------------------------+----------+----------------------------+ -| Space Name | Document ID | Document Name | Type | Chunks | Last Sync | Status | Result | -+------------+-------------+---------------+----------+--------+----------------------------+----------+----------------------------+ -| default | 61 | Knowledge.pdf | DOCUMENT | 745 | 2023-09-28T03:25:39.065762 | FINISHED | document embedding success | -+------------+-------------+---------------+----------+--------+----------------------------+----------+----------------------------+ -``` - -#### List chunks of document in space `default` - -``` -dbgpt knowledge list --space_name default --doc_id 61 --page_size 5 -``` - - -``` -+-----------------------------------------------------------------------------------+ -| Document 61 in default description | -+------------+-------------+--------------+--------------+--------------+-----------+ -| Space Name | Document ID | Total Chunks | Current Page | Current Size | Page Size | -+------------+-------------+--------------+--------------+--------------+-----------+ -| default | 61 | 745 | 1 | 5 | 5 | -+------------+-------------+--------------+--------------+--------------+-----------+ - -+-----------------------------------------------------------------------------------------------------------------------+ -| chunks of document id 61 in space default | -+------------+-------------+---------------+----------+-----------------------------------------------------------------+ -| Space Name | Document ID | Document Name | Content | Meta Data | -+------------+-------------+---------------+----------+-----------------------------------------------------------------+ -| default | 61 | Knowledge.pdf | [Hidden] | {'source': '/app/pilot/data/default/Knowledge.pdf', 'page': 10} | -| default | 61 | Knowledge.pdf | [Hidden] | {'source': '/app/pilot/data/default/Knowledge.pdf', 'page': 9} | -| default | 61 | Knowledge.pdf | [Hidden] | {'source': '/app/pilot/data/default/Knowledge.pdf', 'page': 9} | -| default | 61 | Knowledge.pdf | [Hidden] | {'source': '/app/pilot/data/default/Knowledge.pdf', 'page': 8} | -| default | 61 | Knowledge.pdf | [Hidden] | {'source': '/app/pilot/data/default/Knowledge.pdf', 'page': 8} | -+------------+-------------+---------------+----------+-----------------------------------------------------------------+ -``` - -#### More list usage - -``` -dbgpt knowledge list --help -``` - -``` -Usage: dbgpt knowledge list [OPTIONS] - - List knowledge space - -Options: - --space_name TEXT Your knowledge space name. If None, list all - spaces - --doc_id INTEGER Your document id in knowledge space. If Not - None, list all chunks in current document - --page INTEGER The page for every query [default: 1] - --page_size INTEGER The page size for every query [default: 20] - --show_content Query the document content of chunks - --output [text|html|csv|latex|json] - The output format - --help Show this message and exit. -``` - - -### Delete your knowledge space or document in space - -#### Delete your knowledge space - -``` -dbgpt knowledge delete --space_name default -``` - -#### Delete your document in space - -``` -dbgpt knowledge delete --space_name default --doc_name Knowledge.pdf -``` - - -#### More delete usage - -``` -dbgpt knowledge delete --help -``` - -``` -Usage: dbgpt knowledge delete [OPTIONS] - - Delete your knowledge space or document in space - -Options: - --space_name TEXT Your knowledge space name [default: default] - --doc_name TEXT The document name you want to delete. If doc_name is - None, this command will delete the whole space. - -y Confirm your choice - --help Show this message and exit. -``` - -#### More knowledge usage - -``` -dbgpt knowledge --help -``` - -``` -Usage: dbgpt knowledge [OPTIONS] COMMAND [ARGS]... - - Knowledge command line tool - -Options: - --address TEXT Address of the Api server(If not set, try to read from - environment variable: API_ADDRESS). [default: - http://127.0.0.1:5000] - --help Show this message and exit. - -Commands: - delete Delete your knowledge space or document in space - list List knowledge space - load Load your local documents to DB-GPT -``` \ No newline at end of file diff --git a/docs/getting_started/application/model/model.md b/docs/getting_started/application/model/model.md deleted file mode 100644 index 92bd31d4d..000000000 --- a/docs/getting_started/application/model/model.md +++ /dev/null @@ -1,61 +0,0 @@ -Model Management -================================== -![model](https://github.com/eosphoros-ai/DB-GPT/assets/13723926/4b160ee7-2e2a-4502-bd54-d7daa14b23e5) -DB-GPT Product Provides LLM Model Management in web interface.Including LLM Create, Start and Stop. -Now DB-GPT support LLMs: -```{admonition} Support LLMs -* Multi LLMs Support, Supports multiple large language models, currently supporting - * [meta-llama/Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf) - * [baichuan2-7b/baichuan2-13b](https://huggingface.co/baichuan-inc) - * [internlm/internlm-chat-7b](https://huggingface.co/internlm/internlm-chat-7b) - * [Qwen/Qwen-7B-Chat/Qwen-14B-Chat](https://huggingface.co/Qwen/) - * [Vicuna](https://huggingface.co/Tribbiani/vicuna-13b) - * [BlinkDL/RWKV-4-Raven](https://huggingface.co/BlinkDL/rwkv-4-raven) - * [camel-ai/CAMEL-13B-Combined-Data](https://huggingface.co/camel-ai/CAMEL-13B-Combined-Data) - * [databricks/dolly-v2-12b](https://huggingface.co/databricks/dolly-v2-12b) - * [FreedomIntelligence/phoenix-inst-chat-7b](https://huggingface.co/FreedomIntelligence/phoenix-inst-chat-7b) - * [h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-7b](https://huggingface.co/h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-7b) - * [lcw99/polyglot-ko-12.8b-chang-instruct-chat](https://huggingface.co/lcw99/polyglot-ko-12.8b-chang-instruct-chat) - * [lmsys/fastchat-t5-3b-v1.0](https://huggingface.co/lmsys/fastchat-t5) - * [mosaicml/mpt-7b-chat](https://huggingface.co/mosaicml/mpt-7b-chat) - * [Neutralzz/BiLLa-7B-SFT](https://huggingface.co/Neutralzz/BiLLa-7B-SFT) - * [nomic-ai/gpt4all-13b-snoozy](https://huggingface.co/nomic-ai/gpt4all-13b-snoozy) - * [NousResearch/Nous-Hermes-13b](https://huggingface.co/NousResearch/Nous-Hermes-13b) - * [openaccess-ai-collective/manticore-13b-chat-pyg](https://huggingface.co/openaccess-ai-collective/manticore-13b-chat-pyg) - * [OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5](https://huggingface.co/OpenAssistant/oasst-sft-4-pythia-12b-epoch-3.5) - * [project-baize/baize-v2-7b](https://huggingface.co/project-baize/baize-v2-7b) - * [Salesforce/codet5p-6b](https://huggingface.co/Salesforce/codet5p-6b) - * [StabilityAI/stablelm-tuned-alpha-7b](https://huggingface.co/stabilityai/stablelm-tuned-alpha-7b) - * [THUDM/chatglm-6b](https://huggingface.co/THUDM/chatglm-6b) - * [THUDM/chatglm2-6b](https://huggingface.co/THUDM/chatglm2-6b) - * [tiiuae/falcon-40b](https://huggingface.co/tiiuae/falcon-40b) - * [timdettmers/guanaco-33b-merged](https://huggingface.co/timdettmers/guanaco-33b-merged) - * [togethercomputer/RedPajama-INCITE-7B-Chat](https://huggingface.co/togethercomputer/RedPajama-INCITE-7B-Chat) - * [WizardLM/WizardLM-13B-V1.0](https://huggingface.co/WizardLM/WizardLM-13B-V1.0) - * [WizardLM/WizardCoder-15B-V1.0](https://huggingface.co/WizardLM/WizardCoder-15B-V1.0) - * [baichuan-inc/baichuan-7B](https://huggingface.co/baichuan-inc/baichuan-7B) - * [HuggingFaceH4/starchat-beta](https://huggingface.co/HuggingFaceH4/starchat-beta) - * [FlagAlpha/Llama2-Chinese-13b-Chat](https://huggingface.co/FlagAlpha/Llama2-Chinese-13b-Chat) - * [BAAI/AquilaChat-7B](https://huggingface.co/BAAI/AquilaChat-7B) - * [all models of OpenOrca](https://huggingface.co/Open-Orca) - * [Spicyboros](https://huggingface.co/jondurbin/spicyboros-7b-2.2?not-for-all-audiences=true) + [airoboros 2.2](https://huggingface.co/jondurbin/airoboros-l2-13b-2.2) - * [VMware's OpenLLaMa OpenInstruct](https://huggingface.co/VMware/open-llama-7b-open-instruct) - -* Support API Proxy LLMs - * [ChatGPT](https://api.openai.com/) - * [Tongyi](https://www.aliyun.com/product/dashscope) - * [Wenxin](https://cloud.baidu.com/product/wenxinworkshop?track=dingbutonglan) - * [ChatGLM](http://open.bigmodel.cn/) -``` -### Create && Start LLM Model -```{note} -Make sure your LLM Model file is downloaded or LLM Model Proxy api service is ready. -``` -![model-start](https://github.com/eosphoros-ai/DB-GPT/assets/13723926/dacabcb9-92c6-43eb-95ed-8cabaa2d18e6) - When create success, you can see: -![image](https://github.com/eosphoros-ai/DB-GPT/assets/13723926/1b69bff6-8b37-493d-b6be-38f7b6e8ae2d) -Then you can choose and switch llm model service to chat. -![image](https://github.com/eosphoros-ai/DB-GPT/assets/13723926/2d20eb6b-8976-4731-b433-373ac3383602) -### Stop LLM Model -![image](https://github.com/eosphoros-ai/DB-GPT/assets/13723926/a21278d9-7bef-487b-bef1-460ce516b2f5) - diff --git a/docs/getting_started/faq.rst b/docs/getting_started/faq.rst deleted file mode 100644 index 0d758c013..000000000 --- a/docs/getting_started/faq.rst +++ /dev/null @@ -1,22 +0,0 @@ -FAQ -================================== -DB-GPT product is a Web application that you can chat database, chat knowledge, text2dashboard. - -.. image:: ./assets/DB-GPT-Product.jpg - - -- deploy -- llm -- chatdb -- kbqa - -.. toctree:: - :maxdepth: 2 - :caption: Deloy - :name: deploy - :hidden: - - ./faq/deploy/deploy_faq.md - ./faq/llm/llm_faq.md - ./faq/chatdb/chatdb_faq.md - ./faq/kbqa/kbqa_faq.md \ No newline at end of file diff --git a/docs/getting_started/faq/chatdb/chatdb_faq.md b/docs/getting_started/faq/chatdb/chatdb_faq.md deleted file mode 100644 index 19a0537dc..000000000 --- a/docs/getting_started/faq/chatdb/chatdb_faq.md +++ /dev/null @@ -1,24 +0,0 @@ -Chat DB FAQ -================================== - -##### Q1: What difference between ChatData and ChatDB - -ChatData generates SQL from natural language and executes it. ChatDB involves conversing with metadata from the -Database, including metadata about databases, tables, and fields. - -##### Q2: The suitable llm model currently supported for text-to-SQL is? - -Now vicunna-13b-1.5 and llama2-70b is more suitable for text-to-SQL. - -##### Q3: How to fine-tune Text-to-SQL in DB-GPT - -there is another github project for Text-to-SQL fine-tune (https://github.com/eosphoros-ai/DB-GPT-Hub) - -##### Q4: chatdata with clickhouse clickhouse-sqlalchemy 0.2.4 requires sqlalchemy<1.5,>=1.4.24, but you have sqlalchemy 2.0.20 which is incompatible - -Just set sqlalchemy<1.5,>=1.4.24 - -```commandline -pip install clickhouse-driver -pip install sqlalchemy==1.4.24 -``` \ No newline at end of file diff --git a/docs/getting_started/faq/deploy/deploy_faq.md b/docs/getting_started/faq/deploy/deploy_faq.md deleted file mode 100644 index b6083497c..000000000 --- a/docs/getting_started/faq/deploy/deploy_faq.md +++ /dev/null @@ -1,148 +0,0 @@ -Installation FAQ -================================== - - -##### Q1: execute `pip install -e .` error, found some package cannot find correct version. -change the pip source. - -```bash -# pypi -$ pip install -e . -i https://pypi.python.org/simple -``` - -or - -```bash -# tsinghua -$ pip install -e . -i https://pypi.tuna.tsinghua.edu.cn/simple/ -``` - -or - -```bash -# aliyun -$ pip install -e . -i http://mirrors.aliyun.com/pypi/simple/ -``` - -##### Q2: sqlalchemy.exc.OperationalError: (sqlite3.OperationalError) unable to open database file - -make sure you pull latest code or create directory with mkdir pilot/data - -##### Q3: The model keeps getting killed. - -your GPU VRAM size is not enough, try replace your hardware or replace other llms. - -##### Q4: How to access website on the public network - -You can try to use gradio's [network](https://github.com/gradio-app/gradio/blob/main/gradio/networking.py) to achieve. -```python -import secrets -from gradio import networking -token=secrets.token_urlsafe(32) -local_port=5000 -url = networking.setup_tunnel('0.0.0.0', local_port, token) -print(f'Public url: {url}') -time.sleep(60 * 60 * 24) -``` - -Open `url` with your browser to see the website. - -##### Q5: (Windows) execute `pip install -e .` error - -The error log like the following: -``` -× python setup.py bdist_wheel did not run successfully. - │ exit code: 1 - ╰─> [11 lines of output] - running bdist_wheel - running build - running build_py - creating build - creating build\lib.win-amd64-cpython-310 - creating build\lib.win-amd64-cpython-310\cchardet - copying src\cchardet\version.py -> build\lib.win-amd64-cpython-310\cchardet - copying src\cchardet\__init__.py -> build\lib.win-amd64-cpython-310\cchardet - running build_ext - building 'cchardet._cchardet' extension - error: Microsoft Visual C++ 14.0 or greater is required. Get it with "Microsoft C++ Build Tools": https://visualstudio.microsoft.com/visual-cpp-build-tools/ - [end of output] -``` - -Download and install `Microsoft C++ Build Tools` from [visual-cpp-build-tools](https://visualstudio.microsoft.com/visual-cpp-build-tools/) - - - -##### Q6: `Torch not compiled with CUDA enabled` - -``` -2023-08-19 16:24:30 | ERROR | stderr | raise AssertionError("Torch not compiled with CUDA enabled") -2023-08-19 16:24:30 | ERROR | stderr | AssertionError: Torch not compiled with CUDA enabled -``` - -1. Install [CUDA Toolkit](https://developer.nvidia.com/cuda-toolkit-archive) -2. Reinstall PyTorch [start-locally](https://pytorch.org/get-started/locally/#start-locally) with CUDA support. - -##### Q7: ImportError: cannot import name 'PersistentClient' from 'chromadb'. - -```commandline -pip install chromadb==0.4.10 -``` - -##### Q8: pydantic.error_wrappers.ValidationError:1 validation error for HuggingFaceEmbeddings.model_kwargs extra not permitted - -```commandline -pip install langchain>=0.0.286 - -##### Q9: In Centos OS, No matching distribution found for setuptools_scm - -```commandline -pip install --use-pep517 fschat -``` - -##### Q9: alembic.util.exc.CommandError: Target database is not up to date. - -delete files in `DB-GPT/pilot/meta_data/alembic/versions/` and restart. -```commandline -rm -rf DB-GPT/pilot/meta_data/alembic/versions/* -rm -rf DB-GPT/pilot/meta_data/alembic/dbgpt.db -``` - -##### Q10: How to store DB-GPT metadata into my database - -In version 0.4.0, the metadata module of the DB-GPT application has been refactored. All metadata tables will now be automatically saved in the 'dbgpt' database, based on the database type specified in the `.env` file. If you would like to retain the existing data, it is recommended to use a data migration tool to transfer the database table information to the 'dbgpt' database. Additionally, you can change the default database name 'dbgpt' in your `.env` file. - -```commandline -### SQLite database (Current default database) -#LOCAL_DB_PATH=data/default_sqlite.db -#LOCAL_DB_TYPE=sqlite - -### Mysql database -LOCAL_DB_TYPE=mysql -LOCAL_DB_USER=root -LOCAL_DB_PASSWORD=aa12345678 -LOCAL_DB_HOST=127.0.0.1 -LOCAL_DB_PORT=3306 -# You can change it to your actual metadata database name -LOCAL_DB_NAME=dbgpt - -### This option determines the storage location of conversation records. The default is not configured to the old version of duckdb. It can be optionally db or file (if the value is db, the database configured by LOCAL_DB will be used) -CHAT_HISTORY_STORE_TYPE=db -``` - -##### Q11: pymysql.err.OperationalError: (1142, "ALTER command denied to user '{you db user}'@'{you db host}' for table '{some table name}'") - -In version 0.4.0, DB-GPT use migration tool alembic to migrate metadata. If the database user does not have DDL permissions, this error will be reported. You can solve this problem by importing the metadata information separately. - -1. Use a privileged user to execute DDL sql file -```bash -mysql -h127.0.0.1 -uroot -paa12345678 < ./assets/schema/knowledge_management.sql -``` - -2. Run DB-GPT webserver with `--disable_alembic_upgrade` -```bash -python pilot/server/dbgpt_server.py --disable_alembic_upgrade -``` -or -```bash -dbgpt start webserver --disable_alembic_upgrade -``` \ No newline at end of file diff --git a/docs/getting_started/faq/kbqa/kbqa_faq.md b/docs/getting_started/faq/kbqa/kbqa_faq.md deleted file mode 100644 index 7b3ea8780..000000000 --- a/docs/getting_started/faq/kbqa/kbqa_faq.md +++ /dev/null @@ -1,94 +0,0 @@ -KBQA FAQ -================================== - -##### Q1: text2vec-large-chinese not found - -make sure you have download text2vec-large-chinese embedding model in right way - -```tip -centos:yum install git-lfs -ubuntu:apt-get install git-lfs -y -macos:brew install git-lfs -``` -```bash -cd models -git lfs clone https://huggingface.co/GanymedeNil/text2vec-large-chinese -``` - -##### Q2:How to change Vector DB Type in DB-GPT. - -Update .env file and set VECTOR_STORE_TYPE. - -DB-GPT currently support Chroma(Default), Milvus(>2.1), Weaviate vector database. -If you want to change vector db, Update your .env, set your vector store type, VECTOR_STORE_TYPE=Chroma (now only support Chroma and Milvus(>2.1), if you set Milvus, please set MILVUS_URL and MILVUS_PORT) -If you want to support more vector db, you can integrate yourself.[how to integrate](https://db-gpt.readthedocs.io/en/latest/modules/vector.html) -```commandline -#*******************************************************************# -#** VECTOR STORE SETTINGS **# -#*******************************************************************# -VECTOR_STORE_TYPE=Chroma -#MILVUS_URL=127.0.0.1 -#MILVUS_PORT=19530 -#MILVUS_USERNAME -#MILVUS_PASSWORD -#MILVUS_SECURE= - -#WEAVIATE_URL=https://kt-region-m8hcy0wc.weaviate.network -``` -##### Q3:When I use vicuna-13b, found some illegal character like this. -

