diff --git a/docs/getting_started/faq/llm/llm_faq.md b/docs/getting_started/faq/llm/llm_faq.md
index 9948bcf4b..7b4409d1f 100644
--- a/docs/getting_started/faq/llm/llm_faq.md
+++ b/docs/getting_started/faq/llm/llm_faq.md
@@ -1,7 +1,7 @@
 LLM USE FAQ
 ==================================
 ##### Q1:how to use openai chatgpt service
-change your LLM_MODEL
+change your LLM_MODEL in `.env`
 ````shell
 LLM_MODEL=proxyllm
 ````
@@ -16,7 +16,6 @@ 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.
 
@@ -24,7 +23,19 @@ make sure your openapi API_KEY is available
 
 ```
 
-##### Q3 how to use MultiGPUs
+```{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.
diff --git a/docs/getting_started/install/deploy/deploy.md b/docs/getting_started/install/deploy/deploy.md
index b8b91471a..b7ef6e44b 100644
--- a/docs/getting_started/install/deploy/deploy.md
+++ b/docs/getting_started/install/deploy/deploy.md
@@ -60,12 +60,8 @@ For the entire installation process of DB-GPT, we use the miniconda3 virtual env
 python>=3.10
 conda create -n dbgpt_env python=3.10
 conda activate dbgpt_env
+# it will take some minutes
 pip install -e ".[default]"
-```
-Before use DB-GPT Knowledge
-```bash
-python -m spacy download zh_core_web_sm
-
 ```
 
 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
@@ -78,26 +74,34 @@ 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 [LLM Use FAQ](https://db-gpt.readthedocs.io/en/latest/getting_started/faq/llm/llm_faq.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
-#### llm model
-git clone https://huggingface.co/lmsys/vicuna-13b-v1.5
-or
-git clone https://huggingface.co/THUDM/chatglm2-6b
 
 #### 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
 
-if you want to use openai llm service, see [LLM Use FAQ](https://db-gpt.readthedocs.io/en/latest/getting_started/faq/llm/llm_faq.html)
-
 ```{tip}
 cp .env.template .env
 ```
@@ -108,7 +112,7 @@ You can configure basic parameters in the .env file, for example setting LLM_MOD
 
 ### 3. Run
 
-**(Optional) load examples into SQLlite**
+**(Optional) load examples into SQLite**
 ```bash
 bash ./scripts/examples/load_examples.sh
 ```
@@ -118,7 +122,7 @@ On windows platform:
 .\scripts\examples\load_examples.bat
 ```
 
-1.Run db-gpt server 
+Run db-gpt server 
 
 ```bash
 python pilot/server/dbgpt_server.py
@@ -126,19 +130,6 @@ python pilot/server/dbgpt_server.py
 
 Open http://localhost:5000 with your browser to see the product.
 
-```{tip}
-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
-```
-
-If you want to learn about dbgpt-webui, read https://github./csunny/DB-GPT/tree/new-page-framework/datacenter
-
-```bash
-python pilot/server/dbgpt_server.py --light
-```
 
 ### Multiple GPUs
 
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
index 8b588f5ed..c0791b7cb 100644
--- 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
@@ -8,7 +8,7 @@ msgid ""
 msgstr ""
 "Project-Id-Version: DB-GPT 👏👏 0.3.5\n"
 "Report-Msgid-Bugs-To: \n"
-"POT-Creation-Date: 2023-09-25 20:58+0800\n"
+"POT-Creation-Date: 2023-10-20 22:29+0800\n"
 "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
 "Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
 "Language: zh_CN\n"
@@ -19,33 +19,34 @@ msgstr ""
 "Content-Transfer-Encoding: 8bit\n"
 "Generated-By: Babel 2.12.1\n"
 
-#: ../../getting_started/faq/llm/llm_faq.md:1 0d4fc79dbfce4f968ab310de12d69f3b
+#: ../../getting_started/faq/llm/llm_faq.md:1 54763acec7da4deb90669195c54ec3a1
 msgid "LLM USE FAQ"
 msgstr "LLM模型使用FAQ"
 
