docs:v0.3.1 docs

1.fmt
2.docs
This commit is contained in:
aries_ckt 2023-07-13 19:23:03 +08:00
parent 4e33e6ec2e
commit b5f3e079db
19 changed files with 374 additions and 179 deletions

View File

@ -8,7 +8,7 @@ msgid ""
msgstr ""
"Project-Id-Version: DB-GPT 0.3.0\n"
"Report-Msgid-Bugs-To: \n"
"POT-Creation-Date: 2023-07-05 17:51+0800\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 <EMAIL@ADDRESS>\n"
"Language: zh_CN\n"
@ -19,29 +19,29 @@ msgstr ""
"Content-Transfer-Encoding: 8bit\n"
"Generated-By: Babel 2.12.1\n"
#: ../../getting_started/getting_started.md:1 2e1519d628044c07b384e8bbe441863a
#: ../../getting_started/getting_started.md:1 0b2e795438a3413c875fd80191e85bad
msgid "Quickstart Guide"
msgstr "使用指南"
#: ../../getting_started/getting_started.md:3 00e8dc6e242d4f3b8b2fbc5e06f1f14e
#: ../../getting_started/getting_started.md:3 7b84c9776f8a4f9fb55afc640f37f45c
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/getting_started.md:5 4b4473a5fbd64cef996d82fa36abe136
#: ../../getting_started/getting_started.md:5 1b2880e1ef674bfdbf39ac9f330aeec9
msgid "Installation"
msgstr "安装"
#: ../../getting_started/getting_started.md:7 5ab3187dd2134afe958d83a431c98f43
#: ../../getting_started/getting_started.md:7 d0a8c6654bfe4bbdb0eb40ceb2ea3388
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/getting_started.md:9 7286e3a0da00450c9a6e9f29dbd27130
#: ../../getting_started/getting_started.md:9 0a4e0b06c7fe49a9b2ca56ba2eb7b8ba
msgid "1. Hardware Requirements"
msgstr "1. 硬件要求"
#: ../../getting_started/getting_started.md:10 3f3d279ca8a54c8c8ed16af3e0ffb281
#: ../../getting_started/getting_started.md:10 2b42f6546ef141f696943ba2120584e5
msgid ""
"As our project has the ability to achieve ChatGPT performance of over "
"85%, there are certain hardware requirements. However, overall, the "
@ -49,62 +49,62 @@ msgid ""
"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:"
#: ../../getting_started/getting_started.md 6e1e882511254687bd46fe45447794d1
#: ../../getting_started/getting_started.md 4df0c44eff8741f39ca0fdeff222f90c
msgid "GPU"
msgstr "GPU"
#: ../../getting_started/getting_started.md f0ee9919e1254bcdbe6e489a5fbf450f
#: ../../getting_started/getting_started.md b740a2991ce546cca43a426b760e9901
msgid "VRAM Size"
msgstr "显存大小"
#: ../../getting_started/getting_started.md eed88601ef0b49b58d95b89928a3810e
#: ../../getting_started/getting_started.md 222b91ff82f14d12acaac5aa238758c8
msgid "Performance"
msgstr "显存大小"
#: ../../getting_started/getting_started.md 4f717383ef2d4e2da9ee2d1c148aa6c5
#: ../../getting_started/getting_started.md c2d2ae6a4c964c4f90a9009160754782
msgid "RTX 4090"
msgstr "RTX 4090"
#: ../../getting_started/getting_started.md d2d9bd1b57694404b39cdef49fd5b570
#: d7d914b8d5e34ac192b94d48f0ee1781
#: ../../getting_started/getting_started.md 529220ec6a294e449dc460ba2e8829a1
#: 5e0c5900842e4d66b2064b13cc31a3ad
msgid "24 GB"
msgstr "24 GB"
#: ../../getting_started/getting_started.md cb86730ab05e4172941c3e771384c4ba
#: ../../getting_started/getting_started.md 84d29eef342f4d6282295c0e32487548
msgid "Smooth conversation inference"
msgstr "可以流畅的进行对话推理,无卡顿"
#: ../../getting_started/getting_started.md 3e32d5c38bf6499cbfedb80944549114
#: ../../getting_started/getting_started.md 5a10effe322e4afb8315415c04dc05a4
msgid "RTX 3090"
msgstr "RTX 3090"
#: ../../getting_started/getting_started.md 1d3caa2a06844997ad55d20863559e9f
#: ../../getting_started/getting_started.md 8924059525ab43329a8bb6659e034d5e
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"
#: ../../getting_started/getting_started.md b80ec359bd004d5f801ec09ca3b2d0ff
#: ../../getting_started/getting_started.md 10f5bc076f524127a956d7a23f3666ba
msgid "V100"
msgstr "V100"
#: ../../getting_started/getting_started.md aed55a6b8c8d49d9b9c02bfd5c10b062
#: ../../getting_started/getting_started.md 7d664e81984847c7accd08db93fad404
msgid "16 GB"
msgstr "16 GB"
#: ../../getting_started/getting_started.md dcd6daab75fe4bf8b8dd19ea785f0bd6
#: ../../getting_started/getting_started.md 86765bc9ab01409fb7f5edf04f9b32a5
msgid "Conversation inference possible, noticeable stutter"
msgstr "可以进行对话推理,有明显卡顿"
#: ../../getting_started/getting_started.md:18 e39a4b763ed74cea88d54d163ea72ce0
#: ../../getting_started/getting_started.md:18 a0ac5591c0ac4ac6a385e562353daf22
msgid "2. Install"
msgstr "2. 安装"
#: ../../getting_started/getting_started.md:20 9beba274b78a46c6aafb30173372b334