- -

- -Set KNOWLEDGE_SEARCH_TOP_SIZE smaller or set KNOWLEDGE_CHUNK_SIZE smaller, and reboot server. - -##### Q4:space add error (pymysql.err.OperationalError) (1054, "Unknown column 'knowledge_space.context' in 'field list'") - -1.shutdown dbgpt_server(ctrl c) - -2.add column context for table knowledge_space - -```commandline -mysql -h127.0.0.1 -uroot -paa12345678 -``` - -3.execute sql ddl - -```commandline -mysql> use knowledge_management; -mysql> ALTER TABLE knowledge_space ADD COLUMN context TEXT COMMENT "arguments context"; -``` - -4.restart dbgpt serve - -##### Q5:Use Mysql, how to use DB-GPT KBQA - -build Mysql KBQA system database schema. - -```bash -$ mysql -h127.0.0.1 -uroot -paa12345678 < ./assets/schema/knowledge_management.sql -``` - - -##### Q6:when pull from 0.4.0, I found historical knowledge document disappeared - -In version 0.4.0, the metadata module of the DB-GPT application has been refactored. All metadata tables will now be automatically saved in the 'dbgpt' database, based on the database type specified in the `.env` file. If you would like to retain the existing data, it is recommended to use a data migration tool to transfer the database table information to the 'dbgpt' database. Additionally, you can change the default database name 'dbgpt' in your `.env` file. - -```{tip} -old database:knowledge_management; -new database:dbgpt; -``` -```commandline -### SQLite database (Current default database) -#LOCAL_DB_PATH=data/default_sqlite.db -#LOCAL_DB_TYPE=sqlite - -### Mysql database -LOCAL_DB_TYPE=mysql -LOCAL_DB_USER=root -LOCAL_DB_PASSWORD=aa12345678 -LOCAL_DB_HOST=127.0.0.1 -LOCAL_DB_PORT=3306 -# You can change it to your actual metadata database name -LOCAL_DB_NAME=dbgpt -``` diff --git a/docs/getting_started/faq/llm/llm_faq.md b/docs/getting_started/faq/llm/llm_faq.md deleted file mode 100644 index 53b8cf279..000000000 --- a/docs/getting_started/faq/llm/llm_faq.md +++ /dev/null @@ -1,116 +0,0 @@ -LLM USE FAQ -================================== -##### Q1: how to use openai chatgpt service -change your LLM_MODEL in `.env` -````shell -LLM_MODEL=proxyllm -```` - -set your OPENAPI KEY - -````shell -PROXY_API_KEY={your-openai-sk} -PROXY_SERVER_URL=https://api.openai.com/v1/chat/completions -```` - -make sure your openapi API_KEY is available - -##### Q2: What difference between `python dbgpt_server --light` and `python dbgpt_server` -```{note} -* `python dbgpt_server --light` dbgpt_server does not start the llm service. Users can deploy the llm service separately by using `python llmserver`, and dbgpt_server accesses the llm service through set the LLM_SERVER environment variable in .env. The purpose is to allow for the separate deployment of dbgpt's backend service and llm service. - -* `python dbgpt_server` dbgpt_server service and the llm service are deployed on the same instance. when dbgpt_server starts the service, it also starts the llm service at the same time. - -``` - -```{tip} -If you want to access an external LLM service(deployed by DB-GPT), you need to - -1.set the variables LLM_MODEL=YOUR_MODEL_NAME, MODEL_SERVER=YOUR_MODEL_SERVER（eg:http://localhost:5000） in the .env file. - -2.execute dbgpt_server.py in light mode - -python pilot/server/dbgpt_server.py --light - -``` - - -##### Q3: How to use MultiGPUs - -DB-GPT will use all available gpu by default. And you can modify the setting `CUDA_VISIBLE_DEVICES=0,1` in `.env` file -to use the specific gpu IDs. - -Optionally, you can also specify the gpu ID to use before the starting command, as shown below: - -````shell -# Specify 1 gpu -CUDA_VISIBLE_DEVICES=0 python3 pilot/server/dbgpt_server.py - -# Specify 4 gpus -CUDA_VISIBLE_DEVICES=3,4,5,6 python3 pilot/server/dbgpt_server.py -```` - -You can modify the setting `MAX_GPU_MEMORY=xxGib` in `.env` file to configure the maximum memory used by each GPU. - -##### Q4: Not Enough Memory - -DB-GPT supported 8-bit quantization and 4-bit quantization. - -You can modify the setting `QUANTIZE_8bit=True` or `QUANTIZE_4bit=True` in `.env` file to use quantization(8-bit quantization is enabled by default). - -Llama-2-70b with 8-bit quantization can run with 80 GB of VRAM, and 4-bit quantization can run with 48 GB of VRAM. - -Note: you need to install the quantization dependencies with `pip install -e ".[quantization]"` - -##### Q5: How to Add LLM Service dynamic local mode - -Now DB-GPT through multi-llm service switch, so how to add llm service dynamic, - -```commandline -dbgpt model start --model_name ${your_model_name} --model_path ${your_model_path} - -chatglm2-6b -eg: dbgpt model start --model_name chatglm2-6b --model_path /root/DB-GPT/models/chatglm2-6b - -chatgpt -eg: dbgpt model start --model_name chatgpt_proxyllm --model_path chatgpt_proxyllm --proxy_api_key ${OPENAI_KEY} --proxy_server_url {OPENAI_URL} -``` -##### Q6: How to Add LLM Service dynamic in remote mode -If you deploy llm service in remote machine instance, and you want to add model service to dbgpt server to manage - -use dbgpt start worker and set --controller_addr. - -```commandline -eg: dbgpt start worker --model_name vicuna-13b-v1.5 \ ---model_path /app/models/vicuna-13b-v1.5 \ ---port 8002 \ ---controller_addr http://127.0.0.1:8000 - -``` - -##### Q7: dbgpt command not found - -```commandline -pip install -e "pip install -e ".[default]" -``` - -##### Q8: When starting the worker_manager on a cloud server and registering it with the controller, it is noticed that the worker's exposed IP is a private IP instead of a public IP, which leads to the inability to access the service. - -```commandline - ---worker_register_host public_ip The ip address of current worker to register - to ModelController. If None, the address is - automatically determined -``` - -##### Q9: How to customize model path and prompt template - -DB-GPT will read the model path from `pilot.configs.model_config.LLM_MODEL_CONFIG` based on the `LLM_MODEL`. -Of course, you can use the environment variable `LLM_MODEL_PATH` to specify the model path and `LLM_PROMPT_TEMPLATE` to specify your model prompt template. - -``` -LLM_MODEL=vicuna-13b-v1.5 -LLM_MODEL_PATH=/app/models/vicuna-13b-v1.5 -# LLM_PROMPT_TEMPLATE=vicuna_v1.1 -``` - diff --git a/docs/getting_started/getting_started.md b/docs/getting_started/getting_started.md deleted file mode 100644 index 4d0b3b5b6..000000000 --- a/docs/getting_started/getting_started.md +++ /dev/null @@ -1,38 +0,0 @@ -# Quickstart Guide - -#### Welcome to DB-GPT! - -DB-GPT is an experimental open-source project that uses localized GPT large models to interact with your data and -environment. With this solution, you can be assured that there is no risk of data leakage, and your data is 100% private -and secure. - -Our vision is to make it easier and more convenient to build applications around databases and llm. - -## What can I do with DB-GPT? - -- Chat Data with your Datasource. -- Private domain knowledge question answering. -- Quickly provide private LLM Model deployment. - -## Usage with DB-GPT. - -- Follow DB-GPT - application [install tutorial](https://db-gpt.readthedocs.io/en/latest/getting_started/install/deploy/deploy.html). -- Follow - DB-GPT [application usage](https://db-gpt.readthedocs.io/en/latest/getting_started/application/chatdb/chatdb.html). - -If you encounter any issues while using DB-GPT (whether it's during installation or usage), you can refer to -the [FAQ](https://db-gpt.readthedocs.io/en/latest/getting_started/faq/deploy/deploy_faq.html) section for assistance. - -## 🗺️ Ecosystem - -- Github: https://github.com/eosphoros-ai/DB-GPT -- PyPi: - - DB-GPT: https://pypi.org/simple/db-gpt. - -## Associated projects - -- 🧪 DB-GPT-Hub: https://github.com/eosphoros-ai/DB-GPT-Hub | an experimental project to implement Text-to-SQL parsing - using LLMs -- 🏡 DB-GPT-Web: https://github.com/eosphoros-ai/DB-GPT-Web | Web application for DB-GPT. -- 🚀 DB-GPT-Plugins: https://github.com/eosphoros-ai/DB-GPT-Web | DB-GPT Plugins Repo, Which support AutoGPT plugin. \ No newline at end of file diff --git a/docs/getting_started/install.rst b/docs/getting_started/install.rst deleted file mode 100644 index 645467e9e..000000000 --- a/docs/getting_started/install.rst +++ /dev/null @@ -1,27 +0,0 @@ -Install -================================== -DB-GPT product is a Web application that you can chat database, chat knowledge, text2dashboard. - -.. image:: https://github.com/eosphoros-ai/DB-GPT/assets/13723926/13d68dd5-d052-4976-9aeb-60ae13d63d02 - - -- deploy -- docker -- docker_compose -- environment -- cluster deployment -- deploy_faq - -.. toctree:: - :maxdepth: 2 - :caption: Install - :name: deploy - :hidden: - - ./install/deploy.rst - ./install/docker/docker.md - ./install/docker_compose/docker_compose.md - ./install/cluster/cluster.rst - ./install/llm/llm.rst - ./install/environment/environment.md - ./install/faq/deploy_faq.md \ No newline at end of file diff --git a/docs/getting_started/install/cluster/cluster.rst b/docs/getting_started/install/cluster/cluster.rst deleted file mode 100644 index 17895e7bc..000000000 --- a/docs/getting_started/install/cluster/cluster.rst +++ /dev/null @@ -1,80 +0,0 @@ -LLM Deployment -================================== -In the exploration and implementation of AI model applications, it can be challenging to directly integrate with model services. Currently, there is no established standard for deploying large models, and new models and inference methods are constantly being released. As a result, a significant amount of time is spent adapting to the ever-changing underlying model environment. This, to some extent, hinders the exploration and implementation of AI model applications. - -We divide the deployment of large models into two layers: the model inference layer and the model deployment layer. The model inference layer corresponds to model inference frameworks such as vLLM, TGI, and TensorRT. The model deployment layer interfaces with the inference layer below and provides model serving capabilities above. We refer to this layer's framework as the model deployment framework. Positioned above the inference frameworks, the model deployment framework offers capabilities such as multiple model instances, multiple inference frameworks, multiple service protocols, multi-cloud support, automatic scaling, and observability. - -In order to deploy DB-GPT to multiple nodes, you can deploy a cluster. The cluster architecture diagram is as follows: - -.. raw:: html - - - -Design of DB-GPT: ------------------ - -DB-GPT is designed as a llm deployment framework, taking into account the above design objectives. - -- Support for llm and inference frameworks: DB-GPT supports the simultaneous deployment of llm and is compatible with multiple inference frameworks such as vLLM, TGI, and TensorRT. - -- Scalability and stability: DB-GPT has good scalability, allowing easy addition of new models and inference frameworks. It utilizes a distributed architecture and automatic scaling capabilities to handle high concurrency and large-scale requests, ensuring system stability. - -- Performance optimization: DB-GPT undergoes performance optimization to provide fast and efficient model inference capabilities, preventing it from becoming a performance bottleneck during inference. - -- Management and observability capabilities: DB-GPT offers management and monitoring functionalities, including model deployment and configuration management, performance monitoring, and logging. It can generate reports on model performance and service status to promptly identify and resolve issues. - -- Lightweight: DB-GPT is designed as a lightweight framework to improve deployment efficiency and save resources. It employs efficient algorithms and optimization strategies to minimize resource consumption while maintaining sufficient functionality and performance. - -1.Support for multiple models and inference frameworks ------------------ -The field of large models is evolving rapidly, with new models being released and new methods being proposed for model training and inference. We believe that this situation will continue for some time. - -For most users exploring and implementing AI applications, this situation has its pros and cons. The benefits are apparent, as it brings new opportunities and advancements. However, one drawback is that users may feel compelled to constantly try and explore new models and inference frameworks. - -In DB-GPT, seamless support is provided for FastChat, vLLM, and llama.cpp. In theory, any model supported by these frameworks is also supported by DB-GPT. If you have requirements for faster inference speed and concurrency, you can directly use vLLM. If you want good inference performance on CPU or Apple's M1/M2 chips, you can use llama.cpp. Additionally, DB-GPT also supports various proxy models from OpenAI, Azure OpenAI, Google BARD, Wenxin Yiyan, Tongyi Qianwen, and Zhipu AI, among others. - -2.Have good scalability and stability ------------------ -A comprehensive model deployment framework consists of several components: the Model Worker, which directly interfaces with the underlying inference frameworks; the Model Controller, which manages and maintains multiple model components; and the Model API, which provides external model serving capabilities. - -The Model Worker plays a crucial role and needs to be highly extensible. It can be specialized for deploying large language models, embedding models, or other types of models. The choice of Model Worker depends on the deployment environment, such as a regular physical server environment, a Kubernetes environment, or specific cloud environments provided by various cloud service providers. - -Having different Model Worker options allows users to select the most suitable one based on their specific requirements and infrastructure. This flexibility enables efficient deployment and utilization of models across different environments. - -The Model Controller, responsible for managing model metadata, also needs to be scalable. Different deployment environments and model management requirements may call for different choices of Model Controllers. - -Furthermore, I believe that model serving shares many similarities with traditional microservices. In microservices, a service can have multiple instances, and all instances are registered in a central registry. Service consumers retrieve the list of instances based on the service name from the registry and select a specific instance for invocation using a load balancing strategy. - -Similarly, in model deployment, a model can have multiple instances, and all instances can be registered in a model registry. Model service consumers retrieve the list of instances based on the model name from the registry and select a specific instance for invocation using a model-specific load balancing strategy. - -Introducing a model registry, responsible for storing model instance metadata, enables such an architecture. The model registry can leverage existing service registries used in microservices (such as Nacos, Eureka, etcd, Consul, etc.) as implementations. This ensures high availability of the entire deployment system. - -3.High performance for framework. ------------------- -and optimization are complex tasks, and inappropriate framework designs can increase this complexity. In our view, to ensure that the deployment framework does not lag behind in terms of performance, there are two main areas of focus: - -Avoid excessive encapsulation: The more encapsulation and longer the chain, the more challenging it becomes to identify performance issues. - -High-performance communication design: High-performance communication involves various aspects that cannot be elaborated in detail here. However, considering that Python occupies a prominent position in current AIGC applications, asynchronous interfaces are crucial for service performance in Python. Therefore, the model serving layer should only provide asynchronous interfaces and be compatible with the layers that interface with the model inference framework. If the model inference framework offers asynchronous interfaces, direct integration should be implemented. Otherwise, synchronous-to-asynchronous task conversion should be used to provide support. - -4.Management and monitoring capabilities. ------------------- -In the exploration or production implementation of AIGC (Artificial Intelligence and General Computing) applications, it is important for the model deployment system to have certain management capabilities. This involves controlling the deployed model instances through APIs or command-line interfaces, such as for online/offline management, restarting, and debugging. - -Observability is a crucial capability in production systems, and I believe it is equally, if not more, important in AIGC applications. This is because user experiences and interactions with the system are more complex. In addition to traditional observability metrics, we are also interested in user input information and corresponding contextual information, which specific model instance and parameters were invoked, the content and response time of model outputs, user feedback, and more. - -By analyzing this information, we can identify performance bottlenecks in model services and gather user experience data (e.g., response latency, problem resolution, and user satisfaction extracted from user content). These insights serve as important foundations for further optimizing the entire application. - -* On :ref:`Deploying on standalone mode `. Standalone Deployment. -* On :ref:`Deploying on cluster mode `. Cluster Deployment. - - -.. toctree:: - :maxdepth: 2 - :caption: Cluster deployment - :name: cluster_deploy - :hidden: - - ./vms/standalone.md - ./vms/index.md - ./openai.md diff --git a/docs/getting_started/install/cluster/kubernetes/index.md b/docs/getting_started/install/cluster/kubernetes/index.md deleted file mode 100644 index 385a8b054..000000000 --- a/docs/getting_started/install/cluster/kubernetes/index.md +++ /dev/null @@ -1,3 +0,0 @@ -Kubernetes cluster deployment -================================== -(kubernetes-cluster-index)= \ No newline at end of file diff --git a/docs/getting_started/install/cluster/openai.md b/docs/getting_started/install/cluster/openai.md deleted file mode 100644 index 8f23ba0fa..000000000 --- a/docs/getting_started/install/cluster/openai.md +++ /dev/null @@ -1,51 +0,0 @@ -OpenAI-Compatible RESTful APIs -================================== -(openai-apis-index)= - -### Install Prepare - -You must [deploy DB-GPT cluster](https://db-gpt.readthedocs.io/en/latest/getting_started/install/cluster/vms/index.html) first. - -### Launch Model API Server - -```bash -dbgpt start apiserver --controller_addr http://127.0.0.1:8000 --api_keys EMPTY -``` -By default, the Model API Server starts on port 8100. - -### Validate with cURL - -#### List models - -```bash -curl http://127.0.0.1:8100/api/v1/models \ --H "Authorization: Bearer EMPTY" \ --H "Content-Type: application/json" -``` - -#### Chat completions - -```bash -curl http://127.0.0.1:8100/api/v1/chat/completions \ --H "Authorization: Bearer EMPTY" \ --H "Content-Type: application/json" \ --d '{"model": "vicuna-13b-v1.5", "messages": [{"role": "user", "content": "hello"}]}' -``` - -### Validate with OpenAI Official SDK - -#### Chat completions - -```python -import openai -openai.api_key = "EMPTY" -openai.api_base = "http://127.0.0.1:8100/api/v1" -model = "vicuna-13b-v1.5" - -completion = openai.ChatCompletion.create( - model=model, - messages=[{"role": "user", "content": "hello"}] -) -# print the completion -print(completion.choices[0].message.content) -``` \ No newline at end of file diff --git a/docs/getting_started/install/cluster/vms/standalone.md b/docs/getting_started/install/cluster/vms/standalone.md deleted file mode 100644 index 6e75e7d05..000000000 --- a/docs/getting_started/install/cluster/vms/standalone.md +++ /dev/null @@ -1,98 +0,0 @@ -Standalone Deployment -================================== -(standalone-index)= - -### Install Prepare -```commandline -git clone https://github.com/eosphoros-ai/DB-GPT.git - -cd DB-GPT -``` - -### Create conda environment -```commandline -conda create -n dbgpt_env python=3.10 - -conda activate dbgpt_env -``` - - -### Install Default Requirements -```commandline -# Install Default Requirements -pip install -e ".[default]" -``` - -### Download and Prepare LLM Model and Embedding Model -```{tip} - If you don't have high performance hardware server -``` -you can use openai api, tongyi api , bard api, etc. -```commandline -mkdir models && cd models - -# download embedding model, eg: text2vec-large-chinese -git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese - -``` - -set proxy api in .env -```commandline -#set LLM_MODEL TYPE -LLM_MODEL=proxyllm -#set your Proxy Api key and Proxy Server url -PROXY_API_KEY={your-openai-sk} -PROXY_SERVER_URL=https://api.openai.com/v1/chat/completions -``` -```{tip} -If you have high performance hardware server -``` - -```commandline -mkdir models && cd models - -# # download embedding model, eg: vicuna-13b-v1.5 or -git clone https://huggingface.co/lmsys/vicuna-13b-v1.5 - -# download embedding model, eg: text2vec-large-chinese -git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese - -popd -``` -### Start all services with a single command. -```commandline -LLM_MODEL=vicuna-13b-v1.5 -dbgpt start webserver --port 6006 -``` -By default, the "dbgpt start webserver" command will start the Webserver, Model Controller, and Model Worker in a single Python process. Here, we specify the service to be started on port 6006. - -### View and validate the model service in the command line, you can use the following commands -##### 1.list the started model services and deployed Model Workers, you can use the following command -```commandline -dbgpt model list -``` -output is: -```commandline -+-----------------+------------+------------+------+---------+---------+-----------------+----------------------------+ -| Model Name | Model Type | Host | Port | Healthy | Enabled | Prompt Template | Last Heartbeat | -+-----------------+------------+------------+------+---------+---------+-----------------+----------------------------+ -| vicuna-13b-v1.5 | llm | 172.17.0.9 | 6006 | True | True | | 2023-10-16T19:49:59.201313 | -| WorkerManager | service | 172.17.0.9 | 6006 | True | True | | 2023-10-16T19:49:59.246756 | -+-----------------+------------+------------+------+---------+---------+-----------------+----------------------------+ -``` -The WorkerManager is the management process for Model Workers - -##### validate the deployed model in the command line, you can use the following command -```commandline -dbgpt model chat --model_name vicuna-13b-v1.5 -``` -Then an interactive page will be launched where you can have a conversation with the deployed LLM in the terminal. -```commandline -Chatbot started with model vicuna-13b-v1.5. Type 'exit' to leave the chat. - - -You: Hello -Bot: Hello! How can I assist you today? - -You: -``` \ No newline at end of file diff --git a/docs/getting_started/install/deploy.rst b/docs/getting_started/install/deploy.rst deleted file mode 100644 index 075a07403..000000000 --- a/docs/getting_started/install/deploy.rst +++ /dev/null @@ -1,425 +0,0 @@ -.. _installation: - -Installation From Source -============== - -To get started, install DB-GPT with the following steps. - - -1.Preparation ------------------ -**Download DB-GPT** - -.. code-block:: shell - - git clone https://github.com/eosphoros-ai/DB-GPT.git - -**Install Miniconda** - -We use Sqlite as default database, so there is no need for database installation. If you choose to connect to other databases, you can follow our tutorial for installation and configuration. -For the entire installation process of DB-GPT, we use the miniconda3 virtual environment. Create a virtual environment and install the Python dependencies. -`How to install Miniconda `_ - -.. code-block:: shell - - python>=3.10 - conda create -n dbgpt_env python=3.10 - conda activate dbgpt_env - # it will take some minutes - pip install -e ".[default]" - -.. code-block:: shell - - cp .env.template .env - -2.Deploy LLM Service ------------------ -DB-GPT can be deployed on servers with low hardware requirements or on servers with high hardware requirements. - -If you are low hardware requirements you can install DB-GPT by Using third-part LLM REST API Service OpenAI, Azure, tongyi. - -.. tip:: - - As our project has the ability to achieve OpenAI performance of over 85%, - - -.. note:: - - Notice make sure you have install git-lfs - - centos:yum install git-lfs - - ubuntu:apt-get install git-lfs - - macos:brew install git-lfs - -.. tabs:: - - .. tab:: OpenAI - - Installing Dependencies - - .. code-block:: - - pip install -e ".[openai]" - - Download embedding model - - .. code-block:: shell - - cd DB-GPT - mkdir models and cd models - - #### embedding model - git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese - or - git clone https://huggingface.co/moka-ai/m3e-large - - Configure LLM_MODEL, PROXY_API_URL and API_KEY in `.env` file - - .. code-block:: shell - - LLM_MODEL=chatgpt_proxyllm - PROXY_API_KEY={your-openai-sk} - PROXY_SERVER_URL=https://api.openai.com/v1/chat/completions - - .. tip:: - - Make sure your .env configuration is not overwritten - - - .. tab:: Vicuna - `Vicuna-v1.5 `_ based on llama-2 has been released, we recommend you set `LLM_MODEL=vicuna-13b-v1.5` to try this model) - - .. list-table:: vicuna-v1.5 hardware requirements - :widths: 50 50 50 - :header-rows: 1 - - * - Model - - Quantize - - VRAM Size - * - vicuna-7b-v1.5 - - 4-bit - - 8 GB - * - vicuna-7b-v1.5 - - 8-bit - - 12 GB - * - vicuna-13b-v1.5 - - 4-bit - - 12 GB - * - vicuna-13b-v1.5 - - 8-bit - - 20 GB - - - .. code-block:: shell - - cd DB-GPT - mkdir models and cd models - - #### embedding model - git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese - or - git clone https://huggingface.co/moka-ai/m3e-large - - #### llm model, if you use openai or Azure or tongyi llm api service, you don't need to download llm model - git clone https://huggingface.co/lmsys/vicuna-13b-v1.5 - - The model files are large and will take a long time to download. - - **Configure LLM_MODEL in `.env` file** - - - .. code-block:: shell - - LLM_MODEL=vicuna-13b-v1.5 - - .. tab:: Baichuan - - .. list-table:: Baichuan hardware requirements - :widths: 50 50 50 - :header-rows: 1 - - * - Model - - Quantize - - VRAM Size - * - baichuan-7b - - 4-bit - - 8 GB - * - baichuan-7b - - 8-bit - - 12 GB - * - baichuan-13b - - 4-bit - - 12 GB - * - baichuan-13b - - 8-bit - - 20 GB - - - .. code-block:: shell - - cd DB-GPT - mkdir models and cd models - - #### embedding model - git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese - or - git clone https://huggingface.co/moka-ai/m3e-large - - #### llm model - git clone https://huggingface.co/baichuan-inc/Baichuan2-7B-Chat - or - git clone https://huggingface.co/baichuan-inc/Baichuan2-13B-Chat - - The model files are large and will take a long time to download. - - **Configure LLM_MODEL in `.env` file** - - please rename Baichuan path to "baichuan2-13b" or "baichuan2-7b" - - .. code-block:: shell - - LLM_MODEL=baichuan2-13b - - .. tab:: ChatGLM - - - .. code-block:: shell - - cd DB-GPT - mkdir models and cd models - - #### embedding model - git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese - or - git clone https://huggingface.co/moka-ai/m3e-large - - #### llm model - git clone https://huggingface.co/THUDM/chatglm2-6b - - The model files are large and will take a long time to download. - - **Configure LLM_MODEL in `.env` file** - - please rename chatglm model path to "chatglm2-6b" - - .. code-block:: shell - - LLM_MODEL=chatglm2-6b - - .. tab:: Other LLM API - - Download embedding model - - .. code-block:: shell - - cd DB-GPT - mkdir models and cd models - - #### embedding model - git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese - or - git clone https://huggingface.co/moka-ai/m3e-large - - Now DB-GPT support LLM REST API TYPE: - - .. note:: - - * OpenAI - * Azure - * Aliyun tongyi - * Baidu wenxin - * Zhipu - * Baichuan - * Bard - - Configure LLM_MODEL and PROXY_API_URL and API_KEY in `.env` file - - .. code-block:: shell - - #OpenAI - LLM_MODEL=chatgpt_proxyllm - PROXY_API_KEY={your-openai-sk} - PROXY_SERVER_URL=https://api.openai.com/v1/chat/completions - - #Azure - LLM_MODEL=chatgpt_proxyllm - PROXY_API_KEY={your-azure-sk} - PROXY_API_BASE=https://{your domain}.openai.azure.com/ - PROXY_API_TYPE=azure - PROXY_SERVER_URL=xxxx - PROXY_API_VERSION=2023-05-15 - PROXYLLM_BACKEND=gpt-35-turbo - - #Aliyun tongyi - LLM_MODEL=tongyi_proxyllm - TONGYI_PROXY_API_KEY={your-tongyi-sk} - PROXY_SERVER_URL={your_service_url} - - ## Baidu wenxin - LLM_MODEL=wenxin_proxyllm - PROXY_SERVER_URL={your_service_url} - WEN_XIN_MODEL_VERSION={version} - WEN_XIN_API_KEY={your-wenxin-sk} - WEN_XIN_SECRET_KEY={your-wenxin-sct} - - ## Zhipu - LLM_MODEL=zhipu_proxyllm - PROXY_SERVER_URL={your_service_url} - ZHIPU_MODEL_VERSION={version} - ZHIPU_PROXY_API_KEY={your-zhipu-sk} - - ## Baichuan - LLM_MODEL=bc_proxyllm - PROXY_SERVER_URL={your_service_url} - BAICHUN_MODEL_NAME={version} - BAICHUAN_PROXY_API_KEY={your-baichuan-sk} - BAICHUAN_PROXY_API_SECRET={your-baichuan-sct} - - ## bard - LLM_MODEL=bard_proxyllm - PROXY_SERVER_URL={your_service_url} - # from https://bard.google.com/ f12-> application-> __Secure-1PSID - BARD_PROXY_API_KEY={your-bard-token} - - .. tip:: - - Make sure your .env configuration is not overwritten - - .. tab:: llama.cpp - - DB-GPT already supports `llama.cpp `_ via `llama-cpp-python `_ . - - **Preparing Model Files** - - To use llama.cpp, you need to prepare a gguf format model file, and there are two common ways to obtain it, you can choose either: - - **1. Download a pre-converted model file.** - - Suppose you want to use `Vicuna 13B v1.5 `_ , you can download the file already converted from `TheBloke/vicuna-13B-v1.5-GGUF `_ , only one file is needed. Download it to the `models` directory and rename it to `ggml-model-q4_0.gguf`. - - .. code-block:: - - wget https://huggingface.co/TheBloke/vicuna-13B-v1.5-GGUF/resolve/main/vicuna-13b-v1.5.Q4_K_M.gguf -O models/ggml-model-q4_0.gguf - - **2. Convert It Yourself** - - You can convert the model file yourself according to the instructions in `llama.cpp#prepare-data--run `_ , and put the converted file in the models directory and rename it to `ggml-model-q4_0.gguf`. - - **Installing Dependencies** - - llama.cpp is an optional dependency in DB-GPT, and you can manually install it using the following command: - - .. code-block:: - - pip install -e ".[llama_cpp]" - - - **3.Modifying the Configuration File** - - Next, you can directly modify your `.env` file to enable llama.cpp. - - .. code-block:: - - LLM_MODEL=llama-cpp - llama_cpp_prompt_template=vicuna_v1.1 - - Then you can run it according to `Run `_ - - - **More Configurations** - - In DB-GPT, the model configuration can be done through `{model name}_{config key}`. - - .. list-table:: More Configurations - :widths: 50 50 50 - :header-rows: 1 - - * - Environment Variable Key - - Default - - Description - * - llama_cpp_prompt_template - - None - - Prompt template name, now support: zero_shot, vicuna_v1.1,alpaca,llama-2,baichuan-chat,internlm-chat, If None, the prompt template is automatically determined from model path。 - * - llama_cpp_model_path - - None - - Model path - * - llama_cpp_n_gpu_layers - - 1000000000 - - Number of layers to offload to the GPU, Set this to 1000000000 to offload all layers to the GPU. If your GPU VRAM is not enough, you can set a low number, eg: 10 - * - llama_cpp_n_threads - - None - - Number of threads to use. If None, the number of threads is automatically determined - * - llama_cpp_n_batch - - 512 - - Maximum number of prompt tokens to batch together when calling llama_eval - * - llama_cpp_n_gqa - - None - - Grouped-query attention. Must be 8 for llama-2 70b. - * - llama_cpp_rms_norm_eps - - 5e-06 - - 5e-6 is a good value for llama-2 models. - * - llama_cpp_cache_capacity - - None - - Maximum cache capacity. Examples: 2000MiB, 2GiB - * - llama_cpp_prefer_cpu - - False - - If a GPU is available, it will be preferred by default, unless prefer_cpu=False is configured. - - - .. tab:: vllm - - vLLM is a fast and easy-to-use library for LLM inference and serving. - - **Running vLLM** - - **1.Installing Dependencies** - - vLLM is an optional dependency in DB-GPT, and you can manually install it using the following command: - - .. code-block:: - - pip install -e ".[vllm]" - - **2.Modifying the Configuration File** - - Next, you can directly modify your .env file to enable vllm. - - .. code-block:: - - LLM_MODEL=vicuna-13b-v1.5 - MODEL_TYPE=vllm - - You can view the models supported by vLLM `here `_ - - Then you can run it according to `Run `_ - - - - - -3.Prepare sql example(Optional) ------------------ -**(Optional) load examples into SQLite** - -.. code-block:: shell - - bash ./scripts/examples/load_examples.sh - - -On windows platform: - -.. code-block:: shell - - .\scripts\examples\load_examples.bat - -4.Run db-gpt server ------------------ - -.. code-block:: shell - - python pilot/server/dbgpt_server.py - -**Open http://localhost:5000 with your browser to see the product.** - diff --git a/docs/getting_started/install/deploy/deploy.md b/docs/getting_started/install/deploy/deploy.md deleted file mode 100644 index 9317982d1..000000000 --- a/docs/getting_started/install/deploy/deploy.md +++ /dev/null @@ -1,156 +0,0 @@ -# Installation From Source - -This tutorial gives you a quick walkthrough about use DB-GPT with you environment and data. - -## Installation - -To get started, install DB-GPT with the following steps. - -### 1. Hardware Requirements - DB-GPT can be deployed on servers with low hardware requirements or on servers with high hardware requirements. - -##### Low hardware requirements -The low hardware requirements mode is suitable for integrating with third-party LLM services' APIs, such as OpenAI, Tongyi, Wenxin, or Llama.cpp. - -DB-GPT provides set proxy api to support LLM api. - -As our project has the ability to achieve ChatGPT performance of over 85%, - -##### High hardware requirements -The high hardware requirements mode is suitable for independently deploying LLM services, such as Llama series models, Baichuan, ChatGLM, Vicuna, and other private LLM service. -there are certain hardware requirements. However, overall, the project can be deployed and used on consumer-grade graphics cards. The specific hardware requirements for deployment are as follows: - -| GPU | VRAM Size | Performance | -|----------|-----------| ------------------------------------------- | -| RTX 4090 | 24 GB | Smooth conversation inference | -| RTX 3090 | 24 GB | Smooth conversation inference, better than V100 | -| V100 | 16 GB | Conversation inference possible, noticeable stutter | -| T4 | 16 GB | Conversation inference possible, noticeable stutter | - -If your VRAM Size is not enough, DB-GPT supported 8-bit quantization and 4-bit quantization. - -Here are some of the VRAM size usage of the models we tested in some common scenarios. - -| Model | Quantize | VRAM Size | -| --------- | --------- | --------- | -| vicuna-7b-v1.5 | 4-bit | 8 GB | -| vicuna-7b-v1.5 | 8-bit | 12 GB | -| vicuna-13b-v1.5 | 4-bit | 12 GB | -| vicuna-13b-v1.5 | 8-bit | 20 GB | -| llama-2-7b | 4-bit | 8 GB | -| llama-2-7b | 8-bit | 12 GB | -| llama-2-13b | 4-bit | 12 GB | -| llama-2-13b | 8-bit | 20 GB | -| llama-2-70b | 4-bit | 48 GB | -| llama-2-70b | 8-bit | 80 GB | -| baichuan-7b | 4-bit | 8 GB | -| baichuan-7b | 8-bit | 12 GB | -| baichuan-13b | 4-bit | 12 GB | -| baichuan-13b | 8-bit | 20 GB | - -### 2. Install -```bash -git clone https://github.com/eosphoros-ai/DB-GPT.git -``` - -We use Sqlite as default database, so there is no need for database installation. If you choose to connect to other databases, you can follow our tutorial for installation and configuration. -For the entire installation process of DB-GPT, we use the miniconda3 virtual environment. Create a virtual environment and install the Python dependencies. -[How to install Miniconda](https://docs.conda.io/en/latest/miniconda.html) -```bash -python>=3.10 -conda create -n dbgpt_env python=3.10 -conda activate dbgpt_env -# it will take some minutes -pip install -e ".[default]" -``` - -Once the environment is installed, we have to create a new folder "models" in the DB-GPT project, and then we can put all the models downloaded from huggingface in this directory - -```{tip} -Notice make sure you have install git-lfs - -centos:yum install git-lfs - -ubuntu:apt-get install git-lfs - -macos:brew install git-lfs -``` -##### Download LLM Model and Embedding Model - -If you use OpenAI llm service, see [How to Use LLM REST API](https://db-gpt.readthedocs.io/en/latest/getting_started/install/llm/proxyllm/proxyllm.html) - -```{tip} -If you use openai or Axzure or tongyi llm api service, you don't need to download llm model. - -``` - -```bash -cd DB-GPT -mkdir models and cd models - -#### embedding model -git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese -or -git clone https://huggingface.co/moka-ai/m3e-large - -#### llm model, if you use openai or Azure or tongyi llm api service, you don't need to download llm model -git clone https://huggingface.co/lmsys/vicuna-13b-v1.5 -or -git clone https://huggingface.co/THUDM/chatglm2-6b - -``` - -The model files are large and will take a long time to download. During the download, let's configure the .env file, which needs to be copied and created from the .env.template - -```{tip} -cp .env.template .env -``` - -You can configure basic parameters in the .env file, for example setting LLM_MODEL to the model to be used - -([Vicuna-v1.5](https://huggingface.co/lmsys/vicuna-13b-v1.5) based on llama-2 has been released, we recommend you set `LLM_MODEL=vicuna-13b-v1.5` to try this model) - -### 3. Run - -**(Optional) load examples into SQLite** -```bash -bash ./scripts/examples/load_examples.sh -``` - -On windows platform: -```PowerShell -.\scripts\examples\load_examples.bat -``` - -Run db-gpt server - -```bash -python pilot/server/dbgpt_server.py -``` - -Open http://localhost:5000 with your browser to see the product. - - -### Multiple GPUs - -DB-GPT will use all available gpu by default. And you can modify the setting `CUDA_VISIBLE_DEVICES=0,1` in `.env` file to use the specific gpu IDs. - -Optionally, you can also specify the gpu ID to use before the starting command, as shown below: - -````shell -# Specify 1 gpu -CUDA_VISIBLE_DEVICES=0 python3 pilot/server/dbgpt_server.py - -# Specify 4 gpus -CUDA_VISIBLE_DEVICES=3,4,5,6 python3 pilot/server/dbgpt_server.py -```` - -You can modify the setting `MAX_GPU_MEMORY=xxGib` in `.env` file to configure the maximum memory used by each GPU. - -### Not Enough Memory - -DB-GPT supported 8-bit quantization and 4-bit quantization. - -You can modify the setting `QUANTIZE_8bit=True` or `QUANTIZE_4bit=True` in `.env` file to use quantization(8-bit quantization is enabled by default). - -Llama-2-70b with 8-bit quantization can run with 80 GB of VRAM, and 4-bit quantization can run with 48 GB of VRAM. \ No newline at end of file diff --git a/docs/getting_started/install/docker/docker.md b/docs/getting_started/install/docker/docker.md deleted file mode 100644 index f0ba2f331..000000000 --- a/docs/getting_started/install/docker/docker.md +++ /dev/null @@ -1,123 +0,0 @@ -Docker Install -================================== - -### Docker (Experimental) - -#### 1. Preparing docker images - -**Pull docker image from the [Eosphoros AI Docker Hub](https://hub.docker.com/u/eosphorosai)** - -```bash -docker pull eosphorosai/dbgpt:latest -``` - -**(Optional) Building Docker image** - -```bash -bash docker/build_all_images.sh -``` - -Review images by listing them: - -```bash -docker images|grep "eosphorosai/dbgpt" -``` - -Output should look something like the following: - -``` -eosphorosai/dbgpt-allinone latest 349d49726588 27 seconds ago 15.1GB -eosphorosai/dbgpt latest eb3cdc5b4ead About a minute ago 14.5GB -``` - -`eosphorosai/dbgpt` is the base image, which contains the project's base dependencies and a sqlite database. `eosphorosai/dbgpt-allinone` build from `eosphorosai/dbgpt`, which contains a mysql database. - -You can pass some parameters to docker/build_all_images.sh. -```bash -bash docker/build_all_images.sh \ ---base-image nvidia/cuda:11.8.0-runtime-ubuntu22.04 \ ---pip-index-url https://pypi.tuna.tsinghua.edu.cn/simple \ ---language zh -``` - -You can execute the command `bash docker/build_all_images.sh --help` to see more usage. - -#### 2. Run docker container - -**Run with local model and SQLite database** - -```bash -docker run --ipc host --gpus all -d \ - -p 5000:5000 \ - -e LOCAL_DB_TYPE=sqlite \ - -e LOCAL_DB_PATH=data/default_sqlite.db \ - -e LLM_MODEL=vicuna-13b-v1.5 \ - -e LANGUAGE=zh \ - -v /data/models:/app/models \ - --name dbgpt \ - eosphorosai/dbgpt -``` - -Open http://localhost:5000 with your browser to see the product. - - -- `-e LLM_MODEL=vicuna-13b-v1.5`, means we use vicuna-13b-v1.5 as llm model, see /pilot/configs/model_config.LLM_MODEL_CONFIG -- `-v /data/models:/app/models`, means we mount the local model file directory `/data/models` to the docker container directory `/app/models`, please replace it with your model file directory. - -You can see log with command: - -```bash -docker logs dbgpt -f -``` - -**Run with local model and MySQL database** - -```bash -docker run --ipc host --gpus all -d -p 3306:3306 \ - -p 5000:5000 \ - -e LOCAL_DB_HOST=127.0.0.1 \ - -e LOCAL_DB_PASSWORD=aa123456 \ - -e MYSQL_ROOT_PASSWORD=aa123456 \ - -e LLM_MODEL=vicuna-13b-v1.5 \ - -e LANGUAGE=zh \ - -v /data/models:/app/models \ - --name db-gpt-allinone \ - db-gpt-allinone -``` - -Open http://localhost:5000 with your browser to see the product. - - -- `-e LLM_MODEL=vicuna-13b-v1.5`, means we use vicuna-13b-v1.5 as llm model, see /pilot/configs/model_config.LLM_MODEL_CONFIG -- `-v /data/models:/app/models`, means we mount the local model file directory `/data/models` to the docker container directory `/app/models`, please replace it with your model file directory. - -You can see log with command: - -```bash -docker logs db-gpt-allinone -f -``` - -**Run with openai interface** - -```bash -PROXY_API_KEY="You api key" -PROXY_SERVER_URL="https://api.openai.com/v1/chat/completions" -docker run --gpus all -d -p 3306:3306 \ - -p 5000:5000 \ - -e LOCAL_DB_HOST=127.0.0.1 \ - -e LOCAL_DB_PASSWORD=aa123456 \ - -e MYSQL_ROOT_PASSWORD=aa123456 \ - -e LLM_MODEL=proxyllm \ - -e PROXY_API_KEY=$PROXY_API_KEY \ - -e PROXY_SERVER_URL=$PROXY_SERVER_URL \ - -e LANGUAGE=zh \ - -v /data/models/text2vec-large-chinese:/app/models/text2vec-large-chinese \ - --name db-gpt-allinone \ - db-gpt-allinone -``` - -- `-e LLM_MODEL=proxyllm`, means we use proxy llm(openai interface, fastchat interface...) -- `-v /data/models/text2vec-large-chinese:/app/models/text2vec-large-chinese`, means we mount the local text2vec model to the docker container. - - -Open http://localhost:5000 with your browser to see the product. diff --git a/docs/getting_started/install/docker_compose/docker_compose.md b/docs/getting_started/install/docker_compose/docker_compose.md deleted file mode 100644 index 49741c94c..000000000 --- a/docs/getting_started/install/docker_compose/docker_compose.md +++ /dev/null @@ -1,26 +0,0 @@ -Docker Compose -================================== - -#### Run with docker compose - -```bash -$ docker compose up -d -``` - -Output should look something like the following: -``` -[+] Building 0.0s (0/0) -[+] Running 2/2 - ✔ Container db-gpt-db-1 Started 0.4s - ✔ Container db-gpt-webserver-1 Started -``` - -You can see log with command: - -```bash -$ docker logs db-gpt-webserver-1 -f -``` - -Open http://localhost:5000 with your browser to see the product. - -You can open docker-compose.yml in the project root directory to see more details. diff --git a/docs/getting_started/install/environment/environment.md b/docs/getting_started/install/environment/environment.md deleted file mode 100644 index 11aec8d40..000000000 --- a/docs/getting_started/install/environment/environment.md +++ /dev/null @@ -1,109 +0,0 @@ -Environment Parameter -================================== - -```{admonition} LLM MODEL Config -LLM Model Name, see /pilot/configs/model_config.LLM_MODEL_CONFIG -* LLM_MODEL=vicuna-13b - -MODEL_SERVER_ADDRESS - -* MODEL_SERVER=http://127.0.0.1:8000 - -LIMIT_MODEL_CONCURRENCY - -* LIMIT_MODEL_CONCURRENCY=5 - -MAX_POSITION_EMBEDDINGS - -* MAX_POSITION_EMBEDDINGS=4096 - -QUANTIZE_QLORA - -* QUANTIZE_QLORA=True - -QUANTIZE_8bit - -* QUANTIZE_8bit=True -``` - -```{admonition} LLM PROXY Settings -OPENAI Key - -* PROXY_API_KEY={your-openai-sk} -* PROXY_SERVER_URL=https://api.openai.com/v1/chat/completions - -from https://bard.google.com/ f12-> application-> __Secure-1PSID - -* BARD_PROXY_API_KEY={your-bard-token} -``` - -```{admonition} DATABASE SETTINGS -### SQLite database (Current default database) -* LOCAL_DB_PATH=data/default_sqlite.db -* LOCAL_DB_TYPE=sqlite # Database Type default:sqlite - -### MYSQL database -* LOCAL_DB_TYPE=mysql -* LOCAL_DB_USER=root -* LOCAL_DB_PASSWORD=aa12345678 -* LOCAL_DB_HOST=127.0.0.1 -* LOCAL_DB_PORT=3306 -``` - -```{admonition} EMBEDDING SETTINGS -EMBEDDING MODEL Name, see /pilot/configs/model_config.LLM_MODEL_CONFIG -* EMBEDDING_MODEL=text2vec - -Embedding Chunk size, default 500 - -* KNOWLEDGE_CHUNK_SIZE=500 - -Embedding Chunk Overlap, default 100 -* KNOWLEDGE_CHUNK_OVERLAP=100 - -embedding recall top k,5 - -* KNOWLEDGE_SEARCH_TOP_SIZE=5 - -embedding recall max token ,2000 - -* KNOWLEDGE_SEARCH_MAX_TOKEN=5 -``` - -```{admonition} Vector Store SETTINGS -#### Chroma -* VECTOR_STORE_TYPE=Chroma -#### MILVUS -* VECTOR_STORE_TYPE=Milvus -* MILVUS_URL=127.0.0.1 -* MILVUS_PORT=19530 -* MILVUS_USERNAME -* MILVUS_PASSWORD -* MILVUS_SECURE= - -#### WEAVIATE -* VECTOR_STORE_TYPE=Weaviate -* WEAVIATE_URL=https://kt-region-m8hcy0wc.weaviate.network -``` - -```{admonition} Multi-GPU Setting -See https://developer.nvidia.com/blog/cuda-pro-tip-control-gpu-visibility-cuda_visible_devices/ -If CUDA_VISIBLE_DEVICES is not configured, all available gpus will be used - -* CUDA_VISIBLE_DEVICES=0 - -Optionally, you can also specify the gpu ID to use before the starting command - -* CUDA_VISIBLE_DEVICES=3,4,5,6 - -You can configure the maximum memory used by each GPU. - -* MAX_GPU_MEMORY=16Gib -``` - -```{admonition} Other Setting -#### Language Settings(influence prompt language) -* LANGUAGE=en -* LANGUAGE=zh -``` - diff --git a/docs/getting_started/install/llm/llama/llama_cpp.md b/docs/getting_started/install/llm/llama/llama_cpp.md deleted file mode 100644 index 8295884ba..000000000 --- a/docs/getting_started/install/llm/llama/llama_cpp.md +++ /dev/null @@ -1,82 +0,0 @@ -llama.cpp -================================== - - -DB-GPT already supports [llama.cpp](https://github.com/ggerganov/llama.cpp) via [llama-cpp-python](https://github.com/abetlen/llama-cpp-python). - -## Running llama.cpp - -### Preparing Model Files - -To use llama.cpp, you need to prepare a gguf format model file, and there are two common ways to obtain it, you can choose either: - -1. Download a pre-converted model file. - -Suppose you want to use [Vicuna 13B v1.5](https://huggingface.co/lmsys/vicuna-13b-v1.5), you can download the file already converted from [TheBloke/vicuna-13B-v1.5-GGUF](https://huggingface.co/TheBloke/vicuna-13B-v1.5-GGUF), only one file is needed. Download it to the `models` directory and rename it to `ggml-model-q4_0.gguf`. - -```bash -wget https://huggingface.co/TheBloke/vicuna-13B-v1.5-GGUF/resolve/main/vicuna-13b-v1.5.Q4_K_M.gguf -O models/ggml-model-q4_0.gguf -``` - -2. Convert It Yourself - -You can convert the model file yourself according to the instructions in [llama.cpp#prepare-data--run](https://github.com/ggerganov/llama.cpp#prepare-data--run), and put the converted file in the models directory and rename it to `ggml-model-q4_0.gguf`. - -### Installing Dependencies - -llama.cpp is an optional dependency in DB-GPT, and you can manually install it using the following command: - -```bash -pip install -e ".[llama_cpp]" -``` - -### Modifying the Configuration File - -Next, you can directly modify your `.env` file to enable llama.cpp. - -```env -LLM_MODEL=llama-cpp -llama_cpp_prompt_template=vicuna_v1.1 -``` - -Then you can run it according to [Run](https://db-gpt.readthedocs.io/en/latest/getting_started/install/deploy/deploy.html#run). - - -### More Configurations - -In DB-GPT, the model configuration can be done through `{model name}_{config key}`. - -| Environment Variable Key | default | Description | -|----------|-----------| ----------- | -| llama_cpp_prompt_template | None | Prompt template name, now support: `zero_shot, vicuna_v1.1,alpaca,llama-2,baichuan-chat,internlm-chat`, If None, the prompt template is automatically determined from model path。 | -| llama_cpp_model_path | None | Model path | -| llama_cpp_n_gpu_layers | 1000000000 |Number of layers to offload to the GPU, Set this to 1000000000 to offload all layers to the GPU. If your GPU VRAM is not enough, you can set a low number, eg: `10` | -| llama_cpp_n_threads | None | Number of threads to use. If None, the number of threads is automatically determined | -| llama_cpp_n_batch | 512 | Maximum number of prompt tokens to batch together when calling llama_eval | -| llama_cpp_n_gqa | None | Grouped-query attention. Must be 8 for llama-2 70b.| -| llama_cpp_rms_norm_eps | 5e-06 | 5e-6 is a good value for llama-2 models.| -| llama_cpp_cache_capacity | None | Maximum cache capacity. Examples: 2000MiB, 2GiB | -| llama_cpp_prefer_cpu | False | If a GPU is available, it will be preferred by default, unless prefer_cpu=False is configured. | - -## GPU Acceleration - -GPU acceleration is supported by default. If you encounter any issues, you can uninstall the dependent packages with the following command: -```bash -pip uninstall -y llama-cpp-python llama_cpp_python_cuda -``` - -Then install `llama-cpp-python` according to the instructions in [llama-cpp-python](https://github.com/abetlen/llama-cpp-python/blob/main/README.md). - - -### Mac Usage - -Special attention, if you are using Apple Silicon (M1) Mac, it is highly recommended to install arm64 architecture python support, for example: - -```bash -wget https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-MacOSX-arm64.sh -bash Miniforge3-MacOSX-arm64.sh -``` - -### Windows Usage - -The use under the Windows platform has not been rigorously tested and verified, and you are welcome to use it. If you have any problems, you can create an [issue](https://github.com/eosphoros-ai/DB-GPT/issues) or [contact us](https://github.com/eosphoros-ai/DB-GPT/tree/main#contact-information) directly. diff --git a/docs/getting_started/install/llm/llm.rst b/docs/getting_started/install/llm/llm.rst deleted file mode 100644 index c5f69c5fb..000000000 --- a/docs/getting_started/install/llm/llm.rst +++ /dev/null @@ -1,34 +0,0 @@ -LLM Usage -================================== -DB-GPT provides a management and deployment solution for multiple models. This chapter mainly discusses how to deploy different models. - -.. image:: https://github.com/eosphoros-ai/DB-GPT/assets/13723926/a0d0840f-570a-4409-bb7d-bec6535a5f62 - - -Multi LLMs Support, Supports multiple large language models, currently supporting - - 🔥 InternLM(7b,20b) - - 🔥 Baichuan2(7b,13b) - - 🔥 Vicuna-v1.5(7b,13b) - - 🔥 llama-2(7b,13b,70b) - - WizardLM-v1.2(13b) - - Vicuna (7b,13b) - - ChatGLM-6b (int4,int8) - - ChatGLM2-6b (int4,int8) - - guanaco(7b,13b,33b) - - Gorilla(7b,13b) - - Baichuan(7b,13b) - - OpenAI - -- llama_cpp -- quantization - -.. toctree:: - :maxdepth: 2 - :caption: LLM Usage - :name: llama_cpp - :hidden: - - ./proxyllm/proxyllm.md - ./llama/llama_cpp.md - ./quantization/quantization.md - ./vllm/vllm.md diff --git a/docs/getting_started/install/llm/proxyllm/proxyllm.md b/docs/getting_started/install/llm/proxyllm/proxyllm.md deleted file mode 100644 index fae549dd3..000000000 --- a/docs/getting_started/install/llm/proxyllm/proxyllm.md +++ /dev/null @@ -1,78 +0,0 @@ -Proxy LLM API -================================== -Now DB-GPT supports connect LLM service through proxy rest api. - -LLM rest api now supports -```{note} -* OpenAI -* Azure -* Aliyun tongyi -* Baidu wenxin -* Zhipu -* Baichuan -* Bard -``` - - -### How to Integrate LLM rest API, like OpenAI, Azure, tongyi, wenxin llm api service? -update your `.env` file -```commandline -#OpenAI -LLM_MODEL=chatgpt_proxyllm -PROXY_API_KEY={your-openai-sk} -PROXY_SERVER_URL=https://api.openai.com/v1/chat/completions - -#Azure -LLM_MODEL=chatgpt_proxyllm -PROXY_API_KEY={your-azure-sk} -PROXY_API_BASE=https://{your domain}.openai.azure.com/ -PROXY_API_TYPE=azure -PROXY_SERVER_URL=xxxx -PROXY_API_VERSION=2023-05-15 -PROXYLLM_BACKEND=gpt-35-turbo - -#Aliyun tongyi -LLM_MODEL=tongyi_proxyllm -TONGYI_PROXY_API_KEY={your-tongyi-sk} -PROXY_SERVER_URL={your_service_url} - -## Baidu wenxin -LLM_MODEL=wenxin_proxyllm -PROXY_SERVER_URL={your_service_url} -WEN_XIN_MODEL_VERSION={version} -WEN_XIN_API_KEY={your-wenxin-sk} -WEN_XIN_SECRET_KEY={your-wenxin-sct} - -## Zhipu -LLM_MODEL=zhipu_proxyllm -PROXY_SERVER_URL={your_service_url} -ZHIPU_MODEL_VERSION={version} -ZHIPU_PROXY_API_KEY={your-zhipu-sk} - -## Baichuan -LLM_MODEL=bc_proxyllm -PROXY_SERVER_URL={your_service_url} -BAICHUN_MODEL_NAME={version} -BAICHUAN_PROXY_API_KEY={your-baichuan-sk} -BAICHUAN_PROXY_API_SECRET={your-baichuan-sct} - -## bard -LLM_MODEL=bard_proxyllm -PROXY_SERVER_URL={your_service_url} -# from https://bard.google.com/ f12-> application-> __Secure-1PSID -BARD_PROXY_API_KEY={your-bard-token} -``` -```{tip} -Make sure your .env configuration is not overwritten -``` - -### How to Integrate Embedding rest API, like OpenAI, Azure api service? - -```commandline -## Openai embedding model, See /pilot/model/parameter.py -EMBEDDING_MODEL=proxy_openai -proxy_openai_proxy_server_url=https://api.openai.com/v1 -proxy_openai_proxy_api_key={your-openai-sk} -proxy_openai_proxy_backend=text-embedding-ada-002 -``` - diff --git a/docs/getting_started/install/llm/quantization/quantization.md b/docs/getting_started/install/llm/quantization/quantization.md deleted file mode 100644 index 58f0acd8a..000000000 --- a/docs/getting_started/install/llm/quantization/quantization.md +++ /dev/null @@ -1,2 +0,0 @@ -quantization -================================== \ No newline at end of file diff --git a/docs/getting_started/install/llm/vllm/vllm.md b/docs/getting_started/install/llm/vllm/vllm.md deleted file mode 100644 index c4d0d2137..000000000 --- a/docs/getting_started/install/llm/vllm/vllm.md +++ /dev/null @@ -1,26 +0,0 @@ -vLLM -================================== - -[vLLM](https://github.com/vllm-project/vllm) is a fast and easy-to-use library for LLM inference and serving. - -## Running vLLM - -### Installing Dependencies - -vLLM is an optional dependency in DB-GPT, and you can manually install it using the following command: - -```bash -pip install -e ".[vllm]" -``` - -### Modifying the Configuration File - -Next, you can directly modify your `.env` file to enable vllm. - -```env -LLM_MODEL=vicuna-13b-v1.5 -MODEL_TYPE=vllm -``` -You can view the models supported by vLLM [here](https://vllm.readthedocs.io/en/latest/models/supported_models.html#supported-models) - -Then you can run it according to [Run](https://db-gpt.readthedocs.io/en/latest/getting_started/install/deploy/deploy.html#run). \ No newline at end of file diff --git a/docs/getting_started/installation.md b/docs/getting_started/installation.md deleted file mode 100644 index 9ee7c3a7c..000000000 --- a/docs/getting_started/installation.md +++ /dev/null @@ -1,35 +0,0 @@ -# Python SDK -DB-GPT provides a third-party Python API package that you can integrate into your own code. - -### Installation from Pip - -You can simply pip install: -```bash -pip install -i https://pypi.org/simple/ db-gpt==0.3.0 -``` - -```{tip} -Notice:make sure python>=3.10 -``` - -### Environment Setup - -By default, if you use the EmbeddingEngine api - -you will prepare embedding models from huggingface - -```{tip} -Notice make sure you have install git-lfs -``` - -```bash -git clone https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2 - -git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese -``` -version: -- db-gpt0.3.0 - - [embedding_engine api](https://db-gpt.readthedocs.io/en/latest/modules/knowledge.html) - - [multi source embedding](https://db-gpt.readthedocs.io/en/latest/modules/knowledge/pdf/pdf_embedding.html) - - [vector connector](https://db-gpt.readthedocs.io/en/latest/modules/vector.html) - diff --git a/docs/getting_started/tutorials.md b/docs/getting_started/tutorials.md deleted file mode 100644 index 1e0ced59c..000000000 --- a/docs/getting_started/tutorials.md +++ /dev/null @@ -1,23 +0,0 @@ -# Tutorials -------------- - -This is a collection of DB-GPT tutorials on Medium. - -DB-GPT is divided into several functions, including chat with knowledge base, execute SQL, chat with database, and execute plugins. - -### Introduction - -#### youtube -[What is DB-GPT](https://www.youtube.com/watch?v=QszhVJerc0I) - -[How to deploy DB-GPT step by step](https://www.youtube.com/watch?v=OJGU4fQCqPs) - - -#### bilibili -[What is DB-GPT](https://www.bilibili.com/video/BV1SM4y1a7Nj/?spm_id_from=333.788&vd_source=7792e22c03b7da3c556a450eb42c8a0f) - -[How to deploy DB-GPT step by step](https://www.bilibili.com/video/BV1mu411Y7ve/?spm_id_from=pageDriver&vd_source=7792e22c03b7da3c556a450eb42c8a0f) - - - - diff --git a/docs/index.rst b/docs/index.rst deleted file mode 100644 index 56f851227..000000000 --- a/docs/index.rst +++ /dev/null @@ -1,116 +0,0 @@ -.. DB-GPT documentation master file, created by - sphinx-quickstart on Wed May 24 11:50:49 2023. - You can adapt this file completely to your liking, but it should at least - contain the root `toctree` directive. - -Overview ------------------- - -| DB-GPT is an open-source framework for large models in the databases fields. It's purpose is to build infrastructure for the domain of large models, making it easier and more convenient to develop applications around databases. By developing various technical capabilities such as: - -1. **SMMF(Service-oriented Multi-model Management Framework)** -2. **Text2SQL Fine-tuning** -3. **RAG(Retrieval Augmented Generation) framework and optimization** -4. **Data-Driven Agents framework collaboration** -5. **GBI(Generative Business intelligence)** - -etc, DB-GPT simplifies the construction of large model applications based on databases. - -| In the era of Data 3.0, enterprises and developers can build their own customized applications with less code, leveraging models and databases. - -Features -^^^^^^^^^^^ - -| **1. Private Domain Q&A & Data Processing** -| Supports custom construction of knowledge bases through methods such as built-in, multi-file format uploads, and plugin-based web scraping. Enables unified vector storage and retrieval of massive structured and unstructured data. - -| **2.Multi-Data Source & GBI(Generative Business intelligence)** -| Supports interaction between natural language and various data sources such as Excel, databases, and data warehouses. Also supports analysis reporting. - -| **3.SMMF(Service-oriented Multi-model Management Framework)** -| Supports a wide range of models, including dozens of large language models such as open-source models and API proxies. Examples include LLaMA/LLaMA2, Baichuan, ChatGLM, Wenxin, Tongyi, Zhipu, Xinghuo, etc. - -| **4.Automated Fine-tuning** -| A lightweight framework for automated fine-tuning built around large language models, Text2SQL datasets, and methods like LoRA/QLoRA/Pturning. Makes TextSQL fine-tuning as convenient as a production line. - -| **5.Data-Driven Multi-Agents & Plugins** -| Supports executing tasks through custom plugins and natively supports the Auto-GPT plugin model. Agents protocol follows the Agent Protocol standard. - -| **6.Privacy and Security** -| Ensures data privacy and security through techniques such as privatizing large models and proxy de-identification. - - -Getting Started -^^^^^^^^^^^^^^^^^ - -| Quickstart - -- `Quickstart Guide <./getting_started/getting_started.html>`_ - -| Concepts and terminology - -- `Concepts and Terminology <./getting_started/concepts.html>`_ - -.. toctree:: - :maxdepth: 2 - :caption: Getting Started - :name: getting_started - :hidden: - - getting_started/install.rst - getting_started/application.md - getting_started/installation.md - getting_started/concepts.md - getting_started/tutorials.md - getting_started/faq.rst - getting_started/observability.md - - -Modules -^^^^^^^^^ - -| These modules are the core abstractions with which we can interact with data and environment smoothly. It's very important for DB-GPT, DB-GPT also provide standard, extendable interfaces. - -| The docs for each module contain quickstart examples, how to guides, reference docs, and conceptual guides. - -| The modules are as follows - -- `LLMs <./modules/llms.html>`_: Supported multi models management and integrations. - -- `Prompts <./modules/prompts.html>`_: Prompt management, optimization, and serialization for multi database. - -- `Plugins <./modules/plugins.html>`_: Plugins management, scheduler. - -- `Knowledge <./modules/knowledge.html>`_: Knowledge management, embedding, and search. - -- `Connections <./modules/connections.html>`_: Supported multi databases connection. management connections and interact with this. - -- `Vector <./modules/vector.html>`_: Supported multi vector database. - -------------- - -.. toctree:: - :maxdepth: 2 - :caption: Modules - :name: modules - :hidden: - - modules/llms.md - modules/prompts.md - modules/plugins.md - modules/connections.rst - modules/knowledge.rst - modules/vector.rst - -Resources ------------------ - -| Additional resources we think may be useful as you develop your application! - -- `Discord `_: if your have some problem or ideas, you can talk from discord. - -.. toctree:: - :maxdepth: 1 - :caption: Resources - :name: resources - :hidden: diff --git a/docs/locales/zh_CN/LC_MESSAGES/ecosystem.po b/docs/locales/zh_CN/LC_MESSAGES/ecosystem.po deleted file mode 100644 index 769ca0c6c..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/ecosystem.po +++ /dev/null @@ -1,25 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 0.3.0\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-06-11 14:10+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.11.0\n" - -#: ../../ecosystem.md:1 2a67e31428d84197939447c3decf9768 -msgid "Ecosystem" -msgstr "环境系统" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/faq.po b/docs/locales/zh_CN/LC_MESSAGES/faq.po deleted file mode 100644 index 958b9c3d2..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/faq.po +++ /dev/null @@ -1,248 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.3.0\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-08-17 21:23+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../faq.md:1 a39cbc25271841d79095c1557a817a76 -msgid "FAQ" -msgstr "" - -#: ../../faq.md:2 b08ce199a11b4d309142866a637bc3d0 -msgid "Q1: text2vec-large-chinese not found" -msgstr "" - -#: ../../faq.md:4 754a61fa05a846f4847bd988c4049ceb -msgid "" -"A1: make sure you have download text2vec-large-chinese embedding model in" -" right way" -msgstr "" - -#: ../../faq.md:16 5a3d32eacdd94f59bb4039c3d6380fc9 -msgid "" -"Q2: execute `pip install -r requirements.txt` error, found some package " -"cannot find correct version." -msgstr "" - -#: ../../faq.md:19 54b322726a074d6d9c1a957310774aba -msgid "A2: change the pip source." -msgstr "" - -#: ../../faq.md:26 ../../faq.md:33 0c238f86900243e5b5e9a49e4ef37063 -#: 245e48f636524172b1b9ba4144946007 -msgid "or" -msgstr "" - -#: ../../faq.md:41 f2f7025f324c4065abf244a3adb4e4f6 -msgid "Q3:Access denied for user 'root@localhost'(using password :NO)" -msgstr "" - -#: ../../faq.md:43 f14fd1c2d2ed454491e0a876fd2971a4 -msgid "A3: make sure you have installed mysql instance in right way" -msgstr "" - -#: ../../faq.md:45 6d499bfb6c0142ec838f68696f793c3d -msgid "Docker:" -msgstr "" - -#: ../../faq.md:49 71137fe8a30d42e7943dd2a4402b2094 -msgid "Normal: [download mysql instance](https://dev.mysql.com/downloads/mysql/)" -msgstr "" - -#: ../../faq.md:52 ec5d5f79cbe54328902e6e9b820276e7 -msgid "Q4:When I use openai(MODEL_SERVER=proxyllm) to chat" -msgstr "" - -#: ../../faq.md:58 d2cbee8bbfd54b4b853ccbdbf1c30c97 -msgid "A4: make sure your openapi API_KEY is available" -msgstr "" - -#: ../../faq.md:60 c506819975c841468af1899730df3ed1 -msgid "Q5:When I Chat Data and Chat Meta Data, I found the error" -msgstr "Chat Data and Chat Meta Data报如下错" - -#: ../../faq.md:67 af52123acad74c28a50f93d53da6afa9 -msgid "A5: you have not create your database and table" -msgstr "需要创建自己的数据库" - -#: ../../faq.md:68 05bf6d858df44157bfb5480f9e8759fb -msgid "1.create your database." -msgstr "1.先创建数据库" - -#: ../../faq.md:74 363d4fbb2a474c64a54c2659844596b5 -msgid "2.create table {$your_table} and insert your data. eg:" -msgstr "然后创建数据表，模拟数据" - -#: ../../faq.md:88 5f3a9b9d7e6f444a87deb17b5a1a45af -msgid "Q6:How to change Vector DB Type in DB-GPT." -msgstr "" - -#: ../../faq.md:90 ee1d4dfa813942e1a3d1219f21bc041f -msgid "A6: Update .env file and set VECTOR_STORE_TYPE." -msgstr "" - -#: ../../faq.md:91 71e9e9905bdb46e1925f66a6c12a6afd -msgid "" -"DB-GPT currently support Chroma(Default), Milvus(>2.1), Weaviate vector " -"database. If you want to change vector db, Update your .env, set your " -"vector store type, VECTOR_STORE_TYPE=Chroma (now only support Chroma and " -"Milvus(>2.1), if you set Milvus, please set MILVUS_URL and MILVUS_PORT) " -"If you want to support more vector db, you can integrate yourself.[how to" -" integrate](https://db-gpt.readthedocs.io/en/latest/modules/vector.html)" -msgstr "" - -#: ../../faq.md:107 d6c4ed8ff8244aa8aef6ea8d8f0a5555 -msgid "Q7:When I use vicuna-13b, found some illegal character like this." -msgstr "" - -#: ../../faq.md:112 911a5051c37244e1b6ea9d3b1bd1fd97 -msgid "" -"A7: set KNOWLEDGE_SEARCH_TOP_SIZE smaller or set KNOWLEDGE_CHUNK_SIZE " -"smaller, and reboot server." -msgstr "" - -#: ../../faq.md:114 0566430bbc0541709ed60b81c7372175 -msgid "" -"Q8:space add error (pymysql.err.OperationalError) (1054, \"Unknown column" -" 'knowledge_space.context' in 'field list'\")" -msgstr "" - -#: ../../faq.md:117 37419da934b44575bd39bcffffa81482 -msgid "A8:" -msgstr "" - -#: ../../faq.md:118 1c5f46dbccc342329b544ac174a79994 -msgid "1.shutdown dbgpt_server(ctrl c)" -msgstr "" - -#: ../../faq.md:120 35bb76e9d9ec4230a8fab9aed475a4d7 -msgid "2.add column context for table knowledge_space" -msgstr "" - -#: ../../faq.md:124 e198605e42d4452680359487abc349a3 -msgid "3.execute sql ddl" -msgstr "" - -#: ../../faq.md:129 88495f3e66c448faab9f06c4c5cd27ef -msgid "4.restart dbgpt server" -msgstr "" - -#~ msgid "FAQ" -#~ msgstr "FAQ" - -#~ msgid "Q1: text2vec-large-chinese not found" -#~ msgstr "Q1: text2vec-large-chinese not found" - -#~ msgid "" -#~ "A1: make sure you have download " -#~ "text2vec-large-chinese embedding model in" -#~ " right way" -#~ msgstr "按照正确的姿势下载text2vec-large-chinese模型" - -#~ msgid "" -#~ "Q2: execute `pip install -r " -#~ "requirements.txt` error, found some package" -#~ " cannot find correct version." -#~ msgstr "执行`pip install -r requirements.txt`报错" - -#~ msgid "A2: change the pip source." -#~ msgstr "修改pip源" - -#~ msgid "or" -#~ msgstr "或" - -#~ msgid "Q3:Access denied for user 'root@localhost'(using password :NO)" -#~ msgstr "或" - -#~ msgid "A3: make sure you have installed mysql instance in right way" -#~ msgstr "按照正确姿势安装mysql" - -#~ msgid "Docker:" -#~ msgstr "Docker:" - -#~ msgid "" -#~ "Normal: [download mysql " -#~ "instance](https://dev.mysql.com/downloads/mysql/)" -#~ msgstr "[download mysql instance](https://dev.mysql.com/downloads/mysql/)" - -#~ msgid "Q4:When I use openai(MODEL_SERVER=proxyllm) to chat" -#~ msgstr "使用openai-chatgpt模型时(MODEL_SERVER=proxyllm)" - -#~ msgid "A4: make sure your openapi API_KEY is available" -#~ msgstr "确认openapi API_KEY是否可用" - -#~ msgid "Q6:How to change Vector DB Type in DB-GPT." -#~ msgstr "" - -#~ msgid "A6: Update .env file and set VECTOR_STORE_TYPE." -#~ msgstr "" - -#~ msgid "" -#~ "DB-GPT currently support Chroma(Default), " -#~ "Milvus(>2.1), Weaviate vector database. If " -#~ "you want to change vector db, " -#~ "Update your .env, set your vector " -#~ "store type, VECTOR_STORE_TYPE=Chroma (now only" -#~ " support Chroma and Milvus(>2.1), if " -#~ "you set Milvus, please set MILVUS_URL" -#~ " and MILVUS_PORT) If you want to " -#~ "support more vector db, you can " -#~ "integrate yourself.[how to integrate](https://db-" -#~ "gpt.readthedocs.io/en/latest/modules/vector.html)" -#~ msgstr "" -#~ "DB-" -#~ "GPT当前支持Chroma(默认)，如果你想替换向量数据库，需要更新.env文件，VECTOR_STORE_TYPE=Chroma " -#~ "(now only support Chroma, Milvus " -#~ "Weaviate, if you set Milvus(>2.1), " -#~ "please set MILVUS_URL and " -#~ "MILVUS_PORT)。如果当前支持向量数据库无法满足你的需求，可以集成使用自己的向量数据库。[怎样集成](https://db-" -#~ "gpt.readthedocs.io/en/latest/modules/vector.html)" - -#~ msgid "Q7:When I use vicuna-13b, found some illegal character like this." -#~ msgstr "使用vicuna-13b，知识库问答出现乱码" - -#~ msgid "" -#~ "A7: set KNOWLEDGE_SEARCH_TOP_SIZE smaller or" -#~ " set KNOWLEDGE_CHUNK_SIZE smaller, and " -#~ "reboot server." -#~ msgstr "将KNOWLEDGE_SEARCH_TOP_SIZE和KNOWLEDGE_CHUNK_SIZE设置小点然后重启" - -#~ msgid "" -#~ "Q8:space add error (pymysql.err.OperationalError)" -#~ " (1054, \"Unknown column " -#~ "'knowledge_space.context' in 'field list'\")" -#~ msgstr "" -#~ "Q8:space add error (pymysql.err.OperationalError)" -#~ " (1054, \"Unknown column " -#~ "'knowledge_space.context' in 'field list'\")" - -#~ msgid "A8:" -#~ msgstr "A8:" - -#~ msgid "1.shutdown dbgpt_server(ctrl c)" -#~ msgstr "" - -#~ msgid "2.add column context for table knowledge_space" -#~ msgstr "2.add column context for table knowledge_space" - -#~ msgid "3.execute sql ddl" -#~ msgstr "3.执行 sql ddl" - -#~ msgid "4.restart dbgpt server" -#~ msgstr "4.重启 dbgpt server" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/getting_started/application.po b/docs/locales/zh_CN/LC_MESSAGES/getting_started/application.po deleted file mode 100644 index 04cf08b74..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/getting_started/application.po +++ /dev/null @@ -1,51 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.3.5\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-08-16 18:31+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../getting_started/application.rst:13 -msgid "Application" -msgstr "应用" - -#: ../../getting_started/application.rst:2 4de9609785bc406aa6f3965f057f90d8 -msgid "Applications" -msgstr "应用" - -#: ../../getting_started/application.rst:3 1ef4f6d81f7c4a2f9ee330fc890017dd -msgid "" -"DB-GPT product is a Web application that you can chat database, chat " -"knowledge, text2dashboard." -msgstr "DB-GPT是一个可以和数据库对话，知识问答，智能报表的web应用" - -#: ../../getting_started/application.rst:8 0451376d435b47bfa7b3f81c87683610 -msgid "Chat DB" -msgstr "Chat DB" - -#: ../../getting_started/application.rst:9 4b1372dd4ae34881891c1dbcd83b92bf -msgid "Chat Knowledge" -msgstr "知识问答" - -#: ../../getting_started/application.rst:10 d8807a357f1144ccba933338cd0f619a -msgid "Dashboard" -msgstr "Dashboard" - -#: ../../getting_started/application.rst:11 f6a5806d4f0d4271bb0964935d9c2ff3 -msgid "Plugins" -msgstr "Plugins" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/getting_started/application/chatagent/chatagent.po b/docs/locales/zh_CN/LC_MESSAGES/getting_started/application/chatagent/chatagent.po deleted file mode 100644 index 40c13781c..