-#: ../../getting_started/faq/llm/llm_faq.md:3 08873df3ef2741dca8916c4c0d503b4f
+#: ../../getting_started/faq/llm/llm_faq.md:3 66f73fd2ee7b462e92d3f263792a5e33
 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 7741b098acd347659ccf663b5323666c
-msgid "change your LLM_MODEL"
+#: ../../getting_started/faq/llm/llm_faq.md:4 9d178d8462b74cb188bbacf2ac2ac12b
+#, 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 018115ec074c48739b730310a8bafa44
+#: ../../getting_started/faq/llm/llm_faq.md:9 f7ca82f257be4ac09639a7f8af5e83eb
 msgid "set your OPENAPI KEY"
 msgstr "set your OPENAPI KEY"
 
-#: ../../getting_started/faq/llm/llm_faq.md:16 42408d9c11994a848da41c3ab87d7a78
+#: ../../getting_started/faq/llm/llm_faq.md:16 d6255b20dce34a2690df7e2af3505d97
 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 d9aedc07578d4562bad0ba1f130651de
+#: ../../getting_started/faq/llm/llm_faq.md:18 6f1c6dbdb31f4210a6d21f0f3a6ae589
 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:21 03c03fedaa2f4bfdaefb42fd4164c902
+#: ../../getting_started/faq/llm/llm_faq.md:20 b839771ae9e34e998b0edf8d69deabdd
 msgid ""
 "`python dbgpt_server --light` dbgpt_server does not start the llm "
 "service. Users can deploy the llm service separately by using `python "
@@ -57,54 +58,75 @@ msgstr ""
 "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:23 61354a0859284346adc3e07c820aa61a
+#: ../../getting_started/faq/llm/llm_faq.md:22 aba39cef6fe84799bcd03e8f36c41296
 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 41ee95bf0b224be995f7530d0b67f712
+#: ../../getting_started/faq/llm/llm_faq.md:27 c65270d479af49e28e99b35a7932adbd
+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 da153e6d18c543f28e0c4e85618e3d3d
+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 cd89b8a2075f4407b8036a74151a6377
+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 8f4b9401ac4f4a25a7479bee9ef5e8c1
+msgid "python pilot/server/dbgpt_server.py --light"
+msgstr ""
+
+#: ../../getting_started/faq/llm/llm_faq.md:38 69e1064cd7554ce6b49da732f800eacc
 #, fuzzy
-msgid "Q3 how to use MultiGPUs"
+msgid "Q3 How to use MultiGPUs"
 msgstr "Q2 怎么使用 MultiGPUs"
 
-#: ../../getting_started/faq/llm/llm_faq.md:29 7fce22f0327646399b98b0e20574a2fd
+#: ../../getting_started/faq/llm/llm_faq.md:40 6de3f105ce96430db5756f38bbd9ca12
 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:32 3f4eb824dc924d7ca309dc5057f8360a
+#: ../../getting_started/faq/llm/llm_faq.md:43 87cb9bfb20af4b259d719df797c42a7d
 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:42 a77d72f91b864d0aac344b317c100950
+#: ../../getting_started/faq/llm/llm_faq.md:53 bcfa35cda6304ee5ab9a775a2d4eda63
 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:44 b3bb92777a1244d5967a4308d14722fc
+#: ../../getting_started/faq/llm/llm_faq.md:55 a05c5484927844c8bb4791f0a9ccc82e
 #, fuzzy
 msgid "Q4 Not Enough Memory"
 msgstr "Q3 机器显存不够 "
 
-#: ../../getting_started/faq/llm/llm_faq.md:46 c3976d81aafa4c6081e37c0d0a115d96
+#: ../../getting_started/faq/llm/llm_faq.md:57 fe17a023b6eb4a92b1b927e1b94e3784
 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:48 93ade142f949449d8f54c0b6d8c8d261
+#: ../../getting_started/faq/llm/llm_faq.md:59 76c3684c10864b8e87e5c2255b6c0b7f
 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:50 be2573907d624ebf8c901301f938577b
+#: ../../getting_started/faq/llm/llm_faq.md:61 c5d849a38f1a4f0687bbcffb6699dc39
 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."
@@ -112,45 +134,45 @@ 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:52 c084d4624e794f7e8ceebadb6f260b49
+#: ../../getting_started/faq/llm/llm_faq.md:63 867329a5e3b0403083e96f72b8747fb2
 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 ""
 