#: ../../getting_started/getting_started.md:20 a64a9a5945074ece872509f8cb425da9
msgid ""
"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。"
#: ../../getting_started/getting_started.md:25 3bce689bb49043eca5b9aa3c5525eaac
#: ../../getting_started/getting_started.md:25 11e799a372ab4d0f8269cd7be98bebc6
msgid ""
"We use [Chroma embedding database](https://github.com/chroma-core/chroma)"
" as the default for our vector database, so there is no need for special "
@ -117,11 +117,11 @@ 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"
#: ../../getting_started/getting_started.md:34 61ad49740d0b49afa254cb2d10a0d2ae
#: ../../getting_started/getting_started.md:34 dcab69c83d4c48b9bb19c4336ee74a66
msgid "Before use DB-GPT Knowledge Management"
msgstr "使用知识库管理功能之前"
#: ../../getting_started/getting_started.md:40 656041e456f248a0a472be06357d7f89
#: ../../getting_started/getting_started.md:40 735aeb6ae8aa4344b7ff679548279acc
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 "
@ -130,29 +130,33 @@ 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。"
#: ../../getting_started/getting_started.md:42 4dfb7d63fdf544f2bf9dd8663efa8d31
#: ../../getting_started/getting_started.md:43 7cbefe131b24488b9be39b3e8ed4f563
#, fuzzy
msgid "Notice make sure you have install git-lfs"
msgstr "确保你已经安装了git-lfs"
#: ../../getting_started/getting_started.md:50 a52c137b8ef54b7ead41a2d8ff81d457
#: ../../getting_started/getting_started.md:53 54ec90ebb969475988451cd66e6ff412
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/getting_started.md:56 db87d872a47047dc8cd1de390d068ed4
#: ../../getting_started/getting_started.md:56 9bdadbee88af4683a4eb7b4f221fb4b8
msgid "cp .env.template .env"
msgstr "cp .env.template .env"
#: ../../getting_started/getting_started.md:59 6357c4a0154b4f08a079419ac408442d
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/getting_started.md:58 c8865a327b4b44daa55813479c743e3c
#: ../../getting_started/getting_started.md:61 2f349f3ed3184b849ade2a15d5bf0c6c
msgid "3. Run"
msgstr "3. 运行"
#: ../../getting_started/getting_started.md:59 e81dabe730134753a4daa05a7bdd44af
#: ../../getting_started/getting_started.md:62 fe408e4405bd48288e2e746386615925
msgid ""
"You can refer to this document to obtain the Vicuna weights: "
"[Vicuna](https://github.com/lm-sys/FastChat/blob/main/README.md#model-"
@ -161,7 +165,7 @@ 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。"
#: ../../getting_started/getting_started.md:61 714cbc9485ea47d0a06aa1a31b9af3e3
#: ../../getting_started/getting_started.md:64 c0acfe28007f459ca21174f968763fa3
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 "
@ -170,11 +174,11 @@ 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。"
#: ../../getting_started/getting_started.md:63 2b8f6985fe1a414e95d334d3ee9d0878
#: ../../getting_started/getting_started.md:66 cc0f4c4e43f24b679f857a8d937528ee
msgid "prepare server sql script"
msgstr "准备db-gpt server sql脚本"
#: ../../getting_started/getting_started.md:69 7cb9beb0e15a46759dbcb4606dcb6867
#: ../../getting_started/getting_started.md:72 386948064fe646f2b9f51a262dd64bf2
msgid ""
"set .env configuration set your vector store type, "
"eg:VECTOR_STORE_TYPE=Chroma, now we support Chroma and Milvus(version > "
@ -183,17 +187,17 @@ 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) "
#: ../../getting_started/getting_started.md:72 cdb7ef30e8c9441293e8b3fd95d621ed
#: ../../getting_started/getting_started.md:75 e6f6b06459944f2d8509703af365c664
#, fuzzy
msgid "Run db-gpt server"
msgstr "运行模型服务"
#: ../../getting_started/getting_started.md:77 e7bb3001d46b458aa0c522c4a7a8d45b
#: ../../getting_started/getting_started.md:80 489b595dc08a459ca2fd83b1389d3bbd
#, fuzzy
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/getting_started.md:79 68c55e3ecfc642f2869a9917ec65904c
#: ../../getting_started/getting_started.md:82 699afb01c9f243ab837cdc73252f624c
msgid ""
"If you want to access an external LLM service, you need to 1.set the "
"variables LLM_MODEL=YOUR_MODEL_NAME "
@ -201,11 +205,11 @@ msgid ""
"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"
#: ../../getting_started/getting_started.md:86 474aea4023bb44dd970773b110bbf0ee
#: ../../getting_started/getting_started.md:89 7df7f3870e1140d3a17dc322a46d6476
msgid ""
"If you want to learn about dbgpt-webui, read https://github.com/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"
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"