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/getting_started/application/chatagent/chatagent.po +++ /dev/null @@ -1,198 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.3.9\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-10-20 13:43+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../getting_started/application/chatagent/chatagent.md:1 -#: 3d20e06900dd4b26a186d8061e8d20e0 -msgid "ChatAgent" -msgstr "" - -#: ../../getting_started/application/chatagent/chatagent.md:3 -#: 48bbe6fd70a5464abdc85214428173e9 -msgid "" -"ChatAgent can automatically select the right tool to answer and solve " -"user problems through LLM. ![chat_agent0](https://github.com/eosphoros-ai" -"/DB-GPT/assets/13723926/f6a88ab8-9352-444d-80a3-2d5456cd4286)" -msgstr "" - -#: ../../getting_started/application/chatagent/chatagent.md:3 -#: a50f13b6b007459194cbb896d6ac1d1e -msgid "chat_agent0" -msgstr "" - -#: ../../getting_started/application/chatagent/chatagent.md:6 -#: 22d0068943e341eaa0b3cbeecc0302f2 -msgid "1.Update Plugins From Git" -msgstr "" - -#: ../../getting_started/application/chatagent/chatagent.md:7 -#: 83d7d659bb12434aa2ba0872c0b38fbb -msgid "" -"Update the latest plug-in information from the DB-GPT official plug-in " -"repository. Address:https://github.com/eosphoros-ai/DB-GPT-" -"Plugins/tree/main/src/dbgpt_plugins/search_engine" -msgstr "" - -#: ../../getting_started/application/chatagent/chatagent.md:10 -#: 1d15db09b41c437db7c9be747da75181 -msgid "" -"![agent_hub_1](https://github.com/eosphoros-ai/DB-" -"GPT/assets/13723926/1ae406e2-840d-4e82-92f5-716cf69367e2)" -msgstr "" - -#: ../../getting_started/application/chatagent/chatagent.md:10 -#: ../../getting_started/application/chatagent/chatagent.md:15 -#: 9433f2b9ee764881aa4803576d27007a a8aa2659211742c184b2dc123b422c0b -msgid "agent_hub_1" -msgstr "" - -#: ../../getting_started/application/chatagent/chatagent.md:12 -#: 4cc4fff702e34fc5bbacb03080fc71bc -msgid "2.Install Plugin" -msgstr "" - -#: ../../getting_started/application/chatagent/chatagent.md:13 -#: 70bf8e85525b47ba948bdc4c903bed8d -msgid "Install the plugin you want to use from the list of agent hub plugins." -msgstr "" - -#: ../../getting_started/application/chatagent/chatagent.md:15 -#: 413958b102104e0f863b28bac00f685b -msgid "" -"Address:https://github.com/eosphoros-ai/DB-GPT-" -"Plugins/tree/main/src/dbgpt_plugins/search_engine " -"![agent_hub_1](https://github.com/eosphoros-ai/DB-" -"GPT/assets/13723926/1ae406e2-840d-4e82-92f5-716cf69367e2)" -msgstr "" - -#: ../../getting_started/application/chatagent/chatagent.md:18 -#: 965cfcc855314ae38b1080a7d74c40d9 -msgid "3.Upload My Local Plugin File" -msgstr "" - -#: ../../getting_started/application/chatagent/chatagent.md:19 -#: 4edcee6f3590426bb842a72b1124fafb -msgid "" -"If you want to use a private plug-in developed by yourself, you can " -"upload the plug-in first and then use it." -msgstr "" - -#: ../../getting_started/application/chatagent/chatagent.md:21 -#: e957b23e3b96432db489729070e138e3 -msgid "4.Select installed plug-ins dialog" -msgstr "" - -#: ../../getting_started/application/chatagent/chatagent.md:22 -#: 7cfa156721074a8bb1ab1b34614374f1 -msgid "" -"Select an installed plugin to have a conversation. " -"![chat_agent1](https://github.com/eosphoros-ai/DB-GPT/assets/13723926" -"/f0b94bea-23ab-4ae3-8b45-195e1edafed5) ![chat_agent2](https://github.com" -"/eosphoros-ai/DB-" -"GPT/assets/13723926/eae566ff-2105-4553-9125-9e9cab687377)" -msgstr "" - -#: ../../getting_started/application/chatagent/chatagent.md:22 -#: a50f13b6b007459194cbb896d6ac1d1e -msgid "chat_agent1" -msgstr "" - -#: ../../getting_started/application/chatagent/chatagent.md:22 -#: a50f13b6b007459194cbb896d6ac1d1e -msgid "chat_agent2" -msgstr "" - -#: ../../getting_started/application/chatagent/chatagent.md:26 -#: f8837cdb2f774bdf9856611b4dc830e0 -msgid "5.Uninstall My Plugin" -msgstr "" - -#: ../../getting_started/application/chatagent/chatagent.md:27 -#: f3de133280174fe5b8d938a47d5b4c62 -msgid "" -"Uninstall plugins you no longer need. ![agent_hub_2](https://github.com" -"/eosphoros-ai/DB-" -"GPT/assets/13723926/1989a9d1-5b52-4c31-8f07-4d676a26ef75)" -msgstr "" - -#: ../../getting_started/application/chatagent/chatagent.md:27 -#: 84dc512e68ef42849da6254374e2e9ba -msgid "agent_hub_2" -msgstr "" - -#~ msgid "" -#~ "ChatAgent can automatically select the " -#~ "right tool to answer and solve " -#~ "user problems through LLM. " -#~ "![ChatAgent](https://github.com/eosphoros-ai/DB-" -#~ "GPT/assets/13723926/)" -#~ msgstr "" - -#~ msgid "" -#~ "Update the latest plug-in information" -#~ " from the DB-GPT official plug-" -#~ "in repository. ![Update From " -#~ "Github](https://github.com/eosphoros-ai/DB-" -#~ "GPT/assets/13723926/)" -#~ msgstr "" - -#~ msgid "Update From Github" -#~ msgstr "" - -#~ msgid "" -#~ "Install the plugin you want to use" -#~ " from the list of agent hub " -#~ "plugins. ![Install Plugin](https://github.com" -#~ "/eosphoros-ai/DB-GPT/assets/13723926/)" -#~ msgstr "" - -#~ msgid "Install Plugin" -#~ msgstr "" - -#~ msgid "" -#~ "If you want to use a private " -#~ "plug-in developed by yourself, you " -#~ "can upload the plug-in first and" -#~ " then use it. ![Upload Private " -#~ "Plugin](https://github.com/eosphoros-ai/DB-" -#~ "GPT/assets/13723926/)" -#~ msgstr "" - -#~ msgid "Upload Private Plugin" -#~ msgstr "" - -#~ msgid "" -#~ "Select an installed plugin to have " -#~ "a conversation. ![Select Plugins](https://github.com" -#~ "/eosphoros-ai/DB-GPT/assets/13723926/)" -#~ msgstr "" - -#~ msgid "Select Plugins" -#~ msgstr "" - -#~ msgid "" -#~ "Uninstall plugins you no longer need." -#~ " ![Uninstall Plugin](https://github.com/eosphoros-ai" -#~ "/DB-GPT/assets/13723926/)" -#~ msgstr "" - -#~ msgid "Uninstall Plugin" -#~ msgstr "" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/getting_started/application/chatdb/chatdb.po b/docs/locales/zh_CN/LC_MESSAGES/getting_started/application/chatdb/chatdb.po deleted file mode 100644 index d9fbb60a9..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/getting_started/application/chatdb/chatdb.po +++ /dev/null @@ -1,246 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.3.5\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-11-03 15:33+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../getting_started/application/chatdb/chatdb.md:1 -#: c1489293ce464cee9577b0aa9a3f3037 -msgid "ChatData & ChatDB" -msgstr "ChatData & ChatDB" - -#: ../../getting_started/application/chatdb/chatdb.md:3 -#: 2c421938f270427dbd0ffff892b1a5a1 -#, fuzzy -msgid "" -"ChatData generates SQL from natural language and executes it. ChatDB " -"involves conversing with metadata from the Database, including metadata " -"about databases, tables, and fields.![db plugins " -"demonstration](https://github.com/eosphoros-ai/DB-" -"GPT/assets/13723926/d8bfeee9-e982-465e-a2b8-1164b673847e)" -msgstr "" -"ChatData 是会将自然语言生成SQL，并将其执行。ChatDB是与Database里面的元数据，包括库、表、字段的元数据进行对话.![db " -"plugins demonstration](../../../../assets/chat_data/chat_data.jpg)" - -#: ../../getting_started/application/chatdb/chatdb.md:3 -#: ../../getting_started/application/chatdb/chatdb.md:26 -#: ../../getting_started/application/chatdb/chatdb.md:30 -#: ../../getting_started/application/chatdb/chatdb.md:34 -#: ../../getting_started/application/chatdb/chatdb.md:49 -#: ../../getting_started/application/chatdb/chatdb.md:54 -#: ../../getting_started/application/chatdb/chatdb.md:60 -#: 1467691a6012498795a94a14f7eba307 32315140835948c58e1721c7e2fa88a9 -#: 3b8e3c3396ff47348105a6dec9e755ba a314854e9be945dd88ad241bfa340870 -#: d94d5f0e608f4399a0e10d593f0ab1da e0ca6ec1841040bc828ce2ef29c387b6 -msgid "db plugins demonstration" -msgstr "db plugins demonstration" - -#: ../../getting_started/application/chatdb/chatdb.md:7 -#: 67cb0954cfa54e629b75cf9a241f6b9d -#, fuzzy -msgid "The LLM (Language Model) suitable for the ChatData scene is" -msgstr "ChatData场景适用的LLM * chatgpt3.5. * chatgpt4. * Vicuna-v1.5." - -#: ../../getting_started/application/chatdb/chatdb.md:8 -#: c973e19574e2405a96eb003c64063bfc -msgid "chatgpt3.5." -msgstr "" - -#: ../../getting_started/application/chatdb/chatdb.md:9 -#: 649b2382378c416591db7038a269c33b -msgid "chatgpt4." -msgstr "" - -#: ../../getting_started/application/chatdb/chatdb.md:10 -#: fac49de88fe3409f818193b953714cb9 -msgid "Vicuna-v1.5." -msgstr "" - -#: ../../getting_started/application/chatdb/chatdb.md:13 -#: 8bd004993a834b0797ebcb5b6a6b1a23 -msgid "1.Choose Datasource" -msgstr "1.Choose Datasource" - -#: ../../getting_started/application/chatdb/chatdb.md:15 -#: 34abfdced7804b51a212c0e567ffda6b -msgid "" -"If you are using DB-GPT for the first time, you need to add a data source" -" and set the relevant connection information for the data source." -msgstr "如果你是第一次使用DB-GPT, 首先需要添加数据源，设置数据源的相关连接信息" - -#: ../../getting_started/application/chatdb/chatdb.md:19 -#: 3a8d16a8a32c4ac5affbd8093677b4f8 -msgid "there are some example data in DB-GPT-NEW/DB-GPT/docker/examples" -msgstr "在DB-GPT-NEW/DB-GPT/docker/examples有数据示例" - -#: ../../getting_started/application/chatdb/chatdb.md:21 -#: 2c3333a2705648148f79623c220d90cd -msgid "you can execute sql script to generate data." -msgstr "你可以通过执行sql脚本生成测试数据" - -#: ../../getting_started/application/chatdb/chatdb.md:24 -#: 4994182137574d14a3eefb421ceccd8e -msgid "1.1 Datasource management" -msgstr "1.1 Datasource management" - -#: ../../getting_started/application/chatdb/chatdb.md:26 -#: 94680e1487d84092abc51a7da9bf1075 -msgid "" -"![db plugins demonstration](https://github.com/eosphoros-ai/DB-" -"GPT/assets/13723926/7678f07e-9eee-40a9-b980-5b3978a0ed52)" -msgstr "" -"![db plugins demonstration](https://github.com/eosphoros-ai/DB-" -"GPT/assets/13723926/7678f07e-9eee-40a9-b980-5b3978a0ed52)" - -#: ../../getting_started/application/chatdb/chatdb.md:28 -#: 236dbd6d6cb4467593bf30597ecb215c -msgid "1.2 Connection management" -msgstr "1.2 Connection管理" - -#: ../../getting_started/application/chatdb/chatdb.md:30 -#: 6611193e600c4452ac8a9769c6230590 -msgid "" -"![db plugins demonstration](https://github.com/eosphoros-ai/DB-" -"GPT/assets/13723926/25b8f5a9-d322-459e-a8b2-bfe8cb42bdd6)" -msgstr "" -"![db plugins demonstration](https://github.com/eosphoros-ai/DB-" -"GPT/assets/13723926/25b8f5a9-d322-459e-a8b2-bfe8cb42bdd6)" - -#: ../../getting_started/application/chatdb/chatdb.md:32 -#: 7cceb9703af54970bee4a50fb07d4509 -msgid "1.3 Add Datasource" -msgstr "1.3 添加Datasource" - -#: ../../getting_started/application/chatdb/chatdb.md:34 -#: 83c9e18cb87b4f0d9b0ce5e68b7fea77 -msgid "" -"![db plugins demonstration](https://github.com/eosphoros-ai/DB-" -"GPT/assets/13723926/19ce31a7-4061-4da8-a9cb-efca396cc085)" -msgstr "" -"![db plugins demonstration](https://github.com/eosphoros-ai/DB-" -"GPT/assets/13723926/19ce31a7-4061-4da8-a9cb-efca396cc085)" - -#: ../../getting_started/application/chatdb/chatdb.md:37 -#: 143fb04274cd486687c5766179f6103e -msgid "now DB-GPT support Datasource Type" -msgstr "DB-GPT支持数据源类型" - -#: ../../getting_started/application/chatdb/chatdb.md:39 -#: 8bcf83e66b2d4d858407fc2b21b8fe85 -msgid "Mysql" -msgstr "Mysql" - -#: ../../getting_started/application/chatdb/chatdb.md:40 -#: cd74abd5d6f4410ca001a3de2685e768 -msgid "Sqlite" -msgstr "Sqlite" - -#: ../../getting_started/application/chatdb/chatdb.md:41 -#: fc5e01baba43449f8c3eb9b4b36a0ed8 -msgid "DuckDB" -msgstr "DuckDB" - -#: ../../getting_started/application/chatdb/chatdb.md:42 -#: 10b6fe2153cd4ceba949687a54c3a68c -msgid "Clickhouse" -msgstr "Clickhouse" - -#: ../../getting_started/application/chatdb/chatdb.md:43 -#: 9ce0a41784f041d39138a81099c386e9 -#, fuzzy -msgid "Mssql" -msgstr "Mysql" - -#: ../../getting_started/application/chatdb/chatdb.md:44 -#: 4af6eb835e954e0d937e98b308fb512b -msgid "Spark" -msgstr "Spark" - -#: ../../getting_started/application/chatdb/chatdb.md:47 -#: 8aaa3a73090b4805b2dddf1cc355d83c -msgid "2.ChatData" -msgstr "2.ChatData" - -#: ../../getting_started/application/chatdb/chatdb.md:48 -#: a34c79c99bd34233ae92d3090ff0b877 -msgid "Preview Mode" -msgstr "Preview Mode" - -#: ../../getting_started/application/chatdb/chatdb.md:49 -#: 39e31a2a01494d4191d415a2240e026d -#, fuzzy -msgid "" -"After successfully setting up the data source, you can start conversing " -"with the database. You can ask it to generate SQL for you or inquire " -"about relevant information on the database's metadata. ![db plugins " -"demonstration](https://github.com/eosphoros-ai/DB-" -"GPT/assets/13723926/8acf6a42-e511-48ff-aabf-3d9037485c1c)" -msgstr "" -"设置数据源成功后就可以和数据库进行对话了。你可以让它帮你生成SQL，也可以和问它数据库元数据的相关信息。 ![db plugins " -"demonstration](../../../../assets/chat_data/chatdata_eg.png)" - -#: ../../getting_started/application/chatdb/chatdb.md:53 -#: 999c78e8b604493a8190b0e1258d0da4 -msgid "Editor Mode" -msgstr "Editor Mode" - -#: ../../getting_started/application/chatdb/chatdb.md:54 -#: e4a61d1e62c743f8b13dbed92ec265ba -msgid "" -"In Editor Mode, you can edit your sql and execute it. ![db plugins " -"demonstration](https://github.com/eosphoros-ai/DB-" -"GPT/assets/13723926/1a896dc1-7c0e-4354-8629-30357ffd8d7f)" -msgstr "" -"编辑器模式下可以在线编辑sql进行调试. ![db plugins demonstration](https://github.com" -"/eosphoros-ai/DB-" -"GPT/assets/13723926/1a896dc1-7c0e-4354-8629-30357ffd8d7f)" - -#: ../../getting_started/application/chatdb/chatdb.md:58 -#: b3a0d94083524d249f97dd426e1e1f26 -msgid "3.ChatDB" -msgstr "3.ChatDB" - -#: ../../getting_started/application/chatdb/chatdb.md:60 -#: 8f4bd453447f48019a597eb3e4a59875 -msgid "" -"![db plugins demonstration](https://github.com/eosphoros-ai/DB-" -"GPT/assets/13723926/e04bc1b1-2c58-4b33-af62-97e89098ace7)" -msgstr "" -"![db plugins demonstration](https://github.com/eosphoros-ai/DB-" -"GPT/assets/13723926/e04bc1b1-2c58-4b33-af62-97e89098ace7)" - -#~ msgid "![db plugins demonstration](../../../../assets/chat_data/db_entry.png)" -#~ msgstr "![db plugins demonstration](../../../../assets/chat_data/db_entry.png)" - -#~ msgid "" -#~ "![db plugins " -#~ "demonstration](../../../../assets/chat_data/db_connect.png)" -#~ msgstr "" -#~ "![db plugins " -#~ "demonstration](../../../../assets/chat_data/db_connect.png)" - -#~ msgid "" -#~ "![db plugins " -#~ "demonstration](../../../../assets/chat_data/add_datasource.png)" -#~ msgstr "" -#~ "![db plugins " -#~ "demonstration](../../../../assets/chat_data/add_datasource.png)" - -#~ msgid "![db plugins demonstration](../../../../assets/chat_data/chatdb_eg.png)" -#~ msgstr "![db plugins demonstration](../../../../assets/chat_data/chatdb_eg.png)" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/getting_started/application/chatexcel/chatexcel.po b/docs/locales/zh_CN/LC_MESSAGES/getting_started/application/chatexcel/chatexcel.po deleted file mode 100644 index 08f842573..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/getting_started/application/chatexcel/chatexcel.po +++ /dev/null @@ -1,116 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.3.6\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-11-03 15:33+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../getting_started/application/chatexcel/chatexcel.md:1 -#: ../../getting_started/application/chatexcel/chatexcel.md:14 -#: 5e9c1de21de240839a510b9e05afcba1 96556d6d1d734f67ab15e548c9fdce2f -msgid "ChatExcel" -msgstr "" - -#: ../../getting_started/application/chatexcel/chatexcel.md:3 -#: 19590f67feea4f2580602538b79cd138 -#, fuzzy -msgid "" -"![db plugins demonstration](https://github.com/eosphoros-ai/DB-" -"GPT/assets/13723926/4113ac15-83c2-4350-86c0-5fc795677abd) ChatExcel uses " -"natural language to analyze and query Excel data.![db plugins " -"demonstration](../../../../assets/chat_excel/chat_excel_1.png)" -msgstr "使用自然语言进行Excel数据的分析处理" - -#: ../../getting_started/application/chatexcel/chatexcel.md:3 -#: ../../getting_started/application/chatexcel/chatexcel.md:18 -#: ../../getting_started/application/chatexcel/chatexcel.md:22 -#: ../../getting_started/application/chatexcel/chatexcel.md:26 -#: 286462d6d79b4189bcd9d17937a96233 7009abd113244cc5badb8e90837dc9af -#: 7eb17d02534d4f77b7602f3756da0d5e f5c1cfd0f77d4199a45988114174c67f -msgid "db plugins demonstration" -msgstr "" - -#: ../../getting_started/application/chatexcel/chatexcel.md:6 -#: 338f0b19314f4026b84a670d35056e6c -#, fuzzy -msgid "The LLM (Language Model) suitable for the ChatExcel scene is" -msgstr "ChatExcel场景适用的LLM 是 scene is * chatgpt3.5. * chatgpt4." - -#: ../../getting_started/application/chatexcel/chatexcel.md:7 -#: bc09e8af60b64a8fbeecedb927a5a854 -msgid "chatgpt3.5." -msgstr "" - -#: ../../getting_started/application/chatexcel/chatexcel.md:8 -#: e840c31d671946c190e27e1b7dd28647 -msgid "chatgpt4." -msgstr "" - -#: ../../getting_started/application/chatexcel/chatexcel.md:11 -#: 2a710e2650bb44ef9d4a1ee4b8225a35 -msgid "1.Select And Upload Excel or CSV File" -msgstr "" - -#: ../../getting_started/application/chatexcel/chatexcel.md:12 -#: df48b1003f3640cfa621e416f0405e8d -msgid "Select your excel or csv file to upload and start the conversation." -msgstr "选择你的Excel或者CSV文件上传开始对话" - -#: ../../getting_started/application/chatexcel/chatexcel.md:16 -#: 7ef5d5ebb634406ea4b566bbf5e30fd7 -msgid "" -"The ChatExcel function supports Excel and CSV format files, select the " -"corresponding file to use." -msgstr "ChatExcel功能支持Excel和CSV格式的文件，选择对应格式的文件开始使用" - -#: ../../getting_started/application/chatexcel/chatexcel.md:18 -#: 40c79b71820f44439b1f541db2be9dd9 -msgid "" -"![db plugins " -"demonstration](../../../../assets/chat_excel/chat_excel_2.png) ![db " -"plugins demonstration](../../../../assets/chat_excel/chat_excel_3.png)" -msgstr "" - -#: ../../getting_started/application/chatexcel/chatexcel.md:21 -#: 0dd469b6f56a442485392346065e345d -msgid "2.Wait for Data Processing" -msgstr "等待数据处理" - -#: ../../getting_started/application/chatexcel/chatexcel.md:22 -#: 0e9213342664465187981d6fea41e7ba -msgid "" -"After the data is uploaded, it will first learn and process the data " -"structure and field meaning. ![db plugins " -"demonstration](../../../../assets/chat_excel/chat_excel_4.png)" -msgstr "等待数据上传完成，会自动进行数据结构的学习和处理" - -#: ../../getting_started/application/chatexcel/chatexcel.md:25 -#: dd2047d1199542f7abda4767b953cfac -msgid "3.Use Data Analysis Calculation" -msgstr "开始使用数据分析计算" - -#: ../../getting_started/application/chatexcel/chatexcel.md:26 -#: 4e168def205743c898586e99e34d3e18 -msgid "" -"Now you can use natural language to analyze and query data in the dialog " -"box. ![db plugins " -"demonstration](../../../../assets/chat_excel/chat_excel_5.png) ![db " -"plugins demonstration](../../../../assets/chat_excel/chat_excel_6.png) " -"![db plugins " -"demonstration](../../../../assets/chat_excel/chat_excel_7.png)" -msgstr "现在可以开始进行自然语言进行数据的分析查询对话了" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/getting_started/application/dashboard/dashboard.po b/docs/locales/zh_CN/LC_MESSAGES/getting_started/application/dashboard/dashboard.po deleted file mode 100644 index 7ec08a868..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/getting_started/application/dashboard/dashboard.po +++ /dev/null @@ -1,182 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.3.5\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-11-03 15:33+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../getting_started/application/dashboard/dashboard.md:1 -#: 3e4ef12c51894e5d93adcbf090a4783b -msgid "Dashboard" -msgstr "Dashboard" - -#: ../../getting_started/application/dashboard/dashboard.md:3 -#: df9eb8d62bbe460d94e448c23fffa529 -msgid "" -"The purpose of the DB-GPT Dashboard is to empower data analysts with " -"efficiency. DB-GPT provides intelligent reporting technology, allowing " -"business analysts to perform self-service analysis directly using natural" -" language and gain insights into their respective areas of business." -msgstr "DB-GPT Dashboard目的是赋能数据分析人员。DB-GPT通过提供智能报表技术，使得业务分析人员可以直接使用简单的自然语言进行自助分析。" - -#: ../../getting_started/application/dashboard/dashboard.md:7 -#: 3ce90998ab9547fc95105f0000e232da -#, fuzzy -msgid "The LLM (Language Model) suitable for the Dashboard scene is" -msgstr "Dashboard场景适用的LLM是 * chatgpt3.5. * chatgpt4." - -#: ../../getting_started/application/dashboard/dashboard.md:8 -#: be8fe8f9d9344e64acf51e54f8a17d7c -msgid "chatgpt3.5." -msgstr "" - -#: ../../getting_started/application/dashboard/dashboard.md:9 -#: 82ef8f03db3f4741a92113a485a40599 -msgid "chatgpt4." -msgstr "" - -#: ../../getting_started/application/dashboard/dashboard.md:13 -#: da3aaa82126942058e72c472e2495641 -msgid "Dashboard now support Datasource Type" -msgstr "Dashboard目前支持的数据源类型" - -#: ../../getting_started/application/dashboard/dashboard.md:14 -#: d21cfc9594a24b69a5040f60cba00abb -msgid "Mysql" -msgstr "Mysql" - -#: ../../getting_started/application/dashboard/dashboard.md:15 -#: fc0e345321e84de5b9a96107fef5467e -msgid "Sqlite" -msgstr "Sqlite" - -#: ../../getting_started/application/dashboard/dashboard.md:16 -#: f5cc4387997441b88a9f10ba9b35b621 -msgid "DuckDB" -msgstr "DuckDB" - -#: ../../getting_started/application/dashboard/dashboard.md:18 -#: d8a86c3d05f84df0aa63c88f5dbfbd78 -msgid "Steps to Dashboard In DB-GPT" -msgstr "Dashboard使用步骤" - -#: ../../getting_started/application/dashboard/dashboard.md:20 -#: dbf7b3f73677411a8e660f8d90c11e05 -msgid "1 add datasource" -msgstr "1.添加数据源" - -#: ../../getting_started/application/dashboard/dashboard.md:22 -#: 70a599bc716a4af2b5a07a40de6fed9d -#, fuzzy -msgid "" -"If you are using Dashboard for the first time, you need to mock some data" -" to test. DB-GPT provide some dashboard test data in pilot/mock_datas/, " -"you should follow the steps. ![add_datasource](https://github.com" -"/eosphoros-ai/DB-GPT/assets/13723926/0afc72ea-83c8-45ff-" -"8c36-213b1c6fb5dd)" -msgstr "如果你是第一次使用Dashboard，需要构造测试数据，DB-GPT在pilot/mock_datas/提供了测试数据，只需要将数据源进行添加即可" - -#: ../../getting_started/application/dashboard/dashboard.md:22 -#: e38d15f091264563840cf15f0a2fe97c -msgid "add_datasource" -msgstr "添加数据源" - -#: ../../getting_started/application/dashboard/dashboard.md:26 -#: c6e87a5b20bb439ab1b3dc88e764d20b -msgid "2.Choose Dashboard Mode" -msgstr "2.进入Dashboard" - -#: ../../getting_started/application/dashboard/dashboard.md:28 -#: 54c25766650546998d3aaa3655f5275b -msgid "" -"![create_space](https://github.com/eosphoros-ai/DB-" -"GPT/assets/13723926/5e888880-0e97-4b60-8e5c-b7e7224197f0)" -msgstr "" -"![create_space](https://github.com/eosphoros-ai/DB-" -"GPT/assets/13723926/5e888880-0e97-4b60-8e5c-b7e7224197f0)" - -#: ../../getting_started/application/dashboard/dashboard.md:28 -#: ea1781528db04000ab4a72308c7be97e -msgid "create_space" -msgstr "create_space" - -#: ../../getting_started/application/dashboard/dashboard.md:30 -#: 5de9b0f0853443368d90e42114e99d6e -msgid "3.Select Datasource" -msgstr "3.选择数据源" - -#: ../../getting_started/application/dashboard/dashboard.md:32 -#: 3d4c429c4660414a8d5c44dea0ea0192 -msgid "" -"![document](https://github.com/eosphoros-ai/DB-" -"GPT/assets/13723926/da2ac8b5-eca4-48ef-938f-f9dc1ca711b3)" -msgstr "" -"![document](https://github.com/eosphoros-ai/DB-" -"GPT/assets/13723926/da2ac8b5-eca4-48ef-938f-f9dc1ca711b3)" - -#: ../../getting_started/application/dashboard/dashboard.md:32 -#: ../../getting_started/application/dashboard/dashboard.md:36 -#: 338912391ae441328549accdb6d5522b -msgid "document" -msgstr "document" - -#: ../../getting_started/application/dashboard/dashboard.md:34 -#: 2c0fd7e79393417aa218908c5cc89461 -msgid "4.Input your analysis goals" -msgstr "4.输入分析目标" - -#: ../../getting_started/application/dashboard/dashboard.md:36 -#: fb0bb655581a4109a5510240e54db006 -#, fuzzy -msgid "" -"![document](https://github.com/eosphoros-ai/DB-" -"GPT/assets/13723926/3f427350-5bd5-4675-8f89-1bd5c63ff2c6) ![db plugins " -"demonstration](../../../../assets/chat_dashboard/chat_dashboard_1.png)" -msgstr "" -"![document](https://github.com/eosphoros-ai/DB-" -"GPT/assets/13723926/3f427350-5bd5-4675-8f89-1bd5c63ff2c6) " -"![document](https://github.com/eosphoros-ai/DB-GPT/assets/13723926" -"/3d14a2da-165e-4b2f-a921-325c20fe5ae9)" - -#: ../../getting_started/application/dashboard/dashboard.md:36 -#: ../../getting_started/application/dashboard/dashboard.md:40 -#: 44680217a9794eddb97bcb98593a1071 -msgid "db plugins demonstration" -msgstr "" - -#: ../../getting_started/application/dashboard/dashboard.md:39 -#: 4a9a8eac8e77465a9519b532afdfd1b7 -msgid "5.Adjust and modify your report" -msgstr "5.调整" - -#: ../../getting_started/application/dashboard/dashboard.md:40 -#: b56da5e50ced4085bb376caa26e50e78 -msgid "" -"![db plugins " -"demonstration](../../../../assets/chat_dashboard/chat_dashboard_2.png)" -msgstr "" - -#~ msgid "" -#~ "![upload](https://github.com/eosphoros-ai/DB-" -#~ "GPT/assets/13723926/cb802b94-041b-44b4-b6ec-891bf8da52a4)" -#~ msgstr "" -#~ "![upload](https://github.com/eosphoros-ai/DB-" -#~ "GPT/assets/13723926/cb802b94-041b-44b4-b6ec-891bf8da52a4)" - -#~ msgid "upload" -#~ msgstr "upload" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/getting_started/application/kbqa/kbqa.po b/docs/locales/zh_CN/LC_MESSAGES/getting_started/application/kbqa/kbqa.po deleted file mode 100644 index c54d455f6..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/getting_started/application/kbqa/kbqa.po +++ /dev/null @@ -1,489 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.3.5\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-09-28 12:43+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../getting_started/application/kbqa/kbqa.md:1 -#: 2f77b0e5795f4d3593b5f04c54c2c6c2 -msgid "KBQA" -msgstr "" - -#: ../../getting_started/application/kbqa/kbqa.md:3 -#: 1e4f61ecf9084777ae451d2259bf804d -msgid "" -"![chat_knowledge](https://github.com/eosphoros-ai/DB-" -"GPT/assets/13723926/bc343c94-df3e-41e5-90d5-23b68c768c59)" -msgstr "" - -#: ../../getting_started/application/kbqa/kbqa.md:3 -#: ../../getting_started/application/kbqa/kbqa.md:7 -#: 7144258d06f3459d9404ef583b4f3696 e0aec0e78a9a40a2a6c6d496a5966fe8 -msgid "chat_knowledge" -msgstr "chat_knowledge" - -#: ../../getting_started/application/kbqa/kbqa.md:5 -#: 4eeebe69ee5b4055bb2ac48444b5f3cc -msgid "" -"DB-GPT supports a knowledge question-answering module, which aims to " -"create an intelligent expert in the field of databases and provide " -"professional knowledge-based answers to database practitioners." -msgstr " DB-GPT支持知识问答模块，知识问答的初衷是打造DB领域的智能专家，为数据库从业人员解决专业的知识问题回答" - -#: ../../getting_started/application/kbqa/kbqa.md:7 -#: 99ec2e6a023744878a8e970de7588dfe -msgid "" -"![chat_knowledge](https://github.com/eosphoros-ai/DB-" -"GPT/assets/13723926/6e55f2e5-94f7-4906-aed6-097db5c6c721)" -msgstr "" - -#: ../../getting_started/application/kbqa/kbqa.md:9 -#: ../../getting_started/application/kbqa/kbqa.md:12 -#: 77f6d58b0c714a0cbb2510aa2a036560 f3837660bb674945904a2acb34fd816a -msgid "KBQA abilities" -msgstr "KBQA现有能力" - -#: ../../getting_started/application/kbqa/kbqa.md:13 -#: 96d691596d1f4309bd29e4d8b3a3bc61 -msgid "Knowledge Space." -msgstr "知识空间" - -#: ../../getting_started/application/kbqa/kbqa.md:14 -#: 36fe78a666a0410380e338674bb76e96 -msgid "Multi Source Knowledge Source Embedding." -msgstr "多数据源Embedding" - -#: ../../getting_started/application/kbqa/kbqa.md:15 -#: 14659bb6964b402ba2aa912feffe0a28 -msgid "Embedding Argument Adjust" -msgstr "Embedding参数自定义" - -#: ../../getting_started/application/kbqa/kbqa.md:16 -#: c72212e1a0e54aa9b0b5adee687fed65 -msgid "Chat Knowledge" -msgstr "知识问答" - -#: ../../getting_started/application/kbqa/kbqa.md:17 -#: d5fea791138240e8b26b4da0a7d3a4bf -msgid "Multi Vector DB" -msgstr "多向量数据库管理" - -#: ../../getting_started/application/kbqa/kbqa.md:21 -#: d2460e9418c44064be16f8b8bd76bf7a -msgid "" -"If your DB type is Sqlite, there is nothing to do to build KBQA service " -"database schema." -msgstr "" - -#: ../../getting_started/application/kbqa/kbqa.md:23 -#: b0ebff37da05465fb5c91abb496647ee -msgid "" -"If your DB type is Mysql or other DBTYPE, you will build kbqa service " -"database schema." -msgstr "" - -#: ../../getting_started/application/kbqa/kbqa.md:25 -#: ac0e3e657e9c4dfaafdb8884bf0d915a -msgid "Mysql" -msgstr "" - -#: ../../getting_started/application/kbqa/kbqa.md:26 -#: 4b899ec4f62c47a79e9cff79524ed069 -msgid "" -"$ mysql -h127.0.0.1 -uroot -paa12345678 < " -"./assets/schema/knowledge_management.sql" -msgstr "" - -#: ../../getting_started/application/kbqa/kbqa.md:28 -#: a74b6c512b4d4ed399d5ee25e4a4f44a -msgid "or" -msgstr "" - -#: ../../getting_started/application/kbqa/kbqa.md:30 -#: 87216b282f664c6abfe736db5e3badd5 -msgid "execute DBGPT/assets/schema/knowledge_management.sql" -msgstr "" - -#: ../../getting_started/application/kbqa/kbqa.md:33 -#: 67aaa574f941485c8ba55a9058750175 -msgid "Steps to KBQA In DB-GPT" -msgstr "怎样一步一步使用KBQA" - -#: ../../getting_started/application/kbqa/kbqa.md:35 -#: 202ed073da4948a49d32b1beca69292d -msgid "1.Create Knowledge Space" -msgstr "1.首先创建知识空间" - -#: ../../getting_started/application/kbqa/kbqa.md:36 -#: f1defb29643f4664a125cf127e63ef71 -#, fuzzy -msgid "" -"If you are using Knowledge Space for the first time, you need to create a" -" Knowledge Space and set your name, owner, description. " -"![create_space](https://github.com/eosphoros-ai/DB-" -"GPT/assets/13723926/a93e597b-c392-465f-89d5-b55621d068a8)" -msgstr "如果你是第一次使用，先创建知识空间，指定名字,拥有者和描述信息" - -#: ../../getting_started/application/kbqa/kbqa.md:36 -#: 378e6091c3eb4f0d8ca4d4144303dde1 -msgid "create_space" -msgstr "create_space" - -#: ../../getting_started/application/kbqa/kbqa.md:41 -#: 669504b548ce4b7b9ea4c463b446cf39 -msgid "2.Create Knowledge Document" -msgstr "2.上传知识" - -#: ../../getting_started/application/kbqa/kbqa.md:42 -#: 731b15e4396b450589d619fccd78d542 -msgid "" -"DB-GPT now support Multi Knowledge Source, including Text, WebUrl, and " -"Document(PDF, Markdown, Word, PPT, HTML and CSV). After successfully " -"uploading a document for translation, the backend system will " -"automatically read and split and chunk the document, and then import it " -"into the vector database. Alternatively, you can manually synchronize the" -" document. You can also click on details to view the specific document " -"slicing content." -msgstr "" -"DB-GPT支持多数据源，包括Text纯文本, WebUrl和Document(PDF, Markdown, Word, PPT, HTML " -"and " -"CSV)。上传文档成功后后台会自动将文档内容进行读取，切片，然后导入到向量数据库中，当然你也可以手动进行同步，你也可以点击详情查看具体的文档切片内容" - -#: ../../getting_started/application/kbqa/kbqa.md:44 -#: 7c020f677a364693800952d558ba357e -msgid "2.1 Choose Knowledge Type:" -msgstr "2.1 选择知识类型" - -#: ../../getting_started/application/kbqa/kbqa.md:45 -#: c88460c498ff4fbca22f35e181c66723 -msgid "" -"![document](https://github.com/eosphoros-ai/DB-" -"GPT/assets/13723926/5b8173da-f444-4607-9d12-14bcab8179d0)" -msgstr "" - -#: ../../getting_started/application/kbqa/kbqa.md:45 -#: 60fcd6db28c546728bf9c015b63e9434 -msgid "document" -msgstr "document" - -#: ../../getting_started/application/kbqa/kbqa.md:47 -#: ffb8436b6e97468296e5852530e3d9c8 -msgid "2.2 Upload Document:" -msgstr "2.2上传文档" - -#: ../../getting_started/application/kbqa/kbqa.md:48 -#: a652b17e64b040938cf4e09ef7ed470a -msgid "" -"![upload](https://github.com/eosphoros-ai/DB-GPT/assets/13723926" -"/91b338fc-d3b2-476e-9396-3f6b4f16a890)" -msgstr "" - -#: ../../getting_started/application/kbqa/kbqa.md:48 -#: ../../getting_started/application/kbqa/kbqa.md:52 -#: ../../getting_started/application/kbqa/kbqa.md:57 -#: ../../getting_started/application/kbqa/kbqa.md:70 -#: 3f1c6873d54c47fea96d91188f728af9 434f854aa1af4f4bbf9ec4060388c643 -#: c1404f398cc3480d9c59b4ce326501e7 f18624fc081d4276859d4a4c99e998ee -msgid "upload" -msgstr "upload" - -#: ../../getting_started/application/kbqa/kbqa.md:51 -#: 6695dbe6d16e43d7b88dbad61039ff7e -msgid "3.Chat With Knowledge" -msgstr "3.知识问答" - -#: ../../getting_started/application/kbqa/kbqa.md:52 -#: 30b3afb9cb4d4705833ba15580425b05 -msgid "" -"![upload](https://github.com/eosphoros-ai/DB-" -"GPT/assets/13723926/a8281be7-1454-467d-81c9-15ef108aac10)" -msgstr "" - -#: ../../getting_started/application/kbqa/kbqa.md:54 -#: 05cc4bf0473f4f88aef63342b714d472 -msgid "4.Adjust Space arguments" -msgstr "4.调整知识参数" - -#: ../../getting_started/application/kbqa/kbqa.md:55 -#: 9ec125362dbb4aec864777313b1a8327 -msgid "" -"Each knowledge space supports argument customization, including the " -"relevant arguments for vector retrieval and the arguments for knowledge " -"question-answering prompts." -msgstr "每一个知识空间都支持参数自定义, 包括向量召回的相关参数以及知识问答Promp参数" - -#: ../../getting_started/application/kbqa/kbqa.md:56 -#: 54fd9461ced1436aa6c51984024caa74 -msgid "4.1 Embedding" -msgstr "4.1 Embedding" - -#: ../../getting_started/application/kbqa/kbqa.md:57 -#: 4b17fde7063e40e88dd121024f3e1c42 -msgid "" -"Embedding Argument ![upload](https://github.com/eosphoros-ai/DB-" -"GPT/assets/13723926/f1221bd5-d049-4ceb-96e6-8709e76e502e)" -msgstr "" - -#: ../../getting_started/application/kbqa/kbqa.md:61 -#: 6715234540d74eb79da60cf5ec29e236 -msgid "Embedding arguments" -msgstr "Embedding arguments" - -#: ../../getting_started/application/kbqa/kbqa.md:62 -#: af7ed9e32c6846b6a75893a55e0d78a4 -msgid "topk:the top k vectors based on similarity score." -msgstr "topk:相似性检索出tok条文档" - -#: ../../getting_started/application/kbqa/kbqa.md:63 -#: 05290f955cd142a2857d20786edf0952 -msgid "recall_score:set a threshold score for the retrieval of similar vectors." -msgstr "recall_score:向量检索相关度衡量指标分数" - -#: ../../getting_started/application/kbqa/kbqa.md:64 -#: b6e088dda8f142438bc0baebd357fa0e -msgid "recall_type:recall type." -msgstr "recall_type:召回类型" - -#: ../../getting_started/application/kbqa/kbqa.md:65 -#: 509bb3adefb74b65baea79bcbe94a240 -msgid "model:A model used to create vector representations of text or other data." -msgstr "model:embdding模型" - -#: ../../getting_started/application/kbqa/kbqa.md:66 -#: 43ef5b6a16c0435b9b7416d3600556e5 -msgid "chunk_size:The size of the data chunks used in processing." -msgstr "chunk_size:文档切片阈值大小" - -#: ../../getting_started/application/kbqa/kbqa.md:67 -#: 800fb14f22304155bedc5dc666f56a25 -msgid "chunk_overlap:The amount of overlap between adjacent data chunks." -msgstr "chunk_overlap:文本块之间的最大重叠量。保留一些重叠可以保持文本块之间的连续性（例如使用滑动窗口）" - -#: ../../getting_started/application/kbqa/kbqa.md:69 -#: 5497d17bcf014ad5b61d5febd7a9fda5 -msgid "4.2 Prompt" -msgstr "4.2 Prompt" - -#: ../../getting_started/application/kbqa/kbqa.md:70 -#: dd9cdfac5aae44c8998b36ae0ed286b8 -msgid "" -"Prompt Argument ![upload](https://github.com/eosphoros-ai/DB-" -"GPT/assets/13723926/9918c9c3-ed64-4804-9e05-fa7d7d177bec)" -msgstr "" - -#: ../../getting_started/application/kbqa/kbqa.md:74 -#: fbede51cc73444aab74fa646834ea1c2 -msgid "Prompt arguments" -msgstr "Prompt arguments" - -#: ../../getting_started/application/kbqa/kbqa.md:75 -#: a85ab9b05ec04cd59d3f4539599a8e35 -msgid "" -"scene:A contextual parameter used to define the setting or environment in" -" which the prompt is being used." -msgstr "scene:上下文环境的场景定义" - -#: ../../getting_started/application/kbqa/kbqa.md:76 -#: 48258fcdbb134a0e820347185ea45ca0 -msgid "" -"template:A pre-defined structure or format for the prompt, which can help" -" ensure that the AI system generates responses that are consistent with " -"the desired style or tone." -msgstr "template:预定义的提示结构或格式，可以帮助确保AI系统生成与所期望的风格或语气一致的回复。" - -#: ../../getting_started/application/kbqa/kbqa.md:77 -#: 2dab662fc6a945b3b2691831f16b52e7 -msgid "max_token:The maximum number of tokens or words allowed in a prompt." -msgstr "max_token: prompt token最大值" - -#: ../../getting_started/application/kbqa/kbqa.md:79 -#: a7c5a81457334f39a8956146fe4aa951 -msgid "5.Change Vector Database" -msgstr "5.Change Vector Database" - -#: ../../getting_started/application/kbqa/kbqa.md:81 -#: dccbc6e611e64f79aadb849ae1cdf0d2 -msgid "Vector Store SETTINGS" -msgstr "Vector Store SETTINGS" - -#: ../../getting_started/application/kbqa/kbqa.md:82 -#: a3af9f960c3144b2884a5ff3dc4f8cfa -msgid "Chroma" -msgstr "Chroma" - -#: ../../getting_started/application/kbqa/kbqa.md:83 -#: f195989635ec403d9f7ece263c451fa2 -msgid "VECTOR_STORE_TYPE=Chroma" -msgstr "VECTOR_STORE_TYPE=Chroma" - -#: ../../getting_started/application/kbqa/kbqa.md:84 -#: 9821aa494e514654bf33335c2db7700f -msgid "MILVUS" -msgstr "MILVUS" - -#: ../../getting_started/application/kbqa/kbqa.md:85 -#: 1d7ef3150b6549fc834567f2647c32db -msgid "VECTOR_STORE_TYPE=Milvus" -msgstr "VECTOR_STORE_TYPE=Milvus" - -#: ../../getting_started/application/kbqa/kbqa.md:86 -#: 702e9fc52c1d45cc9136ffd0a1bbcbc8 -msgid "MILVUS_URL=127.0.0.1" -msgstr "MILVUS_URL=127.0.0.1" - -#: ../../getting_started/application/kbqa/kbqa.md:87 -#: 44ed55973e50490db566f5d65fa87207 -msgid "MILVUS_PORT=19530" -msgstr "MILVUS_PORT=19530" - -#: ../../getting_started/application/kbqa/kbqa.md:88 -#: e1e13a389f404a3384e96b178b7887d0 -msgid "MILVUS_USERNAME" -msgstr "MILVUS_USERNAME" - -#: ../../getting_started/application/kbqa/kbqa.md:89 -#: 5755432971214b6dbe016a1556be759c -msgid "MILVUS_PASSWORD" -msgstr "MILVUS_PASSWORD" - -#: ../../getting_started/application/kbqa/kbqa.md:90 -#: f92e8123fadc4f67a3a81ce76f642d67 -msgid "MILVUS_SECURE=" -msgstr "MILVUS_SECURE=" - -#: ../../getting_started/application/kbqa/kbqa.md:92 -#: 5ad47c8768484e67a0b919d290b0fcde -msgid "WEAVIATE" -msgstr "WEAVIATE" - -#: ../../getting_started/application/kbqa/kbqa.md:93 -#: 139b2fab9a294215ba152710e464d425 -msgid "WEAVIATE_URL=https://kt-region-m8hcy0wc.weaviate.network" -msgstr "WEAVIATE_URL=https://kt-region-m8hcy0wc.weaviate.networkc" - -#: ../../getting_started/application/kbqa/kbqa.md:96 -#: bd9c81cd547142fab5857dbf0df441d0 -msgid "KBQA command line" -msgstr "KBQA 命令行工具" - -#: ../../getting_started/application/kbqa/kbqa.md:98 -#: fba52bfa428549e683c9cfb8e9684636 -msgid "Load your local documents to DB-GPT" -msgstr "将你的本地文档导入到 DB-GPT" - -#: ../../getting_started/application/kbqa/kbqa.md:104 -#: 5c3e7fa9b2b04e6097781d3f406c2bae -msgid "`--space_name`: Your knowledge space name, default: `default`" -msgstr "" - -#: ../../getting_started/application/kbqa/kbqa.md:105 -#: 083bb6913da64f8a880b20e31d138d7b -msgid "" -"`--local_doc_path`: Your document directory or document file path, " -"default: `./pilot/datasets`" -msgstr "" - -#: ../../getting_started/application/kbqa/kbqa.md:106 -#: 7b17564ffc7a43ab8e5beb023f18a59a -msgid "`--vector_store_type`: Vector store type, default: `Chroma`" -msgstr "" - -#: ../../getting_started/application/kbqa/kbqa.md:108 -#: 814bdf5ecddd4490af57dcab73ae8c85 -msgid "**View the `dbgpt knowledge load --help`help**" -msgstr "" - -#: ../../getting_started/application/kbqa/kbqa.md:114 -#: f1aaa308ef4b46f1adbb8ec64738f361 -msgid "Here you can see the parameters:" -msgstr "" - -#: ../../getting_started/application/kbqa/kbqa.md:141 -#: ../../getting_started/application/kbqa/kbqa.md:143 -#: 163ff96e128641509933c1871b6bde64 fca3ea3c13bc4fa3bfa33845f4d88b52 -#, fuzzy -msgid "List knowledge space" -msgstr "查看知识空间" - -#: ../../getting_started/application/kbqa/kbqa.md:149 -#: ../../getting_started/application/kbqa/kbqa.md:169 -#: 57b89ee3fde745ff8502ede525fc4a8c d9852d13a9b444618a598ba4abe47493 -msgid "Output should look something like the following:" -msgstr "输出如下：" - -#: ../../getting_started/application/kbqa/kbqa.md:163 -#: 14300078a0a74aee9cf6e54c470e3862 -#, fuzzy -msgid "List documents in knowledge space" -msgstr "查看某个知识空间中的文档" - -#: ../../getting_started/application/kbqa/kbqa.md:188 -#: b9afd5b23fb947c691d66f82f86c36f2 -msgid "List chunks of document in space `default`" -msgstr "查看某个知识空间文档中的块" - -#: ../../getting_started/application/kbqa/kbqa.md:217 -#: 294d9d963299400db39c5c51ab5d2e23 -msgid "More list usage" -msgstr "更多 list 命令用户" - -#: ../../getting_started/application/kbqa/kbqa.md:242 -#: 5d962a6b5b2d4fb6809bc84cb7711120 -msgid "Delete your knowledge space or document in space" -msgstr "删除你的知识空间或者知识空间中的文档" - -#: ../../getting_started/application/kbqa/kbqa.md:244 -#: f1deee3aaf8e41308f2f81974032e4d4 -#, fuzzy -msgid "Delete your knowledge space" -msgstr "删除知识空间" - -#: ../../getting_started/application/kbqa/kbqa.md:250 -#: ba2314a2d20944f7b64a60e67a5b8d94 -msgid "Delete your document in space" -msgstr "删除知识空间中的文档" - -#: ../../getting_started/application/kbqa/kbqa.md:257 -#: 2400777f270d40e2adcdc38a2d3cb73a -msgid "More delete usage" -msgstr "更多删除用法" - -#: ../../getting_started/application/kbqa/kbqa.md:276 -#: 4e79bbda201347f2822b1742805923a6 -#, fuzzy -msgid "More knowledge usage" -msgstr "更知识库命令用法" - -#~ msgid "![chat_knowledge](../../../../assets/chat_knowledge.png)" -#~ msgstr "![chat_knowledge](../../../../assets/chat_knowledge.png)" - -#~ msgid "![document](../../../../assets/kbqa/document.jpg)" -#~ msgstr "![document](../../../../assets/kbqa/document.jpg)" - -#~ msgid "![upload](../../../../assets/kbqa/upload.jpg)" -#~ msgstr "![upload](../../../../assets/kbqa/upload.jpg)" - -#~ msgid "![upload](../../../../assets/kbqa/begin_chat.jpg)" -#~ msgstr "![upload](../../../../assets/kbqa/begin_chat.jpg)" - -#~ msgid "Embedding Argument ![upload](../../../../assets/kbqa/embedding.png)" -#~ msgstr "Embedding Argument ![upload](../../../../assets/kbqa/embedding.png)" - -#~ msgid "Prompt Argument ![upload](../../../../assets/kbqa/prompt.png)" -#~ msgstr "Prompt Argument ![upload](../../../../assets/kbqa/prompt.png)" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/getting_started/application/model/model.po b/docs/locales/zh_CN/LC_MESSAGES/getting_started/application/model/model.po deleted file mode 100644 index 3e540eec5..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/getting_started/application/model/model.po +++ /dev/null @@ -1,346 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.3.9\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-10-17 19:39+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../getting_started/application/model/model.md:1 -#: 9d942556958a4a83ba09229f08774e18 -msgid "Model Management" -msgstr "模型服务管理" - -#: ../../getting_started/application/model/model.md:3 -#: 5b8688af589b4ad1ab6fb0ec8a3a664f -msgid "" -"![model](https://github.com/eosphoros-ai/DB-" -"GPT/assets/13723926/4b160ee7-2e2a-4502-bd54-d7daa14b23e5) DB-GPT Product " -"Provides LLM Model Management in web interface.Including LLM Create, " -"Start and Stop. Now DB-GPT support LLMs:" -msgstr "![model](https://github.com/eosphoros-ai/DB-" -"GPT/assets/13723926/4b160ee7-2e2a-4502-bd54-d7daa14b23e5) DB-GPT " -"在web界面上提供模型管理能力.包括模型创建、启动、停止。目前支持的模型：" - -#: ../../getting_started/application/model/model.md:3 -#: 023da40dc5334f93948f429b1360ff50 -msgid "model" -msgstr "model" - -#: ../../getting_started/application/model/model.md:6 -#: 77fbd490f31946f3af627a6575b04f95 -msgid "Support LLMs" -msgstr "支持的模型" - -#: ../../getting_started/application/model/model.md:7 -#: 1fa23499c6bd4a498880f007341601e3 -msgid "" -"Multi LLMs Support, Supports multiple large language models, currently " -"supporting" -msgstr "支持的模型类型：" - -#: ../../getting_started/application/model/model.md:8 -#: 20ad38e471c241ab9f162db9acfdbefa -msgid "" -"[meta-llama/Llama-2-7b-chat-hf](https://huggingface.co/meta-llama/Llama-2" -"-7b-chat-hf)" -msgstr "" - -#: ../../getting_started/application/model/model.md:9 -#: 1984188d04d74e7e93cdae6c8f1e00a8 -msgid "[baichuan2-7b/baichuan2-13b](https://huggingface.co/baichuan-inc)" -msgstr "" - -#: ../../getting_started/application/model/model.md:10 -#: 3b4aa596176241ca94a9c023edf911b8 -msgid "" -"[internlm/internlm-chat-7b](https://huggingface.co/internlm/internlm-" -"chat-7b)" -msgstr "" - -#: ../../getting_started/application/model/model.md:11 -#: 2608358ee0284d26b64b18ca86c584c5 -msgid "[Qwen/Qwen-7B-Chat/Qwen-14B-Chat](https://huggingface.co/Qwen/)" -msgstr "" - -#: ../../getting_started/application/model/model.md:12 -#: 0153627d59fb4268bfd2b8f2be0f8257 -msgid "[Vicuna](https://huggingface.co/Tribbiani/vicuna-13b)" -msgstr "" - -#: ../../getting_started/application/model/model.md:13 -#: 930768d5e2ca4c9891d81ed9d6e4ad8d -msgid "[BlinkDL/RWKV-4-Raven](https://huggingface.co/BlinkDL/rwkv-4-raven)" -msgstr "" - -#: ../../getting_started/application/model/model.md:14 -#: 2b4ab4bf8b604ba082c382bd8d4df40c -msgid "" -"[camel-ai/CAMEL-13B-Combined-Data](https://huggingface.co/camel-ai/CAMEL-" -"13B-Combined-Data)" -msgstr "" - -#: ../../getting_started/application/model/model.md:15 -#: a9b65b74c53d464988399baba8d35684 -msgid "[databricks/dolly-v2-12b](https://huggingface.co/databricks/dolly-v2-12b)" -msgstr "" - -#: ../../getting_started/application/model/model.md:16 -#: 96703db7e5764b998b87f3dc8932745b -msgid "" -"[FreedomIntelligence/phoenix-inst-chat-" -"7b](https://huggingface.co/FreedomIntelligence/phoenix-inst-chat-7b)" -msgstr "" - -#: ../../getting_started/application/model/model.md:17 -#: de76d7426b4846d495aa8631ce0d9d20 -msgid "" -"[h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-" -"7b](https://huggingface.co/h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-7b)" -msgstr "" - -#: ../../getting_started/application/model/model.md:18 -#: 7b49bcb8879b4ab4bf5f458709c3d695 -msgid "" -"[lcw99/polyglot-ko-12.8b-chang-instruct-" -"chat](https://huggingface.co/lcw99/polyglot-ko-12.8b-chang-instruct-chat)" -msgstr "" - -#: ../../getting_started/application/model/model.md:19 -#: 1ec742759fee4fbf98cc2839c72f70d9 -msgid "[lmsys/fastchat-t5-3b-v1.0](https://huggingface.co/lmsys/fastchat-t5)" -msgstr "" - -#: ../../getting_started/application/model/model.md:20 -#: bc1a8be505684b728e6fb7f758d75ae2 -msgid "[mosaicml/mpt-7b-chat](https://huggingface.co/mosaicml/mpt-7b-chat)" -msgstr "" - -#: ../../getting_started/application/model/model.md:21 -#: 41496816f052446da7364d39839f5135 -msgid "[Neutralzz/BiLLa-7B-SFT](https://huggingface.co/Neutralzz/BiLLa-7B-SFT)" -msgstr "" - -#: ../../getting_started/application/model/model.md:22 -#: 35ecfef506e040a8bac2102c28b977dd -msgid "" -"[nomic-ai/gpt4all-13b-snoozy](https://huggingface.co/nomic-ai/gpt4all-" -"13b-snoozy)" -msgstr "" - -#: ../../getting_started/application/model/model.md:23 -#: 1d8704b20f2c4dc5a8974ab813139a62 -msgid "" -"[NousResearch/Nous-Hermes-13b](https://huggingface.co/NousResearch/Nous-" -"Hermes-13b)" -msgstr "" - -#: ../../getting_started/application/model/model.md:24 -#: a9a04ac4211f4001912073668b5baf60 -msgid "" -"[openaccess-ai-collective/manticore-13b-chat-pyg](https://huggingface.co" -"/openaccess-ai-collective/manticore-13b-chat-pyg)" -msgstr "" - -#: ../../getting_started/application/model/model.md:25 -#: 0c1106b0e03a41c98b03dc17baa1298b -msgid "" -"[OpenAssistant/oasst-sft-4-pythia-12b-" -"epoch-3.5](https://huggingface.co/OpenAssistant/oasst-sft-4-pythia-12b-" -"epoch-3.5)" -msgstr "" - -#: ../../getting_started/application/model/model.md:26 -#: b7bccd9805914aeba74685d837fa367c -msgid "" -"[project-baize/baize-v2-7b](https://huggingface.co/project-" -"baize/baize-v2-7b)" -msgstr "" - -#: ../../getting_started/application/model/model.md:27 -#: 522805e911364c6ebdf7e56d674a7378 -msgid "[Salesforce/codet5p-6b](https://huggingface.co/Salesforce/codet5p-6b)" -msgstr "" - -#: ../../getting_started/application/model/model.md:28 -#: 19571aa2347347dabdc03fe1d4656be7 -msgid "" -"[StabilityAI/stablelm-tuned-alpha-7b](https://huggingface.co/stabilityai" -"/stablelm-tuned-alpha-7b)" -msgstr "" - -#: ../../getting_started/application/model/model.md:29 -#: fba42e0373e743b08c0c49899ab970b9 -msgid "[THUDM/chatglm-6b](https://huggingface.co/THUDM/chatglm-6b)" -msgstr "" - -#: ../../getting_started/application/model/model.md:30 -#: d518e63d906e41909c95d62c441aa746 -msgid "[THUDM/chatglm2-6b](https://huggingface.co/THUDM/chatglm2-6b)" -msgstr "" - -#: ../../getting_started/application/model/model.md:31 -#: 48d6eacaabd14992be49428c3d5d205a -msgid "[tiiuae/falcon-40b](https://huggingface.co/tiiuae/falcon-40b)" -msgstr "" - -#: ../../getting_started/application/model/model.md:32 -#: 6594a1859162405bb3df610d0982f71e -msgid "" -"[timdettmers/guanaco-33b-merged](https://huggingface.co/timdettmers" -"/guanaco-33b-merged)" -msgstr "" - -#: ../../getting_started/application/model/model.md:33 -#: b146beb3e6d043c38dd6211bddc9f0b4 -msgid "" -"[togethercomputer/RedPajama-INCITE-7B-" -"Chat](https://huggingface.co/togethercomputer/RedPajama-INCITE-7B-Chat)" -msgstr "" - -#: ../../getting_started/application/model/model.md:34 -#: 65f4089de9eb4056b90212efc1995db7 -msgid "" -"[WizardLM/WizardLM-13B-V1.0](https://huggingface.co/WizardLM/WizardLM-" -"13B-V1.0)" -msgstr "" - -#: ../../getting_started/application/model/model.md:35 -#: 6184f69597b9446daa869d03b8de2f55 -msgid "" -"[WizardLM/WizardCoder-15B-V1.0](https://huggingface.co/WizardLM" -"/WizardCoder-15B-V1.0)" -msgstr "" - -#: ../../getting_started/application/model/model.md:36 -#: 74c552cf701a4b179065e0cb62c15f0c -msgid "" -"[baichuan-inc/baichuan-7B](https://huggingface.co/baichuan-inc/baichuan-" -"7B)" -msgstr "" - -#: ../../getting_started/application/model/model.md:37 -#: aa5bf7e5f91c417598a298b06d4fa8b1 -msgid "" -"[HuggingFaceH4/starchat-beta](https://huggingface.co/HuggingFaceH4" -"/starchat-beta)" -msgstr "" - -#: ../../getting_started/application/model/model.md:38 -#: 507210a5746746f8bfc9ef5421e0f712 -msgid "" -"[FlagAlpha/Llama2-Chinese-13b-" -"Chat](https://huggingface.co/FlagAlpha/Llama2-Chinese-13b-Chat)" -msgstr "" - -#: ../../getting_started/application/model/model.md:39 -#: 8a45141e06584b23bfae1eb1d7b3152a -msgid "[BAAI/AquilaChat-7B](https://huggingface.co/BAAI/AquilaChat-7B)" -msgstr "" - -#: ../../getting_started/application/model/model.md:40 -#: 78f34f97c6a441a29d20d0ec3164a466 -msgid "[all models of OpenOrca](https://huggingface.co/Open-Orca)" -msgstr "" - -#: ../../getting_started/application/model/model.md:41 -#: b7b0f7867d61464faa7b4913daaaca5c -msgid "" -"[Spicyboros](https://huggingface.co/jondurbin/spicyboros-7b-2.2?not-for-" -"all-audiences=true) + [airoboros " -"2.2](https://huggingface.co/jondurbin/airoboros-l2-13b-2.2)" -msgstr "" - -#: ../../getting_started/application/model/model.md:42 -#: c3750533dfc64a9fb37044eb83c857dc -msgid "" -"[VMware's OpenLLaMa OpenInstruct](https://huggingface.co/VMware/open-" -"llama-7b-open-instruct)" -msgstr "" - -#: ../../getting_started/application/model/model.md:44 -#: 325d5b147abe4360997d2d6cbd6da986 -msgid "Support API Proxy LLMs" -msgstr "支持第三方模型服务" - -#: ../../getting_started/application/model/model.md:45 -#: 426d835ec30c4171b05817fc0bbafeb6 -msgid "[ChatGPT](https://api.openai.com/)" -msgstr "" - -#: ../../getting_started/application/model/model.md:46 -#: 659eefe6896c49e09d81edd6e3c36afe -msgid "[Tongyi](https://www.aliyun.com/product/dashscope)" -msgstr "" - -#: ../../getting_started/application/model/model.md:47 -#: ff24d85761c6492bbd546ecda67f38ea -msgid "[Wenxin](https://cloud.baidu.com/product/wenxinworkshop?track=dingbutonglan)" -msgstr "" - -#: ../../getting_started/application/model/model.md:48 -#: a798259b3694447091d6f1cee969e6af -msgid "[ChatGLM](http://open.bigmodel.cn/)" -msgstr "" - -#: ../../getting_started/application/model/model.md:50 -#: e053ece66b444b37a4bced21a4353c95 -msgid "Create && Start LLM Model" -msgstr "创建并启动模型服务" - -#: ../../getting_started/application/model/model.md:52 -#: 58c44380ae2946d4a3ecd22dd0ae47ac -msgid "" -"Make sure your LLM Model file is downloaded or LLM Model Proxy api " -"service is ready." -msgstr "需要事先下载模型文件或者准备好第三方模型服务api" - -#: ../../getting_started/application/model/model.md:54 -#: 659e756c822d4ef68b086a6e69d3ed9f -msgid "" -"![model-start](https://github.com/eosphoros-ai/DB-" -"GPT/assets/13723926/dacabcb9-92c6-43eb-95ed-8cabaa2d18e6) When create " -"success, you can see: ![image](https://github.com/eosphoros-ai/DB-" -"GPT/assets/13723926/1b69bff6-8b37-493d-b6be-38f7b6e8ae2d) Then you can " -"choose and switch llm model service to chat. ![image](https://github.com" -"/eosphoros-ai/DB-" -"GPT/assets/13723926/2d20eb6b-8976-4731-b433-373ac3383602)" -msgstr "" - -#: ../../getting_started/application/model/model.md:54 -#: e662c48673a94b0e9f4343f900a51af2 -msgid "model-start" -msgstr "" - -#: ../../getting_started/application/model/model.md:54 -#: ../../getting_started/application/model/model.md:60 -#: 38dd8f0de66740b3961fbd9444437d76 4190bd7bb2d34a6688382df6ee6ac610 -#: f60becdb866a411babe22ad27922fdcc -msgid "image" -msgstr "" - -#: ../../getting_started/application/model/model.md:59 -#: 61bfa8fa14ec40e2ba56a6bc65fda9df -msgid "Stop LLM Model" -msgstr "" - -#: ../../getting_started/application/model/model.md:60 -#: 98188d79b0034913a500f1c0da603741 -msgid "" -"![image](https://github.com/eosphoros-ai/DB-GPT/assets/13723926/a21278d9" -"-7bef-487b-bef1-460ce516b2f5)" -msgstr "" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/getting_started/concepts.po b/docs/locales/zh_CN/LC_MESSAGES/getting_started/concepts.po deleted file mode 100644 index d5ad4f63f..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/getting_started/concepts.po +++ /dev/null @@ -1,25 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 0.3.0\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-06-11 14:10+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.11.0\n" - -#: ../../getting_started/concepts.md:1 bbfc919428fd48f886677ada33b9c495 -msgid "Concepts" -msgstr "概念" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/getting_started/faq.po b/docs/locales/zh_CN/LC_MESSAGES/getting_started/faq.po deleted file mode 100644 index ed7fadc10..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/getting_started/faq.po +++ /dev/null @@ -1,51 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.3.5\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-08-16 18:31+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../getting_started/faq.rst:13 -msgid "Deloy" -msgstr "Deloy" - -#: ../../getting_started/faq.rst:2 136e86216b564bcb91709d97ae03013c -msgid "FAQ" -msgstr "FAQ" - -#: ../../getting_started/faq.rst:3 9350e190f83648248a4e53a4703529a0 -msgid "" -"DB-GPT product is a Web application that you can chat database, chat " -"knowledge, text2dashboard." -msgstr "" - -#: ../../getting_started/faq.rst:8 c4d7887a869f48ddb1819a5df9206005 -msgid "deploy" -msgstr "deploy" - -#: ../../getting_started/faq.rst:9 3859638a380043dfa466d6f9c593ff14 -msgid "llm" -msgstr "llm" - -#: ../../getting_started/faq.rst:10 2039dce8389d4f9fb8fb7a8afa393809 -msgid "chatdb" -msgstr "chatdb" - -#: ../../getting_started/faq.rst:11 24a115044f984a71a83dea6000a98de8 -msgid "kbqa" -msgstr "kbqa" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/getting_started/faq/chatdb/chatdb_faq.po b/docs/locales/zh_CN/LC_MESSAGES/getting_started/faq/chatdb/chatdb_faq.po deleted file mode 100644 index 38cb58cc1..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/getting_started/faq/chatdb/chatdb_faq.po +++ /dev/null @@ -1,76 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.3.5\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-08-22 13:28+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../getting_started/faq/chatdb/chatdb_faq.md:1 -#: 371f153c45484caea125cc4841a3ab7c -msgid "Chat DB FAQ" -msgstr "Chat DB FAQ" - -#: ../../getting_started/faq/chatdb/chatdb_faq.md:3 -#: f5d4e14316ef4d6db20b76872768b012 -msgid "Q1: What difference between ChatData and ChatDB" -msgstr "" - -#: ../../getting_started/faq/chatdb/chatdb_faq.md:4 -#: ee16d1c26d54456ba5cc51f0f5fb82fe -msgid "" -"ChatData generates SQL from natural language and executes it. ChatDB " -"involves conversing with metadata from the Database, including metadata " -"about databases, tables, and fields." -msgstr "ChatData 是将自然语言转换成SQL并执行获取结果，ChatDB主要是和数据库元数据信息（包括表、字段、索引信息）， 用于db诊断和数据库答疑" - -#: ../../getting_started/faq/chatdb/chatdb_faq.md:6 -#: a65f2f4603e44a8396d84daa78ba337d -msgid "Q2: The suitable llm model currently supported for text-to-SQL is?" -msgstr "Q2: 目前DB-GPT最适合text-to-SQL的开源模型是什么" - -#: ../../getting_started/faq/chatdb/chatdb_faq.md:7 -#: 77763b99ef924e2b90961e550f5c3d88 -msgid "Now vicunna-13b-1.5 and llama2-70b is more suitable for text-to-SQL." -msgstr "vicunna-13b-1.5 和 llama2-70b" - -#: ../../getting_started/faq/chatdb/chatdb_faq.md:9 -#: 776a487a2c624cfdbf59fdb64a5649f5 -msgid "Q3: How to fine-tune Text-to-SQL in DB-GPT" -msgstr "Q3: 我想fine-tune Text-to-SQL in DB-GPT" - -#: ../../getting_started/faq/chatdb/chatdb_faq.md:10 -#: 17ae1a5ee4234d3b86940d179262f37b -msgid "" -"there is another github project for Text-to-SQL fine-tune " -"(https://github.com/eosphoros-ai/DB-GPT-Hub)" -msgstr "" -"参与另外一个项目 Text-to-SQL fine-tune (https://github.com/eosphoros-ai/DB-GPT-" -"Hub)" - -#: ../../getting_started/faq/chatdb/chatdb_faq.md:12 -#: d34324bce192484a8afe066f22854801 -msgid "" -"Q4: chatdata with clickhouse clickhouse-sqlalchemy 0.2.4 requires " -"sqlalchemy<1.5,>=1.4.24, but you have sqlalchemy 2.0.20 which is " -"incompatible" -msgstr "chatData 使用clickhouse时发现driver与clickhouse-sqlalchemy不兼容" - -#: ../../getting_started/faq/chatdb/chatdb_faq.md:13 -#: e3746b0538b045e883cfbb17b0177f04 -msgid "Just set sqlalchemy<1.5,>=1.4.24" -msgstr "调整下版本 sqlalchemy<1.5,>=1.4.24" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/getting_started/faq/deploy/deploy_faq.po b/docs/locales/zh_CN/LC_MESSAGES/getting_started/faq/deploy/deploy_faq.po deleted file mode 100644 index 27b103339..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/getting_started/faq/deploy/deploy_faq.po +++ /dev/null @@ -1,214 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.3.5\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-10-27 15:57+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../getting_started/faq/deploy/deploy_faq.md:1 -#: 798fb40c5ec941fcb9d6a0795219132f -msgid "Installation FAQ" -msgstr "安装 FAQ" - -#: ../../getting_started/faq/deploy/deploy_faq.md:5 -#: 47d0aa43c5fe4ca3a8ceba50c18ba608 -#, fuzzy -msgid "" -"Q1: execute `pip install -e .` error, found some package cannot find " -"correct version." -msgstr "" -"Q1: execute `pip install -r requirements.txt` error, found some package " -"cannot find correct version." - -#: ../../getting_started/faq/deploy/deploy_faq.md:6 -#: 944761c1ccc543c0a6aa2fad8dc74a32 -msgid "change the pip source." -msgstr "替换pip源." - -#: ../../getting_started/faq/deploy/deploy_faq.md:13 -#: ../../getting_started/faq/deploy/deploy_faq.md:20 -#: ../../getting_started/faq/deploy/deploy_faq.md:145 -#: 3cff7ea0ee7945be8d03b6b3b032515b 5ba3037287524d6384ca96ffe58798fa -#: 9635f37d34e04764855f21d2266411f6 -msgid "or" -msgstr "或者" - -#: ../../getting_started/faq/deploy/deploy_faq.md:27 -#: c1c71ca902d745b89136bb63beda3dfd -msgid "" -"Q2: sqlalchemy.exc.OperationalError: (sqlite3.OperationalError) unable to" -" open database file" -msgstr "" -"Q2: sqlalchemy.exc.OperationalError: (sqlite3.OperationalError) unable to" -" open database file" - -#: ../../getting_started/faq/deploy/deploy_faq.md:29 -#: 97124a4512534c63bd09f2cf5a76fd13 -msgid "make sure you pull latest code or create directory with mkdir pilot/data" -msgstr "make sure you pull latest code or create directory with mkdir pilot/data" - -#: ../../getting_started/faq/deploy/deploy_faq.md:31 -#: 369ed2cd489d46009184036a8f8ed67a -msgid "Q3: The model keeps getting killed." -msgstr "Q3: The model keeps getting killed." - -#: ../../getting_started/faq/deploy/deploy_faq.md:33 -#: 6d59ca711a95495d9bddf22cd804e20b -msgid "" -"your GPU VRAM size is not enough, try replace your hardware or replace " -"other llms." -msgstr "GPU显存不够, 增加显存或者换一个显存小的模型" - -#: ../../getting_started/faq/deploy/deploy_faq.md:35 -#: 7ef755bf77fa46ccb63076c3561ecc64 -msgid "Q4: How to access website on the public network" -msgstr "" - -#: ../../getting_started/faq/deploy/deploy_faq.md:37 -#: cd3f9144525b49babb826a7447812016 -msgid "" -"You can try to use gradio's [network](https://github.com/gradio-" -"app/gradio/blob/main/gradio/networking.py) to achieve." -msgstr "" - -#: ../../getting_started/faq/deploy/deploy_faq.md:48 -#: 71f0174d58674b1abd3d6a02cf65abf6 -msgid "Open `url` with your browser to see the website." -msgstr "" - -#: ../../getting_started/faq/deploy/deploy_faq.md:50 -#: 81b07e64feef4187beab2022f3af294d -msgid "Q5: (Windows) execute `pip install -e .` error" -msgstr "" - -#: ../../getting_started/faq/deploy/deploy_faq.md:52 -#: f2e7cd453c10486aa9b7d90d1d771b58 -msgid "The error log like the following:" -msgstr "" - -#: ../../getting_started/faq/deploy/deploy_faq.md:71 -#: 2c97bbe2f96142ec8398b376f6a21d7f -msgid "" -"Download and install `Microsoft C++ Build Tools` from [visual-cpp-build-" -"tools](https://visualstudio.microsoft.com/visual-cpp-build-tools/)" -msgstr "" - -#: ../../getting_started/faq/deploy/deploy_faq.md:75 -#: 95120da5a6bf4a26bf64c2dd54632e4b -msgid "Q6: `Torch not compiled with CUDA enabled`" -msgstr "" - -#: ../../getting_started/faq/deploy/deploy_faq.md:82 -#: fa936391d8bd44cebeffc92e0f893700 -msgid "Install [CUDA Toolkit](https://developer.nvidia.com/cuda-toolkit-archive)" -msgstr "" - -#: ../../getting_started/faq/deploy/deploy_faq.md:83 -#: a8eb968b4b5a4f2786f7133299b8d20f -msgid "" -"Reinstall PyTorch [start-locally](https://pytorch.org/get-started/locally" -"/#start-locally) with CUDA support." -msgstr "" - -#: ../../getting_started/faq/deploy/deploy_faq.md:85 -#: 009f8b213c9044888975f1ae8cdf7a75 -msgid "Q7: ImportError: cannot import name 'PersistentClient' from 'chromadb'." -msgstr "Q7: ImportError: cannot import name 'PersistentClient' from 'chromadb'." - -#: ../../getting_started/faq/deploy/deploy_faq.md:91 -#: 237706fe28b846dcbe77e04a3bf89a6c -msgid "" -"Q8: pydantic.error_wrappers.ValidationError:1 validation error for " -"HuggingFaceEmbeddings.model_kwargs extra not permitted" -msgstr "" -"Q8: pydantic.error_wrappers.ValidationError:1 validation error for " -"HuggingFaceEmbeddings.model_kwargs extra not permitted" - -#: ../../getting_started/faq/deploy/deploy_faq.md:102 -#: e20c5fde988b478fb7eaba0f10d7d196 -msgid "Q9: alembic.util.exc.CommandError: Target database is not up to date." -msgstr "" - -#: ../../getting_started/faq/deploy/deploy_faq.md:104 -#: 6d096ff6f4754490868a0ff2b8a08f10 -msgid "delete files in `DB-GPT/pilot/meta_data/alembic/versions/` and restart." -msgstr "删除`DB-GPT/pilot/meta_data/alembic/versions/`目录下文件然后重新启动" - -#: ../../getting_started/faq/deploy/deploy_faq.md:110 -#: 2294a811682d4744b9334ee6deec4a49 -msgid "Q10: How to store DB-GPT metadata into my database" -msgstr "Q10: 如何将 DB-GPT 的元数据存储到自己的数据库中" - -#: ../../getting_started/faq/deploy/deploy_faq.md:112 -#: 034495af54f041bcb560a5366b9be912 -msgid "" -"In version 0.4.0, the metadata module of the DB-GPT application has been " -"refactored. All metadata tables will now be automatically saved in the " -"'dbgpt' database, based on the database type specified in the `.env` " -"file. If you would like to retain the existing data, it is recommended to" -" use a data migration tool to transfer the database table information to " -"the 'dbgpt' database. Additionally, you can change the default database " -"name 'dbgpt' in your `.env` file." -msgstr "" -"v0.4.0 重构了DB-" -"GPT应用的数据库元数据模块，所有的元数据库表都会自动保存在.env文件设置的数据库类型的`dbgpt`数据库中，如果想沿用以前的数据，建议使用数据迁移工具将数据库表信息挪到dbgpt数据库中。" -"另外，你可以在 `.env` 中修改默认的数据库名 'dbgpt' " - -#: ../../getting_started/faq/deploy/deploy_faq.md:132 -#: f9baf853f21b460ba5df63b84b35c040 -msgid "" -"Q11: pymysql.err.OperationalError: (1142, \"ALTER command denied to user " -"'{you db user}'@'{you db host}' for table '{some table name}'\")" -msgstr "" - -#: ../../getting_started/faq/deploy/deploy_faq.md:134 -#: a64cb2d75d6643559420c016362eb435 -msgid "" -"In version 0.4.0, DB-GPT use migration tool alembic to migrate metadata. " -"If the database user does not have DDL permissions, this error will be " -"reported. You can solve this problem by importing the metadata " -"information separately." -msgstr "" -"v0.4.0后，DB-GPT 使用 alembic 作为元数据迁移工具。" -"如果数据库用户没有 DDL 权限则会报这个错，您可以通过单独导入元数据信息来解决这个问题。" - -#: ../../getting_started/faq/deploy/deploy_faq.md:136 -#: 77c6bd4b559d457ab599b7f7730e85f1 -msgid "Use a privileged user to execute DDL sql file" -msgstr "使用一个有权限的用户来执行 DDL SQL 文件。" - -#: ../../getting_started/faq/deploy/deploy_faq.md:141 -#: 30c3fd7f7bfc4a63b5b9c4c15c64430f -msgid "Run DB-GPT webserver with `--disable_alembic_upgrade`" -msgstr "添加参数 `--disable_alembic_upgrade` 来运行 DB-GPT 的 webserver" - -#~ msgid "" -#~ "Q2: When use Mysql, Access denied " -#~ "for user 'root@localhost'(using password :NO)" -#~ msgstr "" - -#~ msgid "A3: make sure you have installed mysql instance in right way" -#~ msgstr "" - -#~ msgid "Docker:" -#~ msgstr "" - -#~ msgid "" -#~ "Normal: [download mysql " -#~ "instance](https://dev.mysql.com/downloads/mysql/)" -#~ msgstr "" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/getting_started/faq/kbqa/kbqa_faq.po b/docs/locales/zh_CN/LC_MESSAGES/getting_started/faq/kbqa/kbqa_faq.po deleted file mode 100644 index 6de5e670d..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/getting_started/faq/kbqa/kbqa_faq.po +++ /dev/null @@ -1,139 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.3.5\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-10-27 15:57+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../getting_started/faq/kbqa/kbqa_faq.md:1 -#: ab7d87ee62774af099fb0a8167b2d4be -msgid "KBQA FAQ" -msgstr "KBQA FAQ" - -#: ../../getting_started/faq/kbqa/kbqa_faq.md:4 -#: 3582be98154f4c3381765c130538d997 -msgid "Q1: text2vec-large-chinese not found" -msgstr "Q1: text2vec-large-chinese not found" - -#: ../../getting_started/faq/kbqa/kbqa_faq.md:6 -#: 3382fb6d60b443029a04e183cb5449cf -msgid "" -"make sure you have download text2vec-large-chinese embedding model in " -"right way" -msgstr "确认下载text2vec-large-chinese模型姿势以及路径正确" - -#: ../../getting_started/faq/kbqa/kbqa_faq.md:18 -#: 9fb65568d9cb4bf0be9371eae38ffe75 -msgid "Q2:How to change Vector DB Type in DB-GPT." -msgstr "怎么修改向量数据库类型" - -#: ../../getting_started/faq/kbqa/kbqa_faq.md:20 -#: 1904c691985044acad9d1cd84a227250 -msgid "Update .env file and set VECTOR_STORE_TYPE." -msgstr "怎样在.env文件设置VECTOR_STORE_TYPE" - -#: ../../getting_started/faq/kbqa/kbqa_faq.md:22 -#: a6ebd5b32fac42fbbdb7e26aaeafd781 -msgid "" -"DB-GPT currently support Chroma(Default), Milvus(>2.1), Weaviate vector " -"database. If you want to change vector db, Update your .env, set your " -"vector store type, VECTOR_STORE_TYPE=Chroma (now only support Chroma and " -"Milvus(>2.1), if you set Milvus, please set MILVUS_URL and MILVUS_PORT) " -"If you want to support more vector db, you can integrate yourself.[how to" -" integrate](https://db-gpt.readthedocs.io/en/latest/modules/vector.html)" -msgstr "" -"DB-GPT当前支持向量数据库有Chroma(Default), Milvus(>2.1), Weaviate. " -"可以在在.env文件设置VECTOR_STORE_TYP，如果你想支持更多向量数据库， 参考[how to integrate](https" -"://db-gpt.readthedocs.io/en/latest/modules/vector.html)" - -#: ../../getting_started/faq/kbqa/kbqa_faq.md:38 -#: 8357695648cf4dcca7d8d2c6d0c48b0a -msgid "Q3:When I use vicuna-13b, found some illegal character like this." -msgstr "当使用vicuna系列模型时出现乱码。" - -#: ../../getting_started/faq/kbqa/kbqa_faq.md:43 -#: ff8cb9ecfd2d4c9fa179b872d03a97dd -msgid "" -"Set KNOWLEDGE_SEARCH_TOP_SIZE smaller or set KNOWLEDGE_CHUNK_SIZE " -"smaller, and reboot server." -msgstr "通过在.env文件将KNOWLEDGE_SEARCH_TOP_SIZE设置更小点或者在文档界面点击参数设置，将topk设置更小点" - -#: ../../getting_started/faq/kbqa/kbqa_faq.md:45 -#: d7a49b1b219c4cf1bcb6ba212e378a7e -msgid "" -"Q4:space add error (pymysql.err.OperationalError) (1054, \"Unknown column" -" 'knowledge_space.context' in 'field list'\")" -msgstr "" -"space add error (pymysql.err.OperationalError) (1054, \"Unknown column " -"'knowledge_space.context' in 'field list'\")" - -#: ../../getting_started/faq/kbqa/kbqa_faq.md:47 -#: 30d34122c9fe4d1a9870c54480c734a6 -msgid "1.shutdown dbgpt_server(ctrl c)" -msgstr "1.终止 dbgpt_server(ctrl c)" - -#: ../../getting_started/faq/kbqa/kbqa_faq.md:49 -#: 1ccc21a493114e399007f9399f98006b -msgid "2.add column context for table knowledge_space" -msgstr "2.新增列 `context` for table knowledge_space" - -#: ../../getting_started/faq/kbqa/kbqa_faq.md:55 -#: 075c48b850354ac7971bd7556b68ef52 -msgid "3.execute sql ddl" -msgstr "3.执行ddl" - -#: ../../getting_started/faq/kbqa/kbqa_faq.md:62 -#: c4484fc646324c9a976b81a4e802c435 -msgid "4.restart dbgpt serve" -msgstr "4.重启dbgpt server" - -#: ../../getting_started/faq/kbqa/kbqa_faq.md:64 -#: b3da50497f37421485d8f0e852f0b09c -msgid "Q5:Use Mysql, how to use DB-GPT KBQA" -msgstr "Q5:当使用 Mysql数据库时, 使用DB-GPT怎么初始化 KBQA service database schema" - -#: ../../getting_started/faq/kbqa/kbqa_faq.md:66 -#: 97484a97b0d14d3f835efb5a0739c97e -msgid "build Mysql KBQA system database schema." -msgstr "构建Mysql KBQA system database schema" - -#: ../../getting_started/faq/kbqa/kbqa_faq.md:73 -#: bdcbaf0559a549468fab021e03ac3876 -msgid "Q6:when pull from 0.4.0, I found historical knowledge document disappeared" -msgstr "当从0.4.0版本拉取代码后，历史知识库问答信息没了" - -#: ../../getting_started/faq/kbqa/kbqa_faq.md:75 -#: ea78542f6be94dfc8d97b2660bb22876 -#, fuzzy -msgid "" -"In version 0.4.0, the metadata module of the DB-GPT application has been " -"refactored. All metadata tables will now be automatically saved in the " -"'dbgpt' database, based on the database type specified in the `.env` " -"file. If you would like to retain the existing data, it is recommended to" -" use a data migration tool to transfer the database table information to " -"the 'dbgpt' database. Additionally, you can change the default database " -"name 'dbgpt' in your `.env` file." -msgstr "" -"v0.4.0 重构了DB-" -"GPT应用的数据库元数据模块，所有的元数据库表都会自动保存在.env文件设置的数据库类型的`dbgpt`数据库中，如果想沿用以前的数据，建议使用数据迁移工具将数据库表信息挪到dbgpt数据库中。" -"另外，你可以在 `.env` 中修改默认的数据库名 'dbgpt' " - -#: ../../getting_started/faq/kbqa/kbqa_faq.md:78 -#: badc49ae6b4340be9700b92b1023e45b -msgid "old database:knowledge_management; new database:dbgpt;" -msgstr "" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/getting_started/faq/llm/llm_faq.po b/docs/locales/zh_CN/LC_MESSAGES/getting_started/faq/llm/llm_faq.po deleted file mode 100644 index 590cccfba..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/getting_started/faq/llm/llm_faq.po +++ /dev/null @@ -1,212 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.3.5\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-10-30 11:37+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../getting_started/faq/llm/llm_faq.md:1 98e23f85313c45169ff2ba7f80193356 -msgid "LLM USE FAQ" -msgstr "LLM模型使用FAQ" - -#: ../../getting_started/faq/llm/llm_faq.md:3 0d49acfb4af947cb969b249346b00d33 -#, fuzzy -msgid "Q1: how to use openai chatgpt service" -msgstr "我怎么使用OPENAI服务" - -#: ../../getting_started/faq/llm/llm_faq.md:4 7010fec33e264987a29de86c54da93e8 -#, fuzzy -msgid "change your LLM_MODEL in `.env`" -msgstr "通过在.env文件设置LLM_MODEL" - -#: ../../getting_started/faq/llm/llm_faq.md:9 0982d6d5d0b3434fb00698aaf675f3f3 -msgid "set your OPENAPI KEY" -msgstr "set your OPENAPI KEY" - -#: ../../getting_started/faq/llm/llm_faq.md:16 63650494c1574de09c007e1d470dd53d -msgid "make sure your openapi API_KEY is available" -msgstr "确认openapi API_KEY是否可用" - -#: ../../getting_started/faq/llm/llm_faq.md:18 5721ec71e344499d96c55b7e531d7c08 -#, fuzzy -msgid "" -"Q2: What difference between `python dbgpt_server --light` and `python " -"dbgpt_server`" -msgstr "Q2: `python dbgpt_server --light` 和 `python dbgpt_server`的区别是什么?" - -#: ../../getting_started/faq/llm/llm_faq.md:20 76a650f195dd40b6a3a3564030cdc040 -msgid "" -"`python dbgpt_server --light` dbgpt_server does not start the llm " -"service. Users can deploy the llm service separately by using `python " -"llmserver`, and dbgpt_server accesses the llm service through set the " -"LLM_SERVER environment variable in .env. The purpose is to allow for the " -"separate deployment of dbgpt's backend service and llm service." -msgstr "" -"`python dbgpt_server --light` dbgpt_server在启动后台服务的时候不启动模型服务, " -"用户可以通过`python " -"llmserver`单独部署模型服务，dbgpt_server通过LLM_SERVER环境变量来访问模型服务。目的是为了可以将dbgpt后台服务和大模型服务分离部署。" - -#: ../../getting_started/faq/llm/llm_faq.md:22 8cd87e3504784d9e891e1fb96c79e143 -msgid "" -"`python dbgpt_server` dbgpt_server service and the llm service are " -"deployed on the same instance. when dbgpt_server starts the service, it " -"also starts the llm service at the same time." -msgstr "`python dbgpt_server` 是将后台服务和模型服务部署在同一台实例上.dbgpt_server在启动服务的时候同时开启模型服务." - -#: ../../getting_started/faq/llm/llm_faq.md:27 58a6eaf57e6d425685f67058b1a642d4 -msgid "" -"If you want to access an external LLM service(deployed by DB-GPT), you " -"need to" -msgstr "如果模型服务部署(通过DB-GPT部署)在别的机器，想通过dbgpt服务访问模型服务" - -#: ../../getting_started/faq/llm/llm_faq.md:29 67ac8823ca2e49ba9c833368e2cfb53c -msgid "" -"1.set the variables LLM_MODEL=YOUR_MODEL_NAME, " -"MODEL_SERVER=YOUR_MODEL_SERVER（eg:http://localhost:5000） in the .env " -"file." -msgstr "" - -#: ../../getting_started/faq/llm/llm_faq.md:31 e5c066bcdf0649a1b33bbfc7fd3b1a66 -msgid "2.execute dbgpt_server.py in light mode" -msgstr "2.execute dbgpt_server.py light 模式" - -#: ../../getting_started/faq/llm/llm_faq.md:33 402ff01d7ee94d97be4a0eb964e39b97 -msgid "python pilot/server/dbgpt_server.py --light" -msgstr "" - -#: ../../getting_started/faq/llm/llm_faq.md:38 86190c689d8f4d9a9b58d904e0b5867b -#, fuzzy -msgid "Q3: How to use MultiGPUs" -msgstr "Q3: 怎么使用 MultiGPUs" - -#: ../../getting_started/faq/llm/llm_faq.md:40 6b08cff88750440b98956203d8b8a084 -msgid "" -"DB-GPT will use all available gpu by default. And you can modify the " -"setting `CUDA_VISIBLE_DEVICES=0,1` in `.env` file to use the specific gpu" -" IDs." -msgstr "DB-GPT默认加载可利用的gpu，你也可以通过修改 在`.env`文件 `CUDA_VISIBLE_DEVICES=0,1`来指定gpu IDs" - -#: ../../getting_started/faq/llm/llm_faq.md:43 93b39089e5be4475b9e90e7813f5a7d9 -msgid "" -"Optionally, you can also specify the gpu ID to use before the starting " -"command, as shown below:" -msgstr "你也可以指定gpu ID启动" - -#: ../../getting_started/faq/llm/llm_faq.md:53 62e3074c109d401fa4bf1ddbdc6c7be1 -msgid "" -"You can modify the setting `MAX_GPU_MEMORY=xxGib` in `.env` file to " -"configure the maximum memory used by each GPU." -msgstr "同时你可以通过在.env文件设置`MAX_GPU_MEMORY=xxGib`修改每个GPU的最大使用内存" - -#: ../../getting_started/faq/llm/llm_faq.md:55 d235bd83545c476f8e12572658d1c723 -#, fuzzy -msgid "Q4: Not Enough Memory" -msgstr "Q4: 机器显存不够 " - -#: ../../getting_started/faq/llm/llm_faq.md:57 b3243ed9147f42bba987d7f9b778e66f -msgid "DB-GPT supported 8-bit quantization and 4-bit quantization." -msgstr "DB-GPT 支持 8-bit quantization 和 4-bit quantization." - -#: ../../getting_started/faq/llm/llm_faq.md:59 1ddb9f94ab994bfebfee46d1c19888d4 -msgid "" -"You can modify the setting `QUANTIZE_8bit=True` or `QUANTIZE_4bit=True` " -"in `.env` file to use quantization(8-bit quantization is enabled by " -"default)." -msgstr "你可以通过在.env文件设置`QUANTIZE_8bit=True` or `QUANTIZE_4bit=True`" - -#: ../../getting_started/faq/llm/llm_faq.md:61 54b85daa3fb24b17b67a6da31d2be8b0 -msgid "" -"Llama-2-70b with 8-bit quantization can run with 80 GB of VRAM, and 4-bit" -" quantization can run with 48 GB of VRAM." -msgstr "" -"Llama-2-70b with 8-bit quantization 可以运行在 80 GB VRAM机器， 4-bit " -"quantization可以运行在 48 GB VRAM" - -#: ../../getting_started/faq/llm/llm_faq.md:63 097d680aed184fee9eceebee55a47ac1 -msgid "" -"Note: you need to install the quantization dependencies with `pip install" -" -e \".