-#: ../../getting_started/faq/llm/llm_faq.md:54 559bcd62af7340f79f5eca817187e13e
+#: ../../getting_started/faq/llm/llm_faq.md:65 60ceee25e9fb4ddba40c5306bfb0a82f
 #, 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:56 e47101d7d47e486e8572f6acd609fa92
+#: ../../getting_started/faq/llm/llm_faq.md:67 c99eb7f7ae844884a8f0da94238ea7e0
 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:67 5710dd9bf8f54bd388354079b29acdd2
+#: ../../getting_started/faq/llm/llm_faq.md:78 cd89b8a2075f4407b8036a74151a6377
 #, fuzzy
 msgid "Q6 How to Add LLM Service dynamic in remote mode"
 msgstr "Q5 怎样动态新增模型服务"
 
-#: ../../getting_started/faq/llm/llm_faq.md:68 9c9311d6daad402a8e0748f00e69e8cf
+#: ../../getting_started/faq/llm/llm_faq.md:79 8833ce89465848259b08ef0a4fa68d96
 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:70 3ec1565e74384beab23df9d8d4a19a39
+#: ../../getting_started/faq/llm/llm_faq.md:81 992eb37e3cca48829636c15ba3ec2ee8
 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:80 e2b8a9119f7843beb787d021c973eea4
+#: ../../getting_started/faq/llm/llm_faq.md:91 0d06d7d6dd3d4780894ecd914c89b5a2
 #, fuzzy
 msgid "Q7 dbgpt command not found"
 msgstr "Q6 dbgpt command not found"
 
-#: ../../getting_started/faq/llm/llm_faq.md:86 257ae9c462cd4a9abe7d2ff00f6bc891
+#: ../../getting_started/faq/llm/llm_faq.md:97 5d9beed0d95a4503a43d0e025664273b
 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 "
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
index 4f131124d..0ed8cfcd9 100644
--- 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
@@ -8,7 +8,7 @@ msgid ""
 msgstr ""
 "Project-Id-Version: DB-GPT 👏👏 0.3.5\n"
 "Report-Msgid-Bugs-To: \n"
-"POT-Creation-Date: 2023-10-17 14:35+0800\n"
+"POT-Creation-Date: 2023-10-20 22:29+0800\n"
 "PO-Revision-Date: YEAR-MO-DA HO:MI+ZONE\n"
 "Last-Translator: FULL NAME <EMAIL@ADDRESS>\n"
 "Language: zh_CN\n"
@@ -20,47 +20,47 @@ msgstr ""
 "Generated-By: Babel 2.12.1\n"
 
 #: ../../getting_started/install/deploy/deploy.md:1
-#: 73f932b662564edba45fbd711fd19005
+#: 7bcf028ff0884ea88f25b7e2c9608153
 msgid "Installation From Source"
 msgstr "源码安装"
 
 #: ../../getting_started/install/deploy/deploy.md:3
-#: 70b623827a26447cb9382f1cb568b93c
+#: 61f0b1135c84423bbaeb5f9f0942ad7d
 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
-#: 6102ada4b19a4062947ad0ee5305dad5
+#: d7622cd5f69f4a32b3c8e979c6b9f601
 msgid "Installation"
 msgstr "安装"
 
 #: ../../getting_started/install/deploy/deploy.md:7
-#: 7c006c0c72944049bba43fd95daf1bd1
+#: 4368072b6384496ebeaff3c09ca2f888
 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
-#: eac8c7f921a042b79b4d0032c01b095a
+#: 0dfdf8ac6e314fe7b624a685d9beebd5
 msgid "1. Hardware Requirements"
 msgstr "1. 硬件要求"
 
 #: ../../getting_started/install/deploy/deploy.md:10
-#: 8c430e2db5ce41e8b9d22e6e13c62cb3
+#: cff920f8732f4f1da3063ec2bc099271
 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
-#: a6b042509e1149fa8213a014e42eaaae
+#: 8e3818824d6146c6b265731c277fbd0b
 #, fuzzy
 msgid "Low hardware requirements"
 msgstr "1. 硬件要求"
 