View File

@ -0,0 +1,85 @@
# SOME DESCRIPTIVE TITLE.
# Copyright (C) 2023, csunny
# This file is distributed under the same license as the DB-GPT package.
# FIRST AUTHOR <EMAIL@ADDRESS>, 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 <EMAIL@ADDRESS>\n"
"Language: zh_CN\n"
"Language-Team: zh_CN <LL@li.org>\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 bc5bfc8ebfc847c5a22f2346357cf747
msgid "Installation"
msgstr "安装dbgpt包指南"
#: ../../getting_started/installation.md:2 1aaef0db5ee9426aa337021d782666af
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 de542f259e20441991a0e5a7d52769b8
msgid "Installation from Pip"
msgstr "使用pip安装"
#: ../../getting_started/installation.md:6 3357f019aa8249b292162de92757eec4
msgid "You can simply pip install:"
msgstr "你可以使用pip install"
#: ../../getting_started/installation.md:12 9c610d593608452f9d7d8d7e462251e3
msgid "Notice:make sure python>=3.10"
msgstr "注意:确保你的python版本>=3.10"
#: ../../getting_started/installation.md:15 b2ed238c29bb40cba990068e8d7ceae7
msgid "Environment Setup"
msgstr "环境设置"
#: ../../getting_started/installation.md:17 4804ad4d8edf44f49b1d35b271635fad
msgid "By default, if you use the EmbeddingEngine api"
msgstr "如果你想使用EmbeddingEngine api"
#: ../../getting_started/installation.md:19 2205f69ec60d4f73bb3a93a583928455
msgid "you will prepare embedding models from huggingface"
msgstr "你需要从huggingface下载embedding models"
#: ../../getting_started/installation.md:22 693c18a83f034dcc8c263674418bcde2
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 dd8d0880b55e4c48bfc414f8cbdda268
msgid "version:"
msgstr "版本:"
#: ../../getting_started/installation.md:31 731e634b96164efbbc1ce9fa88361b12
msgid "db-gpt0.3.0"
msgstr "db-gpt0.3.0"
#: ../../getting_started/installation.md:32 38fb635be4554d94b527c6762253d46d
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 a60b0ffe21a74ebca05529dc1dd1ba99
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 3c752c9305414719bc3f561cf18a75af
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)"