[quantization]\"`" -msgstr "" - -#: ../../getting_started/faq/llm/llm_faq.md:65 f3a51056043c49eb84471040f2b364aa -#, fuzzy -msgid "Q5: How to Add LLM Service dynamic local mode" -msgstr "Q5: 怎样动态新增模型服务" - -#: ../../getting_started/faq/llm/llm_faq.md:67 43ee6b0f23814c94a4ddb2429801a5e1 -msgid "" -"Now DB-GPT through multi-llm service switch, so how to add llm service " -"dynamic," -msgstr "DB-GPT支持多个模型服务切换, 怎样添加一个模型服务呢" - -#: ../../getting_started/faq/llm/llm_faq.md:78 c217bbf0d2b6425fa7a1c691b7704a8d -#, fuzzy -msgid "Q6: How to Add LLM Service dynamic in remote mode" -msgstr "Q6: 怎样动态新增模型服务" - -#: ../../getting_started/faq/llm/llm_faq.md:79 195bdaa937a94c7aa0d8c6e1a5430d6e -msgid "" -"If you deploy llm service in remote machine instance, and you want to " -"add model service to dbgpt server to manage" -msgstr "如果你想在远程机器实例部署大模型服务并添加到本地dbgpt_server进行管理" - -#: ../../getting_started/faq/llm/llm_faq.md:81 c64098b838a94821963a1d16e56497ff -msgid "use dbgpt start worker and set --controller_addr." -msgstr "使用1`dbgpt start worker`命令并设置注册地址--controller_addr" - -#: ../../getting_started/faq/llm/llm_faq.md:91 cb12d5e9d9d24f14abc3ebea877a4b24 -#, fuzzy -msgid "Q7: dbgpt command not found" -msgstr "Q7: dbgpt command not found" - -#: ../../getting_started/faq/llm/llm_faq.md:97 f95cdccfa82d4b3eb2a23dd297131faa -#, fuzzy -msgid "" -"Q8: When starting the worker_manager on a cloud server and registering it" -" with the controller, it is noticed that the worker's exposed IP is a " -"private IP instead of a public IP, which leads to the inability to access" -" the service." -msgstr "" -"Q8: 云服务器启动worker_manager注册到controller时，发现worker暴露的ip是私网ip, " -"没有以公网ip暴露，导致服务访问不到" - -#: ../../getting_started/faq/llm/llm_faq.md:106 -#: 739a2983f3484acf98e877dc12f4ccda -msgid "Q9: How to customize model path and prompt template" -msgstr "Q9: 如何自定义模型路径和 prompt 模板" - -#: ../../getting_started/faq/llm/llm_faq.md:108 -#: 8b82a33a311649c7850c30c00c987c72 -#, fuzzy -msgid "" -"DB-GPT will read the model path from " -"`pilot.configs.model_config.LLM_MODEL_CONFIG` based on the `LLM_MODEL`. " -"Of course, you can use the environment variable `LLM_MODEL_PATH` to " -"specify the model path and `LLM_PROMPT_TEMPLATE` to specify your model " -"prompt template." -msgstr "" -"DB-GPT 会根据 `LLM_MODEL` 从 `pilot.configs.model_config.LLM_MODEL_CONFIG` " -"中读取模型路径。当然，你可以使用环境 `LLM_MODEL_PATH` 来指定模型路径，以及使用 `LLM_PROMPT_TEMPLATE` " -"来指定模型的 prompt 模板。" - -#~ msgid "" -#~ "Note: you need to install the " -#~ "latest dependencies according to " -#~ "[requirements.txt](https://github.com/eosphoros-ai/DB-" -#~ "GPT/blob/main/requirements.txt)." -#~ msgstr "" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/getting_started/getting_started.po b/docs/locales/zh_CN/LC_MESSAGES/getting_started/getting_started.po deleted file mode 100644 index 671ff8bc2..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/getting_started/getting_started.po +++ /dev/null @@ -1,561 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 0.3.0\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-08-28 15:05+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../getting_started/getting_started.md:1 da78e5535cec40a5af378654db5bdd95 -msgid "Quickstart Guide" -msgstr "使用指南" - -#: ../../getting_started/getting_started.md:3 7e54f808055c44578a2364e9a6c95f69 -msgid "Welcome to DB-GPT!" -msgstr "欢迎来到DB-GPT!" - -#: ../../getting_started/getting_started.md:5 3d46f319cc404984a9f3fbf36e3e14f7 -msgid "" -"DB-GPT is an experimental open-source project that uses localized GPT " -"large models to interact with your data and environment. With this " -"solution, you can be assured that there is no risk of data leakage, and " -"your data is 100% private and secure." -msgstr "" -"随着大模型的发布迭代，大模型变得越来越智能，在使用大模型的过程当中，遇到极大的数据安全与隐私挑战。在利用大模型能力的过程中我们的私密数据跟环境需要掌握自己的手里，完全可控，避免任何的数据隐私泄露以及安全风险。基于此" -"，我们发起了DB-GPT项目，为所有以数据库为基础的场景，构建一套完整的私有大模型解决方案。 " -"此方案因为支持本地部署，所以不仅仅可以应用于独立私有环境，而且还可以根据业务模块独立部署隔离，让大模型的能力绝对私有、安全、可控。" - -#: ../../getting_started/getting_started.md:9 777caeb99fb9458f89b7699f9b790dbf -msgid "" -"Our vision is to make it easier and more convenient to build applications" -" around databases and llm." -msgstr "我们的愿景是让围绕数据库构建大模型应用更简单，更方便。" - -#: ../../getting_started/getting_started.md:11 02310b9fc7934df093a2b7f53d82b809 -msgid "What can I do with DB-GPT?" -msgstr "通过DB-GPT我能做什么" - -#: ../../getting_started/getting_started.md:13 ec30099749e94de085ac9d45edc35019 -msgid "Chat Data with your Datasource." -msgstr "和自己的数据聊天，进行数据分析" - -#: ../../getting_started/getting_started.md:14 cf5e7961b73447abb788388d843889d7 -msgid "Private domain knowledge question answering." -msgstr "私有领域的知识问答" - -#: ../../getting_started/getting_started.md:15 60b5ab4b672e4d0589c765843243c66f -msgid "Quickly provide private LLM Model deployment." -msgstr "快速构建私有大模型部署" - -#: ../../getting_started/getting_started.md:17 a5f7f27e3b904eb3b8ad3d457d683c10 -msgid "Usage with DB-GPT." -msgstr "DB-GPT使用姿势." - -#: ../../getting_started/getting_started.md:19 5d1914c6fd6d43a59b83412383706fb5 -msgid "" -"Follow DB-GPT application [install tutorial](https://db-" -"gpt.readthedocs.io/en/latest/getting_started/install/deploy/deploy.html)." -msgstr "" -"先安装部署应用[安装教程](https://db-" -"gpt.readthedocs.io/en/latest/getting_started/install/deploy/deploy.html)." - -#: ../../getting_started/getting_started.md:21 9d9ed9a6cdbc4dbdbb2d4009b446c392 -#, fuzzy -msgid "" -"Follow DB-GPT [application usage](https://db-" -"gpt.readthedocs.io/en/latest/getting_started/application/chatdb/chatdb.html)." -msgstr "" -"先安装部署应用[安装教程](https://db-" -"gpt.readthedocs.io/en/latest/getting_started/install/deploy/deploy.html)." - -#: ../../getting_started/getting_started.md:24 319b71993fcc499a89f477b499a21a84 -msgid "" -"If you encounter any issues while using DB-GPT (whether it's during " -"installation or usage), you can refer to the [FAQ](https://db-" -"gpt.readthedocs.io/en/latest/getting_started/faq/deploy/deploy_faq.html) " -"section for assistance." -msgstr "" -"如果你在使用DB-GPT过程中遇到什么问题(无论是安装还是使用)，可以查看[FAQ](https://db-" -"gpt.readthedocs.io/en/latest/getting_started/faq/deploy/deploy_faq.html)\"" - -#: ../../getting_started/getting_started.md:27 7cb0e2f7384c473e9626e59052c114e1 -msgid "🗺️ Ecosystem" -msgstr "" - -#: ../../getting_started/getting_started.md:29 6067623edfda45c5a7fdfa80ffd886f4 -msgid "Github: https://github.com/eosphoros-ai/DB-GPT" -msgstr "Github: https://github.com/eosphoros-ai/DB-GPT" - -#: ../../getting_started/getting_started.md:30 2eb9498deaac4a928e1df453d71fcddf -msgid "PyPi:" -msgstr "PyPi:" - -#: ../../getting_started/getting_started.md:31 f321d5c1e4bd4556959cd947a23055b9 -msgid "DB-GPT: https://pypi.org/simple/db-gpt." -msgstr "DB-GPT: https://pypi.org/simple/db-gpt." - -#: ../../getting_started/getting_started.md:33 b31a2fa10f0d4c28b8068b44654dfbf9 -msgid "Associated projects" -msgstr "关联的项目" - -#: ../../getting_started/getting_started.md:35 c8b6d0da11fc471a9fefcef8f85500e1 -msgid "" -"🧪 DB-GPT-Hub: https://github.com/eosphoros-ai/DB-GPT-Hub | an " -"experimental project to implement Text-to-SQL parsing using LLMs" -msgstr "" -"🧪 DB-GPT-Hub: https://github.com/eosphoros-ai/DB-GPT-Hub | 基于开源大模型的Text-" -"to-SQL实验性项目" - -#: ../../getting_started/getting_started.md:37 a76faff98a9a49d893a3e15f920c054a -msgid "" -"🏡 DB-GPT-Web: https://github.com/eosphoros-ai/DB-GPT-Web | Web " -"application for DB-GPT." -msgstr "" -"🏡 DB-GPT-Web: https://github.com/eosphoros-ai/DB-GPT-Web | Web 应用 for DB-" -"GPT." - -#: ../../getting_started/getting_started.md:38 be54eeb941564d799cd68a6cfe1bfffc -msgid "" -"🚀 DB-GPT-Plugins: https://github.com/eosphoros-ai/DB-GPT-Web | DB-GPT " -"Plugins Repo, Which support AutoGPT plugin." -msgstr "" -"🚀 DB-GPT-Plugins: https://github.com/eosphoros-ai/DB-GPT-Web | DB-GPT " -"Plugins Repo, Which support AutoGPT plugin." - -#~ msgid "4.2. Run with docker compose" -#~ msgstr "4.2. Run with docker compose" - -#~ msgid "" -#~ "1.This project relies on a local " -#~ "MySQL database service, which you need" -#~ " to install locally. We recommend " -#~ "using Docker for installation." -#~ msgstr "本项目依赖一个本地的 MySQL 数据库服务，你需要本地安装，推荐直接使用 Docker 安装。" - -#~ msgid "prepare server sql script" -#~ msgstr "准备db-gpt server sql脚本" - -#~ msgid "" -#~ "This tutorial gives you a quick " -#~ "walkthrough about use DB-GPT with " -#~ "you environment and data." -#~ msgstr "本教程为您提供了关于如何使用DB-GPT的使用指南。" - -#~ msgid "Installation" -#~ msgstr "安装" - -#~ msgid "To get started, install DB-GPT with the following steps." -#~ msgstr "请按照以下步骤安装DB-GPT" - -#~ msgid "1. Hardware Requirements" -#~ msgstr "1. 硬件要求" - -#~ msgid "" -#~ "As our project has the ability to" -#~ " achieve ChatGPT performance of over " -#~ "85%, there are certain hardware " -#~ "requirements. However, overall, the project" -#~ " can be deployed and used on " -#~ "consumer-grade graphics cards. The specific" -#~ " hardware requirements for deployment are" -#~ " as follows:" -#~ msgstr "由于我们的项目有能力达到85%以上的ChatGPT性能，所以对硬件有一定的要求。但总体来说，我们在消费级的显卡上即可完成项目的部署使用，具体部署的硬件说明如下:" - -#~ msgid "GPU" -#~ msgstr "GPU" - -#~ msgid "VRAM Size" -#~ msgstr "显存大小" - -#~ msgid "Performance" -#~ msgstr "显存大小" - -#~ msgid "RTX 4090" -#~ msgstr "RTX 4090" - -#~ msgid "24 GB" -#~ msgstr "24 GB" - -#~ msgid "Smooth conversation inference" -#~ msgstr "可以流畅的进行对话推理，无卡顿" - -#~ msgid "RTX 3090" -#~ msgstr "RTX 3090" - -#~ msgid "Smooth conversation inference, better than V100" -#~ msgstr "可以流畅进行对话推理，有卡顿感，但好于V100" - -#~ msgid "V100" -#~ msgstr "V100" - -#~ msgid "16 GB" -#~ msgstr "16 GB" - -#~ msgid "Conversation inference possible, noticeable stutter" -#~ msgstr "可以进行对话推理，有明显卡顿" - -#~ msgid "2. Install" -#~ msgstr "2. 安装" - -#~ msgid "" -#~ "We use [Chroma embedding " -#~ "database](https://github.com/chroma-core/chroma) as " -#~ "the default for our vector database " -#~ "and use SQLite as the default for" -#~ " our database, so there is no " -#~ "need for special installation. If you" -#~ " choose to connect to other " -#~ "databases, you can follow our tutorial" -#~ " for installation and configuration. For" -#~ " the entire installation process of " -#~ "DB-GPT, we use the miniconda3 virtual" -#~ " environment. Create a virtual environment" -#~ " and install the Python dependencies." -#~ msgstr "" -#~ "向量数据库我们默认使用的是Chroma内存数据库，所以无需特殊安装，如果有需要连接其他的同学，可以按照我们的教程进行安装配置" -#~ "。整个DB-GPT的安装过程，我们使用的是miniconda3的虚拟环境。创建虚拟环境，并安装python依赖包" - -#~ msgid "Before use DB-GPT Knowledge Management" -#~ msgstr "使用知识库管理功能之前" - -#~ msgid "" -#~ "Once the environment is installed, we" -#~ " have to create a new folder " -#~ "\"models\" in the DB-GPT project, " -#~ "and then we can put all the " -#~ "models downloaded from huggingface in " -#~ "this directory" -#~ msgstr "" -#~ "环境安装完成后，我们必须在DB-" -#~ "GPT项目中创建一个新文件夹\"models\"，然后我们可以把从huggingface下载的所有模型放到这个目录下。" - -#~ msgid "Notice make sure you have install git-lfs" -#~ msgstr "确保你已经安装了git-lfs" - -#~ msgid "" -#~ "The model files are large and will" -#~ " take a long time to download. " -#~ "During the download, let's configure the" -#~ " .env file, which needs to be " -#~ "copied and created from the " -#~ ".env.template" -#~ msgstr "模型文件很大，需要很长时间才能下载。在下载过程中，让我们配置.env文件，它需要从。env.template中复制和创建。" - -#~ msgid "cp .env.template .env" -#~ msgstr "cp .env.template .env" - -#~ msgid "" -#~ "You can configure basic parameters in" -#~ " the .env file, for example setting" -#~ " LLM_MODEL to the model to be " -#~ "used" -#~ msgstr "您可以在.env文件中配置基本参数，例如将LLM_MODEL设置为要使用的模型。" - -#~ msgid "" -#~ "([Vicuna-v1.5](https://huggingface.co/lmsys/vicuna-13b-v1.5) " -#~ "based on llama-2 has been released, " -#~ "we recommend you set `LLM_MODEL=vicuna-" -#~ "13b-v1.5` to try this model)" -#~ msgstr "" - -#~ msgid "3. Run" -#~ msgstr "3. 运行" - -#~ msgid "" -#~ "You can refer to this document to" -#~ " obtain the Vicuna weights: " -#~ "[Vicuna](https://github.com/lm-sys/FastChat/blob/main/README.md" -#~ "#model-weights) ." -#~ msgstr "" -#~ "关于基础模型, 可以根据[Vicuna](https://github.com/lm-" -#~ "sys/FastChat/blob/main/README.md#model-weights) 合成教程进行合成。" - -#~ msgid "" -#~ "If you have difficulty with this " -#~ "step, you can also directly use " -#~ "the model from [this " -#~ "link](https://huggingface.co/Tribbiani/vicuna-7b) as " -#~ "a replacement." -#~ msgstr "" -#~ "如果此步有困难的同学，也可以直接使用[此链接](https://huggingface.co/Tribbiani/vicuna-" -#~ "7b)上的模型进行替代。" - -#~ msgid "" -#~ "set .env configuration set your vector" -#~ " store type, eg:VECTOR_STORE_TYPE=Chroma, now " -#~ "we support Chroma and Milvus(version >" -#~ " 2.1)" -#~ msgstr "" -#~ "在.env文件设置向量数据库环境变量，eg:VECTOR_STORE_TYPE=Chroma, 目前我们支持了 " -#~ "Chroma and Milvus(version >2.1) " - -#~ msgid "1.Run db-gpt server" -#~ msgstr "运行模型服务" - -#~ msgid "Open http://localhost:5000 with your browser to see the product." -#~ msgstr "打开浏览器访问http://localhost:5000" - -#~ msgid "" -#~ "If you want to access an external" -#~ " LLM service, you need to 1.set " -#~ "the variables LLM_MODEL=YOUR_MODEL_NAME " -#~ "MODEL_SERVER=YOUR_MODEL_SERVER（eg:http://localhost:5000） in " -#~ "the .env file. 2.execute dbgpt_server.py " -#~ "in light mode" -#~ msgstr "如果你想访问外部的大模型服务，1.需要在.env文件设置模型名和外部模型服务地址。2.使用light模式启动服务" - -#~ msgid "" -#~ "If you want to learn about " -#~ "dbgpt-webui, read https://github./csunny/DB-" -#~ "GPT/tree/new-page-framework/datacenter" -#~ msgstr "" -#~ "如果你想了解DB-GPT前端服务，访问https://github.com/csunny/DB-GPT/tree" -#~ "/new-page-framework/datacenter" - -#~ msgid "4. Docker (Experimental)" -#~ msgstr "4. Docker (Experimental)" - -#~ msgid "4.1 Building Docker image" -#~ msgstr "4.1 Building Docker image" - -#~ msgid "Review images by listing them:" -#~ msgstr "Review images by listing them:" - -#~ msgid "Output should look something like the following:" -#~ msgstr "Output should look something like the following:" - -#~ msgid "" -#~ "`eosphorosai/dbgpt` is the base image, " -#~ "which contains the project's base " -#~ "dependencies and a sqlite database. " -#~ "`eosphorosai/dbgpt-allinone` build from " -#~ "`eosphorosai/dbgpt`, which contains a mysql" -#~ " database." -#~ msgstr "" - -#~ msgid "You can pass some parameters to docker/build_all_images.sh." -#~ msgstr "You can pass some parameters to docker/build_all_images.sh." - -#~ msgid "" -#~ "You can execute the command `bash " -#~ "docker/build_all_images.sh --help` to see more" -#~ " usage." -#~ msgstr "" -#~ "You can execute the command `bash " -#~ "docker/build_all_images.sh --help` to see more" -#~ " usage." - -#~ msgid "4.2. Run all in one docker container" -#~ msgstr "4.2. Run all in one docker container" - -#~ msgid "**Run with local model and SQLite database**" -#~ msgstr "**Run with local model**" - -#~ msgid "" -#~ "`-e LLM_MODEL=vicuna-13b`, means we use" -#~ " vicuna-13b as llm model, see " -#~ "/pilot/configs/model_config.LLM_MODEL_CONFIG" -#~ msgstr "" -#~ "`-e LLM_MODEL=vicuna-13b`, means we use" -#~ " vicuna-13b as llm model, see " -#~ "/pilot/configs/model_config.LLM_MODEL_CONFIG" - -#~ msgid "" -#~ "`-v /data/models:/app/models`, means we mount" -#~ " the local model file directory " -#~ "`/data/models` to the docker container " -#~ "directory `/app/models`, please replace it " -#~ "with your model file directory." -#~ msgstr "" -#~ "`-v /data/models:/app/models`, means we mount" -#~ " the local model file directory " -#~ "`/data/models` to the docker container " -#~ "directory `/app/models`, please replace it " -#~ "with your model file directory." - -#~ msgid "You can see log with command:" -#~ msgstr "You can see log with command:" - -#~ msgid "**Run with local model and MySQL database**" -#~ msgstr "**Run with local model**" - -#~ msgid "**Run with openai interface**" -#~ msgstr "**Run with openai interface**" - -#~ msgid "" -#~ "`-e LLM_MODEL=proxyllm`, means we use " -#~ "proxy llm(openai interface, fastchat " -#~ "interface...)" -#~ msgstr "" -#~ "`-e LLM_MODEL=proxyllm`, means we use " -#~ "proxy llm(openai interface, fastchat " -#~ "interface...)" - -#~ msgid "" -#~ "`-v /data/models/text2vec-large-chinese:/app/models" -#~ "/text2vec-large-chinese`, means we mount" -#~ " the local text2vec model to the " -#~ "docker container." -#~ msgstr "" -#~ "`-v /data/models/text2vec-large-chinese:/app/models" -#~ "/text2vec-large-chinese`, means we mount" -#~ " the local text2vec model to the " -#~ "docker container." - -#~ msgid "4.3. Run with docker compose" -#~ msgstr "" - -#~ msgid "" -#~ "You can open docker-compose.yml in " -#~ "the project root directory to see " -#~ "more details." -#~ msgstr "" -#~ "You can open docker-compose.yml in " -#~ "the project root directory to see " -#~ "more details." - -#~ msgid "5. Multiple GPUs" -#~ msgstr "5. Multiple GPUs" - -#~ msgid "" -#~ "DB-GPT will use all available gpu" -#~ " by default. And you can modify " -#~ "the setting `CUDA_VISIBLE_DEVICES=0,1` in " -#~ "`.env` file to use the specific " -#~ "gpu IDs." -#~ msgstr "" -#~ "DB-GPT will use all available gpu" -#~ " by default. And you can modify " -#~ "the setting `CUDA_VISIBLE_DEVICES=0,1` in " -#~ "`.env` file to use the specific " -#~ "gpu IDs." - -#~ msgid "" -#~ "Optionally, you can also specify the " -#~ "gpu ID to use before the starting" -#~ " command, as shown below:" -#~ msgstr "" -#~ "Optionally, you can also specify the " -#~ "gpu ID to use before the starting" -#~ " command, as shown below:" - -#~ msgid "" -#~ "You can modify the setting " -#~ "`MAX_GPU_MEMORY=xxGib` in `.env` file to " -#~ "configure the maximum memory used by " -#~ "each GPU." -#~ msgstr "" - -#~ msgid "6. Not Enough Memory" -#~ msgstr "" - -#~ msgid "DB-GPT supported 8-bit quantization and 4-bit quantization." -#~ msgstr "" - -#~ msgid "" -#~ "You can modify the setting " -#~ "`QUANTIZE_8bit=True` or `QUANTIZE_4bit=True` in " -#~ "`.env` file to use quantization(8-bit " -#~ "quantization is enabled by default)." -#~ msgstr "" - -#~ msgid "" -#~ "Llama-2-70b with 8-bit quantization can " -#~ "run with 80 GB of VRAM, and " -#~ "4-bit quantization can run with 48 " -#~ "GB of VRAM." -#~ msgstr "" -#~ "Llama-2-70b with 8-bit quantization can " -#~ "run with 80 GB of VRAM, and " -#~ "4-bit quantization can run with 48 " -#~ "GB of VRAM." - -#~ msgid "" -#~ "Note: you need to install the " -#~ "latest dependencies according to " -#~ "[requirements.txt](https://github.com/eosphoros-ai/DB-" -#~ "GPT/blob/main/requirements.txt)." -#~ msgstr "" -#~ "Note: you need to install the " -#~ "latest dependencies according to " -#~ "[requirements.txt](https://github.com/eosphoros-ai/DB-" -#~ "GPT/blob/main/requirements.txt)." - -#~ msgid "" -#~ "Here are some of the VRAM size " -#~ "usage of the models we tested in" -#~ " some common scenarios." -#~ msgstr "" -#~ "Here are some of the VRAM size " -#~ "usage of the models we tested in" -#~ " some common scenarios." - -#~ msgid "Model" -#~ msgstr "Model" - -#~ msgid "Quantize" -#~ msgstr "Quantize" - -#~ msgid "vicuna-7b-v1.5" -#~ msgstr "vicuna-7b-v1.5" - -#~ msgid "4-bit" -#~ msgstr "4-bit" - -#~ msgid "8 GB" -#~ msgstr "24 GB" - -#~ msgid "8-bit" -#~ msgstr "8-bit" - -#~ msgid "12 GB" -#~ msgstr "24 GB" - -#~ msgid "vicuna-13b-v1.5" -#~ msgstr "vicuna-13b-v1.5" - -#~ msgid "20 GB" -#~ msgstr "24 GB" - -#~ msgid "llama-2-7b" -#~ msgstr "llama-2-7b" - -#~ msgid "llama-2-13b" -#~ msgstr "llama-2-13b" - -#~ msgid "llama-2-70b" -#~ msgstr "llama-2-70b" - -#~ msgid "48 GB" -#~ msgstr "24 GB" - -#~ msgid "80 GB" -#~ msgstr "24 GB" - -#~ msgid "baichuan-7b" -#~ msgstr "" - -#~ msgid "baichuan-13b" -#~ msgstr "baichuan-13b" - -#~ msgid "" -#~ "[应用使用教程](https://db-" -#~ "gpt.readthedocs.io/en/latest/getting_started/application/chatdb/chatdb.html)." -#~ msgstr "" - -#~ msgid "🗺️ 生态" -#~ msgstr "🗺️ 生态" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/getting_started/install.po b/docs/locales/zh_CN/LC_MESSAGES/getting_started/install.po deleted file mode 100644 index a4cfc8e66..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/getting_started/install.po +++ /dev/null @@ -1,56 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.3.5\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-09-13 09:06+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../getting_started/install.rst:2 ../../getting_started/install.rst:15 -#: e2c13385046b4da6b6838db6ba2ea59c -msgid "Install" -msgstr "Install" - -#: ../../getting_started/install.rst:3 3cb6cd251ed440dabe5d4f556435f405 -msgid "" -"DB-GPT product is a Web application that you can chat database, chat " -"knowledge, text2dashboard." -msgstr "DB-GPT 可以生成sql，智能报表, 知识库问答的产品" - -#: ../../getting_started/install.rst:8 6fe8104b70d24f5fbfe2ad9ebf3bc3ba -msgid "deploy" -msgstr "部署" - -#: ../../getting_started/install.rst:9 e67974b3672346809febf99a3b9a55d3 -msgid "docker" -msgstr "docker" - -#: ../../getting_started/install.rst:10 64de16a047c74598966e19a656bf6c4f -msgid "docker_compose" -msgstr "docker_compose" - -#: ../../getting_started/install.rst:11 9f87d65e8675435b87cb9376a5bfd85c -msgid "environment" -msgstr "environment" - -#: ../../getting_started/install.rst:12 e60fa13bb24544ed9d4f902337093ebc -msgid "cluster deployment" -msgstr "集群部署" - -#: ../../getting_started/install.rst:13 7451712679c2412e858e7d3e2af6b174 -msgid "deploy_faq" -msgstr "deploy_faq" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/cluster/cluster.po b/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/cluster/cluster.po deleted file mode 100644 index 6a8d46acb..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/cluster/cluster.po +++ /dev/null @@ -1,430 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.3.6\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-10-17 19:39+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../getting_started/install/cluster/cluster.rst:72 -msgid "Cluster deployment" -msgstr "集群部署" - -#: ../../getting_started/install/cluster/cluster.rst:2 -#: bc5bb85c846b4ad19aeeccdd016f3ce8 -#, fuzzy -msgid "LLM Deployment" -msgstr "集群部署" - -#: ../../getting_started/install/cluster/cluster.rst:3 -#: e1cebf0518db423fbc78e39945a423fa -msgid "" -"In the exploration and implementation of AI model applications, it can be" -" challenging to directly integrate with model services. Currently, there " -"is no established standard for deploying large models, and new models and" -" inference methods are constantly being released. As a result, a " -"significant amount of time is spent adapting to the ever-changing " -"underlying model environment. This, to some extent, hinders the " -"exploration and implementation of AI model applications." -msgstr "" -"在AIGC应用探索和生产落地中，难以避免直接与模型服务对接，但是目前大模型的推理部署目前还没有一个事实标准，不断有新的模型发布，也不断有新的训练和推理方法被提出，而我们就不得不花费相当一部分时间来适配多变的底层模型环境，而这在一定程度上制约了" -" AIGC 应用的探索和落地。" - -#: ../../getting_started/install/cluster/cluster.rst:5 -#: c6179ac327734b7ca7b87612988dad29 -msgid "" -"We divide the deployment of large models into two layers: the model " -"inference layer and the model deployment layer. The model inference layer" -" corresponds to model inference frameworks such as vLLM, TGI, and " -"TensorRT. The model deployment layer interfaces with the inference layer " -"below and provides model serving capabilities above. We refer to this " -"layer's framework as the model deployment framework. Positioned above the" -" inference frameworks, the model deployment framework offers capabilities" -" such as multiple model instances, multiple inference frameworks, " -"multiple service protocols, multi-cloud support, automatic scaling, and " -"observability." -msgstr "" -"我们将大模型推理部署分为两层：模型推理层、模型部署层。模型推理层，对应模型推理框架 vLLM、TGI 和 TensorRT " -"等。模型部署层向下对接推理层，向上提供模型服务能力，这一层的框架我们称为模型部署框架，模型部署框架在推理框架之上，提供了多模型实例、多推理框架、多服务协议、多云、自动扩缩容和可观测性等能力。" - -#: ../../getting_started/install/cluster/cluster.rst:7 -#: 61bae2fc8e3347248ecf084a3977e448 -msgid "" -"In order to deploy DB-GPT to multiple nodes, you can deploy a cluster. " -"The cluster architecture diagram is as follows:" -msgstr "为了能将DB-GPT部署到多个节点上，你可以部署一个集群，集群的架构图如下:" - -#: ../../getting_started/install/cluster/cluster.rst:14 -#: af8d74ac3c5747b3934d02200afbb4ba -msgid "Design of DB-GPT:" -msgstr "设计目标" - -#: ../../getting_started/install/cluster/cluster.rst:16 -#: ab9f332105ac490097501798d7b6cf15 -msgid "" -"DB-GPT is designed as a llm deployment framework, taking into account the" -" above design objectives." -msgstr "支持多模型和多推理框架" - -#: ../../getting_started/install/cluster/cluster.rst:18 -#: 281c38e2e84940098eeeb435db6d1f05 -msgid "" -"Support for llm and inference frameworks: DB-GPT supports the " -"simultaneous deployment of llm and is compatible with multiple inference " -"frameworks such as vLLM, TGI, and TensorRT." -msgstr "" -"在 DB-GPT 中，直接提供了对 FastChat、vLLM和 llama.cpp 的无缝支持，理论上它们支持模型 DB-GPT " -"都支持，如果您对推理速度和并发能力有需求，可以直接使用 vLLM，如果您希望 CPU 或者 mac 的 " -"m1/m2性能也获得不错的推理性能，可以使用 llama.cpp，此外，DB-GPT 还支持了很多代理模型（openai、azure " -"openai、google bard、文心一言、通义千问和智谱AI等）。" - -#: ../../getting_started/install/cluster/cluster.rst:20 -#: ec7e111f2db64c7fa926b1491020ae73 -msgid "" -"Scalability and stability: DB-GPT has good scalability, allowing easy " -"addition of new models and inference frameworks. It utilizes a " -"distributed architecture and automatic scaling capabilities to handle " -"high concurrency and large-scale requests, ensuring system stability." -msgstr "良好的扩展性和稳定性”" - -#: ../../getting_started/install/cluster/cluster.rst:22 -#: 49566c3e708c4ef3a6135ea6245a5417 -msgid "" -"Performance optimization: DB-GPT undergoes performance optimization to " -"provide fast and efficient model inference capabilities, preventing it " -"from becoming a performance bottleneck during inference." -msgstr "框架性能 “不拖后腿”" - -#: ../../getting_started/install/cluster/cluster.rst:24 -#: 0ae41617a7904dcfadd64ec921d3987e -msgid "" -"Management and observability capabilities: DB-GPT offers management and " -"monitoring functionalities, including model deployment and configuration " -"management, performance monitoring, and logging. It can generate reports " -"on model performance and service status to promptly identify and resolve " -"issues." -msgstr "管理与可观测性能力" - -#: ../../getting_started/install/cluster/cluster.rst:26 -#: 7c7c762642754c8d8e8b7d4eaad55384 -msgid "" -"Lightweight: DB-GPT is designed as a lightweight framework to improve " -"deployment efficiency and save resources. It employs efficient algorithms" -" and optimization strategies to minimize resource consumption while " -"maintaining sufficient functionality and performance." -msgstr "轻量化" - -#: ../../getting_started/install/cluster/cluster.rst:29 -#: 32c1d24c20ed4155ad05c505a355ebaf -msgid "1.Support for multiple models and inference frameworks" -msgstr "1.支持多模型和多推理框架" - -#: ../../getting_started/install/cluster/cluster.rst:30 -#: b0d80a26a0d14ab4a6a82bbdc693a9cc -msgid "" -"The field of large models is evolving rapidly, with new models being " -"released and new methods being proposed for model training and inference." -" We believe that this situation will continue for some time." -msgstr "当前大模型领域发展可谓日新月异，不断有新的模型发布，在模型训练和推理方面，也不断有新的方法被提出。我们判断，这样情况还会持续一段时间。" - -#: ../../getting_started/install/cluster/cluster.rst:32 -#: 8b7c3830e5d64567bef9244bd0c4442d -msgid "" -"For most users exploring and implementing AI applications, this situation" -" has its pros and cons. The benefits are apparent, as it brings new " -"opportunities and advancements. However, one drawback is that users may " -"feel compelled to constantly try and explore new models and inference " -"frameworks." -msgstr "" -"大于大部分 AIGC " -"应用场景探索和落地的用户来说，这种情况有利也有弊，利无需多言，而弊端之一就在于被“牵着鼻子走”，需要不断去尝试和探索新的模型、新的推理框架。" - -#: ../../getting_started/install/cluster/cluster.rst:34 -#: b2f7bf8f9ef4406989a366d66e59794b -msgid "" -"In DB-GPT, seamless support is provided for FastChat, vLLM, and " -"llama.cpp. In theory, any model supported by these frameworks is also " -"supported by DB-GPT. If you have requirements for faster inference speed " -"and concurrency, you can directly use vLLM. If you want good inference " -"performance on CPU or Apple's M1/M2 chips, you can use llama.cpp. " -"Additionally, DB-GPT also supports various proxy models from OpenAI, " -"Azure OpenAI, Google BARD, Wenxin Yiyan, Tongyi Qianwen, and Zhipu AI, " -"among others." -msgstr "" -"在 DB-GPT 中，直接提供了对 FastChat、vLLM和 llama.cpp 的无缝支持，理论上它们支持模型 DB-GPT " -"都支持，如果您对推理速度和并发能力有需求，可以直接使用 vLLM，如果您希望 CPU 或者 mac 的 " -"m1/m2性能也获得不错的推理性能，可以使用 llama.cpp，此外，DB-GPT 还支持了很多代理模型（openai、azure " -"openai、google bard、文心一言、通义千问和智谱AI等）。" - -#: ../../getting_started/install/cluster/cluster.rst:37 -#: 9f894d801c364d58814f295222567992 -msgid "2.Have good scalability and stability" -msgstr "2.扩展性和稳定性要足够好" - -#: ../../getting_started/install/cluster/cluster.rst:38 -#: 5423f1f5f0e94804becd3caa500b4046 -msgid "" -"A comprehensive model deployment framework consists of several " -"components: the Model Worker, which directly interfaces with the " -"underlying inference frameworks; the Model Controller, which manages and " -"maintains multiple model components; and the Model API, which provides " -"external model serving capabilities." -msgstr "" -"一个比较完善模型部署框架需要多个部分组成，与底层推理框架直接对接的 Model Worker，管理和维护多个模型组件的 Model " -"Controller 以及对外提供模型服务能力的 Model API。" - -#: ../../getting_started/install/cluster/cluster.rst:40 -#: 6e0948e9a239405ca7d90543569f35fa -msgid "" -"The Model Worker plays a crucial role and needs to be highly extensible. " -"It can be specialized for deploying large language models, embedding " -"models, or other types of models. The choice of Model Worker depends on " -"the deployment environment, such as a regular physical server " -"environment, a Kubernetes environment, or specific cloud environments " -"provided by various cloud service providers." -msgstr "" -"其中 Model Worker 必须要可以扩展，可以是专门部署大语言模型的 Model Worker，也可以是用来部署 Embedding 模型的" -" Model Worker。" - -#: ../../getting_started/install/cluster/cluster.rst:42 -#: 54eba96c95c847e6af77ba94114419ab -msgid "" -"Having different Model Worker options allows users to select the most " -"suitable one based on their specific requirements and infrastructure. " -"This flexibility enables efficient deployment and utilization of models " -"across different environments." -msgstr "当然也可以根据部署的环境，如普通物理机环境、kubernetes 环境以及一些特定云服务商提供的云环境等来选择不同 Model Worker" - -#: ../../getting_started/install/cluster/cluster.rst:44 -#: 693ec0c1b9274f64a1d8fcbd5a8a273d -msgid "" -"The Model Controller, responsible for managing model metadata, also needs" -" to be scalable. Different deployment environments and model management " -"requirements may call for different choices of Model Controllers." -msgstr "" -"用来管理模型元数据的 Model Controller 也需要可扩展，不同的部署环境已经不同的模型管控要求来选择不同的 Model " -"Controller。" - -#: ../../getting_started/install/cluster/cluster.rst:46 -#: 616c0dc43dd84069bde396f1cc99e316 -msgid "" -"Furthermore, I believe that model serving shares many similarities with " -"traditional microservices. In microservices, a service can have multiple " -"instances, and all instances are registered in a central registry. " -"Service consumers retrieve the list of instances based on the service " -"name from the registry and select a specific instance for invocation " -"using a load balancing strategy." -msgstr "另外，在我看来，模型服务与传统的微服务有很多共通之处，在微服务中，微服务中某个服务可以有多个服务实例，所有的服务实例都统一注册到注册中心，服务调用方根据服务名称从注册中心拉取该服务名对应的服务列表，然后根据一定的负载均衡策略选择某个具体的服务实例去调用。" - -#: ../../getting_started/install/cluster/cluster.rst:48 -#: 83389d65894f44598a0eda3984a41cb3 -msgid "" -"Similarly, in model deployment, a model can have multiple instances, and " -"all instances can be registered in a model registry. Model service " -"consumers retrieve the list of instances based on the model name from the" -" registry and select a specific instance for invocation using a model-" -"specific load balancing strategy." -msgstr "而在模型部署中，也可以考虑这样的架构，某一个模型可以有多个模型实例，所有的模型实例都统一注册到模型注册中心，然后模型服务调用方根据模型名称到注册中心去拉取模型实例列表，然后根据模型的负载均衡策略去调用某个具体的的模型实例。" - -#: ../../getting_started/install/cluster/cluster.rst:50 -#: 8524b6f0536446a6900715aaefcdee98 -msgid "" -"Introducing a model registry, responsible for storing model instance " -"metadata, enables such an architecture. The model registry can leverage " -"existing service registries used in microservices (such as Nacos, Eureka," -" etcd, Consul, etc.) as implementations. This ensures high availability " -"of the entire deployment system." -msgstr "" -"这里我们引入模型注册中心，它负责存储 Model Controller 中的模型实例元数据，它可以直接使用微服务中的注册中心作为实现（如 " -"nacos、eureka、etcd 和 consul 等），这样整个部署系统便可以做到高可用。" - -#: ../../getting_started/install/cluster/cluster.rst:53 -#: ff904ff9192248bda12b5ccae28df26f -msgid "3.High performance for framework." -msgstr "3.框架性能“不拖后腿”" - -#: ../../getting_started/install/cluster/cluster.rst:54 -#: c6baf9f2a059487bbf7c3996e401effb -msgid "" -"and optimization are complex tasks, and inappropriate framework designs " -"can increase this complexity. In our view, to ensure that the deployment " -"framework does not lag behind in terms of performance, there are two main" -" areas of focus:" -msgstr "框架层不应该成为模型推理性能的瓶颈，大部分情况下，硬件及推理框架决定了模型服务的服务能力，模型的推理部署和优化是一项复杂的工程，而不恰当的框架设计却可能增加这种复杂度，在我们看来，部署框架为了在性能上“不拖后腿”，有两个主要关注点：" - -#: ../../getting_started/install/cluster/cluster.rst:56 -#: f74418d5394b4afd96578c28ff306116 -msgid "" -"Avoid excessive encapsulation: The more encapsulation and longer the " -"chain, the more challenging it becomes to identify performance issues." -msgstr "避免过多的封装：封装越多、链路越长，性能问题越难以排查。" - -#: ../../getting_started/install/cluster/cluster.rst:58 -#: 692bc702a7f54d48b67c36ac1dc38867 -msgid "" -"High-performance communication design: High-performance communication " -"involves various aspects that cannot be elaborated in detail here. " -"However, considering that Python occupies a prominent position in current" -" AIGC applications, asynchronous interfaces are crucial for service " -"performance in Python. Therefore, the model serving layer should only " -"provide asynchronous interfaces and be compatible with the layers that " -"interface with the model inference framework. If the model inference " -"framework offers asynchronous interfaces, direct integration should be " -"implemented. Otherwise, synchronous-to-asynchronous task conversion " -"should be used to provide support." -msgstr "" -"高性能的通信设计：高性能通信涉及的点很多，这里不做过多阐述。由于目前 AIGC 应用中，Python 占据领导地位，在 Python " -"中，异步接口对于服务的性能至关重要，因此，模型服务层只提供异步接口，与模型推理框架对接的层做兼容，如果模型推理框架提供了异步接口则直接对接，否则使用同步转异步的任务的方式支持。" - -#: ../../getting_started/install/cluster/cluster.rst:61 -#: 3b2bed671a264a13a61b7337e4577185 -msgid "4.Management and monitoring capabilities." -msgstr "4.具备一定的管理和监控能力" - -#: ../../getting_started/install/cluster/cluster.rst:62 -#: 010c26d97cb748d28f86d9d58bdb3c6d -msgid "" -"In the exploration or production implementation of AIGC (Artificial " -"Intelligence and General Computing) applications, it is important for the" -" model deployment system to have certain management capabilities. This " -"involves controlling the deployed model instances through APIs or " -"command-line interfaces, such as for online/offline management, " -"restarting, and debugging." -msgstr "" -"在 AIGC 应用探索中或者 AIGC 应用生产落地中，我们需要模型部署系统能具备一定管理能力：通过 API " -"或者命令行等对部署的模型实例进行一定管控（如上线、下线、重启和 debug 等）。" - -#: ../../getting_started/install/cluster/cluster.rst:64 -#: 49f450fdb5f24d578b4cb8427e57ec15 -msgid "" -"Observability is a crucial capability in production systems, and I " -"believe it is equally, if not more, important in AIGC applications. This " -"is because user experiences and interactions with the system are more " -"complex. In addition to traditional observability metrics, we are also " -"interested in user input information and corresponding contextual " -"information, which specific model instance and parameters were invoked, " -"the content and response time of model outputs, user feedback, and more." -msgstr "" -"可观测性是生产系统的一项重要能力，个人认为在 AIGC " -"应用中，可观测性同样重要，甚至更加重要，因为用户的体验、用户与系统的交互行为更复杂，除了传统的观测指标外，我们还更加关心用户的输入信息及其对应的场景上下文信息、调用了哪个模型实例和模型参数、模型输出的内容和响应时间、用户反馈等等。" - -#: ../../getting_started/install/cluster/cluster.rst:66 -#: 18c940b2e65d4f57ba54b9671ac02254 -msgid "" -"By analyzing this information, we can identify performance bottlenecks in" -" model services and gather user experience data (e.g., response latency, " -"problem resolution, and user satisfaction extracted from user content). " -"These insights serve as important foundations for further optimizing the " -"entire application." -msgstr "我们可以从这些信息中发现一部分模型服务的性能瓶颈，以及一部分用户体验数据（响应延迟如何？是否解决了用户的问题也及用户内容中提取出用户满意度等等），这些都是整个应用进一步优化的重要依据。" - -#: ../../getting_started/install/cluster/cluster.rst:68 -#: a1aa65d7b0694b75a8a298090b3cbfac -#, fuzzy -msgid "" -"On :ref:`Deploying on standalone mode `. Standalone " -"Deployment." -msgstr "关于 :ref:`在本地机器上部署 `。本地集群部署。" - -#: ../../getting_started/install/cluster/cluster.rst:69 -#: 2d74de97891c4a31806ce286c3818631 -#, fuzzy -msgid "" -"On :ref:`Deploying on cluster mode `. Cluster " -"Deployment." -msgstr "关于 :ref:`在本地机器上部署 `。本地集群部署。" - -#~ msgid "" -#~ "When it comes to model deployment, " -#~ "performance is of utmost importance. The" -#~ " framework should be optimized to " -#~ "ensure efficient and fast model " -#~ "inference capabilities. It should not " -#~ "become a performance bottleneck and " -#~ "should be capable of handling high " -#~ "volumes of requests without compromising " -#~ "response times." -#~ msgstr "框架层不应该成为模型推理性能的瓶颈，大部分情况下，硬件及推理框架决定了模型服务的服务能力，模型的推理部署和优化是一项复杂的工程，而不恰当的框架设计却可能增加这种复杂度，在我们看来，部署框架为了在性能上“不拖后腿”，有两个主要关注点：" - -#~ msgid "" -#~ "To achieve this, the framework can " -#~ "employ various performance optimization " -#~ "techniques. This may include utilizing " -#~ "efficient algorithms, leveraging hardware " -#~ "acceleration (such as GPUs or " -#~ "specialized AI chips), optimizing memory " -#~ "usage, and implementing parallel processing" -#~ " techniques to maximize throughput." -#~ msgstr "" - -#~ msgid "" -#~ "By prioritizing performance optimization, the" -#~ " framework can provide seamless and " -#~ "efficient model inference, enabling real-" -#~ "time and high-performance applications " -#~ "without impeding the overall system " -#~ "performance." -#~ msgstr "" - -#~ msgid "" -#~ "To ensure the stability and reliability" -#~ " of model deployment, the framework " -#~ "needs to provide management and " -#~ "monitoring functionalities. This includes " -#~ "managing the lifecycle of models, such" -#~ " as model registration, updates, and " -#~ "deletion. Additionally, the framework should" -#~ " offer monitoring and logging of " -#~ "performance metrics, resource utilization, and" -#~ " system health to promptly identify " -#~ "and resolve potential issues." -#~ msgstr "" -#~ "在 AIGC 应用探索中或者 AIGC " -#~ "应用生产落地中，我们需要模型部署系统能具备一定管理能力：通过 API " -#~ "或者命令行等对部署的模型实例进行一定管控（如上线、下线、重启和 debug 等）。" - -#~ msgid "" -#~ "Management capabilities may involve user " -#~ "permission management, model versioning, and" -#~ " configuration management to facilitate " -#~ "team collaboration and manage multiple " -#~ "versions and configurations of models." -#~ msgstr "" - -#~ msgid "" -#~ "Monitoring capabilities can include real-" -#~ "time monitoring of model performance " -#~ "metrics such as inference latency and" -#~ " throughput. Furthermore, monitoring system " -#~ "resource usage, such as CPU, memory, " -#~ "network, and system health, along with" -#~ " error logging, can be valuable for" -#~ " diagnostics and troubleshooting." -#~ msgstr "" -#~ "可观测性是生产系统的一项重要能力，个人认为在 AIGC " -#~ "应用中，可观测性同样重要，甚至更加重要，因为用户的体验、用户与系统的交互行为更复杂，除了传统的观测指标外，我们还更加关心用户的输入信息及其对应的场景上下文信息、调用了哪个模型实例和模型参数、模型输出的内容和响应时间、用户反馈等等。" - -#~ msgid "" -#~ "By providing management and monitoring " -#~ "capabilities, the framework can assist " -#~ "users in effectively managing and " -#~ "maintaining deployed models, ensuring system" -#~ " stability and reliability, and enabling" -#~ " timely responses to and resolution " -#~ "of issues, thus enhancing overall system" -#~ " efficiency and availability." -#~ msgstr "" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/cluster/kubernetes/index.po b/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/cluster/kubernetes/index.po deleted file mode 100644 index b785f94f4..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/cluster/kubernetes/index.po +++ /dev/null @@ -1,26 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.3.6\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-09-13 09:06+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../getting_started/install/cluster/kubernetes/index.md:1 -#: 48e6f08f27c74f31a8b12758fe33dc24 -msgid "Kubernetes cluster deployment" -msgstr "Kubernetes 集群部署" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/cluster/openai.po b/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/cluster/openai.po deleted file mode 100644 index 0ef41aa6d..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/cluster/openai.po +++ /dev/null @@ -1,71 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.4.0\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-11-02 21:09+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../getting_started/install/cluster/openai.md:1 -#: 01f4e2bf853341198633b367efec1522 -msgid "OpenAI-Compatible RESTful APIs" -msgstr "OpenAI RESTful 兼容接口" - -#: ../../getting_started/install/cluster/openai.md:5 -#: d8717e42335e4027bf4e76b3d28768ee -msgid "Install Prepare" -msgstr "安装准备" - -#: ../../getting_started/install/cluster/openai.md:7 -#: 9a48d8ee116942468de4c6faf9a64758 -msgid "" -"You must [deploy DB-GPT cluster](https://db-" -"gpt.readthedocs.io/en/latest/getting_started/install/cluster/vms/index.html)" -" first." -msgstr "你必须先部署 [DB-GPT 集群]" -"(https://db-gpt.readthedocs.io/projects/db-gpt-docs-zh-cn/zh-cn/latest/getting_started/install/cluster/vms/index.html)。" - -#: ../../getting_started/install/cluster/openai.md:9 -#: 7673a7121f004f7ca6b1a94a7e238fa3 -msgid "Launch Model API Server" -msgstr "启动模型 API Server" - -#: ../../getting_started/install/cluster/openai.md:14 -#: 84a925c2cbcd4e4895a1d2d2fe8f720f -msgid "By default, the Model API Server starts on port 8100." -msgstr "默认情况下，模型 API Server 使用 8100 端口启动。" - -#: ../../getting_started/install/cluster/openai.md:16 -#: e53ed41977cd4721becd51eba05c6609 -msgid "Validate with cURL" -msgstr "通过 cURL 验证" - -#: ../../getting_started/install/cluster/openai.md:18 -#: 7c883b410b5c4e53a256bf17c1ded80d -msgid "List models" -msgstr "列出模型" - -#: ../../getting_started/install/cluster/openai.md:26 -#: ../../getting_started/install/cluster/openai.md:37 -#: 7cf0ed13f0754f149ec085cd6cf7a45a 990d5d5ed5d64ab49550e68495b9e7a0 -msgid "Chat completions" -msgstr "" - -#: ../../getting_started/install/cluster/openai.md:35 -#: 81583edd22df44e091d18a0832278131 -msgid "Validate with OpenAI Official SDK" -msgstr "通过 OpenAI 官方 SDK 验证" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/cluster/vms/index.po b/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/cluster/vms/index.po deleted file mode 100644 index 3525f0751..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/cluster/vms/index.po +++ /dev/null @@ -1,179 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.3.6\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-10-17 17:24+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../getting_started/install/cluster/vms/index.md:1 -#: b23e82d177c443ca8a36b94343ce2173 -#, fuzzy -msgid "Cluster Deployment" -msgstr "模型集群部署" - -#: ../../getting_started/install/cluster/vms/index.md:4 -#: 47ba242f687a41438f1fa41febbe81a3 -msgid "Model cluster deployment" -msgstr "模型集群部署" - -#: ../../getting_started/install/cluster/vms/index.md:7 -#: 077917ec4fa940689ec2e08e3a000578 -msgid "**Installing Command-Line Tool**" -msgstr "**安装命令行工具**" - -#: ../../getting_started/install/cluster/vms/index.md:9 -#: ad498ea7e59f4126838d0a6760da41a3 -#, fuzzy -msgid "" -"All operations below are performed using the `dbgpt` command. To use the " -"`dbgpt` command, you need to install the DB-GPT project with `pip install" -" -e \".[default]\"`. Alternatively, you can use `python " -"pilot/scripts/cli_scripts.py` as a substitute for the `dbgpt` command." -msgstr "" -"以下所有操作都使用 `dbgpt` 命令完成。要使用 `dbgpt` 命令，您需要安装DB-GPT项目，方法是使用`pip install -e " -".`。或者，您可以使用 `python pilot/scripts/cli_scripts.py` 作为 `dbgpt` 命令的替代。" - -#: ../../getting_started/install/cluster/vms/index.md:11 -#: 33e6fa8572054ed1b7e92e14487ef044 -msgid "Launch Model Controller" -msgstr "启动 Model Controller" - -#: ../../getting_started/install/cluster/vms/index.md:17 -#: 2016f7400d9c4013a2da40e3ecfbe02c -msgid "By default, the Model Controller starts on port 8000." -msgstr "默认情况下，Model Controller 启动在 8000 端口。" - -#: ../../getting_started/install/cluster/vms/index.md:20 -#: 82338f543db649c1adc2dc57867e2094 -msgid "Launch LLM Model Worker" -msgstr "启动 LLM Model Worker" - -#: ../../getting_started/install/cluster/vms/index.md:22 -#: 49c2a89381be4fdda17d3cb002899d1f -msgid "If you are starting `chatglm2-6b`:" -msgstr "如果您启动的是 `chatglm2-6b`：" - -#: ../../getting_started/install/cluster/vms/index.md:31 -#: 5c8b223521d640d9a18b169924225510 -msgid "If you are starting `vicuna-13b-v1.5`:" -msgstr "如果您启动的是 `vicuna-13b-v1.5`：" - -#: ../../getting_started/install/cluster/vms/index.md:40 -#: ../../getting_started/install/cluster/vms/index.md:53 -#: 1ad98a11e3f6488cad3d6f7349d4ff70 64b71a7581c34a0d9ba0c9455167b81d -msgid "Note: Be sure to use your own model name and model path." -msgstr "注意：确保使用您自己的模型名称和模型路径。" - -#: ../../getting_started/install/cluster/vms/index.md:42 -#: 5929f47166b241fa9988f1ecb1e45186 -msgid "Launch Embedding Model Worker" -msgstr "启动 Embedding Model Worker" - -#: ../../getting_started/install/cluster/vms/index.md:55 -#: db56788d6758451a823f5b1c91719b56 -msgid "Check your model:" -msgstr "检查您的模型：" - -#: ../../getting_started/install/cluster/vms/index.md:61 -#: e0dae6b3b0c84b5ba24194dffee8c919 -msgid "You will see the following output:" -msgstr "您将看到以下输出：" - -#: ../../getting_started/install/cluster/vms/index.md:75 -#: 9806216c698b44909b3664c72cc09710 -msgid "Connect to the model service in the webserver (dbgpt_server)" -msgstr "在 webserver (dbgpt_server) 中连接到模型服务 (dbgpt_server)" - -#: ../../getting_started/install/cluster/vms/index.md:77 -#: 25fb95f7850a4b0e90f6d949bf440f86 -msgid "" -"**First, modify the `.env` file to change the model name and the Model " -"Controller connection address.**" -msgstr "**首先，修改 `.env` 文件以更改模型名称和模型控制器连接地址。**" - -#: ../../getting_started/install/cluster/vms/index.md:85 -#: 4f66546f32934c5080ca5b7044eeffb8 -msgid "Start the webserver" -msgstr "启动 webserver" - -#: ../../getting_started/install/cluster/vms/index.md:91 -#: 4cc99c718b6c470e93d3e5016cdb5be9 -msgid "`--light` indicates not to start the embedded model service." -msgstr "`--light` 表示不启动嵌入式模型服务。" - -#: ../../getting_started/install/cluster/vms/index.md:93 -#: 4242d989fec249c98a53bdf8a776a103 -msgid "" -"Alternatively, you can prepend the command with `LLM_MODEL=chatglm2-6b` " -"to start:" -msgstr "或者，您可以在命令前加上 `LLM_MODEL=chatglm2-6b` 来启动：" - -#: ../../getting_started/install/cluster/vms/index.md:100 -#: b50e829504b24d64ac9bb3c96bba0271 -msgid "More Command-Line Usages" -msgstr "更多命令行用法" - -#: ../../getting_started/install/cluster/vms/index.md:102 -#: 332f11f9f2f24039a0e512cac2672ded -msgid "You can view more command-line usages through the help command." -msgstr "您可以通过帮助命令查看更多命令行用法。" - -#: ../../getting_started/install/cluster/vms/index.md:104 -#: 89676ed8d92d4d008183aff4c156bcfe -msgid "**View the `dbgpt` help**" -msgstr "**查看 `dbgpt` 帮助**" - -#: ../../getting_started/install/cluster/vms/index.md:109 -#: 384b15e4ee434026814f72044f2eae20 -msgid "You will see the basic command parameters and usage:" -msgstr "您将看到基本的命令参数和用法：" - -#: ../../getting_started/install/cluster/vms/index.md:127 -#: 342307aee3a74b5b80c948a53ec4c99f -msgid "**View the `dbgpt start` help**" -msgstr "**查看 `dbgpt start` 帮助**" - -#: ../../getting_started/install/cluster/vms/index.md:133 -#: 7a3e29aa9caf49ac885e5842606a3d00 -msgid "Here you can see the related commands and usage for start:" -msgstr "在这里，您可以看到启动的相关命令和用法：" - -#: ../../getting_started/install/cluster/vms/index.md:150 -#: d64bac2b25ec4c619f74a7209e634ff3 -msgid "**View the `dbgpt start worker`help**" -msgstr "**查看 `dbgpt start worker` 帮助**" - -#: ../../getting_started/install/cluster/vms/index.md:156 -#: 4bb1293ffd6e40f7923943f62c452925 -msgid "Here you can see the parameters to start Model Worker:" -msgstr "在这里，您可以看到启动 Model Worker 的参数：" - -#: ../../getting_started/install/cluster/vms/index.md:215 -#: 110dd6d71c2845afbe8550d1de9393de -msgid "**View the `dbgpt model`help**" -msgstr "**查看 `dbgpt model` 帮助**" - -#: ../../getting_started/install/cluster/vms/index.md:221 -#: b7ac90dffb84457f8dd87a531ddb72a2 -msgid "" -"The `dbgpt model ` command can connect to the Model Controller via the " -"Model Controller address and then manage a remote model:" -msgstr "`dbgpt model` 命令可以通过 Model Controller 地址连接到 Model Controller，然后管理远程模型：" - -#~ msgid "Local cluster deployment" -#~ msgstr "本地集群部署" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/cluster/vms/standalone.po b/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/cluster/vms/standalone.po deleted file mode 100644 index a183fb2c4..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/cluster/vms/standalone.po +++ /dev/null @@ -1,117 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.3.9\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-10-17 17:24+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../getting_started/install/cluster/vms/standalone.md:1 -#: 40af95d327574e5ea9a6c29f68a7709c -msgid "Standalone Deployment" -msgstr "" - -#: ../../getting_started/install/cluster/vms/standalone.md:5 -#: 7ef23971a0d2415a857d5eb9c4d955ac -msgid "Install Prepare" -msgstr "" - -#: ../../getting_started/install/cluster/vms/standalone.md:12 -#: f3cd2941fa2d49d686fc246237f82e68 -msgid "Create conda environment" -msgstr "" - -#: ../../getting_started/install/cluster/vms/standalone.md:20 -#: 589d80d5d97044ee93747091904583c5 -msgid "Install Default Requirements" -msgstr "" - -#: ../../getting_started/install/cluster/vms/standalone.md:26 -#: 1d151e72660644e7b43084ffccb99598 -msgid "Download and Prepare LLM Model and Embedding Model" -msgstr "" - -#: ../../getting_started/install/cluster/vms/standalone.md:28 -#: 4443c83f8dfa4fdba30929f1e5ecf619 -msgid "If you don't have high performance hardware server" -msgstr "" - -#: ../../getting_started/install/cluster/vms/standalone.md:30 -#: 33a6ee878a4a467d8bcfe5dfbdcbe184 -msgid "you can use openai api, tongyi api , bard api, etc." -msgstr "" - -#: ../../getting_started/install/cluster/vms/standalone.md:39 -#: 7efdb99bc36d42819b1fcd1341b45eef -msgid "set proxy api in .env" -msgstr "" - -#: ../../getting_started/install/cluster/vms/standalone.md:48 -#: 50154ece70bc421ebe7ac05966369bc8 -msgid "If you have high performance hardware server" -msgstr "" - -#: ../../getting_started/install/cluster/vms/standalone.md:62 -#: 4f3696ed069a4a84b2d794593df23765 -msgid "Start all services with a single command." -msgstr "" - -#: ../../getting_started/install/cluster/vms/standalone.md:67 -#: f5f671962cb14a10aba34c4274d2fc2c -msgid "" -"By default, the \"dbgpt start webserver\" command will start the " -"Webserver, Model Controller, and Model Worker in a single Python process." -" Here, we specify the service to be started on port 6006." -msgstr "" - -#: ../../getting_started/install/cluster/vms/standalone.md:69 -#: 4883221a356843f6a6335c25847aecd2 -msgid "" -"View and validate the model service in the command line, you can use the " -"following commands" -msgstr "" - -#: ../../getting_started/install/cluster/vms/standalone.md:70 -#: 1346eb55d7c647be90a90a867ba04ec3 -msgid "" -"1.list the started model services and deployed Model Workers, you can use" -" the following command" -msgstr "" - -#: ../../getting_started/install/cluster/vms/standalone.md:74 -#: 8ab332ebce554758952dbe85c68330a9 -msgid "output is:" -msgstr "" - -#: ../../getting_started/install/cluster/vms/standalone.md:83 -#: efb460bbb70842218f5c056cf05ba1a0 -msgid "The WorkerManager is the management process for Model Workers" -msgstr "" - -#: ../../getting_started/install/cluster/vms/standalone.md:85 -#: 10e5b79f3d914ee3974b1a0d07962fe2 -msgid "" -"validate the deployed model in the command line, you can use the " -"following command" -msgstr "" - -#: ../../getting_started/install/cluster/vms/standalone.md:89 -#: 39d062e7fea948949c1c5c099893f308 -msgid "" -"Then an interactive page will be launched where you can have a " -"conversation with the deployed LLM in the terminal." -msgstr "" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/deploy.po b/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/deploy.po deleted file mode 100644 index f4c85b8b4..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/deploy.po +++ /dev/null @@ -1,652 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.4.0\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-11-06 19:38+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../getting_started/install/deploy.rst:4 f3ea3305f122460aaa11999edc4b5de6 -msgid "Installation From Source" -msgstr "源码安装" - -#: ../../getting_started/install/deploy.rst:6 bb941f2bd56d4eb48f7c4f75ebd74176 -msgid "To get started, install DB-GPT with the following steps." -msgstr "按照以下步骤进行安装" - -#: ../../getting_started/install/deploy.rst:10 27a1e092c1f945ceb9946ebdaf89b600 -msgid "1.Preparation" -msgstr "1.准备" - -#: ../../getting_started/install/deploy.rst:11 5c5bfbdc74a14c3b9b1f1ed66617cac8 -msgid "**Download DB-GPT**" -msgstr "**下载DB-GPT项目**" - -#: ../../getting_started/install/deploy.rst:17 3065ee2f34f9417598a37fd699a4863e -msgid "**Install Miniconda**" -msgstr "**安装Miniconda**" - -#: ../../getting_started/install/deploy.rst:19 f9f3a653ffb8447284686aa37a7bb79a -msgid "" -"We use Sqlite as default database, so there is no need for database " -"installation. If you choose to connect to other databases, you can " -"follow our tutorial for installation and configuration. For the entire " -"installation process of DB-GPT, we use the miniconda3 virtual " -"environment. Create a virtual environment and install the Python " -"dependencies. `How to install Miniconda " -"`_" -msgstr "" -"目前使用Sqlite作为默认数据库，因此DB-" -"GPT快速部署不需要部署相关数据库服务。如果你想使用其他数据库，需要先部署相关数据库服务。我们目前使用Miniconda进行python环境和包依赖管理。`如何安装" -" Miniconda `_ 。" - -#: ../../getting_started/install/deploy.rst:36 a2cd2fdd1d16421f9cbe341040b153b6 -msgid "2.Deploy LLM Service" -msgstr "2.部署LLM服务" - -#: ../../getting_started/install/deploy.rst:37 180a121e3c994a92a917ace80bf12386 -msgid "" -"DB-GPT can be deployed on servers with low hardware requirements or on " -"servers with high hardware requirements." -msgstr "DB-GPT可以部署在对硬件要求不高的服务器，也可以部署在对硬件要求高的服务器" - -#: ../../getting_started/install/deploy.rst:39 395608515c0348d5849030b58da7b659 -msgid "" -"If you are low hardware requirements you can install DB-GPT by Using " -"third-part LLM REST API Service OpenAI, Azure, tongyi." -msgstr "低硬件要求模式适用于对接第三方模型服务的 API，比如 OpenAI、通义千问、 文心一言等。" - -#: ../../getting_started/install/deploy.rst:43 e29297e61e2e4d05ba88f0e1c2b1f365 -msgid "As our project has the ability to achieve OpenAI performance of over 85%," -msgstr "使用OpenAI服务可以让DB-GPT准确率达到85%" - -#: ../../getting_started/install/deploy.rst:48 d0d70d51e8684c2891c58a6da4941a52 -msgid "Notice make sure you have install git-lfs" -msgstr "确认是否已经安装git-lfs" - -#: ../../getting_started/install/deploy.rst:50 0d2781fd38eb467ebad2a3c310a344e6 -msgid "centos:yum install git-lfs" -msgstr "" - -#: ../../getting_started/install/deploy.rst:52 1574ea24ad6443409070aa3a1f7abe87 -msgid "ubuntu:apt-get install git-lfs" -msgstr "" - -#: ../../getting_started/install/deploy.rst:54 ad86473d5c87447091c713f45cbfed0e -msgid "macos:brew install git-lfs" -msgstr "" - -#: ../../getting_started/install/deploy.rst:58 -#: ../../getting_started/install/deploy.rst:229 -#: 3dd1e40f33924faab63634907a7f6511 dce32420face4ab2b99caf7f3900ede9 -msgid "OpenAI" -msgstr "OpenAI" - -#: ../../getting_started/install/deploy.rst:60 1f66400540114de2820761ef80137805 -msgid "Installing Dependencies" -msgstr "安装依赖" - -#: ../../getting_started/install/deploy.rst:66 -#: ../../getting_started/install/deploy.rst:213 -#: 31b856a6fc094334a37914c046cb1bb1 42b2f6d36ca4487f8e31d59bba123fca -msgid "Download embedding model" -msgstr "下载 embedding 模型" - -#: ../../getting_started/install/deploy.rst:78 f970fb69e47c40d7bda381ec6f045829 -msgid "Configure LLM_MODEL, PROXY_API_URL and API_KEY in `.env` file" -msgstr "在 `.env` 文件中设置 LLM_MODEL、PROXY_API_URL 和 API_KEY" - -#: ../../getting_started/install/deploy.rst:88 -#: ../../getting_started/install/deploy.rst:288 -#: 6ca04c88fc60480db2ebdc9b234a0bbb 709cfe74c45c4eff83a7d77bb30b4a2b -msgid "Make sure your .env configuration is not overwritten" -msgstr "确保你的 .env 文件不会被覆盖" - -#: ../../getting_started/install/deploy.rst:91 147aea0d753f44588f4a0c56002334ab -msgid "Vicuna" -msgstr "Vicuna" - -#: ../../getting_started/install/deploy.rst:92 6a0bd60c4ca2478cb0f3d85aff70cd3b -msgid "" -"`Vicuna-v1.5 `_ based on " -"llama-2 has been released, we recommend you set `LLM_MODEL=vicuna-" -"13b-v1.5` to try this model)" -msgstr "" -"基于 llama-2 的模型 `Vicuna-v1.5 `_ 已经发布，我们推荐你通过配置 `LLM_MODEL=vicuna-13b-v1.5` 来尝试这个模型" - -#: ../../getting_started/install/deploy.rst:94 6a111c2ef31f41d4b737cf8b6f36fb16 -msgid "vicuna-v1.5 hardware requirements" -msgstr "vicuna-v1.5 的硬件要求" - -#: ../../getting_started/install/deploy.rst:98 -#: ../../getting_started/install/deploy.rst:143 -#: dc24c0238ce141df8bdce26cc0e2ddbb e04f1ea4b36940f3a28b66cdff7b702e -msgid "Model" -msgstr "模型" - -#: ../../getting_started/install/deploy.rst:99 -#: ../../getting_started/install/deploy.rst:144 -#: b6473e65ca1a437a84226531be4da26d e0a2f7580685480aa13ca462418764d3 -msgid "Quantize" -msgstr "量化" - -#: ../../getting_started/install/deploy.rst:100 -#: ../../getting_started/install/deploy.rst:145 -#: 56471c3b174d4adf9e8cb5bebaa300a6 d82297b8b9c148c3906d8ee4ed10d8a0 -msgid "VRAM Size" -msgstr "显存" - -#: ../../getting_started/install/deploy.rst:101 -#: ../../getting_started/install/deploy.rst:104 -#: 1214432602fe47a28479ce3e21a7d88b 51838e72e42248f199653f1bf08c8155 -msgid "vicuna-7b-v1.5" -msgstr "" - -#: ../../getting_started/install/deploy.rst:102 -#: ../../getting_started/install/deploy.rst:108 -#: ../../getting_started/install/deploy.rst:147 -#: ../../getting_started/install/deploy.rst:153 -#: a64439f4e6f64c42bb76fbb819556784 ed95f498641e4a0f976318df608a1d67 -#: fc400814509048b4a1cbe1e07c539285 ff7a8cb2cce8438cb6cb0d80dabfc2b5 -msgid "4-bit" -msgstr "" - -#: ../../getting_started/install/deploy.rst:103 -#: ../../getting_started/install/deploy.rst:148 -#: 2726e8a278c34e6db59147e9f66f2436 5feab5755a41403c9d641da697de4651 -msgid "8 GB" -msgstr "" - -#: ../../getting_started/install/deploy.rst:105 -#: ../../getting_started/install/deploy.rst:111 -#: ../../getting_started/install/deploy.rst:150 -#: ../../getting_started/install/deploy.rst:156 -#: 1984406682da4da3ad7b275e44085d07 2f027d838d0c46409e54c066d7983aae -#: 5c5878fe64944872b6769f075fedca05 e2507408a9c5423988e17b7029b487e4 -msgid "8-bit" -msgstr "" - -#: ../../getting_started/install/deploy.rst:106 -#: ../../getting_started/install/deploy.rst:109 -#: ../../getting_started/install/deploy.rst:151 -#: ../../getting_started/install/deploy.rst:154 -#: 332f50702c7b46e79ea0af5cbf86c6d5 381d23253cfd40109bacefca6a179f91 -#: aafe2423c25546e789e4804e3fd91d1d cc56990a58e941d6ba023cbd4dca0357 -msgid "12 GB" -msgstr "" - -#: ../../getting_started/install/deploy.rst:107 -#: ../../getting_started/install/deploy.rst:110 -#: 1f14e2fa6d41493cb208f55eddff9773 6457f6307d8546beb5f2fb69c30922d8 -msgid "vicuna-13b-v1.5" -msgstr "" - -#: ../../getting_started/install/deploy.rst:112 -#: ../../getting_started/install/deploy.rst:157 -#: e24d3a36b5ce4cfe861dce2d1c4db592 f2e66b2da7954aaab0ee526b25a371f5 -msgid "20 GB" -msgstr "" - -#: ../../getting_started/install/deploy.rst:128 -#: ../../getting_started/install/deploy.rst:175 -#: ../../getting_started/install/deploy.rst:201 -#: 1719c11f92874c47a87c00c634b9fad8 4596fcbe415d42fdbb29b92964fae070 -#: e639ae6076a64b7b9de08527966e4550 -msgid "The model files are large and will take a long time to download." -msgstr "这个模型权重文件比较大，需要花费较长时间来下载。" - -#: ../../getting_started/install/deploy.rst:130 -#: ../../getting_started/install/deploy.rst:177 -#: ../../getting_started/install/deploy.rst:203 -#: 4ec1492d389f403ebd9dd805fcaac68e ac6c68e2bf9b47c694ea8e0506014b10 -#: e39be72282e64760903aaba45f8effb8 -msgid "**Configure LLM_MODEL in `.env` file**" -msgstr "**在 `.env` 文件中配置 LLM_MODEL**" - -#: ../../getting_started/install/deploy.rst:137 -#: ../../getting_started/install/deploy.rst:234 -#: 7ce4e2253ef24a7ea890ade04ce36682 b9d5bf4fa09649c4a098503132ce7c0c -msgid "Baichuan" -msgstr "百川" - -#: ../../getting_started/install/deploy.rst:139 -#: ffdad6a70558457fa825bad4d811100d -msgid "Baichuan hardware requirements" -msgstr "百川 的硬件要求" - -#: ../../getting_started/install/deploy.rst:146 -#: ../../getting_started/install/deploy.rst:149 -#: 59d9b64f54d34971a68e93e3101def06 a66ce354d8f143ce920303241cd8947e -msgid "baichuan-7b" -msgstr "" - -#: ../../getting_started/install/deploy.rst:152 -#: ../../getting_started/install/deploy.rst:155 -#: c530662259ca4ec5b03a18e4b690e17a fa3af65ecca54daab961f55729bbc40e -msgid "baichuan-13b" -msgstr "" - -#: ../../getting_started/install/deploy.rst:179 -#: efd73637994a4b7c97ef3557e1f3161c -msgid "please rename Baichuan path to \"baichuan2-13b\" or \"baichuan2-7b\"" -msgstr "将Baichuan模型目录修改为\"baichuan2-13b\" 或 \"baichuan2-7b\"" - -#: ../../getting_started/install/deploy.rst:185 -#: 435a3f0d0fe84b49a7305e2c0f51a5df -msgid "ChatGLM" -msgstr "" - -#: ../../getting_started/install/deploy.rst:205 -#: 165e23d3d40d4756b5a6a2580d015213 -msgid "please rename chatglm model path to \"chatglm2-6b\"" -msgstr "将 chatglm 模型目录修改为\"chatglm2-6b\"" - -#: ../../getting_started/install/deploy.rst:211 -#: b651ebb5e0424b8992bc8b49d2280bee -msgid "Other LLM API" -msgstr "其它模型 API" - -#: ../../getting_started/install/deploy.rst:225 -#: 4eabdc25f4a34676b3ece620c88d866f -msgid "Now DB-GPT support LLM REST API TYPE:" -msgstr "目前DB-GPT支持的大模型 REST API 类型:" - -#: ../../getting_started/install/deploy.rst:230 -#: d361963cc3404e5ca55a823f1f1f545c -msgid "Azure" -msgstr "" - -#: ../../getting_started/install/deploy.rst:231 -#: 3b0f17c74aaa4bbd9db935973fa1c36b -msgid "Aliyun tongyi" -msgstr "" - -#: ../../getting_started/install/deploy.rst:232 -#: 7c4c457a499943b8804e31046551006d -msgid "Baidu wenxin" -msgstr "" - -#: ../../getting_started/install/deploy.rst:233 -#: ac1880a995184295acf07fff987d7c56 -msgid "Zhipu" -msgstr "" - -#: ../../getting_started/install/deploy.rst:235 -#: 6927500d7d3445b7b1981da1df4e1666 -msgid "Bard" -msgstr "" - -#: ../../getting_started/install/deploy.rst:237 -#: 419d564de18c485780d9336b852735b6 -msgid "Configure LLM_MODEL and PROXY_API_URL and API_KEY in `.env` file" -msgstr "在`.env`文件设置 LLM_MODEL、PROXY_API_URL和 API_KEY" - -#: ../../getting_started/install/deploy.rst:290 -#: 71d5203682e24e2e896e4b9913471f78 -msgid "llama.cpp" -msgstr "" - -#: ../../getting_started/install/deploy.rst:292 -#: 36a2b82f711a4c0f9491aca9c84d3c91 -msgid "" -"DB-GPT already supports `llama.cpp " -"`_ via `llama-cpp-python " -"`_ ." -msgstr "" -"DB-GPT 已经通过 `llama-cpp-python `_ 支持了 `llama.cpp `_ 。" - -#: ../../getting_started/install/deploy.rst:294 -#: 439064115dca4ae08d8e60041f2ffe17 -msgid "**Preparing Model Files**" -msgstr "**准备模型文件**" - -#: ../../getting_started/install/deploy.rst:296 -#: 7291d6fa20b34942926e7765c01f25c9 -msgid "" -"To use llama.cpp, you need to prepare a gguf format model file, and there" -" are two common ways to obtain it, you can choose either:" -msgstr "为了使用 llama.cpp，你需要准备 gguf 格式的文件，你可以通过以下两种方法获取" - -#: ../../getting_started/install/deploy.rst:298 -#: 45752f3f5dd847469da0c5edddc530fa -msgid "**1. Download a pre-converted model file.**" -msgstr "**1.下载已转换的模型文件.**" - -#: ../../getting_started/install/deploy.rst:300 -#: c451db2157ff49b2b4992aed9907ddfa -msgid "" -"Suppose you want to use `Vicuna 13B v1.5 `_ , you can download the file already converted from " -"`TheBloke/vicuna-13B-v1.5-GGUF `_ , only one file is needed. Download it to the `models` " -"directory and rename it to `ggml-model-q4_0.gguf`." -msgstr "" -"假设您想使用 `Vicuna 13B v1.5 `_ 您可以从 `TheBloke/vicuna-" -"13B-v1.5-GGUF `_ 下载已转换的文件，只需要一个文件。将其下载到models目录并将其重命名为 `ggml-" -"model-q4_0.gguf`。" - -#: ../../getting_started/install/deploy.rst:306 -#: f5b92b51622b43d398b3dc13a5892c29 -msgid "**2. Convert It Yourself**" -msgstr "**2. 自行转换**" - -#: ../../getting_started/install/deploy.rst:308 -#: 8838ae6dcecf44ecad3fd963980c8eb3 -msgid "" -"You can convert the model file yourself according to the instructions in " -"`llama.cpp#prepare-data--run `_ , and put the converted file in the models " -"directory and rename it to `ggml-model-q4_0.gguf`." -msgstr "" -"您可以根据 `llama.cpp#prepare-data--run `_ 中的说明自行转换模型文件，并把转换后的文件放在models目录中，并重命名为`ggml-" -"model-q4_0.gguf`。" - -#: ../../getting_started/install/deploy.rst:310 -#: 3fe28d6e5eaa4bdf9c5c44a914c3577c -msgid "**Installing Dependencies**" -msgstr "**安装依赖**" - -#: ../../getting_started/install/deploy.rst:312 -#: bdc10d2e88cc4c3f84a8c4a8dc2037a9 -msgid "" -"llama.cpp is an optional dependency in DB-GPT, and you can manually " -"install it using the following command:" -msgstr "llama.cpp在DB-GPT中是可选安装项, 你可以通过以下命令进行安装" - -#: ../../getting_started/install/deploy.rst:319 -#: 9c136493448b43b5b27f66af74ff721e -msgid "**3.Modifying the Configuration File**" -msgstr "**3.修改配置文件**" - -#: ../../getting_started/install/deploy.rst:321 -#: c835a7dee1dd409fb861e7b886c6dc5b -msgid "Next, you can directly modify your `.env` file to enable llama.cpp." -msgstr "修改`.env`文件使用llama.cpp" - -#: ../../getting_started/install/deploy.rst:328 -#: ../../getting_started/install/deploy.rst:396 -#: 296e6d08409544918fee0c31b1bf195c a81e5d882faf4722b0e10d53f635f53c -msgid "" -"Then you can run it according to `Run `_" -msgstr "" -"然后你可以根据 `运行 `_ 来运行。" - -#: ../../getting_started/install/deploy.rst:331 -#: 0f7f487ee11a4e01a95f7c504f0469ba -msgid "**More Configurations**" -msgstr "**更多配置文件**" - -#: ../../getting_started/install/deploy.rst:333 -#: b0f9964497f64fb5b3740099232cd72b -msgid "" -"In DB-GPT, the model configuration can be done through `{model " -"name}_{config key}`." -msgstr "在DB-GPT中，模型配置可以通过`{模型名称}_{配置名}` 来配置。" - -#: ../../getting_started/install/deploy.rst:335 -#: 7c225de4fe9d4dd3a3c2b2a33802e656 -msgid "More Configurations" -msgstr "**更多配置文件**" - -#: ../../getting_started/install/deploy.rst:339 -#: 5cc1671910314796a9ce0b5107d3c9fe -msgid "Environment Variable Key" -msgstr "环境变量Key" - -#: ../../getting_started/install/deploy.rst:340 -#: 4359ed4e11bb47ad89a605cbf9016cd5 -msgid "Default" -msgstr "默认值" - -#: ../../getting_started/install/deploy.rst:341 -#: 5cf0efc6d1014665bb9dbdae96bf2726 -msgid "Description" -msgstr "描述" - -#: ../../getting_started/install/deploy.rst:342 -#: e7c291f80a9a40fa90d642901eca02c6 -msgid "llama_cpp_prompt_template" -msgstr "" - -#: ../../getting_started/install/deploy.rst:343 -#: ../../getting_started/install/deploy.rst:346 -#: ../../getting_started/install/deploy.rst:352 -#: ../../getting_started/install/deploy.rst:358 -#: ../../getting_started/install/deploy.rst:364 -#: 07dc7fc4e51e4d9faf8e5221bcf03ee0 549f3c57a2e9427880e457e653ce1182 -#: 7ad961957f7b49d08e4aff347749b78d c1eab368175c4fa88fe0b471919523b2 -#: e2e0bf9903484972b6d20e6837010029 -msgid "None" -msgstr "" - -#: ../../getting_started/install/deploy.rst:344 -#: 6b5044a2009f432c92fcd65db42506d8 -msgid "" -"Prompt template name, now support: zero_shot, vicuna_v1.1,alpaca,llama-2" -",baichuan-chat,internlm-chat, If None, the prompt template is " -"automatically determined from model path。" -msgstr "" -"Prompt template 现在可以支持`zero_shot, vicuna_v1.1,alpaca,llama-2,baichuan-" -"chat,internlm-chat`, 如果是None, 可以根据模型路径来自动获取模型 Prompt template" - -#: ../../getting_started/install/deploy.rst:345 -#: e01c860441ad43b88c0a8d012f97d2d8 -msgid "llama_cpp_model_path" -msgstr "" - -#: ../../getting_started/install/deploy.rst:347 -#: 1cb68d772e454812a1a0c6de4950b8ce -msgid "Model path" -msgstr "模型路径" - -#: ../../getting_started/install/deploy.rst:348 -#: 6dac03820edb4fbd8a0856405e84c5bc -msgid "llama_cpp_n_gpu_layers" -msgstr "" - -#: ../../getting_started/install/deploy.rst:349 -#: 8cd5607b7941427f9a342ca7a00e5778 -msgid "1000000000" -msgstr "" - -#: ../../getting_started/install/deploy.rst:350 -#: 61c9297656da434aa7ac2b49cf61ea9d -msgid "" -"Number of layers to offload to the GPU, Set this to 1000000000 to offload" -" all layers to the GPU. If your GPU VRAM is not enough, you can set a low" -" number, eg: 10" -msgstr "要将多少网络层转移到GPU上，将其设置为1000000000以将所有层转移到GPU上。如果您的 GPU 内存不足，可以设置较低的数字，例如：10。" - -#: ../../getting_started/install/deploy.rst:351 -#: 8c2d2182557a483aa2fda590c24faaf3 -msgid "llama_cpp_n_threads" -msgstr "" - -#: ../../getting_started/install/deploy.rst:353 -#: cc442f61ffc442ecbd98c1e7f5598e1a -msgid "" -"Number of threads to use. If None, the number of threads is automatically" -" determined" -msgstr "要使用的线程数量。如果为None，则线程数量将自动确定。" - -#: ../../getting_started/install/deploy.rst:354 -#: 8d5e917d86f048348106e6923638a0c2 -msgid "llama_cpp_n_batch" -msgstr "" - -#: ../../getting_started/install/deploy.rst:355 -#: ee2719a0a8cd4a77846cffd8e675638f -msgid "512" -msgstr "" - -#: ../../getting_started/install/deploy.rst:356 -#: 845b354315384762a611ad2daa539d57 -msgid "Maximum number of prompt tokens to batch together when calling llama_eval" -msgstr "在调用llama_eval时，批处理在一起的prompt tokens的最大数量" - -#: ../../getting_started/install/deploy.rst:357 -#: a95e788bfa5f46f3bcd6356dfd9f87eb -msgid "llama_cpp_n_gqa" -msgstr "" - -#: ../../getting_started/install/deploy.rst:359 -#: 23ad9b5f34b5440bb90b2b21bab25763 -msgid "Grouped-query attention. Must be 8 for llama-2 70b." -msgstr "对于 llama-2 70B 模型，Grouped-query attention 必须为8。" - -#: ../../getting_started/install/deploy.rst:360 -#: 9ce25b7966fc40ec8be47ecfaf5f9994 -msgid "llama_cpp_rms_norm_eps" -msgstr "" - -#: ../../getting_started/install/deploy.rst:361 -#: 58365f0d36af447ba976213646018431 -msgid "5e-06" -msgstr "" - -#: ../../getting_started/install/deploy.rst:362 -#: d00b742a759140b795ba5949f1ce9a36 -msgid "5e-6 is a good value for llama-2 models." -msgstr "对于llama-2模型来说，5e-6是一个不错的值。" - -#: ../../getting_started/install/deploy.rst:363 -#: b9972e9b19354f55a5e6d9c50513a620 -msgid "llama_cpp_cache_capacity" -msgstr "" - -#: ../../getting_started/install/deploy.rst:365 -#: 3c98c5396dd74db8b6d70fc50fa0754f -msgid "Maximum cache capacity. Examples: 2000MiB, 2GiB" -msgstr "模型缓存最大值. 例如: 2000MiB, 2GiB" - -#: ../../getting_started/install/deploy.rst:366 -#: 4277e155992c4442b69d665d6269bed6 -msgid "llama_cpp_prefer_cpu" -msgstr "" - -#: ../../getting_started/install/deploy.rst:367 -#: 049169c1210a4ecabb25702ed813ea0a -msgid "False" -msgstr "" - -#: ../../getting_started/install/deploy.rst:368 -#: 60a39e93e7874491a93893de78b7d37e -msgid "" -"If a GPU is available, it will be preferred by default, unless " -"prefer_cpu=False is configured." -msgstr "如果有可用的GPU，默认情况下会优先使用GPU，除非配置了 prefer_cpu=False。" - -#: ../../getting_started/install/deploy.rst:371 -#: 7c86780fbf634de8873afd439389cf89 -msgid "vllm" -msgstr "" - -#: ../../getting_started/install/deploy.rst:373 -#: e2827892e43d420c85b8b83c4855d197 -msgid "vLLM is a fast and easy-to-use library for LLM inference and serving." -msgstr "vLLM 是一个快速且易于使用的 LLM 推理和服务的库。" - -#: ../../getting_started/install/deploy.rst:375 -#: 81bbfa3876a74244acc82d295803fdd4 -msgid "**Running vLLM**" -msgstr "**运行vLLM**" - -#: ../../getting_started/install/deploy.rst:377 -#: 75bc518b444c417ba4d9c15246549327 -msgid "**1.Installing Dependencies**" -msgstr "**1.安装依赖**" - -#: ../../getting_started/install/deploy.rst:379 -#: 725c620b0a5045c1a64a3b2a2e9b48f3 -msgid "" -"vLLM is an optional dependency in DB-GPT, and you can manually install it" -" using the following command:" -msgstr "vLLM 在 DB-GPT 是一个可选依赖, 你可以使用下面的命令手动安装它：" - -#: ../../getting_started/install/deploy.rst:385 -#: 6f4b540107764f3592cc07cf170e4911 -msgid "**2.Modifying the Configuration File**" -msgstr "**2.修改配置文件**" - -#: ../../getting_started/install/deploy.rst:387 -#: b8576a1572674c4890e09b73e02cf0e8 -msgid "Next, you can directly modify your .env file to enable vllm." -msgstr "你可以直接修改你的 `.env` 文件" - -#: ../../getting_started/install/deploy.rst:394 -#: b006745f3aee4651aaa0cf79081b5d7f -msgid "" -"You can view the models supported by vLLM `here " -"`_" -msgstr "" -"你可以在 `这里 " -"`_ 查看 vLLM 支持的模型。" - -#: ../../getting_started/install/deploy.rst:403 -#: bc8057ee75e14737bf8fca3ceb555dac -msgid "3.Prepare sql example(Optional)" -msgstr "3.