 #: ../../getting_started/install/deploy/deploy.md:13
-#: 577c8c4edc2e4f45963b2a668385852f
+#: ca95d66526994173ac1fea20bdea5d67
 msgid ""
 "The low hardware requirements mode is suitable for integrating with "
 "third-party LLM services' APIs, such as OpenAI, Tongyi, Wenxin, or "
@@ -68,23 +68,23 @@ msgid ""
 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
-#: 384475d3a87043eb9eebc384052ac9cc
+#: 83fc53cc1b4248139f69f490b859ad8d
 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
-#: e5bd8a999adb4e07b8b5221f1893251d
+#: 418a9f24eafc4571b74d86c3f1e57a2d
 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
-#: 6a97ed5893414e17bb9c1f8bb21bc965
+#: 6f85149ab0024cc99e43804206a595ed
 #, fuzzy
 msgid "High hardware requirements"
 msgstr "1. 硬件要求"
 
 #: ../../getting_started/install/deploy/deploy.md:20
-#: d0c248939b4143a2b01afd051b02ec12
+#: 31635ffff5084814a14deb3220dd2c17
 #, fuzzy
 msgid ""
 "The high hardware requirements mode is suitable for independently "
@@ -93,70 +93,72 @@ msgid ""
 "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:"
+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
-#: 2ee432394f6b4d9cb0a424f4b99bf3be
+#: d806b90be1614ad3b2e06c92f4b17e5c
 msgid "GPU"
 msgstr "GPU"
 
 #: ../../getting_started/install/deploy/deploy.md
-#: 4cd716486f994080880f84853b047a5d
+#: 4b02f41145484389ace0b547384ac269 bbba2ff3fab94482a1761264264deef9
 msgid "VRAM Size"
 msgstr "显存"
 
 #: ../../getting_started/install/deploy/deploy.md
-#: d1b33d0348894bfc8a843a3d38c6daaa
+#: 0ea63c2dcc0e43858a61e01d59ad09f9
 msgid "Performance"
 msgstr "Performance"
 
 #: ../../getting_started/install/deploy/deploy.md
-#: d5850bbe7d0a430d993b7e6bd1f24bff
+#: 6521683eb91e450c928a72688550a63d
 msgid "RTX 4090"
 msgstr "RTX 4090"
 
 #: ../../getting_started/install/deploy/deploy.md
-#: c7d15be08ac74624bbfb5eb4554fc7ff
+#: bb6340c9cdc048fbb0ed55defc1aaeb6 d991b39845ee404198e1a1e35cc416f3
 msgid "24 GB"
 msgstr "24 GB"
 
 #: ../../getting_started/install/deploy/deploy.md
-#: 219dff2fee83460da55d9d628569365e
+#: 4134d3a89d364e33b2bdf1c7667e4755
 msgid "Smooth conversation inference"
 msgstr "丝滑的对话体验"
 
 #: ../../getting_started/install/deploy/deploy.md
-#: 56025c5f37984963943de7accea85850
+#: 096ff425ac7646a990a7133961c6e6af
 msgid "RTX 3090"
 msgstr "RTX 3090"
 
 #: ../../getting_started/install/deploy/deploy.md
-#: 8a0b8a0afa0c4cc39eb7c2271775cf60
+#: ecf670cdbec3493f804e6a785a83c608
 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
-#: 2fc5e6ac8a6b4c508944c659adffa0c1
+#: 837b14e0a3d243bda0df7ab35b70b7e7
 msgid "V100"
 msgstr "V100"
 
 #: ../../getting_started/install/deploy/deploy.md
-#: f92a1393539a49db983b06f7276f446b
+#: 3b20a087c8e342c89ccb807ffc3817c2 b8b6b45253084436a5893896b35a2bd5
 msgid "16 GB"
 msgstr "16 GB"
 
 #: ../../getting_started/install/deploy/deploy.md
-#: 4e7de52a58d24a0bb10e45e1435128a6
+#: 772e18bb0ace4f7ea68b51bfc05816ce 9351389a1fac479cbe67b1f8c2c37de5
 msgid "Conversation inference possible, noticeable stutter"
 msgstr "Conversation inference possible, noticeable stutter"
 
 #: ../../getting_started/install/deploy/deploy.md
-#: 217fe55f590a497ba6622698945e7be8
+#: aadb62bf48bb49d99a714bcdf3092260
 msgid "T4"
 msgstr "T4"
 
