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doc:llm deploy docs (#692)
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docs/getting_started/install/cluster/vms/standalone.md
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Standalone Deployment
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==================================
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(standalone-index)=
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### Install Prepare
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```commandline
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git clone https://github.com/eosphoros-ai/DB-GPT.git
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cd DB-GPT
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```
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### Create conda environment
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```commandline
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conda create -n dbgpt_env python=3.10
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conda activate dbgpt_env
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```
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### Install Default Requirements
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```commandline
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# Install Default Requirements
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pip install -e ".[default]"
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```
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### Download and Prepare LLM Model and Embedding Model
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```{tip}
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If you don't have high performance hardware server
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```
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you can use openai api, tongyi api , bard api, etc.
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```commandline
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mkdir models && cd models
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# download embedding model, eg: text2vec-large-chinese
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git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese
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```
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set proxy api in .env
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```commandline
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#set LLM_MODEL TYPE
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LLM_MODEL=proxyllm
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#set your Proxy Api key and Proxy Server url
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PROXY_API_KEY={your-openai-sk}
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PROXY_SERVER_URL=https://api.openai.com/v1/chat/completions
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```
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```{tip}
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If you have high performance hardware server
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```
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```commandline
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mkdir models && cd models
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# # download embedding model, eg: vicuna-13b-v1.5 or
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git clone https://huggingface.co/lmsys/vicuna-13b-v1.5
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# download embedding model, eg: text2vec-large-chinese
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git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese
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popd
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```
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### Start all services with a single command.
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```commandline
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LLM_MODEL=vicuna-13b-v1.5
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dbgpt start webserver --port 6006
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```
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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.
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### View and validate the model service in the command line, you can use the following commands
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##### 1.list the started model services and deployed Model Workers, you can use the following command
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```commandline
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dbgpt model list
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```
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output is:
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```commandline
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+-----------------+------------+------------+------+---------+---------+-----------------+----------------------------+
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| Model Name | Model Type | Host | Port | Healthy | Enabled | Prompt Template | Last Heartbeat |
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+-----------------+------------+------------+------+---------+---------+-----------------+----------------------------+
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| vicuna-13b-v1.5 | llm | 172.17.0.9 | 6006 | True | True | | 2023-10-16T19:49:59.201313 |
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| WorkerManager | service | 172.17.0.9 | 6006 | True | True | | 2023-10-16T19:49:59.246756 |
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+-----------------+------------+------------+------+---------+---------+-----------------+----------------------------+
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```
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The WorkerManager is the management process for Model Workers
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##### validate the deployed model in the command line, you can use the following command
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```commandline
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dbgpt model chat --model_name vicuna-13b-v1.5
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```
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Then an interactive page will be launched where you can have a conversation with the deployed LLM in the terminal.
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```commandline
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Chatbot started with model vicuna-13b-v1.5. Type 'exit' to leave the chat.
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You: Hello
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Bot: Hello! How can I assist you today?
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You:
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```
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# SOME DESCRIPTIVE TITLE.
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# Copyright (C) 2023, csunny
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# This file is distributed under the same license as the DB-GPT package.
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# FIRST AUTHOR <EMAIL@ADDRESS>, 2023.