View File

@ -8,7 +8,7 @@ msgid ""
msgstr ""
"Project-Id-Version: DB-GPT 0.3.0\n"
"Report-Msgid-Bugs-To: \n"
"POT-Creation-Date: 2023-06-30 17:16+0800\n"
"POT-Creation-Date: 2023-07-12 16:23+0800\n"
"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
"Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
"Language: zh_CN\n"
@ -19,25 +19,25 @@ msgstr ""
"Content-Transfer-Encoding: 8bit\n"
"Generated-By: Babel 2.12.1\n"
#: ../../getting_started/tutorials.md:1 e494f27e68fd40efa2864a532087cfef
#: ../../getting_started/tutorials.md:1 cb100b89a2a747cd90759e415c737070
msgid "Tutorials"
msgstr "教程"
#: ../../getting_started/tutorials.md:4 8eecfbf3240b44fcb425034600316cea
#: ../../getting_started/tutorials.md:4 dbc2a2346b384cc3930086f97181b14b
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 a40601867a3d4ce886a197f2f337ec0f
#: ../../getting_started/tutorials.md:6 67e5b6dbac654d428e6a8be9d1ec6473
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 493e6f56a75d45ef8bb15d3049a24994
#: ../../getting_started/tutorials.md:8 744aaec68aa3413c9b17b09714476d32
msgid "Introduction"
msgstr "介绍"
#: ../../getting_started/tutorials.md:9 4526a793cdb94b8f99f41c48cd5ee453
#: ../../getting_started/tutorials.md:9 305bcf5e847a4322a2834b84fa3c694a
#, fuzzy
msgid "[What is DB-GPT](https://www.youtube.com/watch?v=QszhVJerc0I)"
msgstr ""
@ -45,12 +45,12 @@ msgstr ""
"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&timestamp=1686307943&unique_k=bhO3lgQ&up_id=31375446)"
" by csunny (https://github.com/csunny/DB-GPT)"
#: ../../getting_started/tutorials.md:11 95313384e5da4f5db96ac990596b2e73
#: ../../getting_started/tutorials.md:11 22fdc6937b2248ae8f5a7ef385aa55d9
#, fuzzy
msgid "Knowledge"
msgstr "知识库"
#: ../../getting_started/tutorials.md:13 e7a141f4df8d4974b0797dd7723c4658
#: ../../getting_started/tutorials.md:13 9bbf0f5aece64389b93b16235abda58e
#, fuzzy
msgid ""
"[How to Create your own knowledge repository](https://db-"
@ -59,55 +59,55 @@ msgstr ""
"[怎么创建自己的知识库](https://db-"
"gpt.readthedocs.io/en/latest/modules/knowledge.html)"
#: ../../getting_started/tutorials.md:15 f7db5b05a2db44e6a98b7d0df0a6f4ee
#: ../../getting_started/tutorials.md:15 ae201d75a3aa485e99b258103245db1c
#, fuzzy
msgid "![Add new Knowledge demonstration](../../assets/new_knownledge.gif)"
msgstr "[新增知识库演示](../../assets/new_knownledge_en.gif)"
#: ../../getting_started/tutorials.md:15 1a1647a7ca23423294823529301dd75f
#: ../../getting_started/tutorials.md:15 e7bfb3396f7b42f1a1be9f29df1773a2
#, fuzzy
msgid "Add new Knowledge demonstration"
msgstr "[新增知识库演示](../../assets/new_knownledge_en.gif)"
#: ../../getting_started/tutorials.md:17 de26224a814e4c6798d3a342b0f0fe3a
#: ../../getting_started/tutorials.md:17 d37acc0486ec40309e7e944bb0458b0a
msgid "SQL Generation"
msgstr "SQL生成"
#: ../../getting_started/tutorials.md:18 f8fe82c554424239beb522f94d285c52
#: ../../getting_started/tutorials.md:18 86a328c9e15f46679a2611f7162f9fbe
#, fuzzy
msgid "![sql generation demonstration](../../assets/demo_en.gif)"
msgstr "[sql生成演示](../../assets/demo_en.gif)"
#: ../../getting_started/tutorials.md:18 41e932b692074fccb8059cadb0ed320e
#: ../../getting_started/tutorials.md:18 03bc8d7320be44f0879a553a324ec26f
#, fuzzy
msgid "sql generation demonstration"
msgstr "[sql生成演示](../../assets/demo_en.gif)"
#: ../../getting_started/tutorials.md:20 78bda916272f4cf99e9b26b4d9ba09ab
#: ../../getting_started/tutorials.md:20 5f3b241f24634c09880d5de014f64f1b
msgid "SQL Execute"
msgstr "SQL执行"
#: ../../getting_started/tutorials.md:21 53cc83de34784c3c8d4d8204eacccbe9
#: ../../getting_started/tutorials.md:21 13a16debf2624f44bfb2e0453c11572d
#, fuzzy
msgid "![sql execute demonstration](../../assets/auto_sql_en.gif)"
msgstr "[sql execute 演示](../../assets/auto_sql_en.gif)"
#: ../../getting_started/tutorials.md:21 535c06f487ed4d15a6cdd17a0154d798
#: ../../getting_started/tutorials.md:21 2d9673cfd48b49a5b1942fdc9de292bf
#, fuzzy
msgid "sql execute demonstration"
msgstr "SQL执行演示"
#: ../../getting_started/tutorials.md:23 0482e6155dc44843adc3a3aa77528f03
#: ../../getting_started/tutorials.md:23 8cc0c647ad804969b470b133708de37f
#, fuzzy
msgid "Plugins"
msgstr "DB插件"
#: ../../getting_started/tutorials.md:24 632617dd88fe4688b789fbb941686c0f
#: ../../getting_started/tutorials.md:24 cad5cc0cb94b42a1a6619bbd2a8b9f4c
#, fuzzy
msgid "![db plugins demonstration](../../assets/chart_db_city_users.png)"
msgid "![db plugins demonstration](../../assets/dashboard.png)"
msgstr "[db plugins 演示](../../assets/dbgpt_bytebase_plugin.gif)"
#: ../../getting_started/tutorials.md:24 020ff499469145f0a34ac468fff91948
#: ../../getting_started/tutorials.md:24 adeee7ea37b743c9b251976124520725
msgid "db plugins demonstration"
msgstr "DB插件演示"