 #: ../../getting_started/install/deploy/deploy.md:30
-#: 30ca67fe27f64df093a2d281e1288c5c
+#: 4de80d9fcf34470bae806d829836b7d7
 #, fuzzy
 msgid ""
 "If your VRAM Size is not enough, DB-GPT supported 8-bit quantization and "
@@ -164,105 +166,109 @@ msgid ""
 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
-#: fc0c3a0730d64e9e98d1b25f4dd5db34
+#: 00d81cbf48b549f3b9128d3840d01b2e
 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
-#: 1f1f6c10209b446f99d520fdb68e0f5d
+#: dc346f2bca794bb7ae34b330e82ccbcf
 msgid "Model"
 msgstr "Model"
 
 #: ../../getting_started/install/deploy/deploy.md
-#: 18e3240d407e41f88028b24aeced1bf4
+#: 8de6cd40de78460ba774650466f8df26
 msgid "Quantize"
 msgstr "Quantize"
 
 #: ../../getting_started/install/deploy/deploy.md
-#: 03aa79d3c3f54e3c834180b0d1ed9a5c
+#: 3e412b8f4852482ab07a0f546e37ae7f f30054e0558b41a192cc9a2462b299ec
 msgid "vicuna-7b-v1.5"
 msgstr "vicuna-7b-v1.5"
 
 #: ../../getting_started/install/deploy/deploy.md
-#: 09419ad0a88c4179979505ef71204fd6 1b4ab0186184493d895eeec12d078c52
-#: 6acec7b76e604343885aa71d92b04d1e 9b73ca1c18d14972b894db69438e3fb2
-#: b869995505ae4895b9f13e271470e5cb c9eaf983eeb2486da08e628728ae301f
-#: ff0a86dc63ce4cd580f354d15d333501
+#: 14358fa40cf94614acf39a803987631f 2a3f52b26b444783be04ffa795246a03
+#: 3956734b19aa44c3be08d56348b47a38 751034ca7d00447895fda1d9b8a7364f
+#: a66d16e5424a42a3a1309dfb8ffc33f9 b8ebce0a9e7e481da5f16214f955665d
+#: f533b3f37e6f4594aec5e0f59f241683
 msgid "4-bit"
 msgstr "4-bit"
 
 #: ../../getting_started/install/deploy/deploy.md
-#: d0d959f022f44bbeb34d67ccf49ba3bd
+#: 9eac7e866ebe45169c64a952c363ce43 aa56722db3014abd9022067ed5fc4f98
+#: af4df898fb47471fbb487fcf6e2d40d6
 msgid "8 GB"
 msgstr "8 GB"
 
 #: ../../getting_started/install/deploy/deploy.md
-#: 01cb7be0064940e8a637df7ed8e15310 13568d8a793b4c2db655f89dc690929a
-#: 28ce31711f91455b9b910276fa059c65 2dddf2e87a70452fb27a627d62464346
-#: 3f3f4dc00acb43258dce311f144e0fd7 5aa76fd2fb35474e8d06795e7369ceb4
-#: d660be499efc4b6ca61da0d5af758620
+#: 211aaf2e234d46108b5eee5006d5f4bb 40214b2f71ce452db3501ea9d81a0c8a
+#: 72fcd5e0634e48d79813f1037e6acb45 7756b67568cc40c4b73079b26e79c85d
+#: 8c21f8e90154407682c093a46b93939d ad937c14bbcd41ac92a3dbbdb8339eed
+#: d1e7ee217dd64b15b934456c3a72c450
 msgid "8-bit"
 msgstr "8-bit"
 
 #: ../../getting_started/install/deploy/deploy.md
-#: 3b963a1ce6934229ba7658cb407b6a52
+#: 4812504dfb9a4b25a5db773d9a08f34f 76ae2407ba4e4013953b9f243d9a5d92
+#: 927054919de047fd8a83df67e1400622 9773e73eb89847f8a85a2dc55b562916
+#: ce33d0c3792f43398fc7e2694653d8fc d3dc0d4cceb24d2b9dc5c7120fbed94e
 msgid "12 GB"
 msgstr "12 GB"
 
 #: ../../getting_started/install/deploy/deploy.md
-#: 30d28dcaa64545198aaa20fe4562bb6d
+#: 83e6d6ba1aa74946858f0162424752ab b6b99caeaeff44c488e3e819ed337074
 msgid "vicuna-13b-v1.5"
 msgstr "vicuna-13b-v1.5"
 