准备 sql example(可选)" - -#: ../../getting_started/install/deploy.rst:404 -#: 9b0b9112237c4b3aaa1dd5d704ea32e6 -msgid "**(Optional) load examples into SQLite**" -msgstr "**(可选) 加载样例数据到 SQLite 数据库中**" - -#: ../../getting_started/install/deploy.rst:411 -#: 0815e13b96264ffcba1526c82ba2e7c8 -msgid "On windows platform:" -msgstr "在 Windows 平台：" - -#: ../../getting_started/install/deploy.rst:418 -#: 577a4167ecac4fa88586961f225f0487 -msgid "4.Run db-gpt server" -msgstr "4.运行db-gpt server" - -#: ../../getting_started/install/deploy.rst:424 -#: a9f96b064b674f80824257b4b0a18e2a -msgid "**Open http://localhost:5000 with your browser to see the product.**" -msgstr "打开浏览器访问http://localhost:5000" - -#~ msgid "" -#~ "DB-GPT can be deployed on servers" -#~ " with low hardware requirements or on" -#~ " servers with high hardware requirements." -#~ " You can install DB-GPT by " -#~ "Using third-part LLM REST API " -#~ "Service OpenAI, Azure." -#~ msgstr "" - -#~ msgid "" -#~ "And you can also install DB-GPT" -#~ " by deploy LLM Service by download" -#~ " LLM model." -#~ msgstr "" - -#~ msgid "百川" -#~ msgstr "" - -#~ msgid "百川 硬件要求" -#~ msgstr "" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/deploy/deploy.po b/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/deploy/deploy.po deleted file mode 100644 index abb04818d..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/deploy/deploy.po +++ /dev/null @@ -1,523 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.3.5\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-10-26 11:34+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../getting_started/install/deploy/deploy.md:1 -#: c9d9195862204bb9b526d728b1527a98 -msgid "Installation From Source" -msgstr "源码安装" - -#: ../../getting_started/install/deploy/deploy.md:3 -#: e462f24ec27645c3afd23866fdeea761 -msgid "" -"This tutorial gives you a quick walkthrough about use DB-GPT with you " -"environment and data." -msgstr "本教程为您提供了关于如何使用DB-GPT的使用指南。" - -#: ../../getting_started/install/deploy/deploy.md:5 -#: 065a4cf91565437cbad46726e5aee89c -msgid "Installation" -msgstr "安装" - -#: ../../getting_started/install/deploy/deploy.md:7 -#: 07ebe19dbb5040419c6016258d975904 -msgid "To get started, install DB-GPT with the following steps." -msgstr "请按照以下步骤安装DB-GPT" - -#: ../../getting_started/install/deploy/deploy.md:9 -#: 1a552a8bb4fe481ba7695e1a2f8985f8 -msgid "1. Hardware Requirements" -msgstr "1. 硬件要求" - -#: ../../getting_started/install/deploy/deploy.md:10 -#: bd292acafdb74b99a570c4a8e126df5d -msgid "" -"DB-GPT can be deployed on servers with low hardware requirements or on " -"servers with high hardware requirements." -msgstr "DB-GPT可以部署在对硬件要求不高的服务器，也可以部署在对硬件要求高的服务器" - -#: ../../getting_started/install/deploy/deploy.md:12 -#: 913c8d0630f2460997fb856b81967903 -#, fuzzy -msgid "Low hardware requirements" -msgstr "1. 硬件要求" - -#: ../../getting_started/install/deploy/deploy.md:13 -#: 70ca521385c642049789e14ab61bc46b -msgid "" -"The low hardware requirements mode is suitable for integrating with " -"third-party LLM services' APIs, such as OpenAI, Tongyi, Wenxin, or " -"Llama.cpp." -msgstr "Low hardware requirements模式适用于对接第三方模型服务的api,比如OpenAI, 通义千问, 文心.cpp。" - -#: ../../getting_started/install/deploy/deploy.md:15 -#: 7aacaa2505c447bfa3d0ef6418ae73d2 -msgid "DB-GPT provides set proxy api to support LLM api." -msgstr "DB-GPT可以通过设置proxy api来支持第三方大模型服务" - -#: ../../getting_started/install/deploy/deploy.md:17 -#: 6b5a9f7d61d54a559363a9a5d270a580 -msgid "As our project has the ability to achieve ChatGPT performance of over 85%," -msgstr "由于我们的项目有能力达到85%以上的ChatGPT性能" - -#: ../../getting_started/install/deploy/deploy.md:19 -#: cf4b1f1115c041cbafb15af61946378c -#, fuzzy -msgid "High hardware requirements" -msgstr "1. 硬件要求" - -#: ../../getting_started/install/deploy/deploy.md:20 -#: dae1e9a698144a919dc3740cd676eb81 -#, fuzzy -msgid "" -"The high hardware requirements mode is suitable for independently " -"deploying LLM services, such as Llama series models, Baichuan, ChatGLM, " -"Vicuna, and other private LLM service. there are certain hardware " -"requirements. However, overall, the project can be deployed and used on " -"consumer-grade graphics cards. The specific hardware requirements for " -"deployment are as follows:" -msgstr "" -"High hardware requirements模式适用于需要独立部署私有大模型服务，比如Llama系列模型，Baichuan, " -"chatglm，vicuna等私有大模型所以对硬件有一定的要求。但总体来说，我们在消费级的显卡上即可完成项目的部署使用，具体部署的硬件说明如下:" - -#: ../../getting_started/install/deploy/deploy.md -#: a6457364eccd49c99dc6a020a9aa5185 -msgid "GPU" -msgstr "GPU" - -#: ../../getting_started/install/deploy/deploy.md -#: 2d737c43c9fd45efbaf1e4204227ab51 bc0aa12f56dd4d26af74d7c10187fc0c -msgid "VRAM Size" -msgstr "显存" - -#: ../../getting_started/install/deploy/deploy.md -#: 8bfd4e58a63a42858b6be2d0ce11b2fa -msgid "Performance" -msgstr "Performance" - -#: ../../getting_started/install/deploy/deploy.md -#: 9ff11248bfdc43e18e6c29ed95d4f807 -msgid "RTX 4090" -msgstr "RTX 4090" - -#: ../../getting_started/install/deploy/deploy.md -#: 229e141d0a0e4d558b11c204654f36a9 94a76fe065164a67883a79f75d10139c -msgid "24 GB" -msgstr "24 GB" - -#: ../../getting_started/install/deploy/deploy.md -#: 2edf99edf84e43ea8a5dce2a5ad0056a -msgid "Smooth conversation inference" -msgstr "丝滑的对话体验" - -#: ../../getting_started/install/deploy/deploy.md -#: df67002e7eb84939a1f452acc88a1fa2 -msgid "RTX 3090" -msgstr "RTX 3090" - -#: ../../getting_started/install/deploy/deploy.md -#: 333303d5e7054d2697f11bb2b53e92ec -msgid "Smooth conversation inference, better than V100" -msgstr "丝滑的对话体验，性能好于V100" - -#: ../../getting_started/install/deploy/deploy.md -#: acfb9e152ec74bacb715cd758a9be964 -msgid "V100" -msgstr "V100" - -#: ../../getting_started/install/deploy/deploy.md -#: 1127ebc45a1b4fdb828f13d55f99ce79 ed6dd464a7f640cd866712eb7f4d4b1b -msgid "16 GB" -msgstr "16 GB" - -#: ../../getting_started/install/deploy/deploy.md -#: 0b6ef92756204be6984f39ee1b95d423 a5aad9380cd742c59934e5ead433a22e -msgid "Conversation inference possible, noticeable stutter" -msgstr "Conversation inference possible, noticeable stutter" - -#: ../../getting_started/install/deploy/deploy.md -#: 7a5a394f02b04cdcb3a9785cfa0cfc7c -msgid "T4" -msgstr "T4" - -#: ../../getting_started/install/deploy/deploy.md:30 -#: 055b00b30901485a841d958a63750341 -#, fuzzy -msgid "" -"If your VRAM Size is not enough, DB-GPT supported 8-bit quantization and " -"4-bit quantization." -msgstr "如果你的显存不够，DB-GPT支持8-bit和4-bit量化版本" - -#: ../../getting_started/install/deploy/deploy.md:32 -#: 34175af61e2e4ecc9e56180b8872a30b -msgid "" -"Here are some of the VRAM size usage of the models we tested in some " -"common scenarios." -msgstr "这里是量化版本的相关说明" - -#: ../../getting_started/install/deploy/deploy.md -#: 1d1adf0f341b4ed7b47887c5923fbe08 -msgid "Model" -msgstr "Model" - -#: ../../getting_started/install/deploy/deploy.md -#: 2e36f6ffdb084de3ae3d1568af60cecc -msgid "Quantize" -msgstr "Quantize" - -#: ../../getting_started/install/deploy/deploy.md -#: 54df9f9813274db482a683c001003e86 61380cdbc434467fbf9cb7cb1efe49b7 -msgid "vicuna-7b-v1.5" -msgstr "vicuna-7b-v1.5" - -#: ../../getting_started/install/deploy/deploy.md -#: 4390ae926c094187bf2905361a5d6cff 467d31fb940c4daf9b2afec6bb7ea7f0 -#: 525896b27182457486018a348c068c01 6788cb202dc044e59e6ae42936b1aca8 -#: 74e07aaf7fa7461e824c653129240ad1 83b491c17b434fdb910b92c4cbc007a0 -#: c14cc4d0ac384fc699a196bf62573f01 -msgid "4-bit" -msgstr "4-bit" - -#: ../../getting_started/install/deploy/deploy.md -#: 25bbb9742e604003aeb2da782e50fa46 334153c71b624064b4f50342ab79c30e -#: 6039634dfcfc4ad3a3298938534ef1e4 -msgid "8 GB" -msgstr "8 GB" - -#: ../../getting_started/install/deploy/deploy.md -#: 0d31a4a235b949eabd8e98c2dcb6d5ff 15bcdb7aedf1497fb0790c1bf3e5ee47 -#: 3125bc143cb0476db0a07b7788bc9928 be257ed0772d448b95873db9e044a713 -#: cf4e3ed197a84dba87a60cc5fc70f8ac eb399647bafe418c90212787e695afbb -#: ee40d24463a143ca8768da7423d25b9b -msgid "8-bit" -msgstr "8-bit" - -#: ../../getting_started/install/deploy/deploy.md -#: 21efb501692440cf80fd29401e1f0afa 246e4fc9b5f44f42a36bb49fd65c08f2 -#: 9adc65ad9d9344efa83f3507fb6ed2fd b00fd0d15bf441f48f9ea75d8877d4fd -#: d92aa46491b442a69709b9b8d7322c2e f8499e166ca04bc2a84bfa2d42cee890 -msgid "12 GB" -msgstr "12 GB" - -#: ../../getting_started/install/deploy/deploy.md -#: 39950e71d2884d2c8ce4dbc9b0cb4491 ab3349160edf447ea67b15d7a056cc6e -msgid "vicuna-13b-v1.5" -msgstr "vicuna-13b-v1.5" - -#: ../../getting_started/install/deploy/deploy.md -#: 53bd397b40e449988d9fdfd201030387 6123ea3af97f4f3dafc6be44ecfed416 -#: f493c256788e4a318cf57fa9340948a4 -msgid "20 GB" -msgstr "20 GB" - -#: ../../getting_started/install/deploy/deploy.md -#: 11903db1ac944b60a40c92f752c1f3dc 76831b0fad014348a081f3f64260c73e -msgid "llama-2-7b" -msgstr "llama-2-7b" - -#: ../../getting_started/install/deploy/deploy.md -#: 2576bd18e1714557b33420e5ed56a95b 997fe3a3a46e4891b39171b81386a601 -msgid "llama-2-13b" -msgstr "llama-2-13b" - -#: ../../getting_started/install/deploy/deploy.md -#: 8a1cf1ae302c4c2d8bfbb1a666cc9ba6 9cbe2dae8bf44181b24d9806b654b80f -msgid "llama-2-70b" -msgstr "llama-2-70b" - -#: ../../getting_started/install/deploy/deploy.md -#: d5e875e84f534aac8f2cac4eacde7ead -msgid "48 GB" -msgstr "48 GB" - -#: ../../getting_started/install/deploy/deploy.md -#: 2e32ea59cce24ff0a96c8c152afeb09b -msgid "80 GB" -msgstr "80 GB" - -#: ../../getting_started/install/deploy/deploy.md -#: 176feab13e554986a1e09ce3c1d060ee edcf6676d3274fd3a578d337894467bf -msgid "baichuan-7b" -msgstr "baichuan-7b" - -#: ../../getting_started/install/deploy/deploy.md -#: 3da976a65887483abc029acb7e7640d4 837745bfb1ac41a99604f55e94fd4099 -msgid "baichuan-13b" -msgstr "baichuan-13b" - -#: ../../getting_started/install/deploy/deploy.md:51 -#: 3c573a548e6a4767b4acc2e4d2dbd20c -msgid "2. Install" -msgstr "2. Install" - -#: ../../getting_started/install/deploy/deploy.md:56 -#: 40d61f4ee30d4d70a45a0ffb97001cd6 -msgid "" -"We use Sqlite as default database, so there is no need for database " -"installation. If you choose to connect to other databases, you can " -"follow our tutorial for installation and configuration. For the entire " -"installation process of DB-GPT, we use the miniconda3 virtual " -"environment. Create a virtual environment and install the Python " -"dependencies. [How to install " -"Miniconda](https://docs.conda.io/en/latest/miniconda.html)" -msgstr "" -"目前使用Sqlite作为默认数据库，因此DB-" -"GPT快速部署不需要部署相关数据库服务。如果你想使用其他数据库，需要先部署相关数据库服务。我们目前使用Miniconda进行python环境和包依赖管理[安装" -" Miniconda](https://docs.conda.io/en/latest/miniconda.html)" - -#: ../../getting_started/install/deploy/deploy.md:67 -#: 69c950c69b204b94a768d1f023cc978a -msgid "" -"Once the environment is installed, we have to create a new folder " -"\"models\" in the DB-GPT project, and then we can put all the models " -"downloaded from huggingface in this directory" -msgstr "如果你已经安装好了环境需要创建models, 然后到huggingface官网下载模型" - -#: ../../getting_started/install/deploy/deploy.md:70 -#: 2ab1a4d9de8e412f80bd04ce6b40cdf6 -msgid "Notice make sure you have install git-lfs" -msgstr "注意确认你已经安装了git-lfs" - -#: ../../getting_started/install/deploy/deploy.md:72 -#: e718db01f5404485a05857b8403df93c -msgid "centos:yum install git-lfs" -msgstr "" - -#: ../../getting_started/install/deploy/deploy.md:74 -#: e98570774d28430295a094cc5f5220ae -msgid "ubuntu:apt-get install git-lfs" -msgstr "" - -#: ../../getting_started/install/deploy/deploy.md:76 -#: 34c33b64b8de4b00be92b525ad038f23 -msgid "macos:brew install git-lfs" -msgstr "" - -#: ../../getting_started/install/deploy/deploy.md:78 -#: 34bd5fbc8a8c4898a4caa7d630137061 -msgid "Download LLM Model and Embedding Model" -msgstr "下载LLM模型和Embedding模型" - -#: ../../getting_started/install/deploy/deploy.md:80 -#: a67d0e365e684a3bbb5e8618c98884ce -#, fuzzy -msgid "" -"If you use OpenAI llm service, see [How to Use LLM REST API](https://db-" -"gpt.readthedocs.io/en/latest/getting_started/install/llm/proxyllm/proxyllm.html)" -msgstr "如果想使用openai大模型服务, 可以参考[如何集成LLM REST API](https://db-gpt.readthedocs.io/projects/db-gpt-docs-zh-cn/zh-cn/latest/getting_started/install/llm/proxyllm/proxyllm.html)" - -#: ../../getting_started/install/deploy/deploy.md:83 -#: f1a43cd2eba3458c863bfc77cf13ac1f -#, fuzzy -msgid "" -"If you use openai or Axzure or tongyi llm api service, you don't need to " -"download llm model." -msgstr "如果你想通过openai or Azure or tongyi第三方api访问模型服务，你可以不用下载llm模型" - -#: ../../getting_started/install/deploy/deploy.md:103 -#: 9f46746726ec4791b6963a2e2c4376c4 -msgid "" -"The model files are large and will take a long time to download. During " -"the download, let's configure the .env file, which needs to be copied and" -" created from the .env.template" -msgstr "模型文件很大，需要很长时间才能下载。在下载过程中，让我们配置.env文件，它需要从。env.template中复制和创建。" - -#: ../../getting_started/install/deploy/deploy.md:106 -#: 53e713c8a9664d92a6e4055789c4a7da -msgid "cp .env.template .env" -msgstr "cp .env.template .env" - -#: ../../getting_started/install/deploy/deploy.md:109 -#: 21c38ebc721242478e7ad4be4d672dc6 -msgid "" -"You can configure basic parameters in the .env file, for example setting " -"LLM_MODEL to the model to be used" -msgstr "您可以在.env文件中配置基本参数，例如将LLM_MODEL设置为要使用的模型。" - -#: ../../getting_started/install/deploy/deploy.md:111 -#: 6ca180c2142b455ebcc3a8b37f3bc25a -msgid "" -"([Vicuna-v1.5](https://huggingface.co/lmsys/vicuna-13b-v1.5) based on " -"llama-2 has been released, we recommend you set `LLM_MODEL=vicuna-" -"13b-v1.5` to try this model)" -msgstr "" -"您可以在.env文件中配置基本参数，例如将LLM_MODEL设置为要使用的模型。([Vicuna-v1.5](https://huggingface.co/lmsys" -"/vicuna-13b-v1.5)， " -"目前Vicuna-v1.5模型(基于llama2)已经开源了，我们推荐你使用这个模型通过设置LLM_MODEL=vicuna-13b-v1.5" - -#: ../../getting_started/install/deploy/deploy.md:113 -#: 1a346658ec4b4074b3458fc806538aae -msgid "3. Run" -msgstr "3. Run" - -#: ../../getting_started/install/deploy/deploy.md:115 -#: 70f6300673834c9eb3e80145bb5bfcb8 -msgid "**(Optional) load examples into SQLite**" -msgstr "" - -#: ../../getting_started/install/deploy/deploy.md:120 -#: c10f16bd300e473a950617b814d743a0 -msgid "On windows platform:" -msgstr "" - -#: ../../getting_started/install/deploy/deploy.md:125 -#: 64213616228643a7b0413805061b7a12 -#, fuzzy -msgid "Run db-gpt server" -msgstr "1.Run db-gpt server" - -#: ../../getting_started/install/deploy/deploy.md:131 -#: cb3248ebbade45bfba1366a66e4220f6 -msgid "Open http://localhost:5000 with your browser to see the product." -msgstr "打开浏览器访问http://localhost:5000" - -#: ../../getting_started/install/deploy/deploy.md:134 -#: 0499acfd344b4d70a0cdce31f245971c -#, fuzzy -msgid "Multiple GPUs" -msgstr "4. Multiple GPUs" - -#: ../../getting_started/install/deploy/deploy.md:136 -#: d56b6c4aa795428aa64e3740401645d3 -msgid "" -"DB-GPT will use all available gpu by default. And you can modify the " -"setting `CUDA_VISIBLE_DEVICES=0,1` in `.env` file to use the specific gpu" -" IDs." -msgstr "DB-GPT默认加载可利用的gpu，你也可以通过修改 在`.env`文件 `CUDA_VISIBLE_DEVICES=0,1`来指定gpu IDs" - -#: ../../getting_started/install/deploy/deploy.md:138 -#: ca208283904441ab802827d94b3b9590 -msgid "" -"Optionally, you can also specify the gpu ID to use before the starting " -"command, as shown below:" -msgstr "你也可以指定gpu ID启动" - -#: ../../getting_started/install/deploy/deploy.md:148 -#: 30f7c3b3d9784a4698cdd15a0c046e81 -msgid "" -"You can modify the setting `MAX_GPU_MEMORY=xxGib` in `.env` file to " -"configure the maximum memory used by each GPU." -msgstr "同时你可以通过在.env文件设置`MAX_GPU_MEMORY=xxGib`修改每个GPU的最大使用内存" - -#: ../../getting_started/install/deploy/deploy.md:150 -#: ab02884bb7f24e59b21b797501c3794b -#, fuzzy -msgid "Not Enough Memory" -msgstr "5. Not Enough Memory" - -#: ../../getting_started/install/deploy/deploy.md:152 -#: 5b246b0456f8448bb0207312a17d40c5 -msgid "DB-GPT supported 8-bit quantization and 4-bit quantization." -msgstr "DB-GPT 支持 8-bit quantization 和 4-bit quantization." - -#: ../../getting_started/install/deploy/deploy.md:154 -#: a002dc2572d34b0f9b3ca6ac3b3b6147 -msgid "" -"You can modify the setting `QUANTIZE_8bit=True` or `QUANTIZE_4bit=True` " -"in `.env` file to use quantization(8-bit quantization is enabled by " -"default)." -msgstr "你可以通过在.env文件设置`QUANTIZE_8bit=True` or `QUANTIZE_4bit=True`" - -#: ../../getting_started/install/deploy/deploy.md:156 -#: 16d429bd42a44b02875e505273d35228 -msgid "" -"Llama-2-70b with 8-bit quantization can run with 80 GB of VRAM, and 4-bit" -" quantization can run with 48 GB of VRAM." -msgstr "" -"Llama-2-70b with 8-bit quantization 可以运行在80GB VRAM机器， 4-bit " -"quantization可以运行在 48 GB VRAM" - -#~ msgid "" -#~ "Notice make sure you have install " -#~ "git-lfs centos:yum install git-lfs " -#~ "ubuntu:app-get install git-lfs " -#~ "macos:brew install git-lfs" -#~ msgstr "" -#~ "注意下载模型之前确保git-lfs已经安ubuntu:app-get install " -#~ "git-lfs macos:brew install git-lfs" - -#~ msgid "" -#~ "You can refer to this document to" -#~ " obtain the Vicuna weights: " -#~ "[Vicuna](https://github.com/lm-sys/FastChat/blob/main/README.md" -#~ "#model-weights) ." -#~ msgstr "" -#~ "你可以参考如何获取Vicuna weights文档[Vicuna](https://github.com/lm-" -#~ "sys/FastChat/blob/main/README.md#model-weights) ." - -#~ msgid "" -#~ "If you have difficulty with this " -#~ "step, you can also directly use " -#~ "the model from [this " -#~ "link](https://huggingface.co/Tribbiani/vicuna-7b) as " -#~ "a replacement." -#~ msgstr "" -#~ "如果觉得模型太大你也可以下载vicuna-7b [this " -#~ "link](https://huggingface.co/Tribbiani/vicuna-7b) " - -#~ msgid "" -#~ "If you want to access an external" -#~ " LLM service, you need to 1.set " -#~ "the variables LLM_MODEL=YOUR_MODEL_NAME " -#~ "MODEL_SERVER=YOUR_MODEL_SERVER（eg:http://localhost:5000） in " -#~ "the .env file. 2.execute dbgpt_server.py " -#~ "in light mode" -#~ msgstr "" -#~ "如果你想访问外部的大模型服务(是通过DB-" -#~ "GPT/pilot/server/llmserver.py启动的模型服务)，1.需要在.env文件设置模型名和外部模型服务地址。2.使用light模式启动服务" - -#~ msgid "" -#~ "Note: you need to install the " -#~ "latest dependencies according to " -#~ "[requirements.txt](https://github.com/eosphoros-ai/DB-" -#~ "GPT/blob/main/requirements.txt)." -#~ msgstr "" -#~ "注意，需要安装[requirements.txt](https://github.com/eosphoros-ai/DB-" -#~ "GPT/blob/main/requirements.txt)涉及的所有的依赖" - -#~ msgid "ubuntu:app-get install git-lfs" -#~ msgstr "" - -#~ msgid "Before use DB-GPT Knowledge" -#~ msgstr "在使用知识库之前" - -#~ msgid "**(Optional) load examples into SQLlite**" -#~ msgstr "" - -#~ msgid "If you want to access an external LLM service, you need to" -#~ msgstr "" - -#~ msgid "" -#~ "1.set the variables LLM_MODEL=YOUR_MODEL_NAME, " -#~ "MODEL_SERVER=YOUR_MODEL_SERVER（eg:http://localhost:5000） in " -#~ "the .env file." -#~ msgstr "" - -#~ msgid "2.execute dbgpt_server.py in light mode" -#~ msgstr "" - -#~ msgid "" -#~ "If you want to learn about " -#~ "dbgpt-webui, read https://github./csunny/DB-" -#~ "GPT/tree/new-page-framework/datacenter" -#~ msgstr "" -#~ "如果你想了解web-ui, 请访问https://github./csunny/DB-GPT/tree" -#~ "/new-page-framework/datacenter" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/docker/docker.po b/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/docker/docker.po deleted file mode 100644 index 219f0fd86..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/docker/docker.po +++ /dev/null @@ -1,156 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.3.5\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-08-29 20:50+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../getting_started/install/docker/docker.md:1 -#: b1f8f6a0b8974ea09a5fe2812f31d941 -msgid "Docker Install" -msgstr "Docker 安装" - -#: ../../getting_started/install/docker/docker.md:4 -#: d9145d02ed984d45b33eb46117a2484b -msgid "Docker (Experimental)" -msgstr "Docker (Experimental)" - -#: ../../getting_started/install/docker/docker.md:6 -#: 7d2a5e4016f543748b80dedcee36f3c6 -#, fuzzy -msgid "1. Preparing docker images" -msgstr "1.构建Docker镜像" - -#: ../../getting_started/install/docker/docker.md:8 -#: 1cb08cc1662f45579b82f0d402c39cc3 -msgid "" -"**Pull docker image from the [Eosphoros AI Docker " -"Hub](https://hub.docker.com/u/eosphorosai)**" -msgstr "" - -#: ../../getting_started/install/docker/docker.md:14 -#: 23781bc56d394d07927186c6cf619a91 -#, fuzzy -msgid "**(Optional) Building Docker image**" -msgstr "1.构建Docker镜像" - -#: ../../getting_started/install/docker/docker.md:20 -#: 77a31390bd024d5f87f8d8ec386a23ae -msgid "Review images by listing them:" -msgstr "Review images by listing them:" - -#: ../../getting_started/install/docker/docker.md:26 -#: e5f6c40d68f346e1bbb57a5f7ac2f10b -msgid "Output should look something like the following:" -msgstr "输出日志应该长这样:" - -#: ../../getting_started/install/docker/docker.md:33 -#: b26892bf338c484ba8ed34f09c0fda23 -msgid "" -"`eosphorosai/dbgpt` is the base image, which contains the project's base " -"dependencies and a sqlite database. `eosphorosai/dbgpt-allinone` build " -"from `eosphorosai/dbgpt`, which contains a mysql database." -msgstr "" - -#: ../../getting_started/install/docker/docker.md:35 -#: 7aabb767dcd8439ea7ca14fd8deccb87 -msgid "You can pass some parameters to docker/build_all_images.sh." -msgstr "你也可以docker/build_all_images.sh构建的时候指定参数" - -#: ../../getting_started/install/docker/docker.md:43 -#: 36a85e7aca484e5cb0656dea8dc3568c -msgid "" -"You can execute the command `bash docker/build_all_images.sh --help` to " -"see more usage." -msgstr "可以指定命令`bash docker/build_all_images.sh --help`查看如何使用" - -#: ../../getting_started/install/docker/docker.md:45 -#: c0d04891ed784cd8a8403ea395c56a45 -#, fuzzy -msgid "2. Run docker container" -msgstr "2. Run all in one docker container" - -#: ../../getting_started/install/docker/docker.md:47 -#: 7d5cb8366aa849b684fe5c3805213d0d -#, fuzzy -msgid "**Run with local model and SQLite database**" -msgstr "**Run with local model**" - -#: ../../getting_started/install/docker/docker.md:61 -#: ../../getting_started/install/docker/docker.md:88 -#: ../../getting_started/install/docker/docker.md:123 -#: 2ef66d0c87cf4ab48f9bbf4473071b43 9b594d33ef9f472d9fccfe1bd07d5564 -#: f86c8364bd9948b29224c6ef0e1d6a83 -msgid "Open http://localhost:5000 with your browser to see the product." -msgstr "打开浏览器访问http://localhost:5000" - -#: ../../getting_started/install/docker/docker.md:64 -#: ../../getting_started/install/docker/docker.md:91 -#: a462082e866f46a8b99a4d95e6fa5b83 d262fdeb9f9c4156898875db75997874 -#, fuzzy -msgid "" -"`-e LLM_MODEL=vicuna-13b-v1.5`, means we use vicuna-13b-v1.5 as llm " -"model, see /pilot/configs/model_config.LLM_MODEL_CONFIG" -msgstr "`-e LLM_MODEL=vicuna-13b` 指定llm model is vicuna-13b " - -#: ../../getting_started/install/docker/docker.md:65 -#: ../../getting_started/install/docker/docker.md:92 -#: c8c172873ff145aeb4f0f9cb04c209a8 f1b2e1f27cd24ed9ae233445f3fe1301 -msgid "" -"`-v /data/models:/app/models`, means we mount the local model file " -"directory `/data/models` to the docker container directory `/app/models`," -" please replace it with your model file directory." -msgstr "" -"`-v /data/models:/app/models`, 指定挂载的模型文件 directory `/data/models` to the " -"docker container directory `/app/models`, 你也可以替换成你自己的模型." - -#: ../../getting_started/install/docker/docker.md:67 -#: ../../getting_started/install/docker/docker.md:94 -#: 432463d5993a4e6eb34497390d89e891 da8df3262b834b359c080e84b25e431e -msgid "You can see log with command:" -msgstr "你也可以通过命令查看日志" - -#: ../../getting_started/install/docker/docker.md:73 -#: a4963b927a87455c90a4fbb1d3814a09 -#, fuzzy -msgid "**Run with local model and MySQL database**" -msgstr "**Run with local model**" - -#: ../../getting_started/install/docker/docker.md:100 -#: 81ecd658f7c54070bcb47838d3a9f533 -msgid "**Run with openai interface**" -msgstr "**Run with openai interface**" - -#: ../../getting_started/install/docker/docker.md:119 -#: 2c01b849a0fe4b4d9554a9adf9cbf8fc -msgid "" -"`-e LLM_MODEL=proxyllm`, means we use proxy llm(openai interface, " -"fastchat interface...)" -msgstr "" -"`-e LLM_MODEL=proxyllm`, 通过设置模型为第三方模型服务API， 可以是openai, 也可以是fastchat " -"interface..." - -#: ../../getting_started/install/docker/docker.md:120 -#: 262af25e0ec748e3a8b12274004624bb -msgid "" -"`-v /data/models/text2vec-large-chinese:/app/models/text2vec-large-" -"chinese`, means we mount the local text2vec model to the docker " -"container." -msgstr "" -"`-v /data/models/text2vec-large-chinese:/app/models/text2vec-large-" -"chinese`, 设置知识库embedding模型为text2vec. container.\"" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/docker_compose/docker_compose.po b/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/docker_compose/docker_compose.po deleted file mode 100644 index e0e17c38d..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/docker_compose/docker_compose.po +++ /dev/null @@ -1,53 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.3.5\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-08-16 18:31+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../getting_started/install/docker_compose/docker_compose.md:1 -#: f1092bd1601c48789cb6f35ff9141c69 -msgid "Docker Compose" -msgstr "Docker Compose" - -#: ../../getting_started/install/docker_compose/docker_compose.md:4 -#: 63460a1c4e0f46378c6a48643684fa17 -msgid "Run with docker compose" -msgstr "Run with docker compose" - -#: ../../getting_started/install/docker_compose/docker_compose.md:10 -#: fa53c93a8c8b451788987461e6b296b6 -msgid "Output should look something like the following:" -msgstr "输出应该这样:" - -#: ../../getting_started/install/docker_compose/docker_compose.md:18 -#: 6c56a6ef5367442ab924f9a49d955d11 -msgid "You can see log with command:" -msgstr "你可以通过命令查看日志" - -#: ../../getting_started/install/docker_compose/docker_compose.md:24 -#: 1bd9fac3803641fa9ec1730c7d15d3f1 -msgid "Open http://localhost:5000 with your browser to see the product." -msgstr "打开浏览器访问Open http://localhost:5000" - -#: ../../getting_started/install/docker_compose/docker_compose.md:26 -#: 21214a8bf62746078ccf7ab83ccca4f7 -msgid "" -"You can open docker-compose.yml in the project root directory to see more" -" details." -msgstr "可以打开docker-compose.yml查看更多内容" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/environment/environment.po b/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/environment/environment.po deleted file mode 100644 index bd4d6fa0b..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/environment/environment.po +++ /dev/null @@ -1,358 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.3.5\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-11-14 16:08+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../getting_started/install/environment/environment.md:1 -#: e4787ab6eacc4362802752528bb786ec -#, fuzzy -msgid "Environment Parameter" -msgstr "环境变量说明" - -#: ../../getting_started/install/environment/environment.md:4 -#: 4682a0734a034e0e9f2c22fa061b889e -msgid "LLM MODEL Config" -msgstr "模型配置" - -#: ../../getting_started/install/environment/environment.md:5 -#: c148f178b2964344a570bb2b3713fba3 -msgid "LLM Model Name, see /pilot/configs/model_config.LLM_MODEL_CONFIG" -msgstr "LLM Model Name, see /pilot/configs/model_config.LLM_MODEL_CONFIG" - -#: ../../getting_started/install/environment/environment.md:6 -#: 9ab8d82fb338439a8c0042b92ad2f7c4 -msgid "LLM_MODEL=vicuna-13b" -msgstr "LLM_MODEL=vicuna-13b" - -#: ../../getting_started/install/environment/environment.md:8 -#: 76fb3b1299694730852f120db6fec7f9 -msgid "MODEL_SERVER_ADDRESS" -msgstr "MODEL_SERVER_ADDRESS" - -#: ../../getting_started/install/environment/environment.md:10 -#: 7476a0ee342f4517bbf999abecec029e -#, fuzzy -msgid "MODEL_SERVER=http://127.0.0.1:8000" -msgstr "MODEL_SERVER=http://127.0.0.1:8000 LIMIT_MODEL_CONCURRENCY" - -#: ../../getting_started/install/environment/environment.md:12 -#: fb3c73990a6443e8b63c35d61175e467 -#, fuzzy -msgid "LIMIT_MODEL_CONCURRENCY" -msgstr "LIMIT_MODEL_CONCURRENCY=5" - -#: ../../getting_started/install/environment/environment.md:14 -#: 0eb187fffa3643dbac4bbe7237d2e011 -msgid "LIMIT_MODEL_CONCURRENCY=5" -msgstr "LIMIT_MODEL_CONCURRENCY=5" - -#: ../../getting_started/install/environment/environment.md:16 -#: 1d7b8bf89c1b44e9871d9d0c382db114 -msgid "MAX_POSITION_EMBEDDINGS" -msgstr "MAX_POSITION_EMBEDDINGS" - -#: ../../getting_started/install/environment/environment.md:18 -#: 50d0b3f760fd4ff9829cd1ba0653fd79 -msgid "MAX_POSITION_EMBEDDINGS=4096" -msgstr "MAX_POSITION_EMBEDDINGS=4096" - -#: ../../getting_started/install/environment/environment.md:20 -#: d07c4bbcde214f5993d73ac2bfb1bf9e -msgid "QUANTIZE_QLORA" -msgstr "QUANTIZE_QLORA" - -#: ../../getting_started/install/environment/environment.md:22 -#: 6bceef51780f45d9805270d16847ddc2 -msgid "QUANTIZE_QLORA=True" -msgstr "QUANTIZE_QLORA=True" - -#: ../../getting_started/install/environment/environment.md:24 -#: df9d560f69334e4aa3f6803e40a7f38d -msgid "QUANTIZE_8bit" -msgstr "QUANTIZE_8bit" - -#: ../../getting_started/install/environment/environment.md:26 -#: ac433b8574574432add7315558b845ea -msgid "QUANTIZE_8bit=True" -msgstr "QUANTIZE_8bit=True" - -#: ../../getting_started/install/environment/environment.md:29 -#: 7b1c407517984bff9f4d509c5f45b92e -msgid "LLM PROXY Settings" -msgstr "LLM PROXY Settings" - -#: ../../getting_started/install/environment/environment.md:30 -#: ba7d52c0e95143ebb973e7eda69f0bc1 -msgid "OPENAI Key" -msgstr "OPENAI Key" - -#: ../../getting_started/install/environment/environment.md:32 -#: 0f0bd20a7a60461e8bcfc91297cc3666 -msgid "PROXY_API_KEY={your-openai-sk}" -msgstr "PROXY_API_KEY={your-openai-sk}" - -#: ../../getting_started/install/environment/environment.md:33 -#: d9c03e0b3316415eb2ca59ad9c419b8c -msgid "PROXY_SERVER_URL=https://api.openai.com/v1/chat/completions" -msgstr "PROXY_SERVER_URL=https://api.openai.com/v1/chat/completions" - -#: ../../getting_started/install/environment/environment.md:35 -#: 45883f99c1fd494ea513f3c0f92562a3 -msgid "from https://bard.google.com/ f12-> application-> __Secure-1PSID" -msgstr "from https://bard.google.com/ f12-> application-> __Secure-1PSID" - -#: ../../getting_started/install/environment/environment.md:37 -#: 70665dbe72c545a3b61c6efe37dfa7d5 -msgid "BARD_PROXY_API_KEY={your-bard-token}" -msgstr "BARD_PROXY_API_KEY={your-bard-token}" - -#: ../../getting_started/install/environment/environment.md:40 -#: 782f8a9c9cd745a4990542ba8130c66a -msgid "DATABASE SETTINGS" -msgstr "DATABASE SETTINGS" - -#: ../../getting_started/install/environment/environment.md:41 -#: 50ad9eae827a407c8c77692f48b9d423 -msgid "SQLite database (Current default database)" -msgstr "SQLite database (Current default database)" - -#: ../../getting_started/install/environment/environment.md:42 -#: 410041683b664cabbe7ce6cb2050c629 -msgid "LOCAL_DB_PATH=data/default_sqlite.db" -msgstr "LOCAL_DB_PATH=data/default_sqlite.db" - -#: ../../getting_started/install/environment/environment.md:43 -#: 0fcf0f9da84d4e4a8a1503a96dd6734b -msgid "LOCAL_DB_TYPE=sqlite # Database Type default:sqlite" -msgstr "LOCAL_DB_TYPE=sqlite # Database Type default:sqlite" - -#: ../../getting_started/install/environment/environment.md:45 -#: 15fb9cdc51e44b71a1a375e49fb7bc6d -msgid "MYSQL database" -msgstr "MYSQL database" - -#: ../../getting_started/install/environment/environment.md:46 -#: c8cc4cb61d1c44cd9ef3546455929ef6 -msgid "LOCAL_DB_TYPE=mysql" -msgstr "LOCAL_DB_TYPE=mysql" - -#: ../../getting_started/install/environment/environment.md:47 -#: a6caf3cabc4041b5879ec3af25c85139 -msgid "LOCAL_DB_USER=root" -msgstr "LOCAL_DB_USER=root" - -#: ../../getting_started/install/environment/environment.md:48 -#: b839bde122374e299086f120fce0144c -msgid "LOCAL_DB_PASSWORD=aa12345678" -msgstr "LOCAL_DB_PASSWORD=aa12345678" - -#: ../../getting_started/install/environment/environment.md:49 -#: 52cdbfdefda142b4a3b5cb3b060916a8 -msgid "LOCAL_DB_HOST=127.0.0.1" -msgstr "LOCAL_DB_HOST=127.0.0.1" - -#: ../../getting_started/install/environment/environment.md:50 -#: 492db6e5c13b40898f38063980c5897c -msgid "LOCAL_DB_PORT=3306" -msgstr "LOCAL_DB_PORT=3306" - -#: ../../getting_started/install/environment/environment.md:53 -#: 20b101603f054c70af633439abddefec -msgid "EMBEDDING SETTINGS" -msgstr "EMBEDDING SETTINGS" - -#: ../../getting_started/install/environment/environment.md:54 -#: 3463a5a74cea494c8442100c0069285c -msgid "EMBEDDING MODEL Name, see /pilot/configs/model_config.LLM_MODEL_CONFIG" -msgstr "EMBEDDING模型, 参考see /pilot/configs/model_config.LLM_MODEL_CONFIG" - -#: ../../getting_started/install/environment/environment.md:55 -#: 4c8adbf52110474bbfcd3b63cf2839f6 -msgid "EMBEDDING_MODEL=text2vec" -msgstr "EMBEDDING_MODEL=text2vec" - -#: ../../getting_started/install/environment/environment.md:57 -#: 8a85a75151e64827971b1a367b31ecfa -msgid "Embedding Chunk size, default 500" -msgstr "Embedding 切片大小, 默认500" - -#: ../../getting_started/install/environment/environment.md:59 -#: 947939b0fa7e46de97d48eadf5c443d2 -msgid "KNOWLEDGE_CHUNK_SIZE=500" -msgstr "KNOWLEDGE_CHUNK_SIZE=500" - -#: ../../getting_started/install/environment/environment.md:61 -#: 2785ad6bb0de4534a6523ac420f2c84c -msgid "Embedding Chunk Overlap, default 100" -msgstr "Embedding chunk Overlap, 文本块之间的最大重叠量。保留一些重叠可以保持文本块之间的连续性（例如使用滑动窗口）,默认100" - -#: ../../getting_started/install/environment/environment.md:62 -#: 40b6a8f57ee14ec1ab73143ba1516e78 -msgid "KNOWLEDGE_CHUNK_OVERLAP=100" -msgstr "KNOWLEDGE_CHUNK_OVERLAP=100" - -#: ../../getting_started/install/environment/environment.md:64 -#: e410faa1087c45639ee210be99cf9336 -#, fuzzy -msgid "embedding recall top k,5" -msgstr "embedding 召回topk, 默认5" - -#: ../../getting_started/install/environment/environment.md:66 -#: abfca38fe2a04161a11259588fa4d205 -msgid "KNOWLEDGE_SEARCH_TOP_SIZE=5" -msgstr "KNOWLEDGE_SEARCH_TOP_SIZE=5" - -#: ../../getting_started/install/environment/environment.md:68 -#: 31182c38607b4c3bbc657b5fe5b7a4f6 -#, fuzzy -msgid "embedding recall max token ,2000" -msgstr "embedding向量召回最大token, 默认2000" - -#: ../../getting_started/install/environment/environment.md:70 -#: 96cd042635bc468e90c792fd9d1a7f4d -msgid "KNOWLEDGE_SEARCH_MAX_TOKEN=5" -msgstr "KNOWLEDGE_SEARCH_MAX_TOKEN=5" - -#: ../../getting_started/install/environment/environment.md:73 -#: d43b408ad9bc46f2b3c97aa91627f6b3 -msgid "Vector Store SETTINGS" -msgstr "Vector Store SETTINGS" - -#: ../../getting_started/install/environment/environment.md:74 -#: b1fcbf6049af4eeea91edd3de58c8512 -msgid "Chroma" -msgstr "Chroma" - -#: ../../getting_started/install/environment/environment.md:75 -#: 2fb31575b274448fb945d47ee0eb108c -msgid "VECTOR_STORE_TYPE=Chroma" -msgstr "VECTOR_STORE_TYPE=Chroma" - -#: ../../getting_started/install/environment/environment.md:76 -#: 601b87cc6f1d4732b935747e907cba5a -msgid "MILVUS" -msgstr "MILVUS" - -#: ../../getting_started/install/environment/environment.md:77 -#: fde6cf6982764020aa1174f7fe3a5b3e -msgid "VECTOR_STORE_TYPE=Milvus" -msgstr "VECTOR_STORE_TYPE=Milvus" - -#: ../../getting_started/install/environment/environment.md:78 -#: 40c6206c7a614edf9b0af82c2c76f518 -msgid "MILVUS_URL=127.0.0.1" -msgstr "MILVUS_URL=127.0.0.1" - -#: ../../getting_started/install/environment/environment.md:79 -#: abde3c75269442cbb94a59c657d847a9 -msgid "MILVUS_PORT=19530" -msgstr "MILVUS_PORT=19530" - -#: ../../getting_started/install/environment/environment.md:80 -#: 375a837cbf6d4d65891612a7f073414a -msgid "MILVUS_USERNAME" -msgstr "MILVUS_USERNAME" - -#: ../../getting_started/install/environment/environment.md:81 -#: f785a796c8d3452c802d9a637f34cb57 -msgid "MILVUS_PASSWORD" -msgstr "MILVUS_PASSWORD" - -#: ../../getting_started/install/environment/environment.md:82 -#: 18cd17a50dc14add9b31f6b4c55069ef -msgid "MILVUS_SECURE=" -msgstr "MILVUS_SECURE=" - -#: ../../getting_started/install/environment/environment.md:84 -#: a4783d775bf2444788b758a71bd5a7e7 -msgid "WEAVIATE" -msgstr "WEAVIATE" - -#: ../../getting_started/install/environment/environment.md:85 -#: 3cc5ca99670947e6868e27db588031e0 -msgid "VECTOR_STORE_TYPE=Weaviate" -msgstr "VECTOR_STORE_TYPE=Weaviate" - -#: ../../getting_started/install/environment/environment.md:86 -#: 141a3da2e36e40ffaa0fb863081a4c07 -msgid "WEAVIATE_URL=https://kt-region-m8hcy0wc.weaviate.network" -msgstr "WEAVIATE_URL=https://kt-region-m8hcy0wc.weaviate.network" - -#: ../../getting_started/install/environment/environment.md:89 -#: fde1941617ec4148b33c298bebeb45e4 -msgid "Multi-GPU Setting" -msgstr "Multi-GPU Setting" - -#: ../../getting_started/install/environment/environment.md:90 -#: fe162354e15e42cda54f6c9322409321 -msgid "" -"See https://developer.nvidia.com/blog/cuda-pro-tip-control-gpu-" -"visibility-cuda_visible_devices/ If CUDA_VISIBLE_DEVICES is not " -"configured, all available gpus will be used" -msgstr "" -"参考 https://developer.nvidia.com/blog/cuda-pro-tip-control-gpu-visibility-" -"cuda_visible_devices/ 如果 CUDA_VISIBLE_DEVICES没有设置, 会使用所有可用的gpu" - -#: ../../getting_started/install/environment/environment.md:93 -#: c8a83b09bfc94dab8226840b275ca034 -msgid "CUDA_VISIBLE_DEVICES=0" -msgstr "CUDA_VISIBLE_DEVICES=0" - -#: ../../getting_started/install/environment/environment.md:95 -#: a1d33bd2492a4a80bd8b679c1331280a -msgid "" -"Optionally, you can also specify the gpu ID to use before the starting " -"command" -msgstr "你也可以通过启动命令设置gpu ID" - -#: ../../getting_started/install/environment/environment.md:97 -#: 961087a5cf1b45168c7439e3a2103253 -msgid "CUDA_VISIBLE_DEVICES=3,4,5,6" -msgstr "CUDA_VISIBLE_DEVICES=3,4,5,6" - -#: ../../getting_started/install/environment/environment.md:99 -#: 545b438ecb9d46edacbd8b4cc95886f9 -msgid "You can configure the maximum memory used by each GPU." -msgstr "可以设置GPU的最大内存" - -#: ../../getting_started/install/environment/environment.md:101 -#: a78dc8082fa04e13a7a3e43302830c26 -msgid "MAX_GPU_MEMORY=16Gib" -msgstr "MAX_GPU_MEMORY=16Gib" - -#: ../../getting_started/install/environment/environment.md:104 -#: eaebcb1784be4047b739ff1b8a78faa1 -msgid "Other Setting" -msgstr "Other Setting" - -#: ../../getting_started/install/environment/environment.md:105 -#: 21f524662fa34bfa9cfb8855bc191cc7 -msgid "Language Settings(influence prompt language)" -msgstr "Language Settings(涉及prompt语言以及知识切片方式)" - -#: ../../getting_started/install/environment/environment.md:106 -#: bb5ce4a6ee794f0e910363673e54055a -msgid "LANGUAGE=en" -msgstr "LANGUAGE=en" - -#: ../../getting_started/install/environment/environment.md:107 -#: 862f113d63b94084b89bfef29f8ab48d -msgid "LANGUAGE=zh" -msgstr "LANGUAGE=zh" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/llm/cluster/model_cluster.po b/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/llm/cluster/model_cluster.po deleted file mode 100644 index 8f71a3391..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/llm/cluster/model_cluster.po +++ /dev/null @@ -1,172 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.3.6\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-08-31 16:43+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../getting_started/install/llm/cluster/model_cluster.md:1 -#: b0614062af2a4c039aa8947e45c4382a -msgid "Cluster deployment" -msgstr "集群部署" - -#: ../../getting_started/install/llm/cluster/model_cluster.md:4 -#: 568a2af68de5410ebd63f34b8a3665c5 -msgid "Model cluster deployment" -msgstr "模型的集群部署" - -#: ../../getting_started/install/llm/cluster/model_cluster.md:7 -#: 41b9c4bf32bd4c95a1a7b733543a322b -msgid "**Installing Command-Line Tool**" -msgstr "**命令行工具的安装**" - -#: ../../getting_started/install/llm/cluster/model_cluster.md:9 -#: b340cf9309a742648fb05910dc6ba741 -msgid "" -"All operations below are performed using the `dbgpt` command. To use the " -"`dbgpt` command, you need to install the DB-GPT project with `pip install" -" -e .`. Alternatively, you can use `python pilot/scripts/cli_scripts.py` " -"as a substitute for the `dbgpt` command." -msgstr "下面的操作都是使用 `dbgpt` 命令来进行，为了使用 `dbgpt` 命令，你需要使用 `pip install -e .` 来安装 DB-GPT 项目，当然，你也可以使用 `python pilot/scripts/cli_scripts.py` 来替代命令 `dbgpt`。" - -#: ../../getting_started/install/llm/cluster/model_cluster.md:11 -#: 9299e223f8ec4060aaf40ddba019bfbf -msgid "Launch Model Controller" -msgstr "启动 Model Controller" - -#: ../../getting_started/install/llm/cluster/model_cluster.md:17 -#: f858b280e1e54feba6639c7270b512c3 -msgid "By default, the Model Controller starts on port 8000." -msgstr "默认情况下 Model Controller 启动端口是 8000。" - -#: ../../getting_started/install/llm/cluster/model_cluster.md:20 -#: 51eecd5331ce441abd9658f873132935 -msgid "Launch Model Worker" -msgstr "启动 Model Worker" - -#: ../../getting_started/install/llm/cluster/model_cluster.md:22 -#: 09b1b7ffe3b740de94163f2ef24e8743 -msgid "If you are starting `chatglm2-6b`:" -msgstr "如果你启动的是 `chatglm2-6b`" - -#: ../../getting_started/install/llm/cluster/model_cluster.md:31 -#: 47f9ec2b957e4a2a858a8833ce2cd104 -msgid "If you are starting `vicuna-13b-v1.5`:" -msgstr "如果你启动的是 `vicuna-13b-v1.5`" - -#: ../../getting_started/install/llm/cluster/model_cluster.md:40 -#: 95a04817be5a473e8b4f7086ac8dfe2c -msgid "Note: Be sure to use your own model name and model path." -msgstr "注意：注意使用你自己的模型名称和模型路径。" - -#: ../../getting_started/install/llm/cluster/model_cluster.md:43 -#: 644fff6c28ca49efa06e0f2c89f45e27 -msgid "Check your model:" -msgstr "查看你的模型：" - -#: ../../getting_started/install/llm/cluster/model_cluster.md:49 -#: 69df9c27c17e44b8a6cb010360c56338 -msgid "You will see the following output:" -msgstr "你将会看到下面的输出：" - -#: ../../getting_started/install/llm/cluster/model_cluster.md:59 -#: a1e1489068d04b51bb239bd32ef3546b -msgid "Connect to the model service in the webserver (dbgpt_server)" -msgstr "在 webserver(dbgpt_server) 中连接模型服务" - -#: ../../getting_started/install/llm/cluster/model_cluster.md:61 -#: 0ab444ac06f34ce0994fe1f945abecde -msgid "" -"**First, modify the `.env` file to change the model name and the Model " -"Controller connection address.**" -msgstr "**先修改 `.env` 文件，修改模型名称和 Model Controller 连接地址。**" - -#: ../../getting_started/install/llm/cluster/model_cluster.md:69 -#: 5125b43d70d744a491a70aa1001303be -msgid "Start the webserver" -msgstr "" - -#: ../../getting_started/install/llm/cluster/model_cluster.md:75 -#: f12f463c27c74337ba8cc9c7e4e934b4 -msgid "`--light` indicates not to start the embedded model service." -msgstr "`--light` 表示不启动内嵌的模型服务。" - -#: ../../getting_started/install/llm/cluster/model_cluster.md:77 -#: de2f7b040fd04c73a89ae453db84108f -msgid "" -"Alternatively, you can prepend the command with `LLM_MODEL=chatglm2-6b` " -"to start:" -msgstr "更简单的，你可以在命令行前添加 `LLM_MODEL=chatglm2-6b` 来启动：" - -#: ../../getting_started/install/llm/cluster/model_cluster.md:84 -#: 83b93195a9fb45aeaeead6b05719f164 -msgid "More Command-Line Usages" -msgstr "命令行的更多用法" - -#: ../../getting_started/install/llm/cluster/model_cluster.md:86 -#: 8622edf06c1d443188e19a26ed306d58 -msgid "You can view more command-line usages through the help command." -msgstr "你可以通过帮助命令来查看更多的命令行用法。" - -#: ../../getting_started/install/llm/cluster/model_cluster.md:88 -#: 391c6fa585d045f5a583e26478adda7e -msgid "**View the `dbgpt` help**" -msgstr "**查看 `dbgpt` 的帮助**" - -#: ../../getting_started/install/llm/cluster/model_cluster.md:93 -#: 4247e8ee8f084fa780fb523530cc64ab -msgid "You will see the basic command parameters and usage:" -msgstr "你将会看到基础的命令参数和用法：" - -#: ../../getting_started/install/llm/cluster/model_cluster.md:109 -#: 87b43469e93e4b62a59488d1ef663b51 -msgid "**View the `dbgpt start` help**" -msgstr "**查看 `dbgpt start` 的帮助**" - -#: ../../getting_started/install/llm/cluster/model_cluster.md:115 -#: 213f7bfc459d4439b3a839292e2684e6 -msgid "Here you can see the related commands and usage for start:" -msgstr "这里你能看到 start 相关的命令和用法。" - -#: ../../getting_started/install/llm/cluster/model_cluster.md:132 -#: eb616a87e01d4cdc87dc61e462d83729 -msgid "**View the `dbgpt start worker`help**" -msgstr "**查看 `dbgpt start worker`的帮助**" - -#: ../../getting_started/install/llm/cluster/model_cluster.md:138 -#: 75918aa07d7c4ec39271358f2b474a63 -msgid "Here you can see the parameters to start Model Worker:" -msgstr "这里你能看启动 Model Worker 的参数：" - -#: ../../getting_started/install/llm/cluster/model_cluster.md:196 -#: 5ee6ea98af4d4693b8cbf059ad3001d8 -msgid "**View the `dbgpt model`help**" -msgstr "**查看 `dbgpt model`的帮助**" - -#: ../../getting_started/install/llm/cluster/model_cluster.md:202 -#: a96a1b58987a481fac2d527470226b90 -msgid "" -"The `dbgpt model ` command can connect to the Model Controller via the " -"Model Controller address and then manage a remote model:" -msgstr "`dbgpt model ` 命令可以通过 Model Controller 地址连接到 Model Controller，然后对远程对某个模型进行管理。" - -#~ msgid "" -#~ "First, modify the `.env` file to " -#~ "change the model name and the " -#~ "Model Controller connection address." -#~ msgstr "" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/llm/llama/llama_cpp.po b/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/llm/llama/llama_cpp.po deleted file mode 100644 index cd7d4689b..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/llm/llama/llama_cpp.po +++ /dev/null @@ -1,343 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.3.5\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-10-07 20:28+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../getting_started/install/llm/llama/llama_cpp.md:1 -#: 95a9a605d97346fb98e0c0977524d354 -msgid "llama.cpp" -msgstr "llama.cpp" - -#: ../../getting_started/install/llm/llama/llama_cpp.md:5 -#: ebe3be273a42492d9832512554b4b7dc -msgid "" -"DB-GPT already supports " -"[llama.cpp](https://github.com/ggerganov/llama.cpp) via [llama-cpp-" -"python](https://github.com/abetlen/llama-cpp-python)." -msgstr "" -"DB-GPT已经通过[llama-cpp-python](https://github.com/abetlen/llama-cpp-" -"python)支持[llama.cpp](https://github.com/ggerganov/llama.cpp)。" - -#: ../../getting_started/install/llm/llama/llama_cpp.md:7 -#: 97a4f6f95d6845258e3753803fc117a3 -msgid "Running llama.cpp" -msgstr "运行 llama.cpp" - -#: ../../getting_started/install/llm/llama/llama_cpp.md:9 -#: 40fcdf93fe3d4542bbd84ed2d5a82623 -msgid "Preparing Model Files" -msgstr "准备模型文件" - -#: ../../getting_started/install/llm/llama/llama_cpp.md:11 -#: f10bd034d24640d3b83572d50b2a9f71 -msgid "" -"To use llama.cpp, you need to prepare a gguf format model file, and there" -" are two common ways to obtain it, you can choose either:" -msgstr "使用 llama.cpp，你需要准备 gguf 格式的文件，你可以通过以下两种方法获取" - -#: ../../getting_started/install/llm/llama/llama_cpp.md:13 -#: fb143586b13849f0bb2b6ae0c9408e95 -msgid "Download a pre-converted model file." -msgstr "下载已转换的模型文件" - -#: ../../getting_started/install/llm/llama/llama_cpp.md:15 -#: a6e89c960ebd4778b8fc72d3d43e9543 -msgid "" -"Suppose you want to use [Vicuna 13B v1.5](https://huggingface.co/lmsys" -"/vicuna-13b-v1.5), you can download the file already converted from " -"[TheBloke/vicuna-13B-v1.5-GGUF](https://huggingface.co/TheBloke/vicuna-" -"13B-v1.5-GGUF), only one file is needed. Download it to the `models` " -"directory and rename it to `ggml-model-q4_0.gguf`." -msgstr "" -"假设您想使用[Vicuna 13B v1.5](https://huggingface.co/lmsys/vicuna-" -"13b-v1.5)您可以从[TheBloke/vicuna-" -"13B-v1.5-GGUF](https://huggingface.co/TheBloke/vicuna-" -"13B-v1.5-GGUF)下载已转换的文件，只需要一个文件。将其下载到models目录并将其重命名为 `ggml-" -"model-q4_0.gguf`。" - -#: ../../getting_started/install/llm/llama/llama_cpp.md:21 -#: 380ebad2c5a04210a48c5d7a9913413d -msgid "Convert It Yourself" -msgstr "自行转换" - -#: ../../getting_started/install/llm/llama/llama_cpp.md:23 -#: cf39ca73d9c6456794fb240b164b7cbb -msgid "" -"You can convert the model file yourself according to the instructions in " -"[llama.cpp#prepare-data--run](https://github.com/ggerganov/llama.cpp" -"#prepare-data--run), and put the converted file in the models directory " -"and rename it to `ggml-model-q4_0.gguf`." -msgstr "" -"您可以根据[llama.cpp#prepare-data--run](https://github.com/ggerganov/llama.cpp" -"#prepare-data--run)中的说明自行转换模型文件，并把转换后的文件放在models目录中，并重命名为`ggml-" -"model-q4_0.gguf`。" - -#: ../../getting_started/install/llm/llama/llama_cpp.md:25 -#: 363cbf1c0b4e4029982519238f776958 -msgid "Installing Dependencies" -msgstr "安装依赖" - -#: ../../getting_started/install/llm/llama/llama_cpp.md:27 -#: a98c36e3d7df40f3a816c0ee451b6114 -msgid "" -"llama.cpp is an optional dependency in DB-GPT, and you can manually " -"install it using the following command:" -msgstr "llama.cpp在DB-GPT中是可选安装项, 你可以通过以下命令进行安装" - -#: ../../getting_started/install/llm/llama/llama_cpp.md:33 -#: b0038a8ba36647c6a62eef907cb6d304 -msgid "Modifying the Configuration File" -msgstr "修改配置文件" - -#: ../../getting_started/install/llm/llama/llama_cpp.md:35 -#: d2002da716744122a44ab4ed2e47e680 -msgid "Next, you can directly modify your `.env` file to enable llama.cpp." -msgstr "修改`.env`文件使用llama.cpp" - -#: ../../getting_started/install/llm/llama/llama_cpp.md:42 -#: 97a5fb5d4ed649f5aa0bbb97c32d54b0 -msgid "" -"Then you can run it according to [Run](https://db-" -"gpt.readthedocs.io/en/latest/getting_started/install/deploy/deploy.html#run)." -msgstr "" -"然后你可以根据[运行]" -"(https://db-gpt.readthedocs.io/projects/db-gpt-docs-zh-cn/zh_CN/latest/getting_started/install/deploy/deploy.html#run)来运行" - -#: ../../getting_started/install/llm/llama/llama_cpp.md:45 -#: 0e3771b6aaa141f89c813507f3317bda -msgid "More Configurations" -msgstr "更多配置文件" - -#: ../../getting_started/install/llm/llama/llama_cpp.md:47 -#: 0802ba524cd1458298fe6f90ae7f2da1 -msgid "" -"In DB-GPT, the model configuration can be done through `{model " -"name}_{config key}`." -msgstr "在DB-GPT中，模型配置可以通过`{模型名称}_{配置名}` 来配置。" - -#: ../../getting_started/install/llm/llama/llama_cpp.md -#: d461d379a523424fb5885e393498ee14 -msgid "Environment Variable Key" -msgstr "环境变量键" - -#: ../../getting_started/install/llm/llama/llama_cpp.md -#: 0263477d0ddb4914baa0d3584b751086 -msgid "default" -msgstr "默认值" - -#: ../../getting_started/install/llm/llama/llama_cpp.md -#: e5188d0ded6540a0bddb46d480f8b7ac -msgid "Description" -msgstr "描述" - -#: ../../getting_started/install/llm/llama/llama_cpp.md -#: 213b27d0e53d4858b7576dc4f2ab4d7f -msgid "llama_cpp_prompt_template" -msgstr "llama_cpp_prompt_template" - -#: ../../getting_started/install/llm/llama/llama_cpp.md -#: 1cb0320826564a89a3e2f51177f8a6ed 23d93dc7d88e431ba31ff64d239a412f -#: 833d5012411a4ad58b04d50a40a29184 95aa2102191946919158ae668b2e3599 -#: becdd178292a48138dcb445ba3c2a6ec -msgid "None" -msgstr "None" - -#: ../../getting_started/install/llm/llama/llama_cpp.md -#: ac835806c79640aa8cd39edb11d7667c -msgid "" -"Prompt template name, now support: `zero_shot, vicuna_v1.1,alpaca,llama-2" -",baichuan-chat,internlm-chat`, If None, the prompt template is " -"automatically determined from model path。" -msgstr "" -"Prompt template 现在可以支持`zero_shot, vicuna_v1.1,alpaca,llama-2,baichuan-" -"chat,internlm-chat`, 如果是None, 可以根据模型路径来自动获取模型 Prompt template" - -#: ../../getting_started/install/llm/llama/llama_cpp.md -#: 41bce5a6bbf2417f8bc40e71c59405ad -msgid "llama_cpp_model_path" -msgstr "llama_cpp_model_path" - -#: ../../getting_started/install/llm/llama/llama_cpp.md -#: 15df4d19645b40e7a209827f9a325b8f -msgid "Model path" -msgstr "模型路径" - -#: ../../getting_started/install/llm/llama/llama_cpp.md -#: caf9ddbfb787418d8b167746e3febe8c -msgid "llama_cpp_n_gpu_layers" -msgstr "llama_cpp_n_gpu_layers" - -#: ../../getting_started/install/llm/llama/llama_cpp.md -#: e12e0ed2c01e4d12b41d5da533073c53 -msgid "1000000000" -msgstr "1000000000" - -#: ../../getting_started/install/llm/llama/llama_cpp.md -#: 1f4a868d3fed4ac78bfa48e13b3a59dc -msgid "" -"Number of layers to offload to the GPU, Set this to 1000000000 to offload" -" all layers to the GPU. If your GPU VRAM is not enough, you can set a low" -" number, eg: `10`" -msgstr "要将多少网络层转移到GPU上，将其设置为1000000000以将所有层转移到GPU上。如果您的 GPU 内存不足，可以设置较低的数字，例如：10。" - -#: ../../getting_started/install/llm/llama/llama_cpp.md -#: 306e083489e24f819d67f38e2f155f0f -msgid "llama_cpp_n_threads" -msgstr "llama_cpp_n_threads" - -#: ../../getting_started/install/llm/llama/llama_cpp.md -#: 0490a543f67f4ecd8588541399846951 -msgid "" -"Number of threads to use. If None, the number of threads is automatically" -" determined" -msgstr "要使用的线程数量。如果为None，则线程数量将自动确定。" - -#: ../../getting_started/install/llm/llama/llama_cpp.md -#: 2ad3f09e1f894e30ae512e1cd803af52 -msgid "llama_cpp_n_batch" -msgstr "llama_cpp_n_batch" - -#: ../../getting_started/install/llm/llama/llama_cpp.md -#: c495776868394df5b311087dfc7c55dd -msgid "512" -msgstr "512" - -#: ../../getting_started/install/llm/llama/llama_cpp.md -#: b5e69dc488cc4ae78ee9daefcf73c290 -msgid "Maximum number of prompt tokens to batch together when calling llama_eval" -msgstr "在调用llama_eval时，批处理在一起的prompt tokens的最大数量" - -#: ../../getting_started/install/llm/llama/llama_cpp.md -#: 516cfc3ed00c4a6181f37a4649c9f041 -msgid "llama_cpp_n_gqa" -msgstr "llama_cpp_n_gqa" - -#: ../../getting_started/install/llm/llama/llama_cpp.md -#: 51847a305c4341af8614a2ceb7aa658f -msgid "Grouped-query attention. Must be 8 for llama-2 70b." -msgstr "对于 llama-2 70B 模型，Grouped-query attention 必须为8。" - -#: ../../getting_started/install/llm/llama/llama_cpp.md -#: 8261108709f341dab19e4fece7682c0c -msgid "llama_cpp_rms_norm_eps" -msgstr "llama_cpp_rms_norm_eps" - -#: ../../getting_started/install/llm/llama/llama_cpp.md -#: 72cc3d9988414f489ddefe3afb332e83 -msgid "5e-06" -msgstr "5e-06" - -#: ../../getting_started/install/llm/llama/llama_cpp.md -#: ebc1baebf57e4009b0fdfa68eb055d80 -msgid "5e-6 is a good value for llama-2 models." -msgstr "对于llama-2模型来说，5e-6是一个不错的值。" - -#: ../../getting_started/install/llm/llama/llama_cpp.md -#: 0cc1199e293741f087c795230d9c8dda -msgid "llama_cpp_cache_capacity" -msgstr "llama_cpp_cache_capacity" - -#: ../../getting_started/install/llm/llama/llama_cpp.md -#: 7d13612da75046b1a3fc0877e229bb91 -msgid "Maximum cache capacity. Examples: 2000MiB, 2GiB" -msgstr "模型缓存最大值. 例如: 2000MiB, 2GiB" - -#: ../../getting_started/install/llm/llama/llama_cpp.md -#: 53332858d3a8472f8eb59d845c594ffd -msgid "llama_cpp_prefer_cpu" -msgstr "llama_cpp_prefer_cpu" - -#: ../../getting_started/install/llm/llama/llama_cpp.md -#: 7ff31fe3233a4243840584bc069654cd -msgid "False" -msgstr "False" - -#: ../../getting_started/install/llm/llama/llama_cpp.md -#: 62d1dbd4f8254141a697448a7a5f6701 -msgid "" -"If a GPU is available, it will be preferred by default, unless " -"prefer_cpu=False is configured." -msgstr "如果有可用的GPU，默认情况下会优先使用GPU，除非配置了 prefer_cpu=False。" - -#: ../../getting_started/install/llm/llama/llama_cpp.md:61 -#: 8de97de28d1a40c3b852a1268255ebed -msgid "GPU Acceleration" -msgstr "GPU 加速" - -#: ../../getting_started/install/llm/llama/llama_cpp.md:63 -#: 8bce74c0ddb5486190ff4d36fd5358be -msgid "" -"GPU acceleration is supported by default. If you encounter any issues, " -"you can uninstall the dependent packages with the following command:" -msgstr "默认情况下支持GPU加速。如果遇到任何问题，您可以使用以下命令卸载相关的依赖包" - -#: ../../getting_started/install/llm/llama/llama_cpp.md:68 -#: 1f3fe88521614d499cb1d046f8d3c125 -msgid "" -"Then install `llama-cpp-python` according to the instructions in [llama-" -"cpp-python](https://github.com/abetlen/llama-cpp-" -"python/blob/main/README.md)." -msgstr "" -"然后通过指令[llama-cpp-python](https://github.com/abetlen/llama-cpp-" -"python/blob/main/README.md).安装`llama-cpp-python`" - -#: ../../getting_started/install/llm/llama/llama_cpp.md:71 -#: fc83106f0a0e4ddfb3c058bec62f4568 -msgid "Mac Usage" -msgstr "Mac 使用" - -#: ../../getting_started/install/llm/llama/llama_cpp.md:73 -#: dcf5904a444342c8a768c4da8b777828 -msgid "" -"Special attention, if you are using Apple Silicon (M1) Mac, it is highly " -"recommended to install arm64 architecture python support, for example:" -msgstr "特别注意：如果您正在使用苹果芯片（M1）的Mac电脑，强烈建议安装 arm64 架构的 Python 支持，例如：" - -#: ../../getting_started/install/llm/llama/llama_cpp.md:80 -#: 547369c011a9412589dad1fac7ac3ef9 -msgid "Windows Usage" -msgstr "Windows使用" - -#: ../../getting_started/install/llm/llama/llama_cpp.md:82 -#: 506fda57977f4aa8b9fe427e3c66f4d7 -msgid "" -"The use under the Windows platform has not been rigorously tested and " -"verified, and you are welcome to use it. If you have any problems, you " -"can create an [issue](https://github.com/eosphoros-ai/DB-GPT/issues) or " -"[contact us](https://github.com/eosphoros-ai/DB-GPT/tree/main#contact-" -"information) directly." -msgstr "" -"在Windows平台上的使用尚未经过严格的测试和验证，欢迎您使用。如果您有任何问题，可以创建一个[issue](https://github.com" -"/eosphoros-ai/DB-GPT/issues)或者直接[联系我们](https://github.com/eosphoros-ai" -"/DB-GPT/tree/main#cntact-information)。" - -#~ msgid "" -#~ "DB-GPT is now supported by " -#~ "[llama-cpp-python](https://github.com/abetlen/llama-" -#~ "cpp-python) through " -#~ "[llama.cpp](https://github.com/ggerganov/llama.cpp)." -#~ msgstr "" -#~ "DB-GPT is now supported by " -#~ "[llama-cpp-python](https://github.com/abetlen/llama-" -#~ "cpp-python) through " -#~ "[llama.cpp](https://github.com/ggerganov/llama.cpp)." - -#~ msgid "Prompt Template Name" -#~ msgstr "Prompt Template Name" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/llm/llm.po b/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/llm/llm.po deleted file mode 100644 index 73788c41e..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/llm/llm.po +++ /dev/null @@ -1,113 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.3.5\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-09-20 17:34+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../getting_started/install/llm/llm.rst:2 -#: ../../getting_started/install/llm/llm.rst:25 -#: 5242ca319fab49988e018cd5b5d893df -msgid "LLM Usage" -msgstr "LLM使用" - -#: ../../getting_started/install/llm/llm.rst:3 b12a86c062f441cd870e94d56146e6ea -msgid "" -"DB-GPT provides a management and deployment solution for multiple models." -" This chapter mainly discusses how to deploy different models." -msgstr "DB-GPT提供了多模型的管理和部署方案，本章主要讲解针对不同的模型该怎么部署" - -#: ../../getting_started/install/llm/llm.rst:20 -#: a7e76642fec94a658a48ced7b4133a61 -msgid "" -"Multi LLMs Support, Supports multiple large language models, currently " -"supporting" -msgstr "目前DB-GPT已适配如下模型" - -#: ../../getting_started/install/llm/llm.rst:9 9dbc17aae88a4d2fa4c291d58e8390e2 -msgid "🔥 InternLM(7b,20b)" -msgstr "" - -#: ../../getting_started/install/llm/llm.rst:10 -#: 7d423bfe0c9f41758f0bf55e30803955 -#, fuzzy -msgid "🔥 Baichuan2(7b,13b)" -msgstr "Baichuan(7b,13b)" - -#: ../../getting_started/install/llm/llm.rst:11 -#: 2e44b9f9f2a842d1969255610974f9c0 -msgid "🔥 Vicuna-v1.5(7b,13b)" -msgstr "🔥 Vicuna-v1.5(7b,13b)" - -#: ../../getting_started/install/llm/llm.rst:12 -#: ea32bf9802054af396accaf55291a3a1 -msgid "🔥 llama-2(7b,13b,70b)" -msgstr "🔥 llama-2(7b,13b,70b)" - -#: ../../getting_started/install/llm/llm.rst:13 -#: fc39e32250424dbaa7c0c65d45a01983 -msgid "WizardLM-v1.2(13b)" -msgstr "WizardLM-v1.2(13b)" - -#: ../../getting_started/install/llm/llm.rst:14 -#: e17ed83eba5a46ea9950c8ba719403ba -msgid "Vicuna (7b,13b)" -msgstr "Vicuna (7b,13b)" - -#: ../../getting_started/install/llm/llm.rst:15 -#: a13575c9b1b1458282d5a6351128735f -msgid "ChatGLM-6b (int4,int8)" -msgstr "ChatGLM-6b (int4,int8)" - -#: ../../getting_started/install/llm/llm.rst:16 -#: 504b4a29240d4e69a258d5ca4d0846d2 -msgid "ChatGLM2-6b (int4,int8)" -msgstr "ChatGLM2-6b (int4,int8)" - -#: ../../getting_started/install/llm/llm.rst:17 -#: 0edd5c73197e4e5d9691665dc79e78b0 -msgid "guanaco(7b,13b,33b)" -msgstr "guanaco(7b,13b,33b)" - -#: ../../getting_started/install/llm/llm.rst:18 -#: bd97e381ac6743e4a03df54b980ac5b9 -msgid "Gorilla(7b,13b)" -msgstr "Gorilla(7b,13b)" - -#: ../../getting_started/install/llm/llm.rst:19 -#: 8d46081371b34471ba8f1dbc374955be -msgid "Baichuan(7b,13b)" -msgstr "Baichuan(7b,13b)" - -#: ../../getting_started/install/llm/llm.rst:20 -#: 08a1d4b2abac4effbc236fcd38f9a205 -msgid "OpenAI" -msgstr "OpenAI" - -#: ../../getting_started/install/llm/llm.rst:22 -#: 4f1e438738854cf1ad35800ddbeb9e12 -msgid "llama_cpp" -msgstr "llama_cpp" - -#: ../../getting_started/install/llm/llm.rst:23 -#: 5db1549fcfca4744b441cde5922d7fd3 -msgid "quantization" -msgstr "quantization" - -#~ msgid "cluster deployment" -#~ msgstr "" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/llm/proxyllm/proxyllm.po b/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/llm/proxyllm/proxyllm.po deleted file mode 100644 index f6411fd1a..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/llm/proxyllm/proxyllm.po +++ /dev/null @@ -1,97 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.4.0\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-10-26 11:26+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../getting_started/install/llm/proxyllm/proxyllm.md:1 -#: b006d689cfd2430da6a2b503a4f2fef3 -msgid "Proxy LLM API" -msgstr "Proxy LLM API" - -#: ../../getting_started/install/llm/proxyllm/proxyllm.md:3 -#: b60328fb6b074edba31c34825038bbf4 -msgid "Now DB-GPT supports connect LLM service through proxy rest api." -msgstr "DB-GPT支持对接第三方的LLM REST API 服务" - -#: ../../getting_started/install/llm/proxyllm/proxyllm.md:5 -#: 82dcc5fc9d314a6f871851c842c3b6b3 -msgid "LLM rest api now supports" -msgstr "LLM REST API服务目前支持" - -#: ../../getting_started/install/llm/proxyllm/proxyllm.md:7 -#: 2a894db1f42544b2bdc932b50050eaf4 -msgid "OpenAI" -msgstr "OpenAI" - -#: ../../getting_started/install/llm/proxyllm/proxyllm.md:8 -#: 52c288434b6b42a1a376f8d698d0aad1 -msgid "Azure" -msgstr "Azure" - -#: ../../getting_started/install/llm/proxyllm/proxyllm.md:9 -#: eeca0b58cf504586b8695e433e1a4458 -msgid "Aliyun tongyi" -msgstr "通义千问API" - -#: ../../getting_started/install/llm/proxyllm/proxyllm.md:10 -#: 7b30a85b145545f0b2d8dd3b85f98bcf -msgid "Baidu wenxin" -msgstr "百度文心API" - -#: ../../getting_started/install/llm/proxyllm/proxyllm.md:11 -#: b4cfeba632cb4f898564cf76d9c1551d -msgid "Zhipu" -msgstr "智谱API" - -#: ../../getting_started/install/llm/proxyllm/proxyllm.md:12 -#: faa92560db2b47d9b9a41bbf703fd84d -msgid "Baichuan" -msgstr "百川API" - -#: ../../getting_started/install/llm/proxyllm/proxyllm.md:13 -#: aba2dcc36b854b6193ababca772e1cf0 -#, fuzzy -msgid "Bard" -msgstr "bard API" - -#: ../../getting_started/install/llm/proxyllm/proxyllm.md:17 -#: f66f0bfcad2a4f428c953452d5f6963b -msgid "" -"How to Integrate LLM rest API, like OpenAI, Azure, tongyi, wenxin llm " -"api service?" -msgstr "如何集成这些LLM rest API呢" - -#: ../../getting_started/install/llm/proxyllm/proxyllm.md:18 -#: 01284baeb4a24bb18d48e51ad8503997 -msgid "update your `.env` file" -msgstr "更新`.env`配置文件" - -#: ../../getting_started/install/llm/proxyllm/proxyllm.md:63 -#: f602876d957446fd8056854b6b2121a1 -msgid "Make sure your .env configuration is not overwritten" -msgstr "确保文件配置不会被覆盖" - -#: ../../getting_started/install/llm/proxyllm/proxyllm.md:66 -#: 51cb501d1500440981b3b93f01ff36f4 -msgid "How to Integrate Embedding rest API, like OpenAI, Azure api service?" -msgstr "如何集成想OpenAI Embedding rest api" - -#~ msgid "Now DB-GPT support connect LLM service through proxy rest api." -#~ msgstr "" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/llm/quantization/quantization.po b/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/llm/quantization/quantization.po deleted file mode 100644 index 3631c9b53..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/llm/quantization/quantization.po +++ /dev/null @@ -1,26 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.3.5\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-08-17 13:07+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../getting_started/install/llm/quantization/quantization.md:1 -#: 2b540d0fbece43c5a9d90e0935eb574c -msgid "quantization" -msgstr "quantization" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/llm/vllm/vllm.po b/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/llm/vllm/vllm.po deleted file mode 100644 index 66d9ddb71..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/getting_started/install/llm/vllm/vllm.po +++ /dev/null @@ -1,79 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.3.9\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-10-09 19:46+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../getting_started/install/llm/vllm/vllm.md:1 -#: 9193438ba52148a3b71f190beeb4ef42 -msgid "vLLM" -msgstr "" - -#: ../../getting_started/install/llm/vllm/vllm.md:4 -#: c30d032965794d7e81636581324be45d -msgid "" -"[vLLM](https://github.com/vllm-project/vllm) is a fast and easy-to-use " -"library for LLM inference and serving." -msgstr "[vLLM](https://github.com/vllm-project/vllm) 是一个快速且易于使用的 LLM 推理和服务的库。" - -#: ../../getting_started/install/llm/vllm/vllm.md:6 -#: b399c7268e0448cb893fbcb11a480849 -msgid "Running vLLM" -msgstr "运行 vLLM" - -#: ../../getting_started/install/llm/vllm/vllm.md:8 -#: 7bed52b8bac946069a24df9e94098df5 -msgid "Installing Dependencies" -msgstr "安装依赖" - -#: ../../getting_started/install/llm/vllm/vllm.md:10 -#: fd50a9f3e1b1459daa3b1a0cd610d1a3 -msgid "" -"vLLM is an optional dependency in DB-GPT, and you can manually install it" -" using the following command:" -msgstr "vLLM 在 DB-GPT 是一个可选依赖, 你可以使用下面的命令手动安装它：" - -#: ../../getting_started/install/llm/vllm/vllm.md:16 -#: 44b251bc6b2c41ebaad9fd5a6a204c7c -msgid "Modifying the Configuration File" -msgstr "修改配置文件" - -#: ../../getting_started/install/llm/vllm/vllm.md:18 -#: 37f4e65148fa4339969265107b70b8fe -msgid "Next, you can directly modify your `.env` file to enable vllm." -msgstr "你可以直接修改你的 `.env` 文件。" - -#: ../../getting_started/install/llm/vllm/vllm.md:24 -#: 15d79c9417d04e779fa00a08a05e30d7 -msgid "" -"You can view the models supported by vLLM " -"[here](https://vllm.readthedocs.io/en/latest/models/supported_models.html" -"#supported-models)" -msgstr "" -"你可以在 " -"[这里](https://vllm.readthedocs.io/en/latest/models/supported_models.html" -"#supported-models) 查看 vLLM 支持的模型。" - -#: ../../getting_started/install/llm/vllm/vllm.md:26 -#: 28d90b1fdf6943d9969c8668a7c1094b -msgid "" -"Then you can run it according to [Run](https://db-" -"gpt.readthedocs.io/en/latest/getting_started/install/deploy/deploy.html#run)." -msgstr "" -"然后你可以根据[运行]" -"(https://db-gpt.readthedocs.io/projects/db-gpt-docs-zh-cn/zh_CN/latest/getting_started/install/deploy/deploy.html#run)来启动项目。" diff --git a/docs/locales/zh_CN/LC_MESSAGES/getting_started/installation.po b/docs/locales/zh_CN/LC_MESSAGES/getting_started/installation.po deleted file mode 100644 index 72147f848..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/getting_started/installation.po +++ /dev/null @@ -1,94 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.3.0\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-08-16 18:31+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../getting_started/installation.md:1 f9e65f84d13249098aa2768bb7cc69ed -msgid "Python SDK" -msgstr "" - -#: ../../getting_started/installation.md:2 1902cffb20fe4994aecb577c1a3fa8bf -msgid "" -"DB-GPT provides a third-party Python API package that you can integrate " -"into your own code." -msgstr "DB-GPT提供了python第三方包，你可以在你的代码中引入" - -#: ../../getting_started/installation.md:4 908a7c1971d04e37bd5e88171bd93d3b -msgid "Installation from Pip" -msgstr "使用pip安装" - -#: ../../getting_started/installation.md:6 0eff7cb3c9c643e0884209daddf5d709 -msgid "You can simply pip install:" -msgstr "你可以使用pip install" - -#: ../../getting_started/installation.md:12 1b0f308412cd44bda55efff5830b99f3 -msgid "Notice:make sure python>=3.10" -msgstr "注意:确保你的python版本>=3.10" - -#: ../../getting_started/installation.md:15 bec8afbfa9af4594bb09307f92c617a4 -msgid "Environment Setup" -msgstr "环境设置" - -#: ../../getting_started/installation.md:17 61f60acc7a6449ac974593bd5f164e3e -msgid "By default, if you use the EmbeddingEngine api" -msgstr "如果你想使用EmbeddingEngine api" - -#: ../../getting_started/installation.md:19 f31d9989e0514881baed8c690bc8035a -msgid "you will prepare embedding models from huggingface" -msgstr "你需要从huggingface下载embedding models" - -#: ../../getting_started/installation.md:22 02eb7897412c4223a013e7921eaed253 -msgid "Notice make sure you have install git-lfs" -msgstr "确保你已经安装了git-lfs" - -#: ../../getting_started/installation.md:30 ced612323d5b47d3b93febbc637515bd -msgid "version:" -msgstr "版本:" - -#: ../../getting_started/installation.md:31 4c168bdddb664c76ad4c2be177ef01a0 -msgid "db-gpt0.3.0" -msgstr "db-gpt0.3.0" - -#: ../../getting_started/installation.md:32 9bc5bb66e7214ca0b945b6b46a989307 -msgid "" -"[embedding_engine api](https://db-" -"gpt.readthedocs.io/en/latest/modules/knowledge.html)" -msgstr "" -"[embedding_engine api](https://db-" -"gpt.readthedocs.io/en/latest/modules/knowledge.html)" - -#: ../../getting_started/installation.md:33 52e656e2f0ae46688a6456a441f9c1e5 -msgid "" -"[multi source embedding](https://db-" -"gpt.readthedocs.io/en/latest/modules/knowledge/pdf/pdf_embedding.html)" -msgstr "" -"[multi source embedding](https://db-" -"gpt.readthedocs.io/en/latest/modules/knowledge/pdf/pdf_embedding.html)" - -#: ../../getting_started/installation.md:34 726c87e53d8e4cd799d422aaf562fa29 -msgid "" -"[vector connector](https://db-" -"gpt.readthedocs.io/en/latest/modules/vector.html)" -msgstr "" -"[vector connector](https://db-" -"gpt.readthedocs.io/en/latest/modules/vector.html)" - -#~ msgid "Installation" -#~ msgstr "安装dbgpt包指南" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/getting_started/observability.po b/docs/locales/zh_CN/LC_MESSAGES/getting_started/observability.po deleted file mode 100644 index f4c033520..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/getting_started/observability.po +++ /dev/null @@ -1,122 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.3.9\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-10-12 11:54+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../getting_started/observability.md:1 c88ce18295444597baa7355efc79ab15 -msgid "Debugging" -msgstr "" - -#: ../../getting_started/observability.md:4 522a4e83c62c493381ca3a452ced8ecf -msgid "" -"DB-GPT provides a set of tools to help you troubleshoot and resolve some " -"of the issues you may encounter." -msgstr "DB-GPT 提供了一套工具来帮助你排查和解决一些遇到的问题。" - -#: ../../getting_started/observability.md:7 7fe5b8ab29194e42b74a8ab3e77006c7 -msgid "Trace Logs" -msgstr "追踪日志" - -#: ../../getting_started/observability.md:9 8a55f7a2b5a247d49728969f179bf50d -msgid "" -"DB-GPT writes some critical system runtime information to trace logs. By " -"default, these are located in `logs/dbgpt*.jsonl`." -msgstr "DB-GPT 会将一些系统运行的关键的信息写入到追踪日志中，默认情况下，在 `logs/dbgpt*.jsonl` 中。" - -#: ../../getting_started/observability.md:11 5e2b847179e9427a8ae022b5338cbbd9 -msgid "" -"DB-GPT also offers a command-line tool, `dbgpt trace`, to help you " -"analyze these trace logs. You can see its specific usage with the command" -" `dbgpt trace --help`." -msgstr "" -"DB-GPT 也提供了命令工具 `dbgpt trace` 命令来帮助你分析追踪日志，你可以使用命令 `dbgpt trace --help` " -"来查看具体的用法。" - -#: ../../getting_started/observability.md:14 6e0c9c4ba6ac4eb49d9289b0d63f77fb -msgid "Viewing Chat Details" -msgstr "查看对话详情" - -#: ../../getting_started/observability.md:16 b9badbab74de47f192ff117d7d36fa72 -msgid "" -"You can use the `dbgpt trace chat` command to view chat details. By " -"default, it will display the latest chat message." -msgstr "你可以使用 `dbgpt trace chat` 命令来查看对话信息，默认情况会显示你最新的一条对话信息。" - -#: ../../getting_started/observability.md:18 55c7466bd80d43c9a355d87daf2a2be7 -msgid "Viewing Service Runtime Information" -msgstr "查看服务运行信息" - -#: ../../getting_started/observability.md:24 -#: ../../getting_started/observability.md:66 -#: ../../getting_started/observability.md:98 -#: ../../getting_started/observability.md:146 -#: ../../getting_started/observability.md:200 -#: ../../getting_started/observability.md:229 -#: ../../getting_started/observability.md:249 -#: ../../getting_started/observability.md:267 18907a58a0c3493aa24c17e367309471 -#: 387f08b6cd864a7682522b5a40863e79 5fe0baa5803d4ca5ad0e8cbd8a859c8c -#: 7abbfdd996444999a24cbad852d2e545 957bdf6826e045608c8c3ebd06c8fe76 -#: acddf2cdf8c94bd6864d66739fa26459 f3fcaf2b47774779bad2feb3ef4318c4 -#: f99bb110024443f68cc8b7f19956eff4 -msgid "You will see an output like:" -msgstr "你将会看到类似的输出：" - -#: ../../getting_started/observability.md:60 5c8c213a5bac434bb3defe6611a03813 -msgid "Viewing the Latest Chat Message" -msgstr "查看最近的一条对话信息" - -#: ../../getting_started/observability.md:92 ce19873d8e754173849d14eaeab963d2 -msgid "Viewing Chat Details and Call Chain" -msgstr "查看对话信息和调用链路" - -#: ../../getting_started/observability.md:140 36bcc37971ce4d6682f1ea32e2e9a980 -msgid "Viewing Chat Details Based on trace_id" -msgstr "根据 `trace_id` 查看对应的对话信息" - -#: ../../getting_started/observability.md:172 c74968492f7544758c9d95fa831c4fcf -msgid "More `chat` Usage" -msgstr "更多 `chat` 用法" - -#: ../../getting_started/observability.md:194 c2e5a7e7b1ee40fea15790d66b79eb11 -msgid "Viewing Call Tree Based on `trace_id`" -msgstr "根据 `trace_id` 查看调用树" - -#: ../../getting_started/observability.md:220 6bd64d2ad0ce442e8e81aa1ae7dd2189 -msgid "Listing Trace Information" -msgstr "列出追踪信息" - -#: ../../getting_started/observability.md:222 ce643441e8744ab09fcbd4081d2adb4a -msgid "Listing All Trace Information" -msgstr "列出全部追踪信息" - -#: ../../getting_started/observability.md:243 374376d81ed54bc2a450505abfe7dc6d -msgid "Listing Trace Information by Trace Type" -msgstr "根据追踪类型列出追踪信息" - -#: ../../getting_started/observability.md:261 8fc08a9c924d47309dc7062811c4fb62 -msgid "Searching Trace Information" -msgstr "搜索追踪信息" - -#: ../../getting_started/observability.md:281 3681413d196144389431422010a7e30f -msgid "More `list` Usage" -msgstr "更多 `list` 用法" - -#~ msgid "查看对话详情" -#~ msgstr "" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/getting_started/tutorials.po b/docs/locales/zh_CN/LC_MESSAGES/getting_started/tutorials.po deleted file mode 100644 index c685143fa..