View File

@ -8,7 +8,7 @@ msgid ""
msgstr ""
"Project-Id-Version: DB-GPT 0.3.0\n"
"Report-Msgid-Bugs-To: \n"
"POT-Creation-Date: 2023-07-12 11:57+0800\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 <EMAIL@ADDRESS>\n"
"Language: zh_CN\n"
@ -19,12 +19,12 @@ msgstr ""
"Content-Transfer-Encoding: 8bit\n"
"Generated-By: Babel 2.12.1\n"
#: ../../modules/knowledge.rst:2 ../../modules/knowledge.rst:98
#: ca36c0ca545c4d70b51fe811a3e7caca
#: ../../modules/knowledge.rst:2 ../../modules/knowledge.rst:136
#: 3cc8fa6e9fbd4d889603d99424e9529a
msgid "Knowledge"
msgstr "知识"
#: ../../modules/knowledge.rst:4 37818bc0ace74e008a52dbd838898c87
#: ../../modules/knowledge.rst:4 0465a393d9d541958c39c1d07c885d1f
#, fuzzy
msgid ""
"As the knowledge base is currently the most significant user demand "
@ -36,47 +36,66 @@ 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.rst:6 ../../modules/knowledge.rst:13
#: c92bd129bf5043fd9d6224d245cc9a55
#, fuzzy
#: ../../modules/knowledge.rst:6 e670cbe14d8e4da88ba935e4120c31e0
msgid ""
"We currently support many document formats: raw text, txt, pdf, md, html,"
" doc, ppt, and url."
msgstr "当前支持txt, pdf, md, html, doc, ppt, url文档格式"
" 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 ""
#: ../../modules/knowledge.rst:9 eec1169fea7a4a669433c347a4d929a2
#: ../../modules/knowledge.rst:9 e0bf601a1a0c458297306db6ff79f931
msgid "**Create your own knowledge repository**"
msgstr "创建你自己的知识库"
#: ../../modules/knowledge.rst:11 20565959da0842aa9f5bb3fe8fb37e10
#: ../../modules/knowledge.rst:11 bb26708135d44615be3c1824668010f6
msgid "1.prepare"
msgstr "准备"
#: ../../modules/knowledge.rst:15 515555d13e7548deb596d80ea1514bb2
#: ../../modules/knowledge.rst:13 c150a0378f3e4625908fa0d8a25860e9
#, fuzzy
msgid ""
"We currently support many document formats: TEXT(raw text), "
"DOCUMENT(.txt, .pdf, .md, .doc, .ppt, .html), and URL."
msgstr "当前支持txt, pdf, md, html, doc, ppt, url文档格式"
#: ../../modules/knowledge.rst:15 7f9f02a93d5d4325b3d2d976f4bb28a0
msgid "before execution:"
msgstr "开始前"
#: ../../modules/knowledge.rst:21 3333f92965ee41ea9cfa542de6c1e976
#: ../../modules/knowledge.rst:24 59699a8385e04982a992cf0d71f6dcd5
#, fuzzy
msgid ""
"2.prepare embedding model, you can download from https://huggingface.co/."
" Notice you have installed git-lfs. eg: git clone "
"https://huggingface.co/THUDM/chatglm2-6b"
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"
" 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"
#: ../../modules/knowledge.rst:29 7abcbe007d594f4aaa43ddef88ef4d89
#: ../../modules/knowledge.rst:27 2be1a17d0b54476b9dea080d244fd747
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"
#: ../../modules/knowledge.rst:33 d328f6e243624c9488ebd27c9324621b
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"
#: ../../modules/knowledge.rst:50 058fa57484a64756ab2650b46f4b33bf
#: ../../modules/knowledge.rst:63 44f97154eff647d399fd30b6f9e3b867
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 "
#: ../../modules/knowledge.rst:62 5f255b96abd346479ab3c371393e47dc
#: ../../modules/knowledge.rst:75 e2581b414f0148bca88253c7af9cd591
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:"
#: ../../modules/knowledge.rst:95 74c110414f924bbfa3d512e45ba2f30f
#, fuzzy
msgid ""
"4.init Document Type EmbeddingEngine api and embedding your document into"
@ -86,17 +105,17 @@ 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)"
#: ../../modules/knowledge.rst:75 d8c85ba7714749269714b03857738f70
#: ../../modules/knowledge.rst:108 0afd40098d5f4dfd9e44fe1d8004da25
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"
#: ../../modules/knowledge.rst:87 c59e4650d57e44ae8d967768dddf908a
#: ../../modules/knowledge.rst:120 a66961bf3efd41fa8ea938129446f5a5
msgid "4.similar search based on your knowledge base. ::"
msgstr "在知识库进行相似性搜索"
#: ../../modules/knowledge.rst:93 f500fcdc791c4286b411819ae9ab3dc6
#: ../../modules/knowledge.rst:126 b7066f408378450db26770f83fbd2716
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 "
@ -106,12 +125,48 @@ 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。"
#: ../../modules/knowledge.rst:95 62a5e10a19844ba9955113f5c78cb460
#: ../../modules/knowledge.rst:128 58481d55cab74936b6e84b24c39b1674
#, fuzzy
msgid ""
"`pdf_embedding <./knowledge/pdf_embedding.html>`_: supported pdf "
"`pdf_embedding <./knowledge/pdf/pdf_embedding.html>`_: supported pdf "
"embedding."
msgstr "pdf_embedding <./knowledge/pdf_embedding.html>`_: supported pdf embedding."
#: ../../modules/knowledge.rst:129 fbb013c4f1bc46af910c91292f6690cf
#, fuzzy
msgid ""
"`markdown_embedding <./knowledge/markdown/markdown_embedding.html>`_: "
"supported markdown embedding."
msgstr "pdf_embedding <./knowledge/pdf_embedding.html>`_: supported pdf embedding."
#: ../../modules/knowledge.rst:130 59d45732f4914d16b4e01aee0992edf7
#, fuzzy
msgid ""
"`word_embedding <./knowledge/word/word_embedding.html>`_: supported word "
"embedding."
msgstr "pdf_embedding <./knowledge/pdf_embedding.html>`_: supported pdf embedding."
#: ../../modules/knowledge.rst:131 df0e6f311861423e885b38e020a7c0f0
#, fuzzy
msgid ""
"`url_embedding <./knowledge/url/url_embedding.html>`_: supported url "
"embedding."
msgstr "pdf_embedding <./knowledge/pdf_embedding.html>`_: supported pdf embedding."
#: ../../modules/knowledge.rst:132 7c550c1f5bc34fe9986731fb465e12cd
#, fuzzy
msgid ""
"`ppt_embedding <./knowledge/ppt/ppt_embedding.html>`_: supported ppt "
"embedding."
msgstr "pdf_embedding <./knowledge/pdf_embedding.html>`_: supported pdf embedding."
#: ../../modules/knowledge.rst:133 8648684cb191476faeeb548389f79050
#, fuzzy
msgid ""
"`string_embedding <./knowledge/string/string_embedding.html>`_: supported"
" raw text embedding."
msgstr "pdf_embedding <./knowledge/pdf_embedding.html>`_: supported pdf embedding."
#~ 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"