 #: ../../getting_started/install/deploy/deploy.md
-#: 28de25a1952049d2b7aff41020e428ff
+#: 492c5f0d560946fe879f6c339975ba37 970063dda21e4dd8be6f89a3c87832a5
+#: a66bad6054b24dd99b370312bc8b6fa6
 msgid "20 GB"
 msgstr "20 GB"
 
 #: ../../getting_started/install/deploy/deploy.md
-#: 535974c886b14c618ca84de1fe63d5e4
+#: a75f3405085441d8920db49f159588d2 cf635931c55846aea4cbccd92e4f0377
 msgid "llama-2-7b"
 msgstr "llama-2-7b"
 
 #: ../../getting_started/install/deploy/deploy.md
-#: cc04760a8b9e4a79a7dada9a11abda2c
+#: 61d632df8c5149b393d03ac802141125 bc98c895d457495ea26e3537de83b432
 msgid "llama-2-13b"
 msgstr "llama-2-13b"
 
 #: ../../getting_started/install/deploy/deploy.md
-#: 9e83d8d5ae44411dba4cc6c2d796b20f
+#: 3ccb1f6d8a924aeeacb5373edc168103 9ecce68e159a4649a8d5e69157af17a1
 msgid "llama-2-70b"
 msgstr "llama-2-70b"
 
 #: ../../getting_started/install/deploy/deploy.md
-#: cb6ce389adfc463a9c851eb1e4abfcff
+#: ca1da6ce08674b3daa0ab9ee0330203f
 msgid "48 GB"
 msgstr "48 GB"
 
 #: ../../getting_started/install/deploy/deploy.md
-#: 906d664156084223a4efa0ae9804bd33
+#: 34d4d20e57c1410fbdcabd09a5968cdd
 msgid "80 GB"
 msgstr "80 GB"
 
 #: ../../getting_started/install/deploy/deploy.md
-#: 957fb0c6f3114a63ba33a1cfb31060e3
+#: 4ec2213171054c96ac9cd46e259ce7bf 68a1752f76a54287a73e82724723ea75
 msgid "baichuan-7b"
 msgstr "baichuan-7b"
 
 #: ../../getting_started/install/deploy/deploy.md
-#: 5f3bc4cf57d946cfb38a941250685151
+#: 103b020a575744ad964c60a367aa1651 c659a720a1024869b09d7cc161bcd8a2
 msgid "baichuan-13b"
 msgstr "baichuan-13b"
 
 #: ../../getting_started/install/deploy/deploy.md:51
-#: 87ae8c58df314b69ae119aa831cb7dd5
+#: 2259a008d0e14f9e8d1e1d9234b97298
 msgid "2. Install"
 msgstr "2. Install"
 
 #: ../../getting_started/install/deploy/deploy.md:56
-#: 79cdebf089614761bf4299a9ce601b81
+#: 875c7d8e32574552a48199577c78ccdd
 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 "
@@ -276,70 +282,78 @@ msgstr ""
 "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:65
-#: 03ff2f444721454588095bb348220276
-msgid "Before use DB-GPT Knowledge"
-msgstr "在使用知识库之前"
-
-#: ../../getting_started/install/deploy/deploy.md:71
-#: b6faa4d078a046d6a7c0313e8deef0f3
+#: ../../getting_started/install/deploy/deploy.md:67
+#: c03e3290e1144320a138d015171ac596
 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:74
-#: f43fd2b74d994bf6bb4016e88c43d51a
+#: ../../getting_started/install/deploy/deploy.md:70
+#: 933401ac909741ada4acf6bcd4142ed6
 msgid "Notice make sure you have install git-lfs"
-msgstr ""
+msgstr "注意确认你已经安装了git-lfs"
 
-#: ../../getting_started/install/deploy/deploy.md:76
-#: f558a7ee728a4344af576aa375b43092
+#: ../../getting_started/install/deploy/deploy.md:72
+#: e8e4886a83dd402c85fe3fa989322991
 msgid "centos:yum install git-lfs"
 msgstr ""
 