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#
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#, fuzzy
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msgid ""
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msgstr ""
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"Project-Id-Version: DB-GPT 👏👏 0.3.9\n"
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"Report-Msgid-Bugs-To: \n"
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"POT-Creation-Date: 2023-10-17 17:24+0800\n"
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"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
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"Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
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"Language: zh_CN\n"
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"Language-Team: zh_CN <LL@li.org>\n"
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"Plural-Forms: nplurals=1; plural=0;\n"
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"MIME-Version: 1.0\n"
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"Content-Type: text/plain; charset=utf-8\n"
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"Content-Transfer-Encoding: 8bit\n"
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"Generated-By: Babel 2.12.1\n"
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#: ../../getting_started/application/chatagent/chatagent.md:1
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#: ../../getting_started/application/chatagent/chatagent.md:3
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#: 17aae18073594c7498c8b2434d50b218 77f0177e55e144a89e3bcf735b0d52de
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msgid "ChatAgent"
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msgstr ""
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#: ../../getting_started/application/chatagent/chatagent.md:3
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#: 41b42808938245dc946960571c09026a
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msgid ""
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"ChatAgent can automatically select the right tool to answer and solve "
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"user problems through LLM. "
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msgstr ""
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#: ../../getting_started/application/chatagent/chatagent.md:6
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#: bb76bb44442647a091d008c9e1427e4a
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msgid "1.Update Plugins From Git"
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msgstr ""
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#: ../../getting_started/application/chatagent/chatagent.md:7
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#: a7f188c3de7e4b85b2d3079128b535b2
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msgid ""
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"Update the latest plug-in information from the DB-GPT official plug-in "
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"repository. "
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msgstr ""
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#: ../../getting_started/application/chatagent/chatagent.md:7
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#: 612cb75edb2f48a087fc99e6d0890b80
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msgid "Update From Github"
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msgstr ""
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#: ../../getting_started/application/chatagent/chatagent.md:10
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#: 1ad3f7680837410cb8018fff5787366f
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msgid "2.Install Plugin"
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msgstr ""
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#: ../../getting_started/application/chatagent/chatagent.md:11
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#: b32e9318a8e347339b6c4cad4b966880
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msgid ""
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"Install the plugin you want to use from the list of agent hub plugins. "
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""
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msgstr ""
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#: ../../getting_started/application/chatagent/chatagent.md:11
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#: bee96f7936564bc6be98655bfc6aae0d
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msgid "Install Plugin"
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msgstr ""
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#: ../../getting_started/application/chatagent/chatagent.md:15
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#: 20d562b9ed004336bb6df8d163554924
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msgid "3.Upload My Local Plugin File"
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msgstr ""
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#: ../../getting_started/application/chatagent/chatagent.md:16
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#: b43e485ff4f042dd80b5950444c0db08
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msgid ""
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"If you want to use a private plug-in developed by yourself, you can "
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"upload the plug-in first and then use it. "
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msgstr ""
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#: ../../getting_started/application/chatagent/chatagent.md:16
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#: a05724784c0e45528039b8238fd9ed3c
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msgid "Upload Private Plugin"
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msgstr ""
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#: ../../getting_started/application/chatagent/chatagent.md:19
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#: 726b5c4cad7d4be9815e9fbeedaecc2b
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msgid "4.Select installed plug-ins dialog"
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msgstr ""
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#: ../../getting_started/application/chatagent/chatagent.md:20
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#: e3d9dc892d054cbca29267cd0fffe7be
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msgid ""
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"Select an installed plugin to have a conversation. "
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msgstr ""
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#: ../../getting_started/application/chatagent/chatagent.md:20
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#: 97f28bacc02444c580f6481b21e6c155
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msgid "Select Plugins"
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msgstr ""
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#: ../../getting_started/application/chatagent/chatagent.md:23
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#: d0272e7d94d743289fb2c1613ee85c36
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msgid "5.Uninstall My Plugin"
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msgstr ""
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#: ../../getting_started/application/chatagent/chatagent.md:24
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#: 2fee213a12da4674b19fe8891e4318f5
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msgid ""
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"Uninstall plugins you no longer need. "
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msgstr ""
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#: ../../getting_started/application/chatagent/chatagent.md:24
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#: 32e5405249134863bcaf85b0ef91260f
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msgid "Uninstall Plugin"
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msgstr ""
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# SOME DESCRIPTIVE TITLE.
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# Copyright (C) 2023, csunny
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# This file is distributed under the same license as the DB-GPT package.
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# FIRST AUTHOR <EMAIL@ADDRESS>, 2023.