View File

@ -8,7 +8,7 @@ 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"
"POT-Creation-Date: 2023-07-13 15:39+0800\n"
"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
"Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
"Language: zh_CN\n"
@ -20,12 +20,13 @@ msgstr ""
"Generated-By: Babel 2.12.1\n"
#: ../../modules/knowledge/markdown/markdown_embedding.md:1
#: b5fd3aea05a64590955b958b753bf22a
msgid "MarkdownEmbedding"
#: 6d4eb4d8566b4dbaa301715148342aca
#, fuzzy
msgid "Markdown"
msgstr "MarkdownEmbedding"
#: ../../modules/knowledge/markdown/markdown_embedding.md:3
#: 0f98ce5b34d44c6f9c828e4b497984de
#: 050625646fa14cb1822d0d430fdf06ec
msgid ""
"markdown embedding can import md text into a vector knowledge base. The "
"entire embedding process includes the read (loading data), data_process "
@ -36,20 +37,20 @@ msgstr ""
"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
#: 7f5ebfa8c7c146d7a340baca85634e16
#: af1313489c164e968def2f5f1716a522
msgid "inheriting the SourceEmbedding"
msgstr "继承SourceEmbedding"
#: ../../modules/knowledge/markdown/markdown_embedding.md:17
#: 732e946bc9d149a5af802b239304b943
#: ../../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:33
#: f7e53658aee7403688b333b24ff08ce2
#: ../../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"

View File

@ -8,7 +8,7 @@ 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"
"POT-Creation-Date: 2023-07-13 15:39+0800\n"
"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
"Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
"Language: zh_CN\n"
@ -20,12 +20,12 @@ msgstr ""
"Generated-By: Babel 2.12.1\n"
#: ../../modules/knowledge/pdf/pdf_embedding.md:1
#: fe600a1f3f9f492da81652ebd3d6d52d
msgid "PDFEmbedding"
#: edf96281acc04612a3384b451dc71391
msgid "PDF"
msgstr ""
#: ../../modules/knowledge/pdf/pdf_embedding.md:3
#: a26a7d6ff041476b975bab5c0bf9f506
#: fdc7396cc2eb4186bb28ea8c491738bc
#, fuzzy
msgid ""
"pdfembedding can import PDF text into a vector knowledge base. The entire"
@ -37,20 +37,23 @@ msgstr ""
"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
#: 1895f2a6272c43f0b328caba092102a9
#: d4950371bace43d8957bce9757d77b6e
msgid "inheriting the SourceEmbedding"
msgstr "继承SourceEmbedding"
#: ../../modules/knowledge/pdf/pdf_embedding.md:17
#: 2a4a349398354f9cb3e8d9630a4b8696
#: ../../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:34
#: 9b5c6d3e9e96443a908a09a8a762ea7a
#: ../../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 ""

View File

@ -8,7 +8,7 @@ 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"
"POT-Creation-Date: 2023-07-13 15:39+0800\n"
"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
"Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
"Language: zh_CN\n"
@ -20,12 +20,12 @@ msgstr ""
"Generated-By: Babel 2.12.1\n"
#: ../../modules/knowledge/ppt/ppt_embedding.md:1
#: 2cdb249b2b284064a0c9117d051e35d4
msgid "PPTEmbedding"
#: 86b98a120d0d4796a034c47a23ec8a03
msgid "PPT"
msgstr ""
#: ../../modules/knowledge/ppt/ppt_embedding.md:3
#: 71676e9b35434a849a206788da8f1394
#: af78e8c3a6c24bf79e03da41c6d13fba
msgid ""
"ppt embedding can import ppt text into a vector knowledge base. The "
"entire embedding process includes the read (loading data), data_process "
@ -36,20 +36,23 @@ msgstr ""
"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
#: 016aeae4786e4d5bad815670bd109481
#: 0ddb5ec40a4e4864b63e7f578c2f3c34
msgid "inheriting the SourceEmbedding"
msgstr "继承SourceEmbedding"
#: ../../modules/knowledge/ppt/ppt_embedding.md:17
#: 2fb5b9dc912342df8c275cfd0e993fe0
#: ../../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:31
#: 9a00f72c7ec84bde9971579c720d2628
#: ../../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 ""