-#: ../../getting_started/install/deploy/deploy.md:78
-#: bab08604a3ba45b9b827ff5a4b931601
+#: ../../getting_started/install/deploy/deploy.md:74
+#: 5ead7e98bddf4fa4845c3d3955f18054
 msgid "ubuntu:apt-get install git-lfs"
 msgstr ""
 
-#: ../../getting_started/install/deploy/deploy.md:80
-#: b4a107e5f8524acc9aed74318880f9f3
+#: ../../getting_started/install/deploy/deploy.md:76
+#: 08acfaaaa2544182a59df54cdf61cd84
 msgid "macos:brew install git-lfs"
 msgstr ""
 
-#: ../../getting_started/install/deploy/deploy.md:97
-#: ecb5fa1f18154685bb4336d04ac3a386
+#: ../../getting_started/install/deploy/deploy.md:78
+#: 312ad44170c34531865576067c58701a
+msgid "Download LLM Model and Embedding Model"
+msgstr "下载LLM模型和Embedding模型"
+
+#: ../../getting_started/install/deploy/deploy.md:80
+#: de54793643434528a417011d2919b2c4
+#, fuzzy
+msgid ""
+"If you use OpenAI llm service, see [LLM Use FAQ](https://db-"
+"gpt.readthedocs.io/en/latest/getting_started/faq/llm/llm_faq.html)"
+msgstr ""
+"如果想使用openai大模型服务, 可以参考[LLM Use FAQ](https://db-"
+"gpt.readthedocs.io/en/latest/getting_started/faq/llm/llm_faq.html)"
+
+#: ../../getting_started/install/deploy/deploy.md:83
+#: 50ec1eb7c56a46ac8fbf911c7adc9b0e
+msgid ""
+"If you use openai or Azure 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
+#: 03950b2a480149388fb7b88f7d251ef5
 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:99
-#: 0f08b0ecbea14cbdba29ea8d87cf24b4
-msgid ""
-"if you want to use openai llm service, see [LLM Use FAQ](https://db-"
-"gpt.readthedocs.io/en/latest/getting_started/faq/llm/llm_faq.html)"
-msgstr ""
-"如果想使用openai大模型服务, 可以参考[LLM Use FAQ](https://db-"
-"gpt.readthedocs.io/en/latest/getting_started/faq/llm/llm_faq.html)"
-
-#: ../../getting_started/install/deploy/deploy.md:102
-#: 6efb9a45ab2c45c7b4770f987b639c52
+#: ../../getting_started/install/deploy/deploy.md:106
+#: 441c4333216a402a84fd52f8e56fc81b
 msgid "cp .env.template .env"
 msgstr "cp .env.template .env"
 
-#: ../../getting_started/install/deploy/deploy.md:105
-#: b9d2b81a2cf440c3b49a5c06759eb2ba
+#: ../../getting_started/install/deploy/deploy.md:109
+#: 4eac3d98df6a4e788234ff0ec1ffd03e
 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:107
-#: 2f6afa40ca994115b16ba28baaf65bde
+#: ../../getting_started/install/deploy/deploy.md:111
+#: a36bd6d6236b4c74b161a935ae792b91
 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-"
@@ -349,107 +363,81 @@ msgstr ""
 "/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:109
-#: 7c5883f9594646198f464e6dafb2f0ff
+#: ../../getting_started/install/deploy/deploy.md:113
+#: 78334cbf0c364eb3bc41a2a6c55ebb0d
 msgid "3. Run"
 msgstr "3. Run"
 
-#: ../../getting_started/install/deploy/deploy.md:111
-#: 0e3719a238eb4332b7c15efa3f16e3e2
-msgid "**(Optional) load examples into SQLlite**"
+#: ../../getting_started/install/deploy/deploy.md:115
+#: 6d5ad6eb067d4e9fa1c574b7b706233f
+msgid "**(Optional) load examples into SQLite**"
 msgstr ""
 
-#: ../../getting_started/install/deploy/deploy.md:116
-#: c901055131ce4688b1c602393913b675
+#: ../../getting_started/install/deploy/deploy.md:120
+#: 07219a4ed3c44e349314ae04ebdf58e1
 msgid "On windows platform:"
 msgstr ""
 
-#: ../../getting_started/install/deploy/deploy.md:121
-#: 777a50f9167c4b8f9c2a96682ccc4c4a
-