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/getting_started/tutorials.po +++ /dev/null @@ -1,123 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 0.3.0\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-08-16 18:31+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../getting_started/tutorials.md:1 3e4b863de01942d5823d5dd3975bcb05 -msgid "Tutorials" -msgstr "教程" - -#: ../../getting_started/tutorials.md:4 bf8a3dc2c8d045d0b4668ecbd25c954d -msgid "This is a collection of DB-GPT tutorials on Medium." -msgstr "这是知乎上DB-GPT教程的集合。．" - -#: ../../getting_started/tutorials.md:6 e72430ed63ca4c13bab165d61293585a -msgid "" -"DB-GPT is divided into several functions, including chat with knowledge " -"base, execute SQL, chat with database, and execute plugins." -msgstr "DB-GPT包含以下功能，和知识库聊天，执行SQL，和数据库聊天以及执行插件。" - -#: ../../getting_started/tutorials.md:8 29cb77fcc97e494ba26ecd61fd21d84f -msgid "Introduction" -msgstr "介绍" - -#: ../../getting_started/tutorials.md:10 0158e41b603a47d8a8d0debcddc1d99c -msgid "youtube" -msgstr "" - -#: ../../getting_started/tutorials.md:11 bd8078ee97094559b3e9b4a90a89651a -#, fuzzy -msgid "[What is DB-GPT](https://www.youtube.com/watch?v=QszhVJerc0I)" -msgstr "" -"###Introduction [什么是DB-" -"GPT](https://www.bilibili.com/video/BV1SM4y1a7Nj/?buvid=551b023900b290f9497610b2155a2668&is_story_h5=false&mid=%2BVyE%2Fwau5woPcUKieCWS0A%3D%3D&p=1&plat_id=116&share_from=ugc&share_medium=iphone&share_plat=ios&share_session_id=5D08B533-82A4-4D40-9615-7826065B4574&share_source=GENERIC&share_tag=s_i×tamp=1686307943&unique_k=bhO3lgQ&up_id=31375446)" -" by csunny (https://github.com/csunny/DB-GPT)" - -#: ../../getting_started/tutorials.md:13 0330432860384964804cc6ea9054d06b -#, fuzzy -msgid "" -"[How to deploy DB-GPT step by " -"step](https://www.youtube.com/watch?v=OJGU4fQCqPs)" -msgstr "" -"###Introduction [什么是DB-" -"GPT](https://www.bilibili.com/video/BV1SM4y1a7Nj/?buvid=551b023900b290f9497610b2155a2668&is_story_h5=false&mid=%2BVyE%2Fwau5woPcUKieCWS0A%3D%3D&p=1&plat_id=116&share_from=ugc&share_medium=iphone&share_plat=ios&share_session_id=5D08B533-82A4-4D40-9615-7826065B4574&share_source=GENERIC&share_tag=s_i×tamp=1686307943&unique_k=bhO3lgQ&up_id=31375446)" -" by csunny (https://github.com/csunny/DB-GPT)" - -#: ../../getting_started/tutorials.md:16 a5b7b6e46df040ddaea184487b6a6ba3 -msgid "bilibili" -msgstr "bilibili" - -#: ../../getting_started/tutorials.md:17 9da89100917742fca40ab71bc1283504 -msgid "" -"[What is DB-" -"GPT](https://www.bilibili.com/video/BV1SM4y1a7Nj/?spm_id_from=333.788&vd_source=7792e22c03b7da3c556a450eb42c8a0f)" -msgstr "[DB-" -"GPT介绍](https://www.bilibili.com/video/BV1SM4y1a7Nj/?spm_id_from=333.788&vd_source=7792e22c03b7da3c556a450eb42c8a0f)" - -#: ../../getting_started/tutorials.md:19 d0b58d505c774d0e867dbd87e703d4ed -msgid "" -"[How to deploy DB-GPT step by " -"step](https://www.bilibili.com/video/BV1mu411Y7ve/?spm_id_from=pageDriver&vd_source=7792e22c03b7da3c556a450eb42c8a0f)" -msgstr "[How to deploy DB-GPT step by " -"step](https://www.bilibili.com/video/BV1mu411Y7ve/?spm_id_from=pageDriver&vd_source=7792e22c03b7da3c556a450eb42c8a0f)" - -#~ msgid "Knowledge" -#~ msgstr "知识库" - -#~ msgid "" -#~ "[How to Create your own knowledge " -#~ "repository](https://db-" -#~ "gpt.readthedocs.io/en/latest/modules/knownledge.html)" -#~ msgstr "" -#~ "[怎么创建自己的知识库](https://db-" -#~ "gpt.readthedocs.io/en/latest/modules/knowledge.html)" - -#~ msgid "![Add new Knowledge demonstration](../../assets/new_knownledge.gif)" -#~ msgstr "[新增知识库演示](../../assets/new_knownledge_en.gif)" - -#~ msgid "Add new Knowledge demonstration" -#~ msgstr "[新增知识库演示](../../assets/new_knownledge_en.gif)" - -#~ msgid "SQL Generation" -#~ msgstr "SQL生成" - -#~ msgid "![sql generation demonstration](../../assets/demo_en.gif)" -#~ msgstr "[sql生成演示](../../assets/demo_en.gif)" - -#~ msgid "sql generation demonstration" -#~ msgstr "[sql生成演示](../../assets/demo_en.gif)" - -#~ msgid "SQL Execute" -#~ msgstr "SQL执行" - -#~ msgid "![sql execute demonstration](../../assets/auto_sql_en.gif)" -#~ msgstr "[sql execute 演示](../../assets/auto_sql_en.gif)" - -#~ msgid "sql execute demonstration" -#~ msgstr "SQL执行演示" - -#~ msgid "Plugins" -#~ msgstr "DB插件" - -#~ msgid "![db plugins demonstration](../../assets/dashboard.png)" -#~ msgstr "[db plugins 演示](../../assets/dbgpt_bytebase_plugin.gif)" - -#~ msgid "db plugins demonstration" -#~ msgstr "DB插件演示" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/index.po b/docs/locales/zh_CN/LC_MESSAGES/index.po deleted file mode 100644 index 3a4c57dbc..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/index.po +++ /dev/null @@ -1,566 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 0.3.0\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-11-14 17:55+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../index.rst:44 ../../index.rst:54 fb98707559574eb29f01bd8f6ebfac60 -msgid "Getting Started" -msgstr "开始" - -#: ../../index.rst:70 ../../index.rst:92 6d9603b978d44e54a257fb359c871867 -msgid "Modules" -msgstr "模块" - -#: ../../index.rst:106 ../../index.rst:112 9df06739ca4446bc86ec2ff6907763ce -msgid "Resources" -msgstr "资源" - -#: ../../index.rst:7 7de875cfbc764937ab7f8b362d997952 -msgid "Overview" -msgstr "概览" - -#: ../../index.rst:9 770a756bd0b640ef863fd72b8d7e882a -msgid "" -"DB-GPT is an open-source framework for large models in the database " -"field. Its purpose is to build infrastructure for the domain of large " -"models, making it easier and more convenient to develop applications " -"around databases. By developing various technical capabilities such as:" -msgstr "DB-GPT是一个开源的数据库领域大模型框架。目的是构建大模型领域的基础设施，通过开发如" - -#: ../../index.rst:11 8774a5ad5ce14baf9eae35fefd62e40b -msgid "**SMMF(Service-oriented Multi-model Management Framework)**" -msgstr "**服务化多模型管理**" - -#: ../../index.rst:12 b2ba120fc994436db7066486c9acd6ad -msgid "**Text2SQL Fine-tuning**" -msgstr "**Text2SQL微调**" - -#: ../../index.rst:13 d55efe86dd6b40ebbe63079edb60e421 -msgid "**RAG(Retrieval Augmented Generation) framework and optimization**" -msgstr "**检索增强**" - -#: ../../index.rst:14 3eca943c44464c9cb9bbc5724c27ad1c -msgid "**Data-Driven Agents framework collaboration**" -msgstr "**数据驱动的Agents协作框架**" - -#: ../../index.rst:15 bf41d57cbc474e2c9829f09d6b983ae1 -msgid "**GBI(Generative Business intelligence)**" -msgstr "**生成式报表分析**" - -#: ../../index.rst:17 36630469cc064317a1c196dd377c3d93 -msgid "" -"etc, DB-GPT simplifies the construction of large model applications based" -" on databases." -msgstr "等能力, 让围绕数据库构建大模型应用更简单，更方便。" - -#: ../../index.rst:19 82f03535c6914ebfa8b3adad34eeed2f -msgid "" -"In the era of Data 3.0, enterprises and developers can build their own " -"customized applications with less code, leveraging models and databases." -msgstr "*数据3.0 时代，基于模型、数据库，企业/开发者可以用更少的代码搭建自己的专属应用*。" - -#: ../../index.rst:22 daf64ec39c28458087d542879d106d1b -msgid "Features" -msgstr "特性" - -#: ../../index.rst:24 7ceb41b710f847e683479dc892baa3d5 -msgid "**1. Private Domain Q&A & Data Processing**" -msgstr "**1. 私域问答&数据处理**" - -#: ../../index.rst:25 3f480e259ee9432b934ee6474bc8de79 -msgid "" -"Supports custom construction of knowledge bases through methods such as " -"built-in, multi-file format uploads, and plugin-based web scraping. " -"Enables unified vector storage and retrieval of massive structured and " -"unstructured data." -msgstr "支持内置、多文件格式上传、插件自抓取等方式自定义构建知识库，对海量结构化，非结构化数据做统一向量存储与检索" - -#: ../../index.rst:27 1f9f12be761a4a6c996788051a3fa4dd -msgid "**2.Multi-Data Source & GBI(Generative Business intelligence)**" -msgstr "**2.多数据源与可视化**" - -#: ../../index.rst:28 e597e6c2d4ad4d1bbcc440b3afb7c0fa -msgid "" -"Supports interaction between natural language and various data sources " -"such as Excel, databases, and data warehouses. Also supports analysis " -"reporting." -msgstr "支持自然语言与Excel、数据库、数仓等多种数据源交互,并支持分析报告。" - -#: ../../index.rst:30 9c63ecf927874f9ea79f1ef5c1535e67 -msgid "**3.SMMF(Service-oriented Multi-model Management Framework)**" -msgstr "**3.多模型管理**" - -#: ../../index.rst:31 d6cfb9b69f9743d083c4644c90fd6108 -msgid "" -"Supports a wide range of models, including dozens of large language " -"models such as open-source models and API proxies. Examples include " -"LLaMA/LLaMA2, Baichuan, ChatGLM, Wenxin, Tongyi, Zhipu, Xinghuo, etc." -msgstr "海量模型支持，包括开源、API代理等几十种大语言模型。如LLaMA/LLaMA2、Baichuan、ChatGLM、文心、通义、智谱、星火等。" - -#: ../../index.rst:33 dda6cec4316e48f2afe77005baa53a06 -msgid "**4.Automated Fine-tuning**" -msgstr "**4.自动化微调**" - -#: ../../index.rst:34 7cf1654a9779444ab3982435887d087b -msgid "" -"A lightweight framework for automated fine-tuning built around large " -"language models, Text2SQL datasets, and methods like LoRA/QLoRA/Pturning." -" Makes TextSQL fine-tuning as convenient as a production line." -msgstr "" -"围绕大语言模型、Text2SQL数据集、LoRA/QLoRA/Pturning等微调方法构建的自动化微调轻量框架, " -"让TextSQL微调像流水线一样方便。" - -#: ../../index.rst:36 f58f114546f04b658aaa67fd895fba2b -msgid "**5.Data-Driven Multi-Agents & Plugins**" -msgstr "**5.数据驱动的插件模型**" - -#: ../../index.rst:37 a93fdca3de054cb0812d7f5ca3d12375 -msgid "" -"Supports executing tasks through custom plugins and natively supports the" -" Auto-GPT plugin model. Agents protocol follows the Agent Protocol " -"standard." -msgstr "支持自定义插件执行任务，原生支持Auto-GPT插件模型，Agents协议采用Agent Protocol标准" - -#: ../../index.rst:39 3a0e89b151694e4b8e87646efe313568 -msgid "**6.Privacy and Security**" -msgstr "**6.隐私安全**" - -#: ../../index.rst:40 aa50fc40f22f4fae8225a0a0a97c17dc -msgid "" -"Ensures data privacy and security through techniques such as privatizing " -"large models and proxy de-identification." -msgstr "通过私有化大模型、代理脱敏等多种技术保障数据的隐私安全" - -#: ../../index.rst:46 d8bf21a7abd749608cddcdb2e358f3be -msgid "Quickstart" -msgstr "快速开始" - -#: ../../index.rst:48 d1f117a7cbb94c80afc0660e899d8154 -#, fuzzy -msgid "`Quickstart Guide <./getting_started/getting_started.html>`_" -msgstr "`使用指南 <./getting_started/getting_started.html>`_" - -#: ../../index.rst:50 5fd56979f31b4a0b93082004f1cb90c7 -msgid "Concepts and terminology" -msgstr "相关概念" - -#: ../../index.rst:52 09c6889d02fa417c9ffde312211726f0 -#, fuzzy -msgid "`Concepts and Terminology <./getting_started/concepts.html>`_" -msgstr "`相关概念 <./getting_started/concepts.html>`_" - -#: ../../index.rst:72 5bd727134fc94cfb88abb755ccceac03 -msgid "" -"These modules are the core abstractions with which we can interact with " -"data and environment smoothly. It's very important for DB-GPT, DB-GPT " -"also provide standard, extendable interfaces." -msgstr "这些模块是我们能够与数据和环境顺利交互的核心抽象。这对于DB-GPT来说非常重要，DB-GPT还提供了标准的、可扩展的接口。" - -#: ../../index.rst:74 1a5eb0b7cb884309be3431112c8f38e5 -msgid "" -"The docs for each module contain quickstart examples, how to guides, " -"reference docs, and conceptual guides." -msgstr "每个模块的文档都包含快速入门的例子、操作指南、参考文档和相关概念等内容。" - -#: ../../index.rst:76 24aa8c08d1dc460ab23d69a5bb9c8fc3 -msgid "The modules are as follows" -msgstr "组成模块如下：" - -#: ../../index.rst:78 9f4280cca1f743cb9b868cc67e3f3ce7 -msgid "" -"`LLMs <./modules/llms.html>`_: Supported multi models management and " -"integrations." -msgstr "`LLMs <./modules/llms.html>`_:基于FastChat提供大模型的运行环境。支持多模型管理和集成。 " - -#: ../../index.rst:80 d357811f110f40e79f0c20ef9cb60d0c -msgid "" -"`Prompts <./modules/prompts.html>`_: Prompt management, optimization, and" -" serialization for multi database." -msgstr "" -"`Prompt自动生成与优化 <./modules/prompts.html>`_: 自动化生成高质量的Prompt " -"，并进行优化，提高系统的响应效率" - -#: ../../index.rst:82 3cb9acc9f11a46638e6687f743d6b7f3 -msgid "`Plugins <./modules/plugins.html>`_: Plugins management, scheduler." -msgstr "`Agent与插件： <./modules/plugins.html>`_:提供Agent和插件机制，使得用户可以自定义并增强系统的行为。" - -#: ../../index.rst:84 b24c462cb5364890a6ca990f09f48cfc -#, fuzzy -msgid "" -"`Knowledge <./modules/knowledge.html>`_: Knowledge management, embedding," -" and search." -msgstr "`知识库能力： <./modules/knowledge.html>`_: 支持私域知识库问答能力, " - -#: ../../index.rst:86 7448b231fe8745f1965a1f48ffc5444a -msgid "" -"`Connections <./modules/connections.html>`_: Supported multi databases " -"connection. management connections and interact with this." -msgstr "`连接模块 <./modules/connections.html>`_: 用于连接不同的模块和数据源，实现数据的流转和交互 " - -#: ../../index.rst:88 c677fb24869347ff907f1529ef333b6b -#, fuzzy -msgid "`Vector <./modules/vector.html>`_: Supported multi vector database." -msgstr "`LLMs <./modules/llms.html>`_:基于FastChat提供大模型的运行环境。支持多模型管理和集成。 " - -#: ../../index.rst:108 2e56f2cb1a8b40dda9465c0a1af94196 -msgid "" -"Additional resources we think may be useful as you develop your " -"application!" -msgstr "我们认为在您开发应用程序时可能有用的其他资源!" - -#: ../../index.rst:110 590362cb3b7442d49eafa58cb323e127 -msgid "" -"`Discord `_: if your have some problem or " -"ideas, you can talk from discord." -msgstr "`Discord `_:如果您有任何问题，可以到discord中进行交流。" - -#~ msgid "FAQ" -#~ msgstr "" - -#~ msgid "DB-GPT FAQ." -#~ msgstr "" - -#~ msgid "Ecosystem" -#~ msgstr "环境系统" - -#~ msgid "Guides for how other companies/products can be used with DB-GPT" -#~ msgstr "其他公司/产品如何与DB-GPT一起使用的方法指南" - -#~ msgid "Use Cases" -#~ msgstr "示例" - -#~ msgid "" -#~ "Best Practices and built-in " -#~ "implementations for common DB-GPT use" -#~ " cases:" -#~ msgstr "DB-GPT用例的最佳实践和内置方法:" - -#~ msgid "" -#~ "`Sql generation and diagnosis " -#~ "<./use_cases/sql_generation_and_diagnosis.html>`_: SQL " -#~ "generation and diagnosis." -#~ msgstr "`Sql生成和诊断 <./use_cases/sql_generation_and_diagnosis.html>`_: Sql生成和诊断。" - -#~ msgid "" -#~ "`knownledge Based QA " -#~ "<./use_cases/knownledge_based_qa.html>`_: A important " -#~ "scene for user to chat with " -#~ "database documents, codes, bugs and " -#~ "schemas." -#~ msgstr "" -#~ "`知识库问答 <./use_cases/knownledge_based_qa.html>`_: " -#~ "用户与数据库文档、代码和bug聊天的重要场景\"" - -#~ msgid "" -#~ "`Chatbots <./use_cases/chatbots.html>`_: Language " -#~ "model love to chat, use multi " -#~ "models to chat." -#~ msgstr "`聊天机器人 <./use_cases/chatbots.html>`_: 使用多模型进行对话" - -#~ msgid "" -#~ "`Querying Database Data " -#~ "<./use_cases/query_database_data.html>`_: Query and " -#~ "Analysis data from databases and give" -#~ " charts." -#~ msgstr "`查询数据库数据 <./use_cases/query_database_data.html>`_:从数据库中查询和分析数据并给出图表。" - -#~ msgid "" -#~ "`Interacting with apis " -#~ "<./use_cases/interacting_with_api.html>`_: Interact with" -#~ " apis, such as create a table, " -#~ "deploy a database cluster, create a " -#~ "database and so on." -#~ msgstr "" -#~ "`API交互 <./use_cases/interacting_with_api.html>`_: " -#~ "与API交互，例如创建表、部署数据库集群、创建数据库等。" - -#~ msgid "" -#~ "`Tool use with plugins " -#~ "<./use_cases/tool_use_with_plugin>`_: According to " -#~ "Plugin use tools to manage databases " -#~ "autonomoly." -#~ msgstr "`插件工具 <./use_cases/tool_use_with_plugin>`_: 根据插件使用工具自主管理数据库。" - -#~ msgid "Reference" -#~ msgstr "参考" - -#~ msgid "Welcome to DB-GPT!" -#~ msgstr "欢迎来到DB-GPT中文文档" - -#~ msgid "" -#~ "As large models are released and " -#~ "iterated upon, they are becoming " -#~ "increasingly intelligent. However, in the " -#~ "process of using large models, we " -#~ "face significant challenges in data " -#~ "security and privacy. We need to " -#~ "ensure that our sensitive data and " -#~ "environments remain completely controlled and" -#~ " avoid any data privacy leaks or " -#~ "security risks. Based on this, we " -#~ "have launched the DB-GPT project " -#~ "to build a complete private large " -#~ "model solution for all database-based" -#~ " scenarios. This solution supports local" -#~ " deployment, allowing it to be " -#~ "applied not only in independent private" -#~ " environments but also to be " -#~ "independently deployed and isolated according" -#~ " to business modules, ensuring that " -#~ "the ability of large models is " -#~ "absolutely private, secure, and controllable." -#~ msgstr "" -#~ "随着大型模型的发布和迭代，它们变得越来越智能。然而，在使用大型模型的过程中，我们在数据安全和隐私方面面临着重大挑战。我们需要确保我们的敏感数据和环境得到完全控制，避免任何数据隐私泄露或安全风险。基于此" -#~ "，我们启动了DB-" -#~ "GPT项目，为所有基于数据库的场景构建一个完整的私有大模型解决方案。该方案“”支持本地部署，既可应用于“独立私有环境”，又可根据业务模块进行“独立部署”和“隔离”，确保“大模型”的能力绝对私有、安全、可控。" - -#~ msgid "" -#~ "**DB-GPT** is an experimental open-" -#~ "source project that uses localized GPT" -#~ " large models to interact with your" -#~ " data and environment. With this " -#~ "solution, you can be assured that " -#~ "there is no risk of data leakage," -#~ " and your data is 100% private " -#~ "and secure." -#~ msgstr "" -#~ "DB-GPT " -#~ "是一个开源的以数据库为基础的GPT实验项目，使用本地化的GPT大模型与您的数据和环境进行交互，无数据泄露风险100% " -#~ "私密，100% 安全。" - -#~ msgid "" -#~ "Currently, we have released multiple key" -#~ " features, which are listed below to" -#~ " demonstrate our current capabilities:" -#~ msgstr "目前我们已经发布了多种关键的特性，这里一一列举展示一下当前发布的能力。" - -#~ msgid "SQL language capabilities - SQL generation - SQL diagnosis" -#~ msgstr "SQL语言能力 - SQL生成 - SQL诊断" - -#~ msgid "" -#~ "Private domain Q&A and data processing" -#~ " - Database knowledge Q&A - Data " -#~ "processing" -#~ msgstr "私有领域问答与数据处理 - 数据库知识问答 - 数据处理" - -#~ msgid "" -#~ "Plugins - Support custom plugin " -#~ "execution tasks and natively support the" -#~ " Auto-GPT plugin, such as:" -#~ msgstr "插件模型 - 支持自定义插件执行任务，并原生支持Auto-GPT插件，例如:* SQL自动执行，获取查询结果 * 自动爬取学习知识" - -#~ msgid "" -#~ "Unified vector storage/indexing of knowledge" -#~ " base - Support for unstructured data" -#~ " such as PDF, Markdown, CSV, and " -#~ "WebURL" -#~ msgstr "知识库统一向量存储/索引 - 非结构化数据支持包括PDF、MarkDown、CSV、WebURL" - -#~ msgid "" -#~ "Multi LLMs Support - Supports multiple" -#~ " large language models, currently " -#~ "supporting Vicuna (7b, 13b), ChatGLM-6b" -#~ " (int4, int8) - TODO: codegen2, " -#~ "codet5p" -#~ msgstr "多模型支持 - 支持多种大语言模型, 当前已支持Vicuna(7b,13b), ChatGLM-6b(int4, int8)" - -#~ msgid "" -#~ "Full documentation on all methods, " -#~ "classes, installation methods, and integration" -#~ " setups for DB-GPT." -#~ msgstr "关于DB-GPT的所有方法、类、安装方法和集成设置的完整文档。" - -#~ msgid "" -#~ "**DB-GPT** is an open-source " -#~ "framework for large models in the " -#~ "database field. Its purpose is to " -#~ "build infrastructure for the domain of" -#~ " large models, making it easier and" -#~ " more convenient to develop applications" -#~ " around databases." -#~ msgstr "" - -#~ msgid "By developing various technical capabilities such as" -#~ msgstr "" - -#~ msgid "SMMF(Service-oriented Multi-model Management Framework)" -#~ msgstr "" - -#~ msgid "Text2SQL Fine-tuning" -#~ msgstr "" - -#~ msgid "RAG(Retrieval Augmented Generation) framework and optimization" -#~ msgstr "" - -#~ msgid "Data-Driven Agents framework collaboration" -#~ msgstr "" - -#~ msgid "" -#~ "5. GBI(Generative Business intelligence) etc," -#~ " DB-GPT simplifies the construction " -#~ "of large model applications based on " -#~ "databases." -#~ msgstr "" - -#~ msgid "" -#~ "**1. Private Domain Q&A & Data " -#~ "Processing** Supports custom construction of" -#~ " knowledge bases through methods such " -#~ "as built-in, multi-file format " -#~ "uploads, and plugin-based web scraping." -#~ " Enables unified vector storage and " -#~ "retrieval of massive structured and " -#~ "unstructured data." -#~ msgstr "" - -#~ msgid "" -#~ "**2.Multi-Data Source & GBI(Generative " -#~ "Business intelligence)** Supports interaction " -#~ "between natural language and various " -#~ "data sources such as Excel, databases," -#~ " and data warehouses. Also supports " -#~ "analysis reporting." -#~ msgstr "" - -#~ msgid "" -#~ "**3.SMMF(Service-oriented Multi-model " -#~ "Management Framework)** Supports a wide " -#~ "range of models, including dozens of " -#~ "large language models such as open-" -#~ "source models and API proxies. Examples" -#~ " include LLaMA/LLaMA2, Baichuan, ChatGLM, " -#~ "Wenxin, Tongyi, Zhipu, Xinghuo, etc." -#~ msgstr "" - -#~ msgid "" -#~ "**4.Automated Fine-tuning** A lightweight " -#~ "framework for automated fine-tuning " -#~ "built around large language models, " -#~ "Text2SQL datasets, and methods like " -#~ "LoRA/QLoRA/Pturning. Makes TextSQL fine-tuning" -#~ " as convenient as a production line." -#~ msgstr "" - -#~ msgid "" -#~ "**5.Data-Driven Multi-Agents & Plugins**" -#~ " Supports executing tasks through custom" -#~ " plugins and natively supports the " -#~ "Auto-GPT plugin model. Agents protocol " -#~ "follows the Agent Protocol standard." -#~ msgstr "" - -#~ msgid "" -#~ "**6.Privacy and Security** Ensures data " -#~ "privacy and security through techniques " -#~ "such as privatizing large models and " -#~ "proxy de-identification." -#~ msgstr "" - -#~ msgid "Coming soon..." -#~ msgstr "" - -#~ msgid "`Tutorials <.getting_started/tutorials.html>`_" -#~ msgstr "`教程 <.getting_started/tutorials.html>`_" - -#~ msgid "" -#~ "DB-GPT is an open-source framework" -#~ " for large models in the database " -#~ "field. Its purpose is to build " -#~ "infrastructure for the domain of large" -#~ " models, making it easier and more" -#~ " convenient to develop applications around" -#~ " databases. By developing various technical" -#~ " capabilities such as **1. SMMF(Service-" -#~ "oriented Multi-model Management Framework)**" -#~ " **2. Text2SQL Fine-tuning** **3. " -#~ "RAG(Retrieval Augmented Generation) framework " -#~ "and optimization** **4. Data-Driven " -#~ "Agents framework collaboration** **5. " -#~ "GBI(Generative Business intelligence)** etc, " -#~ "DB-GPT simplifies the construction of " -#~ "large model applications based on " -#~ "databases." -#~ msgstr "" - -#~ msgid "" -#~ "**1. Private Domain Q&A & Data " -#~ "Processing** ::Supports custom construction of" -#~ " knowledge bases through methods such " -#~ "as built-in, multi-file format " -#~ "uploads, and plugin-based web scraping." -#~ " Enables unified vector storage and " -#~ "retrieval of massive structured and " -#~ "unstructured data." -#~ msgstr "" - -#~ msgid "" -#~ "**2.Multi-Data Source & GBI(Generative " -#~ "Business intelligence)** ::Supports interaction " -#~ "between natural language and various " -#~ "data sources such as Excel, databases," -#~ " and data warehouses. Also supports " -#~ "analysis reporting." -#~ msgstr "" - -#~ msgid "" -#~ "**3.SMMF(Service-oriented Multi-model " -#~ "Management Framework)** ::Supports a wide " -#~ "range of models, including dozens of " -#~ "large language models such as open-" -#~ "source models and API proxies. Examples" -#~ " include LLaMA/LLaMA2, Baichuan, ChatGLM, " -#~ "Wenxin, Tongyi, Zhipu, Xinghuo, etc." -#~ msgstr "" - -#~ msgid "" -#~ "**4.Automated Fine-tuning** ::A lightweight" -#~ " framework for automated fine-tuning " -#~ "built around large language models, " -#~ "Text2SQL datasets, and methods like " -#~ "LoRA/QLoRA/Pturning. Makes TextSQL fine-tuning" -#~ " as convenient as a production line." -#~ msgstr "" - -#~ msgid "" -#~ "**5.Data-Driven Multi-Agents & Plugins**" -#~ " ::Supports executing tasks through custom" -#~ " plugins and natively supports the " -#~ "Auto-GPT plugin model. Agents protocol " -#~ "follows the Agent Protocol standard." -#~ msgstr "" - -#~ msgid "" -#~ "**6.Privacy and Security** ::Ensures data " -#~ "privacy and security through techniques " -#~ "such as privatizing large models and " -#~ "proxy de-identification." -#~ msgstr "" - -#~ msgid "" -#~ "How to get started using DB-GPT" -#~ " to interact with your data and " -#~ "environment." -#~ msgstr "开始使用DB-GPT与您的数据环境进行交互。" - -#~ msgid "" -#~ "It's very important for DB-GPT, " -#~ "DB-GPT also provide standard, extendable" -#~ " interfaces." -#~ msgstr "DB-GPT还提供了标准的、可扩展的接口。" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/modules/connections.po b/docs/locales/zh_CN/LC_MESSAGES/modules/connections.po deleted file mode 100644 index 43f887c14..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/modules/connections.po +++ /dev/null @@ -1,49 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 0.3.0\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-06-14 14:51+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../modules/connections.rst:2 ../../modules/connections.rst:10 -#: c9783fd80b0b476abfbf25d4aa23b6ae -msgid "Connections" -msgstr "连接模块" - -#: ../../modules/connections.rst:3 95fecfbcae0e4170affd6a5e41a4fe56 -#, fuzzy -msgid "" -"**In order to interact more conveniently with users' private " -"environments, the project has designed a connection module, which can " -"support connection to databases, Excel, knowledge bases, and other " -"environments to achieve information and data exchange.**" -msgstr "为了更方便地与用户的私有环境进行交互，项目设计了一个连接模块，可以支持与数据库、Excel、知识库等环境的连接，实现信息和数据的交换。" - -#: ../../modules/connections.rst:5 3a5a6124903c4d1fba8a8eb8426616b7 -msgid "" -"DB-GPT provides base class BaseConnect, you can inheriting and implement " -"get_session(), get_table_names(), get_index_info(), get_database_list() " -"and run()." -msgstr "DB-GPT提供了基础连接模块，你可以继承这个类，然后实现get_session(), get_table_names(), get_index_info(), get_database_list() " -"and run()这些方法即可，如果你的数据库是关系型数据库，可以直接继承RDBMSDatabase即可" - -#: ../../modules/connections.rst:7 78ef1226d576458fbd1a9f1043936fc8 -msgid "" -"`mysql_connection <./connections/mysql_connection.html>`_: supported " -"mysql_connection." -msgstr "mysql connection使用方法" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/modules/connections/mysql/mysql_connection.po b/docs/locales/zh_CN/LC_MESSAGES/modules/connections/mysql/mysql_connection.po deleted file mode 100644 index 2e2c2a7ca..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/modules/connections/mysql/mysql_connection.po +++ /dev/null @@ -1,36 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 0.3.0\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-06-14 14:51+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../modules/connections/mysql/mysql_connection.md:1 -#: 69e13b9e53ff466c9ec85715741dd938 -msgid "MYSQL Connection" -msgstr "MYSQL连接" - -#: ../../modules/connections/mysql/mysql_connection.md:3 -#: 4b8446fe31204688a87a5cff1180bec1 -msgid "MYSQL can connect mysql server." -msgstr "MYSQL可以连接mysql server" - -#: ../../modules/connections/mysql/mysql_connection.md:5 -#: 5a2141fba4bd41269d4ad73885067e0d -msgid "inheriting the RDBMSDatabase" -msgstr "继承RDBMSDatabase" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/modules/index.po b/docs/locales/zh_CN/LC_MESSAGES/modules/index.po deleted file mode 100644 index 7a9a83233..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/modules/index.po +++ /dev/null @@ -1,38 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 0.3.0\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-06-11 14:10+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.11.0\n" - -#: ../../modules/index.md:1 a7cda547b08244fdad5efc00b164432d -msgid "Vector storage and indexing" -msgstr "向量存储和索引" - -#: ../../modules/index.md:3 fcbfbe3dda3d47d8a8ca2fefb1750b9a -msgid "" -"In order to facilitate the management of knowledge after vectorization, " -"we have built-in multiple vector storage engines, from memory-based " -"Chroma to distributed Milvus. Users can choose different storage engines " -"according to their own scenario needs. The storage of knowledge vectors " -"is the cornerstone of AI capability enhancement. As the intermediate " -"language for interaction between humans and large language models, " -"vectors play a very important role in this project." -msgstr "为了便于知识向量化后的管理，我们内置了多个向量存储引擎，从基于内存的Chroma" -"到分布式的Milvus。用户可以根据自己的场景需求选择不同的存储引擎。知识向量的存储是增" -"强人工智能能力的基石。作为人类和大型语言模型之间交互的中间语言，向量在这个项目中扮演" -"着非常重要的角色。" diff --git a/docs/locales/zh_CN/LC_MESSAGES/modules/knowledge.po b/docs/locales/zh_CN/LC_MESSAGES/modules/knowledge.po deleted file mode 100644 index bb2dae7af..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/modules/knowledge.po +++ /dev/null @@ -1,251 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 0.3.0\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-11-02 21:04+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../modules/knowledge.md:1 b94b3b15cb2441ed9d78abd222a717b7 -msgid "Knowledge" -msgstr "知识" - -#: ../../modules/knowledge.md:3 c6d6e308a6ce42948d29e928136ef561 -#, fuzzy -msgid "" -"As the knowledge base is currently the most significant user demand " -"scenario, we natively support the construction and processing of " -"knowledge bases. At the same time, we also provide multiple knowledge " -"base management strategies in this project, such as:" -msgstr "" -"由于知识库是当前用户需求最显著的场景，我们原生支持知识库的构建和处理。同时，我们还在本项目中提供了多种知识库管理策略，如:pdf,md , " -"txt, word, ppt" - -#: ../../modules/knowledge.md:4 268abc408d40410ba90cf5f121dc5270 -msgid "Default built-in knowledge base" -msgstr "" - -#: ../../modules/knowledge.md:5 558c3364c38b458a8ebf81030efc2a48 -msgid "Custom addition of knowledge bases" -msgstr "" - -#: ../../modules/knowledge.md:6 9cb3ce62da1440579c095848c7aef88c -msgid "" -"Various usage scenarios such as constructing knowledge bases through " -"plugin capabilities and web crawling. Users only need to organize the " -"knowledge documents, and they can use our existing capabilities to build " -"the knowledge base required for the large model." -msgstr "" - -#: ../../modules/knowledge.md:9 b8ca6bc4dd9845baa56e36eea7fac2a2 -#, fuzzy -msgid "Create your own knowledge repository" -msgstr "创建你自己的知识库" - -#: ../../modules/knowledge.md:11 17d7178a67924f43aa5b6293707ef041 -msgid "" -"1.Place personal knowledge files or folders in the pilot/datasets " -"directory." -msgstr "" - -#: ../../modules/knowledge.md:13 31c31f14bf444981939689f9a9fb038a -#, fuzzy -msgid "" -"We currently support many document formats: txt, pdf, md, html, doc, ppt," -" and url." -msgstr "当前支持txt, pdf, md, html, doc, ppt, url文档格式" - -#: ../../modules/knowledge.md:15 9ad2f2e05f8842a9b9d8469a3704df23 -msgid "before execution:" -msgstr "开始前" - -#: ../../modules/knowledge.md:22 6fd2775914b641c4b8e486417b558ea6 -msgid "" -"2.Update your .env, set your vector store type, VECTOR_STORE_TYPE=Chroma " -"(now only support Chroma and Milvus, if you set Milvus, please set " -"MILVUS_URL and MILVUS_PORT)" -msgstr "" - -#: ../../modules/knowledge.md:25 131c5f58898a4682940910980edb2043 -msgid "2.Run the knowledge repository initialization command" -msgstr "" - -#: ../../modules/knowledge.md:31 2cf550f17881497bb881b19efcc18c23 -msgid "" -"Optionally, you can run `dbgpt knowledge load --help` command to see more" -" usage." -msgstr "" - -#: ../../modules/knowledge.md:33 c8a2ea571b944bdfbcad48fa8b54fcc9 -msgid "" -"3.Add the knowledge repository in the interface by entering the name of " -"your knowledge repository (if not specified, enter \"default\") so you " -"can use it for Q&A based on your knowledge base." -msgstr "" - -#: ../../modules/knowledge.md:35 b701170ad75e49dea7d7734c15681e0f -msgid "" -"Note that the default vector model used is text2vec-large-chinese (which " -"is a large model, so if your personal computer configuration is not " -"enough, it is recommended to use text2vec-base-chinese). Therefore, " -"ensure that you download the model and place it in the models directory." -msgstr "" -"注意，这里默认向量模型是text2vec-large-chinese(模型比较大，如果个人电脑配置不够建议采用text2vec-base-" -"chinese),因此确保需要将模型download下来放到models目录中。" - -#~ msgid "before execution: python -m spacy download zh_core_web_sm" -#~ msgstr "在执行之前请先执行python -m spacy download zh_core_web_sm" - -#~ msgid "2.Run the knowledge repository script in the tools directory." -#~ msgstr "3.在tools目录执行知识入库脚本" - -#~ msgid "" -#~ "python tools/knowledge_init.py note : " -#~ "--vector_name : your vector store name" -#~ " default_value:default" -#~ msgstr "" - -#~ msgid "" -#~ "3.Add the knowledge repository in the" -#~ " interface by entering the name of" -#~ " your knowledge repository (if not " -#~ "specified, enter \"default\") so you can" -#~ " use it for Q&A based on your" -#~ " knowledge base." -#~ msgstr "如果选择新增知识库，在界面上新增知识库输入你的知识库名" - -#~ msgid "" -#~ "1.Place personal knowledge files or " -#~ "folders in the pilot/datasets directory." -#~ msgstr "1.将个人知识文件或文件夹放在pilot/datasets目录中。" - -#~ msgid "" -#~ "2.Update your .env, set your vector " -#~ "store type, VECTOR_STORE_TYPE=Chroma (now only" -#~ " support Chroma and Milvus, if you" -#~ " set Milvus, please set MILVUS_URL " -#~ "and MILVUS_PORT)" -#~ msgstr "2.更新你的.env，设置你的向量存储类型，VECTOR_STORE_TYPE=Chroma(现在只支持Chroma和Milvus，如果你设置了Milvus，请设置MILVUS_URL和MILVUS_PORT)" - -#~ msgid "" -#~ "We currently support many document " -#~ "formats: raw text, txt, pdf, md, " -#~ "html, doc, ppt, and url. In the" -#~ " future, we will continue to support" -#~ " more types of knowledge, including " -#~ "audio, video, various databases, and big" -#~ " data sources. Of course, we look " -#~ "forward to your active participation in" -#~ " contributing code." -#~ msgstr "" - -#~ msgid "1.prepare" -#~ msgstr "准备" - -#~ msgid "" -#~ "2.prepare embedding model, you can " -#~ "download from https://huggingface.co/. Notice " -#~ "you have installed git-lfs." -#~ msgstr "" -#~ "提前准备Embedding Model, 你可以在https://huggingface.co/进行下载，注意" -#~ "：你需要先安装git-lfs.eg: git clone " -#~ "https://huggingface.co/THUDM/chatglm2-6b" - -#~ msgid "" -#~ "eg: git clone https://huggingface.co/sentence-" -#~ "transformers/all-MiniLM-L6-v2" -#~ msgstr "" -#~ "eg: git clone https://huggingface.co/sentence-" -#~ "transformers/all-MiniLM-L6-v2" - -#~ msgid "" -#~ "3.prepare vector_store instance and vector " -#~ "store config, now we support Chroma, " -#~ "Milvus and Weaviate." -#~ msgstr "提前准备向量数据库环境，目前支持Chroma, Milvus and Weaviate向量数据库" - -#~ msgid "" -#~ "3.init Url Type EmbeddingEngine api and" -#~ " embedding your document into vector " -#~ "store in your code." -#~ msgstr "初始化 Url类型 EmbeddingEngine api， 将url文档embedding向量化到向量数据库 " - -#~ msgid "If you want to add your source_reader or text_splitter, do this:" -#~ msgstr "如果你想手动添加你自定义的source_reader和text_splitter, 请参考:" - -#~ msgid "" -#~ "4.init Document Type EmbeddingEngine api " -#~ "and embedding your document into vector" -#~ " store in your code. Document type" -#~ " can be .txt, .pdf, .md, .doc, " -#~ ".ppt." -#~ msgstr "" -#~ "初始化 文档型类型 EmbeddingEngine api， " -#~ "将文档embedding向量化到向量数据库(文档可以是.txt, .pdf, .md, .html," -#~ " .doc, .ppt)" - -#~ msgid "" -#~ "5.init TEXT Type EmbeddingEngine api and" -#~ " embedding your document into vector " -#~ "store in your code." -#~ msgstr "初始化TEXT类型 EmbeddingEngine api， 将文档embedding向量化到向量数据库" - -#~ msgid "4.similar search based on your knowledge base. ::" -#~ msgstr "在知识库进行相似性搜索" - -#~ msgid "" -#~ "`pdf_embedding <./knowledge/pdf/pdf_embedding.html>`_: " -#~ "supported pdf embedding." -#~ msgstr "" -#~ "pdf_embedding <./knowledge/pdf_embedding.html>`_: " -#~ "supported pdf embedding." - -#~ msgid "" -#~ "`markdown_embedding " -#~ "<./knowledge/markdown/markdown_embedding.html>`_: supported " -#~ "markdown embedding." -#~ msgstr "" -#~ "pdf_embedding <./knowledge/pdf_embedding.html>`_: " -#~ "supported pdf embedding." - -#~ msgid "" -#~ "`word_embedding <./knowledge/word/word_embedding.html>`_: " -#~ "supported word embedding." -#~ msgstr "" -#~ "pdf_embedding <./knowledge/pdf_embedding.html>`_: " -#~ "supported pdf embedding." - -#~ msgid "" -#~ "`url_embedding <./knowledge/url/url_embedding.html>`_: " -#~ "supported url embedding." -#~ msgstr "" -#~ "pdf_embedding <./knowledge/pdf_embedding.html>`_: " -#~ "supported pdf embedding." - -#~ msgid "" -#~ "`ppt_embedding <./knowledge/ppt/ppt_embedding.html>`_: " -#~ "supported ppt embedding." -#~ msgstr "" -#~ "pdf_embedding <./knowledge/pdf_embedding.html>`_: " -#~ "supported pdf embedding." - -#~ msgid "" -#~ "`string_embedding <./knowledge/string/string_embedding.html>`_:" -#~ " supported raw text embedding." -#~ msgstr "" -#~ "pdf_embedding <./knowledge/pdf_embedding.html>`_: " -#~ "supported pdf embedding." - diff --git a/docs/locales/zh_CN/LC_MESSAGES/modules/knowledge/markdown/markdown_embedding.po b/docs/locales/zh_CN/LC_MESSAGES/modules/knowledge/markdown/markdown_embedding.po deleted file mode 100644 index e975215af..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/modules/knowledge/markdown/markdown_embedding.po +++ /dev/null @@ -1,56 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 0.3.0\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-07-13 15:39+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../modules/knowledge/markdown/markdown_embedding.md:1 -#: 6d4eb4d8566b4dbaa301715148342aca -#, fuzzy -msgid "Markdown" -msgstr "MarkdownEmbedding" - -#: ../../modules/knowledge/markdown/markdown_embedding.md:3 -#: 050625646fa14cb1822d0d430fdf06ec -msgid "" -"markdown embedding can import md text into a vector knowledge base. The " -"entire embedding process includes the read (loading data), data_process " -"(data processing), and index_to_store (embedding to the vector database) " -"methods." -msgstr "" -"markdown embedding 可以导入md格式的文档到向量数据库， 整个导入过程分为数据读取read(), " -"数据预处理data_process()和数据进向量数据库index_to_store()" - -#: ../../modules/knowledge/markdown/markdown_embedding.md:5 -#: af1313489c164e968def2f5f1716a522 -msgid "inheriting the SourceEmbedding" -msgstr "继承SourceEmbedding" - -#: ../../modules/knowledge/markdown/markdown_embedding.md:18 -#: aebe894f955b44f3ac677ce50d47c846 -#, fuzzy -msgid "" -"implement read() and data_process() read() method allows you to read data" -" and split data into chunk" -msgstr "实现read方法可以加载数据" - -#: ../../modules/knowledge/markdown/markdown_embedding.md:41 -#: d53a087726be4a0dbb8dadbeb772442b -msgid "data_process() method allows you to pre processing your ways" -msgstr "实现data_process方法可以进行数据预处理" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/modules/knowledge/pdf/pdf_embedding.po b/docs/locales/zh_CN/LC_MESSAGES/modules/knowledge/pdf/pdf_embedding.po deleted file mode 100644 index 30960d3bd..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/modules/knowledge/pdf/pdf_embedding.po +++ /dev/null @@ -1,59 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 0.3.0\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-07-13 15:39+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../modules/knowledge/pdf/pdf_embedding.md:1 -#: edf96281acc04612a3384b451dc71391 -msgid "PDF" -msgstr "" - -#: ../../modules/knowledge/pdf/pdf_embedding.md:3 -#: fdc7396cc2eb4186bb28ea8c491738bc -#, fuzzy -msgid "" -"pdfembedding can import PDF text into a vector knowledge base. The entire" -" embedding process includes the read (loading data), data_process (data " -"processing), and index_to_store (embedding to the vector database) " -"methods." -msgstr "" -"pdf embedding 可以导入pdf格式的文档到向量数据库， 整个导入过程分为数据读取read(), " -"数据预处理data_process()和数据进向量数据库index_to_store()" - -#: ../../modules/knowledge/pdf/pdf_embedding.md:5 -#: d4950371bace43d8957bce9757d77b6e -msgid "inheriting the SourceEmbedding" -msgstr "继承SourceEmbedding" - -#: ../../modules/knowledge/pdf/pdf_embedding.md:18 -#: 990c46bba6f3438da542417e4addb96f -#, fuzzy -msgid "" -"implement read() and data_process() read() method allows you to read data" -" and split data into chunk" -msgstr "实现read方法可以加载数据" - -#: ../../modules/knowledge/pdf/pdf_embedding.md:39 -#: 29cf5a37da2f4ad7ab66750970f62d3f -msgid "data_process() method allows you to pre processing your ways" -msgstr "实现data_process方法可以进行数据预处理" - -#~ msgid "PDFEmbedding" -#~ msgstr "" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/modules/knowledge/ppt/ppt_embedding.po b/docs/locales/zh_CN/LC_MESSAGES/modules/knowledge/ppt/ppt_embedding.po deleted file mode 100644 index 7a8e80c3a..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/modules/knowledge/ppt/ppt_embedding.po +++ /dev/null @@ -1,58 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 0.3.0\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-07-13 15:39+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../modules/knowledge/ppt/ppt_embedding.md:1 -#: 86b98a120d0d4796a034c47a23ec8a03 -msgid "PPT" -msgstr "" - -#: ../../modules/knowledge/ppt/ppt_embedding.md:3 -#: af78e8c3a6c24bf79e03da41c6d13fba -msgid "" -"ppt embedding can import ppt text into a vector knowledge base. The " -"entire embedding process includes the read (loading data), data_process " -"(data processing), and index_to_store (embedding to the vector database) " -"methods." -msgstr "" -"ppt embedding 可以导入ppt格式的文档到向量数据库， 整个导入过程分为数据读取read(), " -"数据预处理data_process()和数据进向量数据库index_to_store()" - -#: ../../modules/knowledge/ppt/ppt_embedding.md:5 -#: 0ddb5ec40a4e4864b63e7f578c2f3c34 -msgid "inheriting the SourceEmbedding" -msgstr "继承SourceEmbedding" - -#: ../../modules/knowledge/ppt/ppt_embedding.md:23 -#: b74741f4a1814fe19842985a3f960972 -#, fuzzy -msgid "" -"implement read() and data_process() read() method allows you to read data" -" and split data into chunk" -msgstr "实现read方法可以加载数据" - -#: ../../modules/knowledge/ppt/ppt_embedding.md:44 -#: bc1e705c60cd4dde921150cb814ac8ae -msgid "data_process() method allows you to pre processing your ways" -msgstr "实现data_process方法可以进行数据预处理" - -#~ msgid "PPTEmbedding" -#~ msgstr "" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/modules/knowledge/string/string_embedding.po b/docs/locales/zh_CN/LC_MESSAGES/modules/knowledge/string/string_embedding.po deleted file mode 100644 index d88fe1071..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/modules/knowledge/string/string_embedding.po +++ /dev/null @@ -1,52 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.3.0\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-07-13 15:39+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../modules/knowledge/string/string_embedding.md:1 -#: 0dbae4a197aa4e45a16cfd90c137c8f2 -msgid "String" -msgstr "" - -#: ../../modules/knowledge/string/string_embedding.md:3 -#: bf9f445b1d2045848ad3c663e4551c1f -msgid "" -"string embedding can import a long raw text into a vector knowledge base." -" The entire embedding process includes the read (loading data), " -"data_process (data processing), and index_to_store (embedding to the " -"vector database) methods." -msgstr "" - -#: ../../modules/knowledge/string/string_embedding.md:5 -#: 4418539511024c2fa8cf1e73ade226a8 -msgid "inheriting the SourceEmbedding" -msgstr "" - -#: ../../modules/knowledge/string/string_embedding.md:23 -#: 178050a4cdd6429aa73406043d89869b -msgid "" -"implement read() and data_process() read() method allows you to read data" -" and split data into chunk" -msgstr "" - -#: ../../modules/knowledge/string/string_embedding.md:32 -#: fdaf95f201624242bbfcff36480e1819 -msgid "data_process() method allows you to pre processing your ways" -msgstr "" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/modules/knowledge/url/url_embedding.po b/docs/locales/zh_CN/LC_MESSAGES/modules/knowledge/url/url_embedding.po deleted file mode 100644 index 6b45cc766..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/modules/knowledge/url/url_embedding.po +++ /dev/null @@ -1,58 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 0.3.0\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-07-13 15:39+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../modules/knowledge/url/url_embedding.md:1 -#: c1db535b997f4a90a75806f389200a4e -msgid "URL" -msgstr "" - -#: ../../modules/knowledge/url/url_embedding.md:3 -#: a4e3929be4964c35b7d169eaae8f29fe -msgid "" -"url embedding can import PDF text into a vector knowledge base. The " -"entire embedding process includes the read (loading data), data_process " -"(data processing), and index_to_store (embedding to the vector database) " -"methods." -msgstr "" -"url embedding 可以导入url格式的文档到向量数据库， 整个导入过程分为数据读取read(), " -"数据预处理data_process()和数据进向量数据库index_to_store()" - -#: ../../modules/knowledge/url/url_embedding.md:5 -#: 0c0be35a31e84e76a60e9e4ffb61a414 -msgid "inheriting the SourceEmbedding" -msgstr "继承SourceEmbedding" - -#: ../../modules/knowledge/url/url_embedding.md:23 -#: f9916af3adee4da2988e5ed1912f2bdd -#, fuzzy -msgid "" -"implement read() and data_process() read() method allows you to read data" -" and split data into chunk" -msgstr "实现read方法可以加载数据" - -#: ../../modules/knowledge/url/url_embedding.md:44 -#: 56c0720ae3d840069daad2ba7edc8122 -msgid "data_process() method allows you to pre processing your ways" -msgstr "实现data_process方法可以进行数据预处理" - -#~ msgid "URL Embedding" -#~ msgstr "" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/modules/knowledge/word/word_embedding.po b/docs/locales/zh_CN/LC_MESSAGES/modules/knowledge/word/word_embedding.po deleted file mode 100644 index 424a23790..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/modules/knowledge/word/word_embedding.po +++ /dev/null @@ -1,58 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 0.3.0\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-07-13 15:39+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../modules/knowledge/word/word_embedding.md:1 -#: fa236aa8d2e5471d8436e0ec60f906e8 -msgid "Word" -msgstr "" - -#: ../../modules/knowledge/word/word_embedding.md:3 -#: 02d0c183f7f646a7b74e22d0166c8718 -msgid "" -"word embedding can import word doc/docx text into a vector knowledge " -"base. The entire embedding process includes the read (loading data), " -"data_process (data processing), and index_to_store (embedding to the " -"vector database) methods." -msgstr "" -"word embedding 可以导入word格式的doc文档到向量数据库， 整个导入过程分为数据读取read(), " -"数据预处理data_process()和数据进向量数据库index_to_store()" - -#: ../../modules/knowledge/word/word_embedding.md:5 -#: ffa094cb7739457d88666c5b624bf078 -msgid "inheriting the SourceEmbedding" -msgstr "继承SourceEmbedding" - -#: ../../modules/knowledge/word/word_embedding.md:18 -#: 146f03d86fd147b7847b7b907d52b408 -#, fuzzy -msgid "" -"implement read() and data_process() read() method allows you to read data" -" and split data into chunk" -msgstr "实现read方法可以加载数据" - -#: ../../modules/knowledge/word/word_embedding.md:39 -#: b29a213855af4446a64aadc5a3b76739 -msgid "data_process() method allows you to pre processing your ways" -msgstr "实现data_process方法可以进行数据预处理" - -#~ msgid "WordEmbedding" -#~ msgstr "" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/modules/knownledge.po b/docs/locales/zh_CN/LC_MESSAGES/modules/knownledge.po deleted file mode 100644 index 7cd855daa..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/modules/knownledge.po +++ /dev/null @@ -1,110 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 0.3.0\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-09-01 18:16+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../modules/knownledge.md:1 ba585bf3ba464c32a156d308f39e65dc -msgid "Knownledge" -msgstr "知识" - -#: ../../modules/knownledge.md:3 bc5d67c51b004ff8b2d1bbca17fd4aa7 -msgid "" -"As the knowledge base is currently the most significant user demand " -"scenario, we natively support the construction and processing of " -"knowledge bases. At the same time, we also provide multiple knowledge " -"base management strategies in this project, such as:" -msgstr "由于知识库是当前用户需求最显著的场景，我们原生支持知识库的构建和处理。同时，我们还在本项目中提供了多种知识库管理策略，如:" - -#: ../../modules/knownledge.md:4 519f2686500340d191ad5a91eabc7676 -msgid "Default built-in knowledge base" -msgstr "默认内置知识库" - -#: ../../modules/knownledge.md:5 93a25018fc144dfe98fcea0755f2ea94 -msgid "Custom addition of knowledge bases" -msgstr "自定义新增知识库" - -#: ../../modules/knownledge.md:6 37359e14b2464b2c9fc4e5621755bb0d -msgid "" -"Various usage scenarios such as constructing knowledge bases through " -"plugin capabilities and web crawling. Users only need to organize the " -"knowledge documents, and they can use our existing capabilities to build " -"the knowledge base required for the large model." -msgstr "各种使用场景，例如通过插件功能和爬虫构建知识库。用户只需要组织知识文档，并且他们可以使用我们现有的功能来构建大型模型所需的知识库。" - -#: ../../modules/knownledge.md:9 656fcb11886546df9e058227d94481b3 -msgid "Create your own knowledge repository" -msgstr "创建你自己的知识库" - -#: ../../modules/knownledge.md:11 37fc3ae2cfe044f8ac61de484bf0653d -msgid "" -"1.Place personal knowledge files or folders in the pilot/datasets " -"directory." -msgstr "1.将个人知识文件或文件夹放在pilot/datasets目录中。" - -#: ../../modules/knownledge.md:13 a675d90485834690bfca68b41a10c085 -msgid "" -"We currently support many document formats: txt, pdf, md, html, doc, ppt," -" and url." -msgstr "当前支持txt, pdf, md, doc, ppt, html文档格式" - -#: ../../modules/knownledge.md:15 f2c25b0536ff4b3191e13f3020e883a6 -msgid "before execution:" -msgstr "在执行之前" - -#: ../../modules/knownledge.md:22 65427906c8b54cd699a07ed482251c83 -msgid "" -"2.Update your .env, set your vector store type, VECTOR_STORE_TYPE=Chroma " -"(now only support Chroma and Milvus, if you set Milvus, please set " -"MILVUS_URL and MILVUS_PORT)" -msgstr "2.更新你的.env，设置你的向量存储类型，VECTOR_STORE_TYPE=Chroma(现在只支持Chroma和Milvus，如果你设置了Milvus，请设置MILVUS_URL和MILVUS_PORT)" - -#: ../../modules/knownledge.md:25 287ae6ee51cc4b668d99e48b81147d3f -#, fuzzy -msgid "2.Run the knowledge repository initialization command" -msgstr "2.执行知识入库命令" - -#: ../../modules/knownledge.md:31 1fe0ac58d8354c7fba782901cb0673d8 -msgid "" -"Optionally, you can run `dbgpt knowledge load --help` command to see more" -" usage." -msgstr "另外，你可以运行 `dbgpt knowledge load --help` 命令来查看更多的用法" - -#: ../../modules/knownledge.md:33 e1607e330195470f9087bd4ffbc6d45d -msgid "" -"3.Add the knowledge repository in the interface by entering the name of " -"your knowledge repository (if not specified, enter \"default\") so you " -"can use it for Q&A based on your knowledge base." -msgstr "如果选择新增知识库，在界面上新增知识库输入你的知识库名" - -#: ../../modules/knownledge.md:35 0614e35ccfba42ea9e63881cb481815e -msgid "" -"Note that the default vector model used is text2vec-large-chinese (which " -"is a large model, so if your personal computer configuration is not " -"enough, it is recommended to use text2vec-base-chinese). Therefore, " -"ensure that you download the model and place it in the models directory." -msgstr "" -"注意，这里默认向量模型是text2vec-large-chinese(模型比较大，如果个人电脑配置不够建议采用text2vec-base-" -"chinese),因此确保需要将模型download下来放到models目录中。" - -#~ msgid "" -#~ "Optionally, you can run `python " -#~ "tools/knowledge_init.py -h` command to see " -#~ "more usage." -#~ msgstr "" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/modules/llms.po b/docs/locales/zh_CN/LC_MESSAGES/modules/llms.po deleted file mode 100644 index 068da5a90..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/modules/llms.po +++ /dev/null @@ -1,216 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 0.3.0\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-08-10 16:38+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../modules/llms.md:1 50913b0297da4485ae3fbdb6a90ba6ba -msgid "LLMs" -msgstr "大语言模型" - -#: ../../modules/llms.md:3 608344bb1c6b49dc94487e400a92e1f9 -#, python-format -msgid "" -"In the underlying large model integration, we have designed an open " -"interface that supports integration with various large models. At the " -"same time, we have a very strict control and evaluation mechanism for the" -" effectiveness of the integrated models. In terms of accuracy, the " -"integrated models need to align with the capability of ChatGPT at a level" -" of 85% or higher. We use higher standards to select models, hoping to " -"save users the cumbersome testing and evaluation process in the process " -"of use." -msgstr "在底层大模型接入中，我们设计了开放的接口，支持对接多种大模型。同时对于接入模型的效果，我们有非常严格的把控与评审机制。对大模型能力上与ChatGPT对比，在准确率上需要满足85%以上的能力对齐。我们用更高的标准筛选模型，是期望在用户使用过程中，可以省去前面繁琐的测试评估环节。" - -#: ../../modules/llms.md:5 138db7b30c624665930a7d532b557ea8 -msgid "Multi LLMs Usage" -msgstr "多模型使用" - -#: ../../modules/llms.md:6 1c82e93d4b334b209d7f3e63c82efb0a -msgid "" -"To use multiple models, modify the LLM_MODEL parameter in the .env " -"configuration file to switch between the models." -msgstr "如果要使用不同的模型，请修改.env配置文件中的LLM MODEL参数以在模型之间切换。" - -#: ../../modules/llms.md:8 5b1846c29dbe42c4b95a2e26dc85a358 -msgid "" -"Notice: you can create .env file from .env.template, just use command " -"like this:" -msgstr "注意:你可以从 .env.template 创建 .env 文件。只需使用如下命令:" - -#: ../../modules/llms.md:14 95ecc02369ab4075bd245662809e4cc9 -#, fuzzy -msgid "" -"now we support models vicuna-13b, vicuna-7b, chatglm-6b, flan-t5-base, " -"guanaco-33b-merged, falcon-40b, gorilla-7b, llama-2-7b, llama-2-13b, " -"baichuan-7b, baichuan-13b" -msgstr "" -"现在我们支持的模型有vicuna-13b, vicuna-7b, chatglm-6b, flan-t5-base, guanaco-33b-" -"merged, falcon-40b, gorilla-7b." - -#: ../../modules/llms.md:16 9397c2959c244f5595c74b417c2b7edb -msgid "" -"if you want use other model, such as chatglm-6b, you just need update " -".env config file." -msgstr "如果你想使用其他模型，比如chatglm-6b, 仅仅需要修改.env 配置文件" - -#: ../../modules/llms.md:20 fe143c38ed9f48adb9042b648529e64c -msgid "" -"or chatglm2-6b, which is the second-generation version of the open-" -"source bilingual (Chinese-English) chat model ChatGLM-6B." -msgstr "" - -#: ../../modules/llms.md:27 d43eb7fe0a4949a1a4772cf8e91b028c -msgid "Run Model with cpu." -msgstr "用CPU运行模型" - -#: ../../modules/llms.md:28 e6caaf6efa774131b8bef036c440db19 -msgid "" -"we alse support smaller models, like gpt4all. you can use it with " -"cpu/mps(M1/M2), Download from [gpt4all model](https://gpt4all.io/models" -"/ggml-gpt4all-j-v1.3-groovy.bin)" -msgstr "" -"我们也支持一些小模型，你可以通过CPU/MPS(M1、M2)运行, 模型下载[gpt4all](https://gpt4all.io/models" -"/ggml-gpt4all-j-v1.3-groovy.bin)" - -#: ../../modules/llms.md:30 8fc07b5d2d79496083ee3a279a131eb8 -msgid "put it in the models path, then change .env config." -msgstr "将模型放在models路径, 修改.env 配置文件" - -#: ../../modules/llms.md:35 ddd90d901eaf4867934ea58fdb2398ab -msgid "" -"DB-GPT provides a model load adapter and chat adapter. load adapter which" -" allows you to easily adapt load different LLM models by inheriting the " -"BaseLLMAdapter. You just implement match() and loader() method." -msgstr "" -"DB-GPT提供了多模型适配器load adapter和chat adapter.load adapter通过继承BaseLLMAdapter类," -" 实现match和loader方法允许你适配不同的LLM." - -#: ../../modules/llms.md:37 a1c446ab4dbe43d9b2558c5fad542069 -msgid "vicuna llm load adapter" -msgstr "vicuna llm load adapter" - -#: ../../modules/llms.md:54 fb8655afefc4411ea1ef97230098e23c -msgid "chatglm load adapter" -msgstr "chatglm load adapter" - -#: ../../modules/llms.md:81 5c8c2b73419049e2b88e5e9d40149187 -msgid "" -"chat adapter which allows you to easily adapt chat different LLM models " -"by inheriting the BaseChatAdpter.you just implement match() and " -"get_generate_stream_func() method" -msgstr "" -"chat " -"adapter通过继承BaseChatAdpter允许你通过实现match和get_generate_stream_func方法允许你适配不同的LLM." - -#: ../../modules/llms.md:83 2d6be71d447846e4921f2e7fde678ae5 -msgid "vicuna llm chat adapter" -msgstr "vicuna llm chat adapter" - -#: ../../modules/llms.md:95 e50e6ef380e74402a131c253f5ef1552 -msgid "chatglm llm chat adapter" -msgstr "chatglm llm chat adapter" - -#: ../../modules/llms.md:108 e1825c1aa2384d4fbd40934ec32a3cf4 -msgid "" -"if you want to integrate your own model, just need to inheriting " -"BaseLLMAdaper and BaseChatAdpter and implement the methods" -msgstr "如果你想集成自己的模型，只需要继承BaseLLMAdaper和BaseChatAdpter类，然后实现里面的方法即可" - -#: ../../modules/llms.md:110 cfc357047ec14638934cc0514514718d -#, fuzzy -msgid "Multi Proxy LLMs" -msgstr "多模型使用" - -#: ../../modules/llms.md:111 5a08dd4f88d4482dbac19403954f60bf -msgid "1. Openai proxy" -msgstr "1. Openai proxy" - -#: ../../modules/llms.md:112 4984400803484dcc8de78252e3f74f9b -msgid "" -"If you haven't deployed a private infrastructure for a large model, or if" -" you want to use DB-GPT in a low-cost and high-efficiency way, you can " -"also use OpenAI's large model as your underlying model." -msgstr "" - -#: ../../modules/llms.md:114 1696bedec29d4385b547a2d977720b76 -msgid "" -"If your environment deploying DB-GPT has access to OpenAI, then modify " -"the .env configuration file as below will work." -msgstr "如果本地能够访问OpenAI，修改.env文件即可" - -#: ../../modules/llms.md:122 908d72c6bdfa40eab24c8966e20f55df -msgid "" -"If you can't access OpenAI locally but have an OpenAI proxy service, you " -"can configure as follows." -msgstr "如果不能访问openapi服务,你可以如下配置" - -#: ../../modules/llms.md:130 141d43ea2f4d49778d5d35ec644ee7f6 -msgid "2. Bard Proxy" -msgstr "2. Bard Proxy" - -#: ../../modules/llms.md:131 47471243adc94f95807e9c0c2a112c20 -msgid "" -"If your environment deploying DB-GPT has access to Bard (F12-> application-> __Secure-" -"1PSID), then modify the .env configuration file as below will work." -msgstr "" - -#: ../../modules/llms.md:139 c6a139d829514d299d92abaa0695b681 -msgid "" -"If you want to use your own bard proxy server like Bard-Proxy, so " -"that you can deploy DB-GPT on your PC easily." -msgstr "如果你想使用 bard proxy server Bard-Proxy 你可以轻松部署 bard proxy server" - -#~ msgid "Multi Proxy LLMs" -#~ msgstr "多模型使用" - -#~ msgid "1. Openai proxy" -#~ msgstr "Openai代理" - -#~ msgid "" -#~ "If you haven't deployed a private " -#~ "infrastructure for a large model, or " -#~ "if you want to use DB-GPT in" -#~ " a low-cost and high-efficiency " -#~ "way, you can also use OpenAI's " -#~ "large model as your underlying model." -#~ msgstr "如果你没有部署私有大模型的资源，或者你想使用低成本启动DB-GPT,你可以使用openai的大模型作为你的底层模型" - -#~ msgid "" -#~ "If your environment deploying DB-GPT " -#~ "has access to OpenAI, then modify " -#~ "the .env configuration file as below " -#~ "will work." -#~ msgstr "如果你的环境能够访问openai，你只需要参考如下修改.env配置文件即可" - -#~ msgid "" -#~ "If you can't access OpenAI locally " -#~ "but have an OpenAI proxy service, " -#~ "you can configure as follows." -#~ msgstr "如果你本地无法访问openai，但是你有一个openai的代理服务，你可以参考如下配置" - -#~ msgid "" -#~ "If your environment deploying DB-GPT " -#~ "has access to https://bard.google.com/ (F12->" -#~ " application-> __Secure-1PSID), then modify" -#~ " the .env configuration file as below" -#~ " will work." -#~ msgstr "" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/modules/plugins.po b/docs/locales/zh_CN/LC_MESSAGES/modules/plugins.po deleted file mode 100644 index 662d7051d..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/modules/plugins.po +++ /dev/null @@ -1,185 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 0.3.0\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-11-03 15:33+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../modules/plugins.md:1 e8c539b65ccd459793e8ed3812903578 -msgid "Plugins" -msgstr "插件" - -#: ../../modules/plugins.md:3 0d6f6bdcf843416fb35d9f51df52bead -msgid "" -"The ability of Agent and Plugin is the core of whether large models can " -"be automated. In this project, we natively support the plugin mode, and " -"large models can automatically achieve their goals. At the same time, in " -"order to give full play to the advantages of the community, the plugins " -"used in this project natively support the Auto-GPT plugin ecology, that " -"is, Auto-GPT plugins can directly run in our project." -msgstr "" -"Agent与插件能力是大模型能否自动化的核心，在本的项目中，原生支持插件模式，大模型可以自动化完成目标。 同时为了充分发挥社区的优势" -"，本项目中所用的插件原生支持Auto-GPT插件生态，即Auto-GPT的插件可以直接在我们的项目中运行。" - -#: ../../modules/plugins.md:5 625763bc41fe417c8e4ea03ab2f8fdfc -#, fuzzy -msgid "The LLM (Language Model) suitable for the Plugin scene is" -msgstr "Plugin场景适用的LLM是 * chatgpt3.5. * chatgpt4." - -#: ../../modules/plugins.md:6 b3bd64693a4f4bf8b64b9224d3e1532e -msgid "chatgpt3.5." -msgstr "" - -#: ../../modules/plugins.md:7 46d9220e63384594b54c2c176077d962 -msgid "chatgpt4." -msgstr "" - -#: ../../modules/plugins.md:10 8c539e139f6648b2bef5dc683b8e093c -#, fuzzy -msgid "Local Plugins" -msgstr "插件" - -#: ../../modules/plugins.md:12 2cc7ba992d524913b3377cad3bf747d3 -msgid "1.1 How to write local plugins." -msgstr "" - -#: ../../modules/plugins.md:14 eddffc1d2c434e45890a9befa1bb5160 -msgid "" -"Local plugins use the Auto-GPT plugin template. A simple example is as " -"follows: first write a plugin file called \"sql_executor.py\"." -msgstr "" - -#: ../../modules/plugins.md:44 06efbea552bb4dc7828d842b779e41d4 -msgid "" -"Then set the \"can_handle_post_prompt\" method of the plugin template to " -"True. In the \"post_prompt\" method, write the prompt information and the" -" mapped plugin function." -msgstr "" - -#: ../../modules/plugins.md:86 afd3cfb379bb463e97e515ae65790830 -msgid "1.2 How to use local plugins" -msgstr "" - -#: ../../modules/plugins.md:88 f43a70e4cb5c4846a5bb8df3853021ba -msgid "" -"Pack your plugin project into `your-plugin.zip` and place it in the " -"`/plugins/` directory of the DB-GPT project. After starting the " -"webserver, you can select and use it in the `Plugin Model` section." -msgstr "" - -#: ../../modules/plugins.md:91 8269458bd7f5480dbc56100865eb1eb0 -#, fuzzy -msgid "Public Plugins" -msgstr "插件" - -#: ../../modules/plugins.md:93 ec5bb7b6b2cf464d8b8400f3dfd9a50e -msgid "1.1 How to use public plugins" -msgstr "" - -#: ../../modules/plugins.md:95 3025a85c905c49b6b2ac3f5c39c84c93 -msgid "" -"By default, after launching the webserver, plugins from the public plugin" -" library `DB-GPT-Plugins` will be automatically loaded. For more details," -" please refer to [DB-GPT-Plugins](https://github.com/csunny/DB-GPT-" -"Plugins)" -msgstr "" - -#: ../../modules/plugins.md:97 e73d7779df254ba49fe7123ce06353aa -msgid "1.2 Contribute to the DB-GPT-Plugins repository" -msgstr "" - -#: ../../modules/plugins.md:99 3297fb00dfc940e8a614c3858640cfe5 -msgid "" -"Please refer to the plugin development process in the public plugin " -"library, and put the configuration parameters in `.plugin_env`" -msgstr "" - -#: ../../modules/plugins.md:101 13280b270b304e139ed67e5b0dafa5b4 -msgid "" -"We warmly welcome everyone to contribute plugins to the public plugin " -"library!" -msgstr "" - -#~ msgid "Local Plugins" -#~ msgstr "插件" - -#~ msgid "1.1 How to write local plugins." -#~ msgstr "如何编写一个本地插件" - -#~ msgid "" -#~ "Local plugins use the Auto-GPT " -#~ "plugin template. A simple example is " -#~ "as follows: first write a plugin " -#~ "file called \"sql_executor.py\"." -#~ msgstr "本地插件使用Auto-GPT插件模板，一个简单的示例如下：首先编写一个插件文件`sql_executor.py`" - -#~ msgid "" -#~ "Then set the \"can_handle_post_prompt\" method" -#~ " of the plugin template to True. " -#~ "In the \"post_prompt\" method, write the" -#~ " prompt information and the mapped " -#~ "plugin function." -#~ msgstr "然后设置can_handle_post_prompt函数为True, 在post_prompt函数中编写prompt信息和插件映射函数" - -#~ msgid "1.2 How to use local plugins" -#~ msgstr "1.2 如何使用本地插件" - -#~ msgid "" -#~ "Pack your plugin project into `your-" -#~ "plugin.zip` and place it in the " -#~ "`/plugins/` directory of the DB-GPT " -#~ "project. After starting the webserver, " -#~ "you can select and use it in " -#~ "the `Plugin Model` section." -#~ msgstr "" -#~ "将您的插件项目打包成your-plugin.zip，并将其放置在DB-" -#~ "GPT项目的/plugins/目录中。启动Web服务器后，您可以在插件模型部分中选择并使用它。" - -#~ msgid "Public Plugins" -#~ msgstr "插件" - -#~ msgid "1.1 How to use public plugins" -#~ msgstr "1.1 如何编写公共插件" - -#~ msgid "" -#~ "By default, after launching the " -#~ "webserver, plugins from the public " -#~ "plugin library `DB-GPT-Plugins` will " -#~ "be automatically loaded. For more " -#~ "details, please refer to [DB-GPT-" -#~ "Plugins](https://github.com/csunny/DB-GPT-Plugins)" -#~ msgstr "" -#~ "默认情况下，在启动Web服务器后，将自动加载来自公共插件库DB-GPT-Plugins的插件。要了解更多详情，请参阅" -#~ "[DB-GPT-Plugins](https://github.com/csunny/DB-GPT-" -#~ "Plugins)" - -#~ msgid "1.2 Contribute to the DB-GPT-Plugins repository" -#~ msgstr "1.2 贡献到DB-GPT-Plugins仓库" - -#~ msgid "" -#~ "Please refer to the plugin development" -#~ " process in the public plugin " -#~ "library, and put the configuration " -#~ "parameters in `.plugin_env`" -#~ msgstr "请参考公共插件库开发过程，将插件配置参数写入.plugin_env文件" - -#~ msgid "" -#~ "We warmly welcome everyone to contribute" -#~ " plugins to the public plugin " -#~ "library!" -#~ msgstr "非常欢迎大家向我们公共插件库贡献插件！" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/modules/prompts.po b/docs/locales/zh_CN/LC_MESSAGES/modules/prompts.po deleted file mode 100644 index 810e20f04..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/modules/prompts.po +++ /dev/null @@ -1,148 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.4.0\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-11-03 11:47+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../modules/prompts.md:1 3c5bdc61dc4a4301acdc9775c854a896 -msgid "Prompts" -msgstr "Prompts" - -#: ../../modules/prompts.md:3 118fc2b85e8b4e02a6868b3bc2a7892c -msgid "" -"**Prompt** is a very important part of the interaction between the large " -"model and the user, and to a certain extent, it determines the quality " -"and accuracy of the answer generated by the large model. In this project," -" we will automatically optimize the corresponding Prompt according to " -"user input and usage scenarios, making it easier and more efficient for " -"users to use large language models." -msgstr "**Prompt**是大模型与用户交互中非常重要的一环，在一定程度上决定了大模型生成答案的质量和准确性。在这个项目中，我们会根据用户输入和使用场景自动地优化相应提示，让用户更轻松、更高效地使用大语言模型。" - -#: ../../modules/prompts.md:5 41614effa0a445b7b5a119311b902305 -msgid "Prompt Management" -msgstr "Prompt 管理" - -#: ../../modules/prompts.md:7 a8ed0a7b3d1243ffa1ed80c24d1ab518 -msgid "" -"Here, you can choose to create a Prompt in **Public Prompts** space or " -"**Private Prompts** space." -msgstr "该页面允许用户选择**公共Prompts**或者**私有Prompts**空间来创建相应的 Prompt。" - -#: ../../modules/prompts.md:9 ../../modules/prompts.md:17 -#: ../../modules/prompts.md:31 ../../modules/prompts.md:45 -#: 68db272acc6b4572aa275940da4b788b 92d46d647bbb4035add92f750511a840 -#: af1789fae8cb47b8a81e68520086f35e d7c2f6f43b5c406d82b7dc5bd92d183c -#: e2f91ca11e784fe5943d0738671f68bf -msgid "image" -msgstr "" - -#: ../../modules/prompts.md:11 102220bf95f04f81acc9a0093458f297 -msgid "" -"The difference between **Public Prompts** and **Private Prompts** is that" -" Prompts in **Public Prompts** space can be viewed and used by all users," -" while prompts in **Private Prompts** space can only be viewed and used " -"by the owner." -msgstr "" -"**公共 Prompts**和**私有 Prompts**空间的区别在于，**公共 Prompts**空间下的 Prompt " -"可供所有的用户查看和使用，而**私有 Prompts**空间下的 Prompt 只能被所有者查看和使用。" - -#: ../../modules/prompts.md:13 2e0d2f6b335a4aacbdc83b7b7042a701 -msgid "Create Prompt" -msgstr "创建 Prompt" - -#: ../../modules/prompts.md:15 c9f8c3d1698941e08b90a35fffb2fce1 -msgid "Click the \"Add Prompts\" button to pop up the following subpage:" -msgstr "点击 \"新增Prompts\"按钮可以弹出如下的子页面：" - -#: ../../modules/prompts.md:19 23ed81a83ab2458f826f2b5d9c55a89a -msgid "" -"**Scene**: It is assumed here that when we have a lot of Prompts, we " -"often classify the Prompts according to scene, such as Prompts in the " -"chat knowledge scene, Prompts in the chat data scene, Prompts in the chat" -" normal scene, etc." -msgstr "" -"**场景**：这里假设，当我们有很多 Prompts 时，往往会根据场景对 Prompts 进行分类，比如在 DB-GPT 项目中，chat " -"knowledge 场景的 Prompts、chat data 场景的 Prompts、chat normal 场景的 Prompts 等等。" - -#: ../../modules/prompts.md:21 11299da493e741869fe67237f1cb1794 -msgid "" -"**Sub Scene**: Continuing with the above, assuming that we have a lot of " -"Prompts, scene classification alone is not enough. For example, in the " -"chat data scenario, there can be many types of sub-scene: anomaly " -"recognition sub scene, attribution analysis sub scene, etc. sub scene is " -"used to distinguish subcategories under each scene." -msgstr "" -"**次级场景**：接着上面的内容，如果我们的 Prompt 很多时，仅使用场景一级分类是不够的。例如，在 chat data " -"场景中，还可以细分为很多的次级场景：异常识别次级场景、归因分析次级场景等等。次级场景是用于区分每个场景下的子类别。" - -#: ../../modules/prompts.md:23 c15d62af27094d14acb6428c0e3e1a1d -msgid "" -"**Name**: Considering that a Prompt generally contains a lot of content, " -"for ease of use and easy search, we need to name the Prompt. Note: The " -"name of the Prompt is not allowed to be repeated. Name is the unique key " -"that identifies a Prompt." -msgstr "" -"**名称**：考虑到每个 Prompt 的内容会非常多，为了方便用户使用和搜索，我们需要给每个 Prompt 命名。注意：Prompt " -"的名称不允许重复，名称是一个 Prompt 的唯一键。" - -#: ../../modules/prompts.md:25 621fe9c729c94e9bbde637b5a1856284 -msgid "**Content**: Here is the actual Prompt content that will be input to LLM." -msgstr "**内容**：这里是实际要输入 LLM 的提示内容。" - -#: ../../modules/prompts.md:27 ac2f153f704c4841a044daaf6548262b -msgid "Edit Prompt" -msgstr "编辑 Prompt" - -#: ../../modules/prompts.md:29 3d6238ea482842e0968f691f3fd0c947 -msgid "" -"Existing Prompts can be edited. Note that except **name**, other items " -"can be modified." -msgstr "已有的 Prompts 可以被编辑，除了名称不可修改，其余的内容均可修改。" - -#: ../../modules/prompts.md:33 7cbe985fd9534471bce5f93a93da82fd -msgid "Delete Prompt" -msgstr "删除 Prompt" - -#: ../../modules/prompts.md:35 849ab9ef2a2c4a29bb827eb373f37b7d -msgid "" -"Ordinary users can only delete Prompts created by themselves in the " -"private Prompts space. Administrator users can delete Prompts in public " -"Prompts spaces and private Prompts spaces." -msgstr "" -"普通用户只能删除他们自己在私有 Prompts 空间中创建的 Prompts，管理员可以删除 公共 Prompts 空间下的 " -"Prompts，也可以删除私有 Prompts 空间下的 Prompts（即使 Prompts 的创建者不是管理员）。" - -#: ../../modules/prompts.md:38 191921e5664d4326b01f0c45dc88a1e5 -msgid "Use Prompt" -msgstr "使用 Prompt" - -#: ../../modules/prompts.md:40 87ad58641f834f30bce178e748d75284 -msgid "" -"Users can find and use Prompts next to the input boxes in each scene. " -"Click to view all contents of Prompts library." -msgstr "用户可以在每个场景中的输入框旁边找到并使用 Prompts。 点击悬浮图标可以查看当前用户能使用的全部 Prompts。" - -#: ../../modules/prompts.md:42 60458c7980174c73bc0d56e9e27cd2b3 -msgid "" -"✓ Hover the mouse over each Prompt to preview the Prompt content. ✓ " -"Click Prompt to automatically fill in the Prompt content in the input " -"box." -msgstr "" -"✓ 将鼠标悬停在每个 Prompt 上，可预览 Prompt 的内容。 ✓ 单击对应的 Prompt，可自动将 Prompt " -"的内容填充到输入框中。" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/modules/server.po b/docs/locales/zh_CN/LC_MESSAGES/modules/server.po deleted file mode 100644 index e7a64f168..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/modules/server.po +++ /dev/null @@ -1,32 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 0.3.0\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-06-11 14:10+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.11.0\n" - -#: ../../modules/server.md:1 e882c271ebc441bca79808bc00f2bc24 -msgid "Server" -msgstr "" - -#: ../../modules/server.md:3 325cc3afd7d04e568c912bbf7f11788d -msgid "" -"TODO: In terms of terminal display, we will provide a multi-platform " -"product interface, including PC, mobile phone, command line, Slack and " -"other platforms." -msgstr "TODO: 在终端展示上，我们将提供多端产品界面。包括PC、手机、命令行、Slack等多种模式。" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/modules/vector.po b/docs/locales/zh_CN/LC_MESSAGES/modules/vector.po deleted file mode 100644 index 9b5e8bed0..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/modules/vector.po +++ /dev/null @@ -1,89 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.2.2\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-07-31 17:15+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../modules/vector.rst:2 ../../modules/vector.rst:19 -#: 3f1436c219c34b138a4db11ff55e070c -msgid "VectorConnector" -msgstr "VectorConnector" - -#: ../../modules/vector.rst:4 55445cdb9379484db2b2127620401adf -msgid "**VectorConnector Introduce**" -msgstr "VectorConnector介绍" - -#: ../../modules/vector.rst:6 b3b361332bf0447c9ed28976e80f61d5 -msgid "" -"vector knowledge base is a method of mapping words in language to a high-" -"dimensional vector space. In the vector space, each word is represented " -"as a vector that contains many numerical features, which represent the " -"relationship between the word and other words. This mapping is a " -"clustering technique, and the semantic relationship between words can be " -"calculated by computing the differences between their vectors in the " -"vector space. Vector knowledge bases can be used for natural language " -"processing tasks such as sentiment analysis, text classification, and " -"machine translation. Common vector knowledge bases include Word2Vec, " -"GloVe, and FastText. The training of these vector knowledge bases usually" -" requires a large corpus and computing resources to complete." -msgstr "向量知识库是一种将语言中的单词映射到一个高维向量空间中的方法。在向量空间中，每个单词都表示为一个向量，这个向量包含了许多数值特征，这些特征代表了该单词与其他单词之间的关系。这种映射是一种聚类技术，通过将语言中的单词映射到向量空间中，单词之间的语义关系可以通过计算它们在向量空间中的差异来计算。向量知识库可以用于自然语言处理任务，如情感分析、文本分类、机器翻译等。常见的向量知识库有Word2Vec、GloVe、FastText等。这些向量知识库的训练通常需要大量的语料库和计算资源来完成。" - -#: ../../modules/vector.rst:8 a3abe6fd2c82463993e5deac78e30700 -msgid "" -"VectorConnector is a vector database connection adapter that allows you " -"to connect different vector databases and abstracts away implementation " -"differences and underlying details of different vector data. For example," -" it can be used to connect to databases such as Milvus, Chroma, " -"Elasticsearch, and Weaviate." -msgstr "" -"vectorconnector是一个向量数据库连接适配器，你可以通过它来连接不同的向量数据库，并且屏蔽掉了不同的向量数据的是实现差异和底层细节。例如Milvus," -" Chroma, Elasticsearch, Weaviate..." - -#: ../../modules/vector.rst:10 60bf9f9feab34835ada5b1954f4edefd -#, fuzzy -msgid "" -"DB-GPT VectorConnector currently support Chroma(Default), Milvus(>2.1), " -"Weaviate vector database." -msgstr "DB-GPT VectorConnector当前支持Milvus和Chroma，未来会越来越多." - -#: ../../modules/vector.rst:12 cd057c92691247d486d0acc4b5827731 -#, fuzzy -msgid "" -"If you want to change vector db, Update your .env, set your vector store " -"type, VECTOR_STORE_TYPE=Chroma (now only support Chroma, Milvus(>2.1) and" -" Weaviate, if you set Milvus, please set MILVUS_URL and MILVUS_PORT)" -msgstr "" -"如果你想替换向量数据库，需要更新.env文件，VECTOR_STORE_TYPE=Chroma (now only support Chroma," -" Milvus Weaviate, if you set Milvus(>2.1), please set MILVUS_URL and " -"MILVUS_PORT)" - -#: ../../modules/vector.rst:14 bce04f3cde7b427895034aa5c2899857 -#, fuzzy -msgid "`chroma <./vector/chroma.html>`_: supported chroma vector database." -msgstr "msgid \"`Chroma <./vector/chroma.html>`_: 支持Chroma向量数据库" - -#: ../../modules/vector.rst:15 f6947639cf0a4e1d8a83d3521c3b2781 -#, fuzzy -msgid "`milvus <./vector/milvus.html>`_: supported milvus vector database." -msgstr "Milvus <./vector/milvus.html>`_: 支持Milvus向量数据库" - -#: ../../modules/vector.rst:16 e5880b2c53fe42ad87b2ee8882abe90e -#, fuzzy -msgid "`weaviate <./vector/weaviate.html>`_: supported weaviate vector database." -msgstr "Milvus <./vector/milvus.html>`_: 支持Milvus向量数据库" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/modules/vector/chroma/chroma.po b/docs/locales/zh_CN/LC_MESSAGES/modules/vector/chroma/chroma.po deleted file mode 100644 index 2eea98c9b..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/modules/vector/chroma/chroma.po +++ /dev/null @@ -1,50 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.2.2\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-06-15 21:28+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../modules/vector/chroma/chroma.md:1 965acb8e092e41d79493a02b77336821 -msgid "ChromaStore" -msgstr "ChromaStore" - -#: ../../modules/vector/chroma/chroma.md:3 c5f9f524398e43f88568c089a8de58f1 -msgid "" -"ChromaStore is one implementation of the Chroma vector database in " -"VectorConnector." -msgstr "ChromaStore是Chroma向量数据库在VectorConnector的一种实现" - -#: ../../modules/vector/chroma/chroma.md:5 4a49fed7474b40cf95c762ed85f46942 -msgid "" -"inheriting the VectorStoreBase and implement similar_search(), " -"vector_name_exists(), load_document()." -msgstr "你需要继承VectorStoreBase类以及实现similar_search(), " -"vector_name_exists(), load_document()." - -#: ../../modules/vector/chroma/chroma.md:21 888f3278562149079a2f878aeb04e45c -msgid "similar_search()" -msgstr "similar_search()" - -#: ../../modules/vector/chroma/chroma.md:30 122e9dd993ba43aa937fa3ee3c191193 -msgid "vector_name_exists()" -msgstr "vector_name_exists()" - -#: ../../modules/vector/chroma/chroma.md:40 74ee4a7aecbf4bf58f47586138143db2 -msgid "load_document()" -msgstr "load_document()" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/modules/vector/milvus/milvus.po b/docs/locales/zh_CN/LC_MESSAGES/modules/vector/milvus/milvus.po deleted file mode 100644 index 7f17748be..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/modules/vector/milvus/milvus.po +++ /dev/null @@ -1,57 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.2.2\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-06-15 21:28+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../modules/vector/milvus/milvus.md:1 8c3b85c26a2541c1a37cbd4f313e1c2f -msgid "MilvusStore" -msgstr "MilvusStore" - -#: ../../modules/vector/milvus/milvus.md:3 ca7da166829144afb78981facefa7b9d -msgid "" -"MilvusStore is one implementation of the Milvus vector database in " -"VectorConnector." -msgstr "MilvusStore是Milvus向量数据库在VectorConnector的一种实现" - -#: ../../modules/vector/milvus/milvus.md:5 48121badae5347a38716364bb170f29e -msgid "" -"[Tutorial on how to create a Milvus instance](https://milvus.io/docs" -"/install_standalone-docker.md)" -msgstr "[怎样创建一个Milvus实例](https://milvus.io/docs" -"/install_standalone-docker.md)" - -#: ../../modules/vector/milvus/milvus.md:7 aa0f5011f4e94d369ecbe61b7edbaece -msgid "" -"inheriting the VectorStoreBase and implement similar_search(), " -"vector_name_exists(), load_document()." -msgstr "你需要继承VectorStoreBase类以及实现similar_search(), " -"vector_name_exists(), load_document()." - -#: ../../modules/vector/milvus/milvus.md:33 38c178195abe4ff38492e69ea16d245c -msgid "similar_search()" -msgstr "similar_search()"" - -#: ../../modules/vector/milvus/milvus.md:53 f8808ba5066d40678e1840cbb28b6bf1 -msgid "vector_name_exists()" -msgstr "vector_name_exists()" - -#: ../../modules/vector/milvus/milvus.md:62 c14e570621394f6983159f2208f62b28 -msgid "load_document()" -msgstr "load_document()" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/modules/vector/weaviate/weaviate.po b/docs/locales/zh_CN/LC_MESSAGES/modules/vector/weaviate/weaviate.po deleted file mode 100644 index 5de8ae416..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/modules/vector/weaviate/weaviate.po +++ /dev/null @@ -1,58 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 👏👏 0.2.2\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-06-19 19:10+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../modules/vector/weaviate/weaviate.md:1 66d5a0e4ef6d41808b27e8401784e061 -msgid "WeaviateStore" -msgstr "WeaviateStore" - -#: ../../modules/vector/weaviate/weaviate.md:3 304e61962e8a48b398317dbb4e3ef533 -msgid "" -"WeaviateStore is one implementation of the Milvus vector database in " -"VectorConnector." -msgstr "WeaviateStore是Weaviate向量数据库在VectorConnector的一种实现" - -#: ../../modules/vector/weaviate/weaviate.md:5 fed48f3ae04b431f869725f1a92aaa1b -msgid "" -"[Tutorial on how to create a Weaviate " -"instance](https://weaviate.io/developers/weaviate/installation)" -msgstr "[怎样创建一个Weaviate实例](https://weaviate.io/developers/weaviate/installation)" - -#: ../../modules/vector/weaviate/weaviate.md:7 7ffc39cf2d974401a4503efdba16c175 -msgid "" -"inheriting the VectorStoreBase and implement similar_search(), " -"vector_name_exists(), load_document()." -msgstr "vector_name_exists(), load_document()." - -#: ../../modules/vector/weaviate/weaviate.md:33 -#: ee62d6a1d23f4197bfe3085d80a6df00 -msgid "similar_search()" -msgstr "similar_search()"" - -#: ../../modules/vector/weaviate/weaviate.md:55 -#: 81a117db4d4846edb78ab592a0d5a491 -msgid "vector_name_exists()" -msgstr "vector_name_exists()" - -#: ../../modules/vector/weaviate/weaviate.md:69 -#: f453b53d3d2242ec9a28e3ce1dc44561 -msgid "load_document()" -msgstr "load_document()" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/reference.po b/docs/locales/zh_CN/LC_MESSAGES/reference.po deleted file mode 100644 index bc9ed06e6..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/reference.po +++ /dev/null @@ -1,25 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 0.3.0\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-06-11 14:10+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.11.0\n" - -#: ../../reference.md:1 83c827fb051c40d8b16f704752c9581b -msgid "Reference" -msgstr "参考文献" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/use_cases/chatbots.po b/docs/locales/zh_CN/LC_MESSAGES/use_cases/chatbots.po deleted file mode 100644 index 903050718..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/use_cases/chatbots.po +++ /dev/null @@ -1,25 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 0.3.0\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-06-11 14:10+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.11.0\n" - -#: ../../use_cases/chatbots.md:1 e599819098be40759193233cc476f26a -msgid "Chatbot" -msgstr "聊天机器人" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/use_cases/interacting_with_api.po b/docs/locales/zh_CN/LC_MESSAGES/use_cases/interacting_with_api.po deleted file mode 100644 index b32cf8871..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/use_cases/interacting_with_api.po +++ /dev/null @@ -1,25 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 0.3.0\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-06-11 14:10+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.11.0\n" - -#: ../../use_cases/interacting_with_api.md:1 2dc3e9c958e24aca90af1b0520d416b4 -msgid "Interacting with api" -msgstr "API交互" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/use_cases/knownledge_based_qa.po b/docs/locales/zh_CN/LC_MESSAGES/use_cases/knownledge_based_qa.po deleted file mode 100644 index 6f6125e68..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/use_cases/knownledge_based_qa.po +++ /dev/null @@ -1,61 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 0.3.0\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-07-13 15:39+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#~ msgid "Knownledge based qa" -#~ msgstr "知识问答" - -#~ msgid "" -#~ "Chat with your own knowledge is a" -#~ " very interesting thing. In the usage" -#~ " scenarios of this chapter, we will" -#~ " introduce how to build your own " -#~ "knowledge base through the knowledge " -#~ "base API. Firstly, building a knowledge" -#~ " store can currently be initialized " -#~ "by executing \"python tool/knowledge_init.py\" " -#~ "to initialize the content of your " -#~ "own knowledge base, which was introduced" -#~ " in the previous knowledge base " -#~ "module. Of course, you can also " -#~ "call our provided knowledge embedding " -#~ "API to store knowledge." -#~ msgstr "" -#~ "用自己的知识聊天是一件很有趣的事情。在本章的使用场景中，我们将介绍如何通过知识库API构建自己的知识库。首先，构建知识存储目前可以通过执行“python" -#~ " " -#~ "tool/knowledge_init.py”来初始化您自己的知识库的内容，这在前面的知识库模块中已经介绍过了。当然，你也可以调用我们提供的知识嵌入API来存储知识。" - -#~ msgid "" -#~ "We currently support many document " -#~ "formats: txt, pdf, md, html, doc, " -#~ "ppt, and url." -#~ msgstr "“我们目前支持四种文件格式: txt, pdf, url, 和md。" - -#~ msgid "" -#~ "Now we currently support vector " -#~ "databases: Chroma (default) and Milvus. " -#~ "You can switch between them by " -#~ "modifying the \"VECTOR_STORE_TYPE\" field in" -#~ " the .env file." -#~ msgstr "“我们目前支持向量数据库:Chroma(默认)和Milvus。你可以通过修改.env文件中的“VECTOR_STORE_TYPE”参数在它们之间切换。" - -#~ msgid "Below is an example of using the knowledge base API to query knowledge:" -#~ msgstr "下面是一个使用知识库API进行查询的例子:" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/use_cases/query_database_data.po b/docs/locales/zh_CN/LC_MESSAGES/use_cases/query_database_data.po deleted file mode 100644 index d173c537e..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/use_cases/query_database_data.po +++ /dev/null @@ -1,25 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 0.3.0\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-06-11 14:10+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.11.0\n" - -#: ../../use_cases/query_database_data.md:1 4a246f7052db497d990d3e65236b7c52 -msgid "Query database data" -msgstr "查询数据库数据" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/use_cases/sql_generation_and_diagnosis.po b/docs/locales/zh_CN/LC_MESSAGES/use_cases/sql_generation_and_diagnosis.po deleted file mode 100644 index af4e4d728..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/use_cases/sql_generation_and_diagnosis.po +++ /dev/null @@ -1,51 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 0.3.0\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-06-14 21:47+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../use_cases/sql_generation_and_diagnosis.md:1 -#: f19384aa3b1d4fc2bed3aa94abe80a3c -msgid "SQL generation and diagnosis" -msgstr "SQL生成和诊断" - -#: ../../use_cases/sql_generation_and_diagnosis.md:3 -#: 0aa11c79b20544b9a1376d184f58a516 -msgid "" -"DB-GPT provides SQL generation and diagnostic capabilities. With advanced" -" natural language processing algorithms and a deep understanding of SQL " -"syntax and semantics, the model can generate complex SQL queries from " -"natural language input, as well as diagnose and fix issues with existing " -"queries. This allows users to save time and streamline their workflow, " -"while also improving the accuracy and efficiency of their SQL operations." -msgstr "" - -#: ../../use_cases/sql_generation_and_diagnosis.md:5 -#: ffcbe5278cdc41a7b656f03bf82a8b26 -msgid "![SQL Generation](../../assets/demo_en.gif)" -msgstr "" - -#: ../../use_cases/sql_generation_and_diagnosis.md:5 -#: 3e5a3a7db4ee4cc8bff28c3f2c7387dd -#, fuzzy -msgid "SQL Generation" -msgstr "SQL生成和诊断" - -#~ msgid "![SQL Generation](../../assets/demo_en.gif)" -#~ msgstr "![SQL 生成](../../assets/demo_en.gif)" - diff --git a/docs/locales/zh_CN/LC_MESSAGES/use_cases/tool_use_with_plugin.po b/docs/locales/zh_CN/LC_MESSAGES/use_cases/tool_use_with_plugin.po deleted file mode 100644 index 86af6ea98..000000000 --- a/docs/locales/zh_CN/LC_MESSAGES/use_cases/tool_use_with_plugin.po +++ /dev/null @@ -1,152 +0,0 @@ -# SOME DESCRIPTIVE TITLE. -# Copyright (C) 2023, csunny -# This file is distributed under the same license as the DB-GPT package. -# FIRST AUTHOR , 2023. -# -#, fuzzy -msgid "" -msgstr "" -"Project-Id-Version: DB-GPT 0.3.0\n" -"Report-Msgid-Bugs-To: \n" -"POT-Creation-Date: 2023-10-17 17:24+0800\n" -"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n" -"Last-Translator: FULL NAME \n" -"Language: zh_CN\n" -"Language-Team: zh_CN \n" -"Plural-Forms: nplurals=1; plural=0;\n" -"MIME-Version: 1.0\n" -"Content-Type: text/plain; charset=utf-8\n" -"Content-Transfer-Encoding: 8bit\n" -"Generated-By: Babel 2.12.1\n" - -#: ../../use_cases/tool_use_with_plugin.md:1 1fb6c590034347ff9bf374dcf0a63fd3 -msgid "Tool use with plugin" -msgstr "插件工具" - -#: ../../use_cases/tool_use_with_plugin.md:3 b48206ede79641fdabb3afd4c5f7fa7e -msgid "" -"DB-GPT supports a variety of plug-ins, such as BaiduSearch, SendEmail. In" -" addition, some database management platforms can also package their " -"interfaces and package them into plug-ins, and use the model to realize " -"the ability of \"single-sentence requirements\"" -msgstr "" - -#: ../../use_cases/tool_use_with_plugin.md:6 e90be2eb88c140b5b0ac3e6b6fac76bc -msgid "Baidu-Search-Plugin" -msgstr "" - -#: ../../use_cases/tool_use_with_plugin.md:8 0b98dfd78d49426098974d3d9c2d962b -msgid "" -"[Db-GPT Plugins](https://github.com/eosphoros-ai/DB-GPT-" -"Plugins/blob/main/src/dbgpt_plugins/Readme.md)" -msgstr "" - -#: ../../use_cases/tool_use_with_plugin.md:10 c34f612a2ec449548ec90d3bcbf5d9a0 -msgid "" -"Perform search queries using the Baidu search engine [DB-GPT-" -"Plugins](https://github.com/eosphoros-ai/DB-GPT-Plugins)." -msgstr "" - -#: ../../use_cases/tool_use_with_plugin.md:21 81638eb1f4f34b39a1ce383f6ef5720f -msgid "" -"Test Case: Use a histogram to analyze the total order amount of users in " -"different cities." -msgstr "" - -#: ../../use_cases/tool_use_with_plugin.md:26 8cf2cbbff8cc408c9e885a406d34dbcb -msgid "" -"More detail see: [DB-DASHBOARD](https://github.com/eosphoros-ai/DB-GPT-" -"Plugins/blob/main/src/dbgpt_plugins/Readme.md)" -msgstr "" - -#~ msgid "" -#~ "DB-GPT supports a variety of " -#~ "plug-ins, such as MySQL, MongoDB, " -#~ "ClickHouse and other database tool " -#~ "plug-ins. In addition, some database " -#~ "management platforms can also package " -#~ "their interfaces and package them into" -#~ " plug-ins, and use the model to" -#~ " realize the ability of \"single-" -#~ "sentence requirements\"" -#~ msgstr "" - -#~ msgid "DB-GPT-DASHBOARD-PLUGIN" -#~ msgstr "" - -#~ msgid "" -#~ "[Db-GPT Chart Plugin](https://github.com/csunny" -#~ "/DB-GPT-Plugins/blob/main/src/dbgpt_plugins/Readme.md)" -#~ msgstr "" -#~ "[Db-GPT Chart Plugin](https://github.com/csunny" -#~ "/DB-GPT-Plugins/blob/main/src/dbgpt_plugins/Readme.md)" - -#~ msgid "" -#~ "This is a DB-GPT plugin to " -#~ "generate data analysis charts, if you" -#~ " want to use the test sample " -#~ "data, please first pull the code " -#~ "of [DB-GPT-Plugins](https://github.com/csunny/DB-" -#~ "GPT-Plugins), run the command to " -#~ "generate test DuckDB data, and then " -#~ "copy the generated data file to " -#~ "the `/pilot/mock_datas` directory of the " -#~ "DB-GPT project." -#~ msgstr "" - -#~ msgid "" -#~ "Test Case: Use a histogram to " -#~ "analyze the total order amount of " -#~ "users in different cities." -#~ msgstr "测试示例：请使用柱状图分析各个城市的用户数" - -#~ msgid "" -#~ "More detail see: [DB-" -#~ "DASHBOARD](https://github.com/csunny/DB-GPT-" -#~ "Plugins/blob/main/src/dbgpt_plugins/Readme.md)" -#~ msgstr "" - -#~ msgid "DB-GPT-SQL-Execution-Plugin" -#~ msgstr "" - -#~ msgid "This is an DbGPT plugin to connect Generic Db And Execute SQL." -#~ msgstr "" - -#~ msgid "DB-GPT-Bytebase-Plugin" -#~ msgstr "" - -#~ msgid "" -#~ "To use a tool or platform plugin," -#~ " you should first deploy a plugin." -#~ " Taking the open-source database " -#~ "management platform Bytebase as an " -#~ "example, you can deploy your Bytebase" -#~ " service with one click using Docker" -#~ " and access it at http://127.0.0.1:5678." -#~ " More details can be found at " -#~ "https://github.com/bytebase/bytebase." -#~ msgstr "" - -#~ msgid "" -#~ "Note: If your machine's CPU architecture" -#~ " is `ARM`, please use `--platform " -#~ "linux/arm64` instead." -#~ msgstr "" - -#~ msgid "" -#~ "Select the plugin on DB-GPT（All " -#~ "built-in plugins are from our " -#~ "repository: https://github.com/csunny/DB-GPT-" -#~ "Plugins），choose DB-GPT-Bytebase-Plugin. " -#~ "Supporting functions include creating " -#~ "projects, creating environments, creating " -#~ "database instances, creating databases, " -#~ "database DDL/DML operations, and ticket " -#~ "approval process, etc." -#~ msgstr "" - -#~ msgid "" -#~ "[](https://github.com/csunny/DB-GPT-" -#~ "Plugins/blob/main/src/dbgpt_plugins/Readme.md)" -#~ msgstr "" - diff --git a/docs/make.bat b/docs/make.bat deleted file mode 100644 index 32bb24529..000000000 --- a/docs/make.bat +++ /dev/null @@ -1,35 +0,0 @@ -@ECHO OFF - -pushd %~dp0 - -REM Command file for Sphinx documentation - -if "%SPHINXBUILD%" == "" ( - set SPHINXBUILD=sphinx-build -) -set SOURCEDIR=. -set BUILDDIR=_build - -%SPHINXBUILD% >NUL 2>NUL -if errorlevel 9009 ( - echo. - echo.The 'sphinx-build' command was not found. Make sure you have Sphinx - echo.installed, then set the SPHINXBUILD environment variable to point - echo.to the full path of the 'sphinx-build' executable. Alternatively you - echo.may add the Sphinx directory to PATH. - echo. - echo.If you don't have Sphinx installed, grab it from - echo.https://www.sphinx-doc.org/ - exit /b 1 -) - -if "%1" == "" goto help - -%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O% -goto end - -:help -%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O% - -:end -popd diff --git a/docs/modules/connections.rst b/docs/modules/connections.rst deleted file mode 100644 index 96cfa1248..000000000 --- a/docs/modules/connections.rst +++ /dev/null @@ -1,16 +0,0 @@ -Connections ---------- -**In order to interact more conveniently with users' private environments, the project has designed a connection module, which can support connection to databases, Excel, knowledge bases, and other environments to achieve information and data exchange.** - -DB-GPT provides base class BaseConnect, you can inheriting and implement get_session(), get_table_names(), get_index_info(), get_database_list() and run(). - -- `mysql_connection <./connections/mysql_connection.html>`_: supported mysql_connection. - - -.. toctree:: - :maxdepth: 2 - :caption: Connections - :name: mysql_connection - :hidden: - - ./connections/mysql/mysql_connection.md \ No newline at end of file diff --git a/docs/modules/connections/mysql/mysql_connection.md b/docs/modules/connections/mysql/mysql_connection.md deleted file mode 100644 index 3204aa5db..000000000 --- a/docs/modules/connections/mysql/mysql_connection.md +++ /dev/null @@ -1,18 +0,0 @@ -MYSQL Connection -================================== -MYSQL can connect mysql server. - -inheriting the RDBMSDatabase -``` -class MySQLConnect(RDBMSDatabase): - """Connect MySQL Database fetch MetaData - Args: - Usage: - """ - - type: str = "MySQL" - dialect: str = "mysql" - driver: str = "pymysql" - - default_db = ["information_schema", "performance_schema", "sys", "mysql"] -``` \ No newline at end of file diff --git a/docs/modules/index.md b/docs/modules/index.md deleted file mode 100644 index abbe16823..000000000 --- a/docs/modules/index.md +++ /dev/null @@ -1,3 +0,0 @@ -# Vector storage and indexing - -In order to facilitate the management of knowledge after vectorization, we have built-in multiple vector storage engines, from memory-based Chroma to distributed Milvus. Users can choose different storage engines according to their own scenario needs. The storage of knowledge vectors is the cornerstone of AI capability enhancement. As the intermediate language for interaction between humans and large language models, vectors play a very important role in this project. \ No newline at end of file diff --git a/docs/modules/knowledge.md b/docs/modules/knowledge.md deleted file mode 100644 index 7c8b2758f..000000000 --- a/docs/modules/knowledge.md +++ /dev/null @@ -1,35 +0,0 @@ -# Knowledge - -As the knowledge base is currently the most significant user demand scenario, we natively support the construction and processing of knowledge bases. At the same time, we also provide multiple knowledge base management strategies in this project, such as: -1. Default built-in knowledge base -2. Custom addition of knowledge bases -3. Various usage scenarios such as constructing knowledge bases through plugin capabilities and web crawling. Users only need to organize the knowledge documents, and they can use our existing capabilities to build the knowledge base required for the large model. - - -### Create your own knowledge repository - -1.Place personal knowledge files or folders in the pilot/datasets directory. - -We currently support many document formats: txt, pdf, md, html, doc, ppt, and url. - -before execution: - -``` -python -m spacy download zh_core_web_sm - -``` - -2.Update your .env, set your vector store type, VECTOR_STORE_TYPE=Chroma -(now only support Chroma and Milvus, if you set Milvus, please set MILVUS_URL and MILVUS_PORT) - -2.Run the knowledge repository initialization command - -```bash -dbgpt knowledge load -``` - -Optionally, you can run `dbgpt knowledge load --help` command to see more usage. - -3.Add the knowledge repository in the interface by entering the name of your knowledge repository (if not specified, enter "default") so you can use it for Q&A based on your knowledge base. - -Note that the default vector model used is text2vec-large-chinese (which is a large model, so if your personal computer configuration is not enough, it is recommended to use text2vec-base-chinese). Therefore, ensure that you download the model and place it in the models directory. diff --git a/docs/modules/knowledge.rst b/docs/modules/knowledge.rst deleted file mode 100644 index 05d716749..000000000 --- a/docs/modules/knowledge.rst +++ /dev/null @@ -1,147 +0,0 @@ -Knowledge ---------- - -| As the knowledge base is currently the most significant user demand scenario, we natively support the construction and processing of knowledge bases. At the same time, we also provide multiple knowledge base management strategies in this project, such as pdf knowledge,md knowledge, txt knowledge, word knowledge, ppt knowledge: - -We currently support many document formats: raw text, txt, pdf, md, html, doc, ppt, and url. -In the future, we will continue to support more types of knowledge, including audio, video, various databases, and big data sources. Of course, we look forward to your active participation in contributing code. - -**Create your own knowledge repository** - -1.prepare - -We currently support many document formats: TEXT(raw text), DOCUMENT(.txt, .pdf, .md, .doc, .ppt, .html), and URL. - -before execution: - -:: - - pip install db-gpt -i https://pypi.org/ - python -m spacy download zh_core_web_sm - from pilot import EmbeddingEngine,KnowledgeType - - -2.prepare embedding model, you can download from https://huggingface.co/. -Notice you have installed git-lfs. - -eg: git clone https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2 - -:: - - embedding_model = "your_embedding_model_path/all-MiniLM-L6-v2" - -3.prepare vector_store instance and vector store config, now we support Chroma, Milvus and Weaviate. - -:: - - #Chroma - vector_store_config = { - "vector_store_type":"Chroma", - "vector_store_name":"your_name",#you can define yourself - "chroma_persist_path":"your_persist_dir" - } - #Milvus - vector_store_config = { - "vector_store_type":"Milvus", - "vector_store_name":"your_name",#you can define yourself - "milvus_url":"your_url", - "milvus_port":"your_port", - "milvus_username":"your_username",(optional) - "milvus_password":"your_password",(optional) - "milvus_secure":"your_secure"(optional) - } - #Weaviate - vector_store_config = { - "vector_store_type":"Weaviate", - "vector_store_name":"your_name",#you can define yourself - "weaviate_url":"your_url", - "weaviate_port":"your_port", - "weaviate_username":"your_username",(optional) - "weaviate_password":"your_password",(optional) - } - -3.init Url Type EmbeddingEngine api and embedding your document into vector store in your code. - -:: - - url = "https://db-gpt.readthedocs.io/en/latest/getting_started/getting_started.html" - embedding_engine = EmbeddingEngine( - knowledge_source=url, - knowledge_type=KnowledgeType.URL.value, - model_name=embedding_model, - vector_store_config=vector_store_config) - embedding_engine.knowledge_embedding() - -If you want to add your source_reader or text_splitter, do this: - -:: - - url = "https://db-gpt.readthedocs.io/en/latest/getting_started/getting_started.html" - - source_reader = WebBaseLoader(web_path=self.file_path) - text_splitter = RecursiveCharacterTextSplitter( - chunk_size=100, chunk_overlap=50 - ) - embedding_engine = EmbeddingEngine( - knowledge_source=url, - knowledge_type=KnowledgeType.URL.value, - model_name=embedding_model, - vector_store_config=vector_store_config, - source_reader=source_reader, - text_splitter=text_splitter - ) - - -4.init Document Type EmbeddingEngine api and embedding your document into vector store in your code. -Document type can be .txt, .pdf, .md, .doc, .ppt. - -:: - - document_path = "your_path/test.md" - embedding_engine = EmbeddingEngine( - knowledge_source=document_path, - knowledge_type=KnowledgeType.DOCUMENT.value, - model_name=embedding_model, - vector_store_config=vector_store_config) - embedding_engine.knowledge_embedding() - -5.init TEXT Type EmbeddingEngine api and embedding your document into vector store in your code. - -:: - - raw_text = "a long passage" - embedding_engine = EmbeddingEngine( - knowledge_source=raw_text, - knowledge_type=KnowledgeType.TEXT.value, - model_name=embedding_model, - vector_store_config=vector_store_config) - embedding_engine.knowledge_embedding() - -4.similar search based on your knowledge base. -:: - query = "please introduce the oceanbase" - topk = 5 - docs = embedding_engine.similar_search(query, topk) - -Note that the default vector model used is text2vec-large-chinese (which is a large model, so if your personal computer configuration is not enough, it is recommended to use text2vec-base-chinese). Therefore, ensure that you download the model and place it in the models directory. - -- `pdf_embedding <./knowledge/pdf/pdf_embedding.html>`_: supported pdf embedding. -- `markdown_embedding <./knowledge/markdown/markdown_embedding.html>`_: supported markdown embedding. -- `word_embedding <./knowledge/word/word_embedding.html>`_: supported word embedding. -- `url_embedding <./knowledge/url/url_embedding.html>`_: supported url embedding. -- `ppt_embedding <./knowledge/ppt/ppt_embedding.html>`_: supported ppt embedding. -- `string_embedding <./knowledge/string/string_embedding.html>`_: supported raw text embedding. - - -.. toctree:: - :maxdepth: 2 - :caption: Knowledge - :name: pdf_embedding - :hidden: - - ./knowledge/pdf/pdf_embedding.md - ./knowledge/markdown/markdown_embedding.md - ./knowledge/word/word_embedding.md - ./knowledge/url/url_embedding.md - ./knowledge/ppt/ppt_embedding.md - ./knowledge/string/string_embedding.md \ No newline at end of file diff --git a/docs/modules/knowledge/markdown/markdown_embedding.md b/docs/modules/knowledge/markdown/markdown_embedding.md deleted file mode 100644 index 870772eb2..000000000 --- a/docs/modules/knowledge/markdown/markdown_embedding.md +++ /dev/null @@ -1,50 +0,0 @@ -Markdown -================================== -markdown embedding can import md text into a vector knowledge base. The entire embedding process includes the read (loading data), data_process (data processing), and index_to_store (embedding to the vector database) methods. - -inheriting the SourceEmbedding - -``` -class MarkdownEmbedding(SourceEmbedding): - """pdf embedding for read markdown document.""" - - def __init__(self, file_path, vector_store_config, text_splitter): - """Initialize with markdown path.""" - super().__init__(file_path, vector_store_config, text_splitter) - self.file_path = file_path - self.vector_store_config = vector_store_config - self.text_splitter = text_splitter or Nore -``` -implement read() and data_process() -read() method allows you to read data and split data into chunk - -``` -@register - def read(self): - """Load from markdown path.""" - loader = EncodeTextLoader(self.file_path) - if self.text_splitter is None: - try: - self.text_splitter = SpacyTextSplitter( - pipeline="zh_core_web_sm", - chunk_size=100, - chunk_overlap=100, - ) - except Exception: - self.text_splitter = RecursiveCharacterTextSplitter( - chunk_size=100, chunk_overlap=50 - ) - - return loader.load_and_split(self.text_splitter) -``` - -data_process() method allows you to pre processing your ways -``` -@register - def data_process(self, documents: List[Document]): - i = 0 - for d in documents: - documents[i].page_content = d.page_content.replace("\n", "") - i += 1 - return documents -``` \ No newline at end of file diff --git a/docs/modules/knowledge/pdf/pdf_embedding.md b/docs/modules/knowledge/pdf/pdf_embedding.md deleted file mode 100644 index d6366f65f..000000000 --- a/docs/modules/knowledge/pdf/pdf_embedding.md +++ /dev/null @@ -1,48 +0,0 @@ -PDF -================================== -pdfembedding can import PDF text into a vector knowledge base. The entire embedding process includes the read (loading data), data_process (data processing), and index_to_store (embedding to the vector database) methods. - -inheriting the SourceEmbedding -``` -class PDFEmbedding(SourceEmbedding): - """pdf embedding for read pdf document.""" - - def __init__(self, file_path, vector_store_config, text_splitter): - """Initialize with pdf path.""" - super().__init__(file_path, vector_store_config, text_splitter) - self.file_path = file_path - self.vector_store_config = vector_store_config - self.text_splitter = text_splitter or Nore -``` - -implement read() and data_process() -read() method allows you to read data and split data into chunk -``` -@register - def read(self): - """Load from pdf path.""" - loader = PyPDFLoader(self.file_path) - if self.text_splitter is None: - try: - self.text_splitter = SpacyTextSplitter( - pipeline="zh_core_web_sm", - chunk_size=100, - chunk_overlap=100, - ) - except Exception: - self.text_splitter = RecursiveCharacterTextSplitter( - chunk_size=100, chunk_overlap=50 - ) - - return loader.load_and_split(self.text_splitter) -``` -data_process() method allows you to pre processing your ways -``` -@register - def data_process(self, documents: List[Document]): - i = 0 - for d in documents: - documents[i].page_content = d.page_content.replace("\n", "") - i += 1 - return documents -``` diff --git a/docs/modules/knowledge/ppt/ppt_embedding.md b/docs/modules/knowledge/ppt/ppt_embedding.md deleted file mode 100644 index 84e5b0135..000000000 --- a/docs/modules/knowledge/ppt/ppt_embedding.md +++ /dev/null @@ -1,53 +0,0 @@ -PPT -================================== -ppt embedding can import ppt text into a vector knowledge base. The entire embedding process includes the read (loading data), data_process (data processing), and index_to_store (embedding to the vector database) methods. - -inheriting the SourceEmbedding -``` -class PPTEmbedding(SourceEmbedding): - """ppt embedding for read ppt document.""" - - def __init__( - self, - file_path, - vector_store_config, - text_splitter: Optional[TextSplitter] = None, - ): - """Initialize ppt word path.""" - super().__init__(file_path, vector_store_config, text_splitter=None) - self.file_path = file_path - self.vector_store_config = vector_store_config - self.text_splitter = text_splitter or None -``` - -implement read() and data_process() -read() method allows you to read data and split data into chunk -``` -@register - def read(self): - """Load from ppt path.""" - loader = UnstructuredPowerPointLoader(self.file_path) - if self.text_splitter is None: - try: - self.text_splitter = SpacyTextSplitter( - pipeline="zh_core_web_sm", - chunk_size=100, - chunk_overlap=100, - ) - except Exception: - self.text_splitter = RecursiveCharacterTextSplitter( - chunk_size=100, chunk_overlap=50 - ) - - return loader.load_and_split(self.text_splitter) -``` -data_process() method allows you to pre processing your ways -``` -@register - def data_process(self, documents: List[Document]): - i = 0 - for d in documents: - documents[i].page_content = d.page_content.replace("\n", "") - i += 1 - return documents -``` diff --git a/docs/modules/knowledge/string/string_embedding.md b/docs/modules/knowledge/string/string_embedding.md deleted file mode 100644 index 385a79ff8..000000000 --- a/docs/modules/knowledge/string/string_embedding.md +++ /dev/null @@ -1,41 +0,0 @@ -String -================================== -string embedding can import a long raw text into a vector knowledge base. The entire embedding process includes the read (loading data), data_process (data processing), and index_to_store (embedding to the vector database) methods. - -inheriting the SourceEmbedding -``` -class StringEmbedding(SourceEmbedding): - """string embedding for read string document.""" - - def __init__( - self, - file_path, - vector_store_config, - text_splitter: Optional[TextSplitter] = None, - ): - """Initialize raw text word path.""" - super().__init__(file_path=file_path, vector_store_config=vector_store_config) - self.file_path = file_path - self.vector_store_config = vector_store_config - self.text_splitter = text_splitter or None -``` - -implement read() and data_process() -read() method allows you to read data and split data into chunk -``` -@register - def read(self): - """Load from String path.""" - metadata = {"source": "raw text"} - return [Document(page_content=self.file_path, metadata=metadata)] -``` -data_process() method allows you to pre processing your ways -``` -@register - def data_process(self, documents: List[Document]): - i = 0 - for d in documents: - documents[i].page_content = d.page_content.replace("\n", "") - i += 1 - return documents -``` diff --git a/docs/modules/knowledge/url/url_embedding.md b/docs/modules/knowledge/url/url_embedding.md deleted file mode 100644 index f23fa82d5..000000000 --- a/docs/modules/knowledge/url/url_embedding.md +++ /dev/null @@ -1,57 +0,0 @@ -URL -================================== -url embedding can import PDF text into a vector knowledge base. The entire embedding process includes the read (loading data), data_process (data processing), and index_to_store (embedding to the vector database) methods. - -inheriting the SourceEmbedding -``` -class URLEmbedding(SourceEmbedding): - """url embedding for read url document.""" - - def __init__( - self, - file_path, - vector_store_config, - text_splitter: Optional[TextSplitter] = None, - ): - """Initialize url word path.""" - super().__init__(file_path, vector_store_config, text_splitter=None) - self.file_path = file_path - self.vector_store_config = vector_store_config - self.text_splitter = text_splitter or None -``` - -implement read() and data_process() -read() method allows you to read data and split data into chunk -``` -@register - def read(self): - """Load from url path.""" - loader = WebBaseLoader(web_path=self.file_path) - if self.text_splitter is None: - try: - self.text_splitter = SpacyTextSplitter( - pipeline="zh_core_web_sm", - chunk_size=100, - chunk_overlap=100, - ) - except Exception: - self.text_splitter = RecursiveCharacterTextSplitter( - chunk_size=100, chunk_overlap=50 - ) - - return loader.load_and_split(self.text_splitter) -``` -data_process() method allows you to pre processing your ways -``` -@register - def data_process(self, documents: List[Document]): - i = 0 - for d in documents: - content = d.page_content.replace("\n", "") - soup = BeautifulSoup(content, "html.parser") - for tag in soup(["!doctype", "meta"]): - tag.extract() - documents[i].page_content = soup.get_text() - i += 1 - return documents -``` diff --git a/docs/modules/knowledge/word/word_embedding.md b/docs/modules/knowledge/word/word_embedding.md deleted file mode 100644 index b2df34d31..000000000 --- a/docs/modules/knowledge/word/word_embedding.md +++ /dev/null @@ -1,48 +0,0 @@ -Word -================================== -word embedding can import word doc/docx text into a vector knowledge base. The entire embedding process includes the read (loading data), data_process (data processing), and index_to_store (embedding to the vector database) methods. - -inheriting the SourceEmbedding -``` -class WordEmbedding(SourceEmbedding): - """word embedding for read word document.""" - - def __init__(self, file_path, vector_store_config, text_splitter): - """Initialize with pdf path.""" - super().__init__(file_path, vector_store_config, text_splitter) - self.file_path = file_path - self.vector_store_config = vector_store_config - self.text_splitter = text_splitter or Nore -``` - -implement read() and data_process() -read() method allows you to read data and split data into chunk -``` -@register - def read(self): - """Load from word path.""" - loader = UnstructuredWordDocumentLoader(self.file_path) - if self.text_splitter is None: - try: - self.text_splitter = SpacyTextSplitter( - pipeline="zh_core_web_sm", - chunk_size=100, - chunk_overlap=100, - ) - except Exception: - self.text_splitter = RecursiveCharacterTextSplitter( - chunk_size=100, chunk_overlap=50 - ) - - return loader.load_and_split(self.text_splitter) -``` -data_process() method allows you to pre processing your ways -``` -@register - def data_process(self, documents: List[Document]): - i = 0 - for d in documents: - documents[i].page_content = d.page_content.replace("\n", "") - i += 1 - return documents -``` diff --git a/docs/modules/llms.md b/docs/modules/llms.md deleted file mode 100644 index 474f7bb9a..000000000 --- a/docs/modules/llms.md +++ /dev/null @@ -1,144 +0,0 @@ -# LLMs - -In the underlying large model integration, we have designed an open interface that supports integration with various large models. At the same time, we have a very strict control and evaluation mechanism for the effectiveness of the integrated models. In terms of accuracy, the integrated models need to align with the capability of ChatGPT at a level of 85% or higher. We use higher standards to select models, hoping to save users the cumbersome testing and evaluation process in the process of use. - -## Multi LLMs Usage -To use multiple models, modify the LLM_MODEL parameter in the .env configuration file to switch between the models. - -Notice: you can create .env file from .env.template, just use command like this: -``` -cp .env.template .env -LLM_MODEL=vicuna-13b -MODEL_SERVER=http://127.0.0.1:8000 -``` -now we support models vicuna-13b, vicuna-7b, chatglm-6b, flan-t5-base, guanaco-33b-merged, falcon-40b, gorilla-7b, llama-2-7b, llama-2-13b, baichuan-7b, baichuan-13b - -if you want use other model, such as chatglm-6b, you just need update .env config file. -``` -LLM_MODEL=chatglm-6b -``` -or chatglm2-6b, which is the second-generation version of the open-source bilingual (Chinese-English) chat model ChatGLM-6B. -``` -LLM_MODEL=chatglm2-6b -``` - - - -## Run Model with cpu. -we alse support smaller models, like gpt4all. you can use it with cpu/mps(M1/M2), Download from [gpt4all model](https://gpt4all.io/models/ggml-gpt4all-j-v1.3-groovy.bin) - -put it in the models path, then change .env config. -``` -LLM_MODEL=gptj-6b -``` - -DB-GPT provides a model load adapter and chat adapter. load adapter which allows you to easily adapt load different LLM models by inheriting the BaseLLMAdapter. You just implement match() and loader() method. - -vicuna llm load adapter - -``` -class VicunaLLMAdapater(BaseLLMAdaper): - """Vicuna Adapter""" - - def match(self, model_path: str): - return "vicuna" in model_path - - def loader(self, model_path: str, from_pretrained_kwagrs: dict): - tokenizer = AutoTokenizer.from_pretrained(model_path, use_fast=False) - model = AutoModelForCausalLM.from_pretrained( - model_path, low_cpu_mem_usage=True, **from_pretrained_kwagrs - ) - return model, tokenizer -``` - -chatglm load adapter -``` - -class ChatGLMAdapater(BaseLLMAdaper): - """LLM Adatpter for THUDM/chatglm-6b""" - - def match(self, model_path: str): - return "chatglm" in model_path - - def loader(self, model_path: str, from_pretrained_kwargs: dict): - tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True) - - if DEVICE != "cuda": - model = AutoModel.from_pretrained( - model_path, trust_remote_code=True, **from_pretrained_kwargs - ).float() - return model, tokenizer - else: - model = ( - AutoModel.from_pretrained( - model_path, trust_remote_code=True, **from_pretrained_kwargs - ) - .half() - .cuda() - ) - return model, tokenizer -``` -chat adapter which allows you to easily adapt chat different LLM models by inheriting the BaseChatAdpter.you just implement match() and get_generate_stream_func() method - -vicuna llm chat adapter -``` -class VicunaChatAdapter(BaseChatAdpter): - """Model chat Adapter for vicuna""" - - def match(self, model_path: str): - return "vicuna" in model_path - - def get_generate_stream_func(self): - return generate_stream -``` - -chatglm llm chat adapter -``` -class ChatGLMChatAdapter(BaseChatAdpter): - """Model chat Adapter for ChatGLM""" - - def match(self, model_path: str): - return "chatglm" in model_path - - def get_generate_stream_func(self): - from pilot.model.llm_out.chatglm_llm import chatglm_generate_stream - - return chatglm_generate_stream -``` - if you want to integrate your own model, just need to inheriting BaseLLMAdaper and BaseChatAdpter and implement the methods - -## Multi Proxy LLMs -### 1. Openai proxy - If you haven't deployed a private infrastructure for a large model, or if you want to use DB-GPT in a low-cost and high-efficiency way, you can also use OpenAI's large model as your underlying model. - -- If your environment deploying DB-GPT has access to OpenAI, then modify the .env configuration file as below will work. -``` -LLM_MODEL=proxyllm -MODEL_SERVER=127.0.0.1:8000 -PROXY_API_KEY=sk-xxx -PROXY_SERVER_URL=https://api.openai.com/v1/chat/completions -``` - -- If you can't access OpenAI locally but have an OpenAI proxy service, you can configure as follows. -``` -LLM_MODEL=proxyllm -MODEL_SERVER=127.0.0.1:8000 -PROXY_API_KEY=sk-xxx -PROXY_SERVER_URL={your-openai-proxy-server/v1/chat/completions} -``` - -### 2. Bard Proxy -- If your environment deploying DB-GPT has access to Bard (F12-> application-> __Secure-1PSID), then modify the .env configuration file as below will work. -``` -LLM_MODEL=bard_proxyllm -MODEL_SERVER=127.0.0.1:8000 -BARD_PROXY_API_KEY={your-bard-key} -# PROXY_SERVER_URL={your-bard-proxy-server/v1/chat/completions} -``` - -- If you want to use your own bard proxy server like Bard-Proxy, so that you can deploy DB-GPT on your PC easily. -``` -LLM_MODEL=bard_proxyllm -MODEL_SERVER=127.0.0.1:8000 -PROXY_SERVER_URL={your-bard-proxy-server/v1/chat/completions} -``` \ No newline at end of file diff --git a/docs/modules/plugins.md b/docs/modules/plugins.md deleted file mode 100644 index b78578066..000000000 --- a/docs/modules/plugins.md +++ /dev/null @@ -1,103 +0,0 @@ -# Plugins - -The ability of Agent and Plugin is the core of whether large models can be automated. In this project, we natively support the plugin mode, and large models can automatically achieve their goals. At the same time, in order to give full play to the advantages of the community, the plugins used in this project natively support the Auto-GPT plugin ecology, that is, Auto-GPT plugins can directly run in our project. - -```{admonition} The LLM (Language Model) suitable for the Plugin scene is -* chatgpt3.5. -* chatgpt4. -``` - -## Local Plugins - -### 1.1 How to write local plugins. - -- Local plugins use the Auto-GPT plugin template. A simple example is as follows: first write a plugin file called "sql_executor.py". -```python -import pymysql -import pymysql.cursors - -def get_conn(): - return pymysql.connect( - host="127.0.0.1", - port=int("2883"), - user="mock", - password="mock", - database="mock", - charset="utf8mb4", - ssl_ca=None, - ) - -def ob_sql_executor(sql: str): - try: - conn = get_conn() - with conn.cursor() as cursor: - cursor.execute(sql) - result = cursor.fetchall() - field_names = tuple(i[0] for i in cursor.description) - result = list(result) - result.insert(0, field_names) - return result - except pymysql.err.ProgrammingError as e: - return str(e) -``` - -Then set the "can_handle_post_prompt" method of the plugin template to True. In the "post_prompt" method, write the prompt information and the mapped plugin function. - -```python -"""This is a template for DB-GPT plugins.""" -from typing import Any, Dict, List, Optional, Tuple, TypeVar, TypedDict - -from auto_gpt_plugin_template import AutoGPTPluginTemplate - -PromptGenerator = TypeVar("PromptGenerator") - -class Message(TypedDict): - role: str - content: str - -class DBGPTOceanBase(AutoGPTPluginTemplate): - """ - This is an DB-GPT plugin to connect OceanBase. - """ - - def __init__(self): - super().__init__() - self._name = "DB-GPT-OB-Serverless-Plugin" - self._version = "0.1.0" - self._description = "This is an DB-GPT plugin to connect OceanBase." - - def can_handle_post_prompt(self) -> bool: - return True - - def post_prompt(self, prompt: PromptGenerator) -> PromptGenerator: - from .sql_executor import ob_sql_executor - - prompt.add_command( - "ob_sql_executor", - "Execute SQL in OceanBase Database.", - {"sql": ""}, - ob_sql_executor, - ) - return prompt - ... - -``` - -### 1.2 How to use local plugins - -- Pack your plugin project into `your-plugin.zip` and place it in the `/plugins/` directory of the DB-GPT project. After starting the webserver, you can select and use it in the `Plugin Model` section. - - -## Public Plugins - -### 1.1 How to use public plugins - -- By default, after launching the webserver, plugins from the public plugin library `DB-GPT-Plugins` will be automatically loaded. For more details, please refer to [DB-GPT-Plugins](https://github.com/csunny/DB-GPT-Plugins) - -### 1.2 Contribute to the DB-GPT-Plugins repository - -- Please refer to the plugin development process in the public plugin library, and put the configuration parameters in `.plugin_env` - -- We warmly welcome everyone to contribute plugins to the public plugin library! - - diff --git a/docs/modules/prompts.md b/docs/modules/prompts.md deleted file mode 100644 index 177475618..000000000 --- a/docs/modules/prompts.md +++ /dev/null @@ -1,46 +0,0 @@ -# Prompts - -**Prompt** is a very important part of the interaction between the large model and the user, and to a certain extent, it determines the quality and accuracy of the answer generated by the large model. In this project, we will automatically optimize the corresponding Prompt according to user input and usage scenarios, making it easier and more efficient for users to use large language models. - -## Prompt Management - -Here, you can choose to create a Prompt in **Public Prompts** space or **Private Prompts** space. - -image - -The difference between **Public Prompts** and **Private Prompts** is that Prompts in **Public Prompts** space can be viewed and used by all users, while prompts in **Private Prompts** space can only be viewed and used by the owner. - -### Create Prompt - -Click the "Add Prompts" button to pop up the following subpage: - -image - -**Scene**: It is assumed here that when we have a lot of Prompts, we often classify the Prompts according to scene, such as Prompts in the chat knowledge scene, Prompts in the chat data scene, Prompts in the chat normal scene, etc. - -**Sub Scene**: Continuing with the above, assuming that we have a lot of Prompts, scene classification alone is not enough. For example, in the chat data scenario, there can be many types of sub-scene: anomaly recognition sub scene, attribution analysis sub scene, etc. sub scene is used to distinguish subcategories under each scene. - -**Name**: Considering that a Prompt generally contains a lot of content, for ease of use and easy search, we need to name the Prompt. Note: The name of the Prompt is not allowed to be repeated. Name is the unique key that identifies a Prompt. - -**Content**: Here is the actual Prompt content that will be input to LLM. - -### Edit Prompt - -Existing Prompts can be edited. Note that except **name**, other items can be modified. - -image - -### Delete Prompt - -Ordinary users can only delete Prompts created by themselves in the private Prompts space. Administrator users can delete Prompts in public Prompts spaces and private Prompts spaces. - - -## Use Prompt - -Users can find and use Prompts next to the input boxes in each scene. Click to view all contents of Prompts library. - -✓ Hover the mouse over each Prompt to preview the Prompt content. -✓ Click Prompt to automatically fill in the Prompt content in the input box. - -image -image \ No newline at end of file diff --git a/docs/modules/server.md b/docs/modules/server.md deleted file mode 100644 index ad1623c65..000000000 --- a/docs/modules/server.md +++ /dev/null @@ -1,3 +0,0 @@ -# Server - -TODO: In terms of terminal display, we will provide a multi-platform product interface, including PC, mobile phone, command line, Slack and other platforms. \ No newline at end of file diff --git a/docs/modules/vector.rst b/docs/modules/vector.rst deleted file mode 100644 index 2cbfdbb32..000000000 --- a/docs/modules/vector.rst +++ /dev/null @@ -1,41 +0,0 @@ -VectorConnector ---------- - -**VectorConnector Introduce** - -vector knowledge base is a method of mapping words in language to a high-dimensional vector space. In the vector space, each word is represented as a vector that contains many numerical features, which represent the relationship between the word and other words. This mapping is a clustering technique, and the semantic relationship between words can be calculated by computing the differences between their vectors in the vector space. Vector knowledge bases can be used for natural language processing tasks such as sentiment analysis, text classification, and machine translation. Common vector knowledge bases include Word2Vec, GloVe, and FastText. The training of these vector knowledge bases usually requires a large corpus and computing resources to complete. - -VectorConnector is a vector database connection adapter that allows you to connect different vector databases and abstracts away implementation differences and underlying details of different vector data. For example, it can be used to connect to databases such as Milvus, Chroma, Elasticsearch, and Weaviate. - -DB-GPT VectorConnector currently support Chroma(Default), Milvus(>2.1), Weaviate vector database. - -If you want to change vector db, Update your .env, set your vector store type, VECTOR_STORE_TYPE=Chroma (now only support Chroma, Milvus(>2.1) and Weaviate, if you set Milvus, please set MILVUS_URL and MILVUS_PORT) - -:: - - #*******************************************************************# - #** VECTOR STORE SETTINGS **# - #*******************************************************************# - VECTOR_STORE_TYPE=Chroma - #MILVUS_URL=127.0.0.1 - #MILVUS_PORT=19530 - #MILVUS_USERNAME - #MILVUS_PASSWORD - #MILVUS_SECURE= - #WEAVIATE_URL=https://kt-region-m8hcy0wc.weaviate.network - - -- `chroma <./vector/chroma.html>`_: supported chroma vector database. -- `milvus <./vector/milvus.html>`_: supported milvus vector database. -- `weaviate <./vector/weaviate.html>`_: supported weaviate vector database. - - -.. toctree:: - :maxdepth: 2 - :caption: VectorConnector - :name: chroma - :hidden: - - ./vector/chroma/chroma.md - ./vector/milvus/milvus.md - ./vector/weaviate/weaviate.md \ No newline at end of file diff --git a/docs/modules/vector/chroma/chroma.md b/docs/modules/vector/chroma/chroma.md deleted file mode 100644 index 7c9f41eea..000000000 --- a/docs/modules/vector/chroma/chroma.md +++ /dev/null @@ -1,50 +0,0 @@ -ChromaStore -================================== -ChromaStore is one implementation of the Chroma vector database in VectorConnector. - -inheriting the VectorStoreBase and implement similar_search(), vector_name_exists(), load_document(). -``` -class ChromaStore(VectorStoreBase): - """chroma database""" - - def __init__(self, ctx: {}) -> None: - self.ctx = ctx - self.embeddings = ctx["embeddings"] - self.persist_dir = os.path.join( - KNOWLEDGE_UPLOAD_ROOT_PATH, ctx["vector_store_name"] + ".vectordb" - ) - self.vector_store_client = Chroma( - persist_directory=self.persist_dir, embedding_function=self.embeddings - ) -``` - -similar_search() - -``` - def similar_search(self, text, topk) -> None: - logger.info("ChromaStore similar search") - return self.vector_store_client.similarity_search(text, topk) - -``` - -vector_name_exists() - -``` - def vector_name_exists(self): - return ( - os.path.exists(self.persist_dir) and len(os.listdir(self.persist_dir)) > 0 - ) - -``` - -load_document() - -``` - def load_document(self, documents): - logger.info("ChromaStore load document") - texts = [doc.page_content for doc in documents] - metadatas = [doc.metadata for doc in documents] - self.vector_store_client.add_texts(texts=texts, metadatas=metadatas) - self.vector_store_client.persist() -``` - diff --git a/docs/modules/vector/milvus/milvus.md b/docs/modules/vector/milvus/milvus.md deleted file mode 100644 index 9cb89314c..000000000 --- a/docs/modules/vector/milvus/milvus.md +++ /dev/null @@ -1,76 +0,0 @@ -MilvusStore -================================== -MilvusStore is one implementation of the Milvus vector database in VectorConnector. - -[Tutorial on how to create a Milvus instance](https://milvus.io/docs/install_standalone-docker.md) - -inheriting the VectorStoreBase and implement similar_search(), vector_name_exists(), load_document(). -``` -class MilvusStore(VectorStoreBase): - """Milvus database""" - - def __init__(self, ctx: {}) -> None: - """init a milvus storage connection. - - Args: - ctx ({}): MilvusStore global config. - """ - # self.configure(cfg) - - connect_kwargs = {} - self.uri = CFG.MILVUS_URL - self.port = CFG.MILVUS_PORT - self.username = CFG.MILVUS_USERNAME - self.password = CFG.MILVUS_PASSWORD - self.collection_name = ctx.get("vector_store_name", None) - self.secure = ctx.get("secure", None) - self.embedding = ctx.get("embeddings", None) - self.fields = [] - self.alias = "default" - ) -``` - -similar_search() - -``` - def similar_search(self, text, topk) -> None: - """similar_search in vector database.""" - self.col = Collection(self.collection_name) - schema = self.col.schema - for x in schema.fields: - self.fields.append(x.name) - if x.auto_id: - self.fields.remove(x.name) - if x.is_primary: - self.primary_field = x.name - if x.dtype == DataType.FLOAT_VECTOR or x.dtype == DataType.BINARY_VECTOR: - self.vector_field = x.name - _, docs_and_scores = self._search(text, topk) - return [doc for doc, _, _ in docs_and_scores] - -``` - -vector_name_exists() - -``` - def vector_name_exists(self): - """is vector store name exist.""" - return utility.has_collection(self.collection_name) - -``` - -load_document() - -``` - def load_document(self, documents) -> None: - """load document in vector database.""" - # self.init_schema_and_load(self.collection_name, documents) - batch_size = 500 - batched_list = [ - documents[i : i + batch_size] for i in range(0, len(documents), batch_size) - ] - # docs = [] - for doc_batch in batched_list: - self.init_schema_and_load(self.collection_name, doc_batch) -``` - diff --git a/docs/modules/vector/weaviate/weaviate.md b/docs/modules/vector/weaviate/weaviate.md deleted file mode 100644 index 709a90a6a..000000000 --- a/docs/modules/vector/weaviate/weaviate.md +++ /dev/null @@ -1,89 +0,0 @@ -WeaviateStore -================================== -WeaviateStore is one implementation of the Milvus vector database in VectorConnector. - -[Tutorial on how to create a Weaviate instance](https://weaviate.io/developers/weaviate/installation) - -inheriting the VectorStoreBase and implement similar_search(), vector_name_exists(), load_document(). -``` -class WeaviateStore(VectorStoreBase): - """Weaviate database""" - - def __init__(self, ctx: dict) -> None: - """Initialize with Weaviate client.""" - try: - import weaviate - except ImportError: - raise ValueError( - "Could not import weaviate python package. " - "Please install it with `pip install weaviate-client`." - ) - - self.ctx = ctx - self.weaviate_url = CFG.WEAVIATE_URL - self.embedding = ctx.get("embeddings", None) - self.vector_name = ctx["vector_store_name"] - self.persist_dir = os.path.join( - KNOWLEDGE_UPLOAD_ROOT_PATH, self.vector_name + ".vectordb" - ) - - self.vector_store_client = weaviate.Client(self.weaviate_url) -``` - -similar_search() - -``` - def similar_search(self, text: str, topk: int) -> None: - """Perform similar search in Weaviate""" - logger.info("Weaviate similar search") - # nearText = { - # "concepts": [text], - # "distance": 0.75, # prior to v1.14 use "certainty" instead of "distance" - # } - # vector = self.embedding.embed_query(text) - response = ( - self.vector_store_client.query.get(self.vector_name, ["metadata", "page_content"]) - # .with_near_vector({"vector": vector}) - .with_limit(topk) - .do() - ) - docs = response['data']['Get'][list(response['data']['Get'].keys())[0]] - return docs - -``` - -vector_name_exists() - -``` - def vector_name_exists(self) -> bool: - """Check if a vector name exists for a given class in Weaviate. - Returns: - bool: True if the vector name exists, False otherwise. - """ - if self.vector_store_client.schema.get(self.vector_name): - return True - return False - -``` - -load_document() - -``` - def load_document(self, documents: list) -> None: - """Load documents into Weaviate""" - logger.info("Weaviate load document") - texts = [doc.page_content for doc in documents] - metadatas = [doc.metadata for doc in documents] - - # Import data - with self.vector_store_client.batch as batch: - batch.batch_size = 100 - - # Batch import all documents - for i in range(len(texts)): - properties = {"metadata": metadatas[i]['source'], "page_content": texts[i]} - - self.vector_store_client.batch.add_data_object(data_object=properties, class_name=self.vector_name) - self.vector_store_client.batch.flush() -``` - diff --git a/docs/package-lock.json 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"prism-react-renderer": "^1.3.5", + "react": "^17.0.2", + "react-dom": "^17.0.2", + "process": "^0.11.10", + "react-flickity-component": "^4.0.6" + }, + "devDependencies": { + "@docusaurus/module-type-aliases": "2.4.1" + }, + "browserslist": { + "production": [ + ">0.5%", + "not dead", + "not op_mini all" + ], + "development": [ + "last 1 chrome version", + "last 1 firefox version", + "last 1 safari version" + ] + }, + "engines": { + "node": ">=16.14" + } +} diff --git a/docs/requirements.txt b/docs/requirements.txt deleted file mode 100644 index d0a125868..000000000 --- a/docs/requirements.txt +++ /dev/null @@ -1,17 +0,0 @@ -autodoc_pydantic==1.8.0 -myst_parser -nbsphinx==0.8.9 -sphinx==4.5.0 -recommonmark -sphinx_intl -sphinx-autobuild==2021.3.14 -sphinx_book_theme -sphinx_rtd_theme==1.0.0 -sphinx-typlog-theme==0.8.0 -sphinx-panels -sphinx-tabs==3.4.0 -toml -myst_nb -sphinx_copybutton -pydata-sphinx-theme==0.13.1 -furo \ No newline at end of file diff --git a/docs/sidebars.js b/docs/sidebars.js new file mode 100755 index 000000000..05b91b0c5 --- /dev/null +++ b/docs/sidebars.js @@ -0,0 +1,234 @@ +/** + * Creating a sidebar enables you to: + - create an ordered group of docs + - render a sidebar for each doc of that group + - provide next/previous navigation + + The sidebars can be generated from the filesystem, or explicitly defined here. + + Create as many sidebars as you want. + */ + +// @ts-check + +/** @type {import('@docusaurus/plugin-content-docs').SidebarsConfig} */ +const sidebars = { + // By default, Docusaurus generates a sidebar from the docs folder structure + tutorialSidebar: [{type: 'autogenerated', dirName: '.'}], + + docs: [ + { + type: "doc", + id: "overview", + label: "Overview" + }, + + { + type: "doc", + id: "quickstart", + label: "Quickstart", + + }, + { + type: "doc", + id: "awel", + }, + + { + type: "category", + label: "Installation", + collapsed: false, + collapsible: false, + items: [ + { + type: 'doc', + id: 'installation/sourcecode', + }, + { + type: 'doc', + id: 'installation/docker', + }, + { + type: 'doc', + id: 'installation/docker_compose', + }, + { + type: 'category', + label: 'Model Service Deployment', + items: [ + { + type: 'doc', + id: 'installation/model_service/stand_alone', + }, + { + type: 'doc', + id: 'installation/model_service/cluster', + }, + ], + }, + { + type: 'category', + label: 'Adanced Usage', + items: [ + { + type: 'doc', + id: 'installation/advanced_usage/vLLM_inference', + }, + { + type: 'doc', + id: 'installation/advanced_usage/OpenAI_SDK_call', + }, + ], + }, + + + ], + link: { + type: 'generated-index', + description: 'DB-GPT provides a wealth of installation and deployment options, supporting source code deployment, Docker deployment, cluster deployment and other modes. At the same time, it can also be deployed and installed based on the AutoDL image.', + slug: "installation", + }, + }, + + { + type: "category", + label: "Operation Manual", + collapsed: false, + collapsible: false, + items: [ + { + type: 'category', + label: 'Getting Started Tutorial', + items: [ + { + type: 'doc', + id: 'operation_manual/started_tutorial/chat_knowledge', + }, + { + type: 'doc', + id: 'operation_manual/started_tutorial/chat_data', + }, + { + type: 'doc', + id: 'operation_manual/started_tutorial/chat_excel', + }, + { + type: 'doc', + id: 'operation_manual/started_tutorial/chat_db', + }, + { + type: 'doc', + id: 'operation_manual/started_tutorial/chat_dashboard', + }, + { + type: 'doc', + id: 'operation_manual/started_tutorial/agent', + }, + ], + }, + { + type: 'category', + label: 'Advanced Tutorial', + items: [ + { + type: 'doc', + id: 'operation_manual/advanced_tutorial/rag', + }, + { + type: 'doc', + id: 'operation_manual/advanced_tutorial/smmf', + }, + { + type: 'doc', + id: 'operation_manual/advanced_tutorial/debugging', + }, + ], + }, + { + type: 'category', + label: 'Fine Tuning Manual', + items: [ + { + type: 'doc', + id: 'operation_manual/fine_tuning_manual/text_to_sql', + }, + + ], + }, + + + + + ], + link: { + type: "generated-index", + description: "DB-GPT Operation Manual", + slug: "operation_manual", + } + }, + + { + type: "category", + label: "Modules", + collapsed: true, + items: [ + { + type: 'doc', + id: 'modules/smmf', + }, + { + type: 'doc', + id: 'modules/rag', + }, + { + type: 'doc', + id: 'modules/agent', + }, + { + type: 'doc', + id: 'modules/fine_tuning', + }, + { + type: 'doc', + id: 'modules/eval', + }, + { + type: 'doc', + id: 'modules/connections', + }, + { + type: 'doc', + id: 'modules/visual', + }, + + ], + }, + + { + type: "doc", + id:"faq" + }, + + { + type: "category", + label: "ChangeLog", + collapsed: true, + items: [ + { + type: 'doc', + id: 'changelog/doc', + }, + ], + + }, + + { + type: "doc", + id: "use_cases", + label: "Use Cases" + }, + ] +}; + + +module.exports = sidebars; diff --git a/docs/src/common/icons/index.ts b/docs/src/common/icons/index.ts new file mode 100644 index 000000000..ea6180b30 --- /dev/null +++ b/docs/src/common/icons/index.ts @@ -0,0 +1 @@ +export * from './tools'; \ No newline at end of file diff --git a/docs/src/common/icons/tools/discord.svg b/docs/src/common/icons/tools/discord.svg new file mode 100644 index 000000000..98ce64cde --- /dev/null +++ b/docs/src/common/icons/tools/discord.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/docs/src/common/icons/tools/discord2.svg b/docs/src/common/icons/tools/discord2.svg new file mode 100644 index 000000000..a4cebd7b2 --- /dev/null +++ b/docs/src/common/icons/tools/discord2.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/docs/src/common/icons/tools/github.svg b/docs/src/common/icons/tools/github.svg new file mode 100644 index 000000000..41b17c655 --- /dev/null +++ b/docs/src/common/icons/tools/github.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/docs/src/common/icons/tools/github2.svg b/docs/src/common/icons/tools/github2.svg new file mode 100644 index 000000000..8c99a3fcb --- /dev/null +++ b/docs/src/common/icons/tools/github2.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/docs/src/common/icons/tools/index.ts b/docs/src/common/icons/tools/index.ts new file mode 100644 index 000000000..bd0878a8b --- /dev/null +++ b/docs/src/common/icons/tools/index.ts @@ -0,0 +1,19 @@ +export { default as Tool1 } from './tool1.svg'; +export { default as Tool2 } from './tool2.svg'; +export { default as Tool3 } from './tool3.svg'; +export { default as Tool4 } from './tool4.svg'; +export { default as Tool5 } from './tool5.svg'; +export { default as Tool6 } from './tool6.svg'; + +export { default as ToolCloud } from './tool_cloud.svg'; +export { default as ToolData } from './tool_data.svg'; +export { default as ToolDev } from './tool_dev.svg'; +export { default as ToolPerson } from './tool_person.svg'; +export { default as ToolSecure } from './tool_secure.svg'; +export { default as ToolSystem } from './tool_system.svg'; +export { default as ToolProduct } from './tool_product.svg'; + +export { default as CommDiscord } from './discord.svg'; +export { default as CommWechat } from './wechat.svg'; +export { default as CommGithub } from './github.svg'; +export { default as CommGithub2 } from './github2.svg'; diff --git a/docs/src/common/icons/tools/tool1.svg b/docs/src/common/icons/tools/tool1.svg new file mode 100644 index 000000000..8a81a3aa8 --- /dev/null +++ b/docs/src/common/icons/tools/tool1.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/docs/src/common/icons/tools/tool2.svg b/docs/src/common/icons/tools/tool2.svg new file mode 100644 index 000000000..8a81a3aa8 --- /dev/null +++ b/docs/src/common/icons/tools/tool2.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/docs/src/common/icons/tools/tool3.svg b/docs/src/common/icons/tools/tool3.svg new file mode 100644 index 000000000..c3f74572c --- /dev/null +++ b/docs/src/common/icons/tools/tool3.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/docs/src/common/icons/tools/tool4.svg b/docs/src/common/icons/tools/tool4.svg new file mode 100644 index 000000000..feb60951c --- /dev/null +++ b/docs/src/common/icons/tools/tool4.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/docs/src/common/icons/tools/tool5.svg b/docs/src/common/icons/tools/tool5.svg new file mode 100644 index 000000000..892003f74 --- /dev/null +++ b/docs/src/common/icons/tools/tool5.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/docs/src/common/icons/tools/tool6.svg b/docs/src/common/icons/tools/tool6.svg new file mode 100644 index 000000000..942b14e04 --- /dev/null +++ b/docs/src/common/icons/tools/tool6.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/docs/src/common/icons/tools/tool_cloud.svg b/docs/src/common/icons/tools/tool_cloud.svg new file mode 100644 index 000000000..4b4e79b10 --- /dev/null +++ b/docs/src/common/icons/tools/tool_cloud.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/docs/src/common/icons/tools/tool_data.svg b/docs/src/common/icons/tools/tool_data.svg new file mode 100644 index 000000000..baefdf518 --- /dev/null +++ b/docs/src/common/icons/tools/tool_data.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/docs/src/common/icons/tools/tool_dev.svg b/docs/src/common/icons/tools/tool_dev.svg new file mode 100644 index 000000000..fa9669053 --- /dev/null +++ b/docs/src/common/icons/tools/tool_dev.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/docs/src/common/icons/tools/tool_person.svg b/docs/src/common/icons/tools/tool_person.svg new file mode 100644 index 000000000..55c0b25d8 --- /dev/null +++ b/docs/src/common/icons/tools/tool_person.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/docs/src/common/icons/tools/tool_product.svg b/docs/src/common/icons/tools/tool_product.svg new file mode 100644 index 000000000..11f53c25a --- /dev/null +++ b/docs/src/common/icons/tools/tool_product.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/docs/src/common/icons/tools/tool_secure.svg b/docs/src/common/icons/tools/tool_secure.svg new file mode 100644 index 000000000..e014d7167 --- /dev/null +++ b/docs/src/common/icons/tools/tool_secure.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/docs/src/common/icons/tools/tool_system.svg b/docs/src/common/icons/tools/tool_system.svg new file mode 100644 index 000000000..7c0576b8c --- /dev/null +++ b/docs/src/common/icons/tools/tool_system.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/docs/src/common/icons/tools/wechat.svg b/docs/src/common/icons/tools/wechat.svg new file mode 100644 index 000000000..24049a053 --- /dev/null +++ b/docs/src/common/icons/tools/wechat.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/docs/src/components/FeaturedSlider/flickity.css b/docs/src/components/FeaturedSlider/flickity.css new file mode 100644 index 000000000..75a8e620a --- /dev/null +++ b/docs/src/components/FeaturedSlider/flickity.css @@ -0,0 +1,156 @@ +/*! Flickity v2.1.2 +https://flickity.metafizzy.co +---------------------------------------------- */ + +.flickity-enabled { + position: relative; + background-color: var(--ifm-color-emphasis-0); + border-bottom: 1px solid var(--ifm-color-emphasis-200); + margin-bottom: 4rem; +} + +:root[data-theme='dark'] .flickity-enabled { + background: linear-gradient( + rgba(41, 56, 88, 0.3), + rgba(19, 31, 55, 0.3) + ) !important; +} + +.flickity-enabled:focus { + outline: none; +} + +.flickity-viewport { + overflow: hidden; + position: relative; + height: 100%; +} + +.flickity-slider { + position: absolute; + width: 100%; + height: 100%; +} + +/* draggable */ + +.flickity-enabled.is-draggable { + -webkit-tap-highlight-color: transparent; + tap-highlight-color: transparent; + -webkit-user-select: none; + -moz-user-select: none; + -ms-user-select: none; + user-select: none; +} + +.flickity-enabled.is-draggable .flickity-viewport { + cursor: move; + cursor: -webkit-grab; + cursor: grab; +} + +.flickity-enabled.is-draggable .flickity-viewport.is-pointer-down { + cursor: -webkit-grabbing; + cursor: grabbing; +} + +/* ---- flickity-button ---- */ + +.flickity-button { + position: absolute; + background: hsla(0, 0%, 100%, 0.75); + border: none; + color: #333; +} + +.flickity-button:hover { + background: white; + cursor: pointer; +} + +.flickity-button:focus { + outline: none; + box-shadow: 0 0 0 5px #19f; +} + +.flickity-button:active { + opacity: 0.6; +} + +.flickity-button:disabled { + opacity: 0.3; + cursor: auto; + /* prevent disabled button from capturing pointer up event. #716 */ + pointer-events: none; +} + +.flickity-button-icon { + fill: #333; +} + +/* ---- previous/next buttons ---- */ + +.flickity-prev-next-button { + top: 50%; + width: 44px; + height: 44px; + border-radius: 50%; + /* vertically center */ + transform: translateY(-50%); +} + +.flickity-prev-next-button.previous { + left: 10px; +} +.flickity-prev-next-button.next { + right: 10px; +} +/* right to left */ +.flickity-rtl .flickity-prev-next-button.previous { + left: auto; + right: 10px; +} +.flickity-rtl .flickity-prev-next-button.next { + right: auto; + left: 10px; +} + +.flickity-prev-next-button .flickity-button-icon { + position: absolute; + left: 20%; + top: 20%; + width: 60%; + height: 60%; +} + +/* ---- page dots ---- */ + +.flickity-page-dots { + position: absolute; + width: 100%; + bottom: -25px; + padding: 0; + margin: 0; + list-style: none; + text-align: center; + line-height: 1; +} + +.flickity-rtl .flickity-page-dots { + direction: rtl; +} + +.flickity-page-dots .dot { + display: inline-block; + width: 10px; + height: 10px; + margin: 0 8px; + background: var(--ifm-color-primary-lightest); + border-radius: 50%; + opacity: 0.25; + cursor: pointer; +} + +.flickity-page-dots .dot.is-selected { + opacity: 1; +} diff --git a/docs/src/components/FeaturedSlider/index.tsx b/docs/src/components/FeaturedSlider/index.tsx new file mode 100644 index 000000000..11755bb70 --- /dev/null +++ b/docs/src/components/FeaturedSlider/index.tsx @@ -0,0 +1,79 @@ +import React from 'react'; +import Flickity from 'react-flickity-component'; +import Link from '@docusaurus/Link'; +import FeaturedSlides from './slides.json'; +import './flickity.css'; +import clsx from 'clsx'; +import styles from './styles.module.css'; + +const flickityOptions = { + initialIndex: 0, + autoPlay: false, + adaptiveHeight: true, + wrapAround: true, + groupCells: false, + fade: true, + pageDots: false, +}; + +export default function FeaturedSlider() { + const RenderSlides: () => void = () => { + return FeaturedSlides.map((slide) => ( +
+
+
+

{slide.title}

+

+ {slide.description} +

+
+ {slide.outlinedButton && ( + + {slide.outlinedButton.buttonText} + + )} + {slide.solidButton && ( + + {slide.solidButton.buttonText} + + )} +
+
+
+
+ )); + }; + + return ( + + + + ); +} diff --git a/docs/src/components/FeaturedSlider/slides.json b/docs/src/components/FeaturedSlider/slides.json new file mode 100644 index 000000000..abf1393bb --- /dev/null +++ b/docs/src/components/FeaturedSlider/slides.json @@ -0,0 +1,15 @@ +[ + { + "title": "DB-GPT", + "description": "Revolutionizing Database Interactions with Private LLM Technology, a solution you can be assured that there is no risk of data leakage, and your data is 100% private and secure.", + "outlinedButton": { + "buttonText": "Learn About DB-GPT", + "url": "/docs/getting_started" + }, + "solidButton": { + "buttonText": "Experience Now!", + "url": "http://dev.dbgpt.site" + }, + "imagePath": "/img/dbgpt_face_page.svg" + } +] \ No newline at end of file diff --git a/docs/src/components/FeaturedSlider/styles.module.css b/docs/src/components/FeaturedSlider/styles.module.css new file mode 100644 index 000000000..77eadffa4 --- /dev/null +++ b/docs/src/components/FeaturedSlider/styles.module.css @@ -0,0 +1,60 @@ +.slide__container { + width: 100%; + align-content: center; + justify-content: space-between; + row-gap: 1rem; + padding: 0 8rem; + display: flex; +} + +.slide { + width: 100%; + max-width: var(--ifm-container-width); + margin: auto; +} + +.slide { + background-color: var(--ifm-color-emphasis-0); +} + +@media (max-width: 996px) { + .slide { + display: flex; + justify-content: space-between; + align-items: flex-end; + width: 100%; + background-repeat: no-repeat; + background-position: right bottom; + } +} +@media (max-width: 720px) { + .slide { + background: none !important; + } +} + +.slide__section { + max-width: 25rem; + margin: 6rem 0; +} + +.slide__header { + font-size: 40px; +} + +.slide__buttons { + display: flex; + flex-wrap: wrap; + gap: 1rem; +} + +.slide__description { + /*height: 8rem;*/ +} + +.slide__button { + flex: 1 1 0; + padding-top: 0.75rem; + padding-bottom: 0.75rem; + max-width: 12rem; +} diff --git a/docs/src/components/HomeLayout/index.tsx b/docs/src/components/HomeLayout/index.tsx new file mode 100644 index 000000000..1e86607cb --- /dev/null +++ b/docs/src/components/HomeLayout/index.tsx @@ -0,0 +1,191 @@ +import React, { FC } from 'react'; +import Layout from '@theme/Layout'; +import Link from '@docusaurus/Link'; +import useDocusaurusContext from '@docusaurus/useDocusaurusContext'; +import clsx from 'clsx'; +import './styles.css'; +import { + Tool1, + Tool2, + Tool3, + Tool4, + Tool5, + Tool6, + ToolDev, + ToolCloud, + ToolData, + ToolSecure, + ToolPerson, + ToolProduct, + ToolSystem, + CommGithub, + CommWechat, + CommDiscord, + CommGithub2, +} from '@site/src/common/icons'; +import FeaturedSlider from '@site/src/components/FeaturedSlider'; + +interface HomepageSectionProps { + header?: string; + description?: string; + className?: string; +} + +const HomepageSection: FC = (props) => { + const toKebabCase = (header) => + header && + header + .match( + /[A-Z]{2,}(?=[A-Z][a-z]+[0-9]*|\b)|[A-Z]?[a-z]+[0-9]*|[A-Z]|[0-9]+/g, + ) + .map((parts) => parts.toLowerCase()) + .join('-'); + + return ( +
+
+ {props.header && ( +

+ {props.header} +

+ )} + {props.description && ( +

{props.description}

+ )} + {props.children} +
+
+ ); +}; + +export default function HomeLayout() { + const { siteConfig } = useDocusaurusContext(); + + return ( + +
+ + + +
+ +
+
+ +
+

Multi-Models

+

+ Support multiply LLMs, such as chatglm, vicuna, Qwen, and proxy of chatgpt and bard. +

+
+ + +
+
+ +
+

Embedding

+

+ Embed data as vectors and store them in vector databases, providing content similarity search. +

+
+ + +
+
+ +
+

BI

+

+ Support multiply scenes, chat to db, chat to dashboard, chat to knowledge and native chat with LLMs. +

+
+ + +
+
+ +
+

Knowledge Based QA

+

+ You can perform high-quality intelligent Q&A based on local documents such as pdf, word, excel and other data. +

+
+ + +
+
+ +
+

Privacy & Secure

+

+ You can be assured that there is no risk of data leakage, and your data is 100% private and secure. +

+
+ + +
+
+ +
+

Agent & Plugins

+

+ Support AutoGPT plugins, and you can build your own plugins as well. +

+
+ +
+ + + + + + + +
+ +
+
+ +
+

Join Discord

+

+ Check out the DB-GPT community on Discord. +

+
+ + +
+
+ +
+

+ Wechat Group +

+

+ 3000+ developers here to learn and communicate with you. +

+
+ + +
+
+ +
+

Github

+

+ Welcome to join us on GitHub and contribute code together. +

+
+ +
+ + +
+ + ); +} diff --git a/docs/src/components/HomeLayout/styles.css b/docs/src/components/HomeLayout/styles.css new file mode 100644 index 000000000..c1c20ded2 --- /dev/null +++ b/docs/src/components/HomeLayout/styles.css @@ -0,0 +1,608 @@ +.homepage { + letter-spacing: 0.75px; + font-weight: 200; + color: var(--ifm-color-emphasis-700); + background-color: var(--ifm-color-emphasis-100); + overflow: auto; +} + +:root[data-theme='dark'] .homepage { + background-color: var(--ifm-color-emphasis-0); +} + +.homepage__section { + display: flex; + justify-content: center; + margin-bottom: 8rem; +} + +.homepage__section--intro { + background-color: var(--ifm-color-emphasis-0); + border-bottom: 1px solid var(--ifm-color-emphasis-200); +} + +:root[data-theme='dark'] .homepage__section--intro { + background: linear-gradient(rgba(41, 56, 88, 0.3), rgba(19, 31, 55, 0.3)); +} + +.homepage__container { + margin: 0 8rem; + width: 100%; + max-width: var(--ifm-container-width); + display: flex; + flex-direction: column; + align-items: center; + row-gap: 1rem; +} + +@media (max-width: 996px) { + .homepage__container { + margin: 0 2rem; + } +} + +.homepage__description { + width: 70%; + text-align: center; +} + +@media (max-width: 996px) { + .homepage__description { + width: 90%; + } +} + +.languages { + flex: 1 1 0; + display: flex; + flex-wrap: wrap; + align-items: flex-start; + justify-content: flex-end; + gap: 0.2rem; +} + +.language { + padding: 0 0.4rem; + border-radius: 0.2rem; + font-size: calc(0.75rem * var(--ifm-button-size-multiplier)); +} + +@media (max-width: 996px) { + .intro { + background: none; + } +} + +.intro__section { + max-width: 25rem; + margin: 6rem 0; +} + +.intro__header { + font-size: 40px; +} + +.intro__buttons { + display: flex; + flex-wrap: wrap; + gap: 1rem; +} + +.intro__button { + flex: 1 1 0; + padding-top: 0.75rem; + padding-bottom: 0.75rem; +} + +.about__cards { + display: grid; + grid-template-columns: repeat(auto-fill, minmax(18rem, 1fr)); + gap: 1rem; + width: 100%; +} + +.about__card { + aspect-ratio: 1/1; + display: flex; + justify-content: center; + align-items: center; + background-color: var(--ifm-color-emphasis-0); + box-shadow: 0 0 5px 0 var(--ifm-color-emphasis-300); + border: 1px solid var(--ifm-color-emphasis-200); + border-radius: var(--ifm-global-radius); + color: inherit; + cursor: pointer; + transition: border-color 200ms ease-in-out; +} + +.about__card:hover { + color: inherit; + border-color: var(--ifm-color-emphasis-400); +} + +:root[data-theme='dark'] .about__card { + box-shadow: none; + background-color: var(--ifm-color-emphasis-100); +} + +.about__section { + display: flex; + flex-direction: column; + align-items: center; + width: 16rem; + height: 12rem; +} + +.about__icon { + display: flex; + justify-content: center; + align-items: center; + background-color: var(--ifm-color-emphasis-200); + border-radius: var(--ifm-global-radius); + fill: var(--ifm-color-emphasis-900); + + width: 4rem; + height: 4rem; +} + +.about__icon > svg { + width: 48px; + height: 48px; +} + +.about__header { + margin-top: 1.5rem; +} + +.about__description { + text-align: center; + margin: 0; + font-size: 0.8rem; +} + +.networks__cards { + display: flex; + flex-wrap: wrap; + gap: 1px; + width: 100%; + background-color: var(--ifm-color-emphasis-200); + border: 1px solid var(--ifm-color-emphasis-200); + border-radius: var(--ifm-global-radius); + color: inherit; +} + +.networks__card { + flex: 1 0 calc(50% - 1px); + display: flex; + flex-direction: column; + justify-content: space-between; + padding: 3rem 2rem; + background-color: var(--ifm-color-emphasis-0); +} + +:root[data-theme='dark'] .networks__card { + background-color: var(--ifm-color-emphasis-100); +} + +.networks__section { + display: flex; + flex-direction: column; + align-items: center; +} + +.networks__icon { + display: flex; + justify-content: center; + align-items: center; + border-radius: 50%; + + width: 5rem; + height: 5rem; +} + +.networks__icon > svg { + width: 4rem; + height: 4rem; +} + +.networks__icon--shimmer { + fill: white; + background-color: #16d4bf; +} + +.networks__label { + font-weight: 800; + font-size: 0.8rem; + color: var(--ifm-color-emphasis-500); + margin-top: 1rem; + margin-bottom: 0.5rem; +} + +.networks__description { + text-align: center; + width: 16rem; +} + +.networks__features { + list-style-type: none; + padding: 0; + margin-bottom: var(--ifm-paragraph-margin-bottom); + white-space: nowrap; +} + +.networks__feature { + display: flex; + align-items: center; + margin: 0.5rem 0; +} + +.networks__button { + padding-top: 0.75rem; + padding-bottom: 0.75rem; +} + +.start-building__header { + font-family: 'Metropolis Regular'; + display: flex; + align-items: center; +} + +.start-building__description { + margin: 2rem 0; + max-width: 38rem; +} + +.start-building__buttons { + display: flex; + flex-wrap: wrap; + gap: 1rem; +} + +.start-building__button { + padding: 0.75rem 2rem; +} + +.libraries__cards { + display: grid; + grid-template-columns: repeat(auto-fill, minmax(20rem, 1fr)); + gap: 1rem; + width: 100%; +} + +@media (max-width: 996px) { + .libraries__cards { + width: unset; + max-width: 100%; + grid-template-columns: repeat(auto-fill, 20rem); + } +} + +.libraries__card { + background-color: var(--ifm-color-emphasis-0); + box-shadow: 0 0 5px 0 var(--ifm-color-emphasis-300); + border: 1px solid var(--ifm-color-emphasis-200); + border-radius: var(--ifm-global-radius); + color: inherit; + padding: 1.5rem; + display: flex; + gap: calc(4rem + 2px); +} + +@media (min-width: 997px) { + .libraries__card--wide { + grid-column: span 2; + } +} + +:root[data-theme='dark'] .libraries__card { + box-shadow: none; + background-color: var(--ifm-color-emphasis-100); +} + +.libraries__logo { + flex: 1 1 0; + aspect-ratio: 1/1; + width: calc(50% - 2rem - 1px); + border-radius: var(--ifm-global-radius); +} + +@media (max-width: 996px) { + .libraries__logo { + display: none; + } +} + +.libraries__section { + flex: 1 1 0; + aspect-ratio: 1/1; + display: flex; + flex-direction: column; +} + +.libraries__head { + display: flex; + gap: 1rem; +} + +.libraries__icon { + display: flex; + justify-content: center; + align-items: center; + background-color: var(--ifm-color-emphasis-200); + border-radius: var(--ifm-global-radius); + + width: 4rem; + height: 4rem; + + fill: var(--ifm-color-emphasis-900); +} + +.libraries__icon > svg { + width: 3rem; + height: 3rem; +} + +.libraries__header { + margin-top: 1.5rem; + margin-bottom: 0rem; + text-transform: uppercase; +} + +.libraries__features { + flex-grow: 1; + margin: 0; + padding-left: 1rem; + font-size: 0.8rem; + white-space: nowrap; +} + +.libraries__feature { + margin: 0.5rem 0; +} + +.nodes__feature > a, +.libraries__feature > a { + color: var(--ifm-color-emphasis-700); +} + +.nodes__feature > a, +.libraries__feature:hover > a { + color: var(--ifm-color-emphasis-700); +} +.libraries__button { + padding-top: 0.75rem; + padding-bottom: 0.75rem; +} + +.nodes__cards { + display: grid; + grid-template-columns: repeat(auto-fill, minmax(30rem, 1fr)); + gap: 1rem; + width: 100%; +} + +@media (max-width: 996px) { + .nodes__cards { + grid-template-columns: repeat(auto-fill, minmax(20rem, 1fr)); + } +} + +.nodes__card { + background-color: var(--ifm-color-emphasis-0); + box-shadow: 0 0 5px 0 var(--ifm-color-emphasis-300); + border: 1px solid var(--ifm-color-emphasis-200); + border-radius: var(--ifm-global-radius); + color: inherit; + padding: 1.5rem; + display: flex; + gap: 1.5rem; +} + +:root[data-theme='dark'] .nodes__card { + box-shadow: none; + background-color: var(--ifm-color-emphasis-100); +} + +.nodes__icon { + flex: 0 0 30%; + display: flex; + justify-content: center; + align-items: center; + background-color: var(--ifm-color-emphasis-200); + border-radius: var(--ifm-global-radius); + fill: var(--ifm-color-emphasis-900); +} + +.nodes__icon > svg { + width: 6rem; +} + +@media (max-width: 996px) { + .nodes__icon { + display: none; + } +} + +.nodes__section { + flex: 1 1 0; + display: flex; + flex-direction: column; +} + +.nodes__header { + margin: 0; + text-transform: uppercase; +} + +.nodes__features { + flex: 1 1 0; + margin: 1rem 0; + padding-left: 1rem; + font-size: 0.8rem; + white-space: nowrap; +} + +.nodes__feature { + margin: 0.5rem 0; +} + +.nodes__button { + padding-top: 0.75rem; + padding-bottom: 0.75rem; +} + +.resources__cards { + display: grid; + grid-template-columns: repeat( + auto-fill, + minmax(max(18rem, calc(50% - 0.75rem)), 1fr) + ); + gap: 1rem; + width: 100%; +} + +.resources__card { + background-color: var(--ifm-color-emphasis-0); + box-shadow: 0 0 5px 0 var(--ifm-color-emphasis-300); + border: 1px solid var(--ifm-color-emphasis-200); + border-radius: var(--ifm-global-radius); + color: inherit; + padding: 1.5rem; + display: flex; + flex-direction: column; + cursor: pointer; + transition: border-color 200ms ease-in-out; +} + +.resources__card:hover { + color: inherit; + border-color: var(--ifm-color-emphasis-400); +} + +:root[data-theme='dark'] .resources__card { + box-shadow: none; + background-color: var(--ifm-color-emphasis-100); +} + +.resources__card--logo:hover { + color: inherit; + border-color: var(--ifm-color-emphasis-200); +} + +@media (max-width: 996px) { + .resources__card--logo { + display: none; + } +} + +.resources__icon { + display: flex; + justify-content: center; + align-items: center; + background-color: var(--ifm-color-emphasis-200); + border-radius: var(--ifm-global-radius); + fill: var(--ifm-color-emphasis-900); + width: 3rem; + height: 3rem; +} + +.resources__icon > svg { + width: 3rem; +} + +.resources__header { + margin-top: 1rem; + margin-bottom: 0.5rem; +} + +.resources__description { + flex-grow: 1; + margin: 0; + font-size: 0.8rem; +} + +.further__cards { + display: grid; + grid-template-columns: repeat(auto-fill, minmax(18rem, 1fr)); + gap: 1rem; + width: 100%; +} + +@media (max-width: 996px) { + .further__cards { + width: unset; + max-width: 100%; + grid-template-columns: repeat(auto-fill, 20rem); + } +} + +.further__card { + aspect-ratio: 1/1; + display: flex; + justify-content: center; + align-items: center; + box-shadow: 0 0 5px 0 var(--ifm-color-emphasis-300); + border: 1px solid var(--ifm-color-emphasis-200); + border-radius: var(--ifm-global-radius); + color: inherit; + cursor: pointer; + transition: border-color 200ms ease-in-out; +} + +.further__card:hover { + color: inherit; + border-color: var(--ifm-color-emphasis-400); +} + +:root[data-theme='dark'] .further__card { + box-shadow: none; +} + +.further__section { + display: flex; + flex-direction: column; + align-items: center; + width: 16rem; + height: 12rem; +} + +.further__icon { + color: inherit; + display: flex; + justify-content: center; + align-items: center; + background-color: var(--ifm-color-emphasis-200); + border-radius: var(--ifm-global-radius); + fill: var(--ifm-color-emphasis-900); + width: 4rem; + height: 4rem; +} + +.further__icon > svg { + width: 3rem; + height: 3rem; +} + +.further__header { + margin-top: 1.5rem; + margin-bottom: 1rem; + text-align: center; +} + +.further__description { + text-align: center; + margin: 0; + font-size: 0.8rem; +} + +.about__card:hover, +.resources__card:hover, +.further__card:hover { + text-decoration: none; +} + +@media (max-width: 996px) { + .spaceholder__card__img { + display: none; + } +} diff --git a/docs/src/css/custom.css b/docs/src/css/custom.css new file mode 100755 index 000000000..646164deb --- /dev/null +++ b/docs/src/css/custom.css @@ -0,0 +1,48 @@ +/** + * Any CSS included here will be global. The classic template + * bundles Infima by default. Infima is a CSS framework designed to + * work well for content-centric websites. + */ + +/* You can override the default Infima variables here. */ +:root { + --ifm-color-primary: #2e8555; + --ifm-color-primary-dark: #29784c; + --ifm-color-primary-darker: #277148; + --ifm-color-primary-darkest: #205d3b; + --ifm-color-primary-light: #33925d; + --ifm-color-primary-lighter: #359962; + --ifm-color-primary-lightest: #3cad6e; + --ifm-code-font-size: 95%; + --docusaurus-highlighted-code-line-bg: rgba(0, 0, 0, 0.1); +} + +/* For readability concerns, you should choose a lighter palette in dark mode. */ +[data-theme='dark'] { + --ifm-color-primary: #25c2a0; + --ifm-color-primary-dark: #21af90; + --ifm-color-primary-darker: #1fa588; + --ifm-color-primary-darkest: #1a8870; + --ifm-color-primary-light: #29d5b0; + --ifm-color-primary-lighter: #32d8b4; + --ifm-color-primary-lightest: #4fddbf; + --docusaurus-highlighted-code-line-bg: rgba(0, 0, 0, 0.3); +} + +/* GitHub */ +.header-github-link:hover { + opacity: 0.6; +} + +.header-github-link:before { + content: ''; + width: 24px; + height: 24px; + display: flex; + background: url("data:image/svg+xml,%3Csvg viewBox='0 0 24 24' xmlns='http://www.w3.org/2000/svg'%3E%3Cpath d='M12 .297c-6.63 0-12 5.373-12 12 0 5.303 3.438 9.8 8.205 11.385.6.113.82-.258.82-.577 0-.285-.01-1.04-.015-2.04-3.338.724-4.042-1.61-4.042-1.61C4.422 18.07 3.633 17.7 3.633 17.7c-1.087-.744.084-.729.084-.729 1.205.084 1.838 1.236 1.838 1.236 1.07 1.835 2.809 1.305 3.495.998.108-.776.417-1.305.76-1.605-2.665-.3-5.466-1.332-5.466-5.93 0-1.31.465-2.38 1.235-3.22-.135-.303-.54-1.523.105-3.176 0 0 1.005-.322 3.3 1.23.96-.267 1.98-.399 3-.405 1.02.006 2.04.138 3 .405 2.28-1.552 3.285-1.23 3.285-1.23.645 1.653.24 2.873.12 3.176.765.84 1.23 1.91 1.23 3.22 0 4.61-2.805 5.625-5.475 5.92.42.36.81 1.096.81 2.22 0 1.606-.015 2.896-.015 3.286 0 .315.21.69.825.57C20.565 22.092 24 17.592 24 12.297c0-6.627-5.373-12-12-12'/%3E%3C/svg%3E") + no-repeat; +} + +.img { + padding: 3px; + border: 1px solid #2f15d6; } \ No newline at end of file diff --git a/docs/src/pages/index.js b/docs/src/pages/index.js new file mode 100755 index 000000000..dc8af1c0e --- /dev/null +++ b/docs/src/pages/index.js @@ -0,0 +1,6 @@ +import React from 'react'; +import HomeLayout from '@site/src/components/HomeLayout'; + +export default function Home() { + return

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a/docs/static/img/plugin/choose_plugin.png b/docs/static/img/plugin/choose_plugin.png new file mode 100644 index 000000000..4c71bd06d Binary files /dev/null and b/docs/static/img/plugin/choose_plugin.png differ diff --git a/docs/static/img/plugin/download.png b/docs/static/img/plugin/download.png new file mode 100644 index 000000000..77a5b889f Binary files /dev/null and b/docs/static/img/plugin/download.png differ diff --git a/docs/static/img/plugin/show_plugin.png b/docs/static/img/plugin/show_plugin.png new file mode 100644 index 000000000..a60ffffb7 Binary files /dev/null and b/docs/static/img/plugin/show_plugin.png differ diff --git a/docs/static/img/plugin/show_plugin_more.png b/docs/static/img/plugin/show_plugin_more.png new file mode 100644 index 000000000..877e775aa Binary files /dev/null and b/docs/static/img/plugin/show_plugin_more.png differ diff --git a/docs/static/redirect.js b/docs/static/redirect.js new file mode 100644 index 000000000..39e157c59 --- /dev/null +++ b/docs/static/redirect.js @@ -0,0 +1,5 @@ +window.onload = function() { + if (window.location.pathname !== '/docs/overview') { + window.location.href = '/docs/overview'; + } +}; \ No newline at end of file diff --git a/docs/use_cases/query_database_data.md b/docs/use_cases/query_database_data.md deleted file mode 100644 index fa25f7de7..000000000 --- a/docs/use_cases/query_database_data.md +++ /dev/null @@ -1 +0,0 @@ -# Query database data \ No newline at end of file diff --git a/docs/use_cases/sql_generation_and_diagnosis.md b/docs/use_cases/sql_generation_and_diagnosis.md deleted file mode 100644 index b0282989f..000000000 --- a/docs/use_cases/sql_generation_and_diagnosis.md +++ /dev/null @@ -1,5 +0,0 @@ -# SQL generation and diagnosis - -DB-GPT provides SQL generation and diagnostic capabilities. With advanced natural language processing algorithms and a deep understanding of SQL syntax and semantics, the model can generate complex SQL queries from natural language input, as well as diagnose and fix issues with existing queries. This allows users to save time and streamline their workflow, while also improving the accuracy and efficiency of their SQL operations. - -![SQL Generation](../../assets/demo_en.gif) \ No newline at end of file diff --git a/docs/use_cases/tool_use_with_plugin.md b/docs/use_cases/tool_use_with_plugin.md deleted file mode 100644 index 93d665c89..000000000 --- a/docs/use_cases/tool_use_with_plugin.md +++ /dev/null @@ -1,27 +0,0 @@ -# Tool use with plugin - -- DB-GPT supports a variety of plug-ins, such as BaiduSearch, SendEmail. In addition, some database management platforms can also package their interfaces and package them into plug-ins, and use the model to realize the ability of "single-sentence requirements" - - -## Baidu-Search-Plugin - -[Db-GPT Plugins](https://github.com/eosphoros-ai/DB-GPT-Plugins/blob/main/src/dbgpt_plugins/Readme.md) - -- Perform search queries using the Baidu search engine [DB-GPT-Plugins](https://github.com/eosphoros-ai/DB-GPT-Plugins). - -```bash -git clone https://github.com/csunny/DB-GPT-Plugins.git -pip install -r requirements.txt -python /DB-GPT-Plugins/src/dbgpt_plugins/db_dashboard/mock_datas.py -cp /DB-GPT-Plugins/src/dbgpt_plugins/db_dashboard/mock_datas/db-gpt-test.db /DB-GPT/pilot/mock_datas/ - -python /DB-GPT/pilot/llmserver.py -python /DB-GPT/pilot/webserver.py -``` -- Test Case: Use a histogram to analyze the total order amount of users in different cities. -

- -

- -- More detail see: [DB-DASHBOARD](https://github.com/eosphoros-ai/DB-GPT-Plugins/blob/main/src/dbgpt_plugins/Readme.md) - diff --git a/docs/yarn.lock b/docs/yarn.lock new file mode 100644 index 000000000..b119b9dd8 --- /dev/null +++ b/docs/yarn.lock @@ -0,0 +1,7731 @@ +# THIS IS AN AUTOGENERATED FILE. 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