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#
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#, fuzzy
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msgid ""
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msgstr ""
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"Project-Id-Version: DB-GPT 👏👏 0.3.9\n"
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"Report-Msgid-Bugs-To: \n"
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"POT-Creation-Date: 2023-10-17 17:24+0800\n"
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"PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
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"Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
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"Language: zh_CN\n"
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"Language-Team: zh_CN <LL@li.org>\n"
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"Plural-Forms: nplurals=1; plural=0;\n"
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"MIME-Version: 1.0\n"
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"Content-Type: text/plain; charset=utf-8\n"
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"Content-Transfer-Encoding: 8bit\n"
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"Generated-By: Babel 2.12.1\n"
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#: ../../getting_started/install/cluster/vms/standalone.md:1
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#: 40af95d327574e5ea9a6c29f68a7709c
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msgid "Standalone Deployment"
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msgstr ""
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#: ../../getting_started/install/cluster/vms/standalone.md:5
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#: 7ef23971a0d2415a857d5eb9c4d955ac
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msgid "Install Prepare"
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msgstr ""
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#: ../../getting_started/install/cluster/vms/standalone.md:12
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#: f3cd2941fa2d49d686fc246237f82e68
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msgid "Create conda environment"
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msgstr ""
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#: ../../getting_started/install/cluster/vms/standalone.md:20
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#: 589d80d5d97044ee93747091904583c5
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msgid "Install Default Requirements"
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msgstr ""
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#: ../../getting_started/install/cluster/vms/standalone.md:26
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#: 1d151e72660644e7b43084ffccb99598
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msgid "Download and Prepare LLM Model and Embedding Model"
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msgstr ""
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#: ../../getting_started/install/cluster/vms/standalone.md:28
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#: 4443c83f8dfa4fdba30929f1e5ecf619
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msgid "If you don't have high performance hardware server"
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msgstr ""
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#: ../../getting_started/install/cluster/vms/standalone.md:30
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#: 33a6ee878a4a467d8bcfe5dfbdcbe184
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msgid "you can use openai api, tongyi api , bard api, etc."
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msgstr ""
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#: ../../getting_started/install/cluster/vms/standalone.md:39
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#: 7efdb99bc36d42819b1fcd1341b45eef
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msgid "set proxy api in .env"
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msgstr ""
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#: ../../getting_started/install/cluster/vms/standalone.md:48
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#: 50154ece70bc421ebe7ac05966369bc8
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msgid "If you have high performance hardware server"
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msgstr ""
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#: ../../getting_started/install/cluster/vms/standalone.md:62
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#: 4f3696ed069a4a84b2d794593df23765
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msgid "Start all services with a single command."
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msgstr ""
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#: ../../getting_started/install/cluster/vms/standalone.md:67
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#: f5f671962cb14a10aba34c4274d2fc2c
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msgid ""
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"By default, the \"dbgpt start webserver\" command will start the "
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"Webserver, Model Controller, and Model Worker in a single Python process."
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" Here, we specify the service to be started on port 6006."
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msgstr ""
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#: ../../getting_started/install/cluster/vms/standalone.md:69
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#: 4883221a356843f6a6335c25847aecd2
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msgid ""
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"View and validate the model service in the command line, you can use the "
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"following commands"
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msgstr ""
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#: ../../getting_started/install/cluster/vms/standalone.md:70
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#: 1346eb55d7c647be90a90a867ba04ec3
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msgid ""
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"1.list the started model services and deployed Model Workers, you can use"
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" the following command"
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msgstr ""
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#: ../../getting_started/install/cluster/vms/standalone.md:74
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#: 8ab332ebce554758952dbe85c68330a9
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msgid "output is:"
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msgstr ""
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#: ../../getting_started/install/cluster/vms/standalone.md:83
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#: efb460bbb70842218f5c056cf05ba1a0
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msgid "The WorkerManager is the management process for Model Workers"
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msgstr ""
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#: ../../getting_started/install/cluster/vms/standalone.md:85
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#: 10e5b79f3d914ee3974b1a0d07962fe2
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msgid ""
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"validate the deployed model in the command line, you can use the "
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"following command"
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msgstr ""
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#: ../../getting_started/install/cluster/vms/standalone.md:89
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#: 39d062e7fea948949c1c5c099893f308
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msgid ""
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"Then an interactive page will be launched where you can have a "
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"conversation with the deployed LLM in the terminal."
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msgstr ""
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