View File

@ -8,7 +8,7 @@ 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"
"POT-Creation-Date: 2023-07-13 15:39+0800\n"
"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
"Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
"Language: zh_CN\n"
@ -20,12 +20,12 @@ msgstr ""
"Generated-By: Babel 2.12.1\n"
#: ../../modules/knowledge/url/url_embedding.md:1
#: e6d335e613ec4c3a80b89de67ba93098
msgid "URL Embedding"
#: c1db535b997f4a90a75806f389200a4e
msgid "URL"
msgstr ""
#: ../../modules/knowledge/url/url_embedding.md:3
#: 25e7643335264bdaaa9386ded243d51d
#: a4e3929be4964c35b7d169eaae8f29fe
msgid ""
"url embedding can import PDF text into a vector knowledge base. The "
"entire embedding process includes the read (loading data), data_process "
@ -36,20 +36,23 @@ msgstr ""
"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
#: 4b8ca6d93ed0412ab1e640bd42b400ac
#: 0c0be35a31e84e76a60e9e4ffb61a414
msgid "inheriting the SourceEmbedding"
msgstr "继承SourceEmbedding"
#: ../../modules/knowledge/url/url_embedding.md:17
#: 5d69d27adc70406db97c398a339f6453
#: ../../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:34
#: 7d055e181d9b4d47965ab249b18bd704
#: ../../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 ""

View File

@ -8,7 +8,7 @@ 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"
"POT-Creation-Date: 2023-07-13 15:39+0800\n"
"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
"Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
"Language: zh_CN\n"
@ -20,12 +20,12 @@ msgstr ""
"Generated-By: Babel 2.12.1\n"
#: ../../modules/knowledge/word/word_embedding.md:1
#: 1b3272def692480bb101060a33d076c6
msgid "WordEmbedding"
#: fa236aa8d2e5471d8436e0ec60f906e8
msgid "Word"
msgstr ""
#: ../../modules/knowledge/word/word_embedding.md:3
#: a7ea0e94e5c74dab9aa7fb80ed42ed39
#: 02d0c183f7f646a7b74e22d0166c8718
msgid ""
"word embedding can import word doc/docx text into a vector knowledge "
"base. The entire embedding process includes the read (loading data), "
@ -36,20 +36,23 @@ msgstr ""
"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
#: 12ba9527ef0745538dffb6b1dcf96933
#: ffa094cb7739457d88666c5b624bf078
msgid "inheriting the SourceEmbedding"
msgstr "继承SourceEmbedding"
#: ../../modules/knowledge/word/word_embedding.md:17
#: a4e5e7553f4a43b0b79ba0de83268ef0
#: ../../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:29
#: 188a434dee7543f89cf5f1584f29ca62
#: ../../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 ""

View File

@ -8,7 +8,7 @@ msgid ""
msgstr ""
"Project-Id-Version: DB-GPT 0.3.0\n"
"Report-Msgid-Bugs-To: \n"
"POT-Creation-Date: 2023-06-13 11:38+0800\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 <EMAIL@ADDRESS>\n"
"Language: zh_CN\n"
@ -19,40 +19,43 @@ msgstr ""
"Content-Transfer-Encoding: 8bit\n"
"Generated-By: Babel 2.12.1\n"
#: ../../use_cases/knownledge_based_qa.md:1 ddfe412b92e14324bdc11ffe58114e5f
msgid "Knownledge based qa"
msgstr "知识问答"
#~ msgid "Knownledge based qa"
#~ msgstr "知识问答"
#: ../../use_cases/knownledge_based_qa.md:3 48635316cc704a779089ff7b5cb9a836
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 ""
#~ "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。"
#: ../../use_cases/knownledge_based_qa.md:6 0a5c68429c9343cf8b88f4f1dddb18eb
#, fuzzy
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 ""
#~ "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。"
#: ../../use_cases/knownledge_based_qa.md:20 83f3544c06954e5cbc0cc7788f699eb1
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 ""
#~ "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。"
#: ../../use_cases/knownledge_based_qa.md:31 ac12f26b81384fc4bf44ccce1c0d86b4
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:"
#~ 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:"

View File

@ -344,7 +344,14 @@ class Database:
return [
d[0]
for d in results
if d[0] not in ["information_schema", "performance_schema", "sys", "mysql", "knowledge_management"]
if d[0]
not in [
"information_schema",
"performance_schema",
"sys",
"mysql",
"knowledge_management",
]
]
def convert_sql_write_to_select(self, write_sql):
@ -421,7 +428,13 @@ class Database:
session = self._db_sessions()
cursor = session.execute(text(f"SHOW CREATE TABLE {table_name}"))
ans = cursor.fetchall()
return ans[0][1]
res = ans[0][1]
res = re.sub(r"\s*ENGINE\s*=\s*InnoDB\s*", " ", res, flags=re.IGNORECASE)
res = re.sub(
r"\s*DEFAULT\s*CHARSET\s*=\s*\w+\s*", " ", res, flags=re.IGNORECASE
)
res = re.sub(r"\s*COLLATE\s*=\s*\w+\s*", " ", res, flags=re.IGNORECASE)
return res
def get_fields(self, table_name):
"""Get column fields about specified table."""

View File

@ -2,7 +2,11 @@ from typing import Dict, List, Optional
from langchain.document_loaders import CSVLoader
from langchain.schema import Document
from langchain.text_splitter import TextSplitter, SpacyTextSplitter, RecursiveCharacterTextSplitter
from langchain.text_splitter import (
TextSplitter,
SpacyTextSplitter,
RecursiveCharacterTextSplitter,
)
from pilot.embedding_engine import SourceEmbedding, register
@ -18,7 +22,9 @@ class CSVEmbedding(SourceEmbedding):
text_splitter: Optional[TextSplitter] = None,
):
"""Initialize with csv path."""
super().__init__(file_path, vector_store_config, source_reader=None, text_splitter=None)
super().__init__(
file_path, vector_store_config, source_reader=None, text_splitter=None
)
self.file_path = file_path
self.vector_store_config = vector_store_config
self.source_reader = source_reader or None

View File

@ -28,7 +28,9 @@ class MarkdownEmbedding(SourceEmbedding):
text_splitter: Optional[TextSplitter] = None,
):
"""Initialize raw text word path."""
super().__init__(file_path, vector_store_config, source_reader=None, text_splitter=None)
super().__init__(
file_path, vector_store_config, source_reader=None, text_splitter=None
)
self.file_path = file_path
self.vector_store_config = vector_store_config
self.source_reader = source_reader or None

View File

@ -24,7 +24,9 @@ class PDFEmbedding(SourceEmbedding):
text_splitter: Optional[TextSplitter] = None,
):
"""Initialize pdf word path."""
super().__init__(file_path, vector_store_config, source_reader=None, text_splitter=None)
super().__init__(
file_path, vector_store_config, source_reader=None, text_splitter=None
)
self.file_path = file_path
self.vector_store_config = vector_store_config
self.source_reader = source_reader or None

View File

@ -24,7 +24,9 @@ class PPTEmbedding(SourceEmbedding):
text_splitter: Optional[TextSplitter] = None,
):
"""Initialize ppt word path."""
super().__init__(file_path, vector_store_config, source_reader=None, text_splitter=None)
super().__init__(
file_path, vector_store_config, source_reader=None, text_splitter=None
)
self.file_path = file_path
self.vector_store_config = vector_store_config
self.source_reader = source_reader or None

View File

@ -1,7 +1,11 @@
from typing import List, Optional
from langchain.schema import Document
from langchain.text_splitter import TextSplitter, SpacyTextSplitter, RecursiveCharacterTextSplitter
from langchain.text_splitter import (
TextSplitter,
SpacyTextSplitter,
RecursiveCharacterTextSplitter,
)
from pilot.embedding_engine import SourceEmbedding, register
@ -17,7 +21,12 @@ class StringEmbedding(SourceEmbedding):
text_splitter: Optional[TextSplitter] = None,
):
"""Initialize raw text word path."""
super().__init__(file_path=file_path, vector_store_config=vector_store_config, source_reader=None, text_splitter=None)
super().__init__(
file_path=file_path,
vector_store_config=vector_store_config,
source_reader=None,
text_splitter=None,
)
self.file_path = file_path
self.vector_store_config = vector_store_config
self.source_reader = source_reader or None
@ -32,16 +41,15 @@ class StringEmbedding(SourceEmbedding):
try:
self.text_splitter = SpacyTextSplitter(
pipeline="zh_core_web_sm",
chunk_size=100,
chunk_size=500,
chunk_overlap=100,
)
except Exception:
self.text_splitter = RecursiveCharacterTextSplitter(
chunk_size=100, chunk_overlap=50
)
return self.text_splitter.split_documents(docs)
return self.text_splitter.split_documents(docs)
return docs
@register
def data_process(self, documents: List[Document]):

View File

@ -23,13 +23,14 @@ class URLEmbedding(SourceEmbedding):
text_splitter: Optional[TextSplitter] = None,
):
"""Initialize url word path."""
super().__init__(file_path, vector_store_config, source_reader=None, text_splitter=None)
super().__init__(
file_path, vector_store_config, source_reader=None, text_splitter=None
)
self.file_path = file_path
self.vector_store_config = vector_store_config
self.source_reader = source_reader or None
self.text_splitter = text_splitter or None
@register
def read(self):
"""Load from url path."""

View File

@ -24,7 +24,9 @@ class WordEmbedding(SourceEmbedding):
text_splitter: Optional[TextSplitter] = None,
):
"""Initialize with word path."""
super().__init__(file_path, vector_store_config, source_reader=None, text_splitter=None)
super().__init__(
file_path, vector_store_config, source_reader=None, text_splitter=None
)
self.file_path = file_path
self.vector_store_config = vector_store_config
self.source_reader = source_reader or None

View File

@ -77,7 +77,6 @@ class DBSummaryClient:
def get_db_summary(self, dbname, query, topk):
vector_store_config = {
"vector_store_name": dbname + "_profile",
"chroma_persist_path": KNOWLEDGE_UPLOAD_ROOT_PATH,
"vector_store_type": CFG.VECTOR_STORE_TYPE,
"chroma_persist_path": KNOWLEDGE_UPLOAD_ROOT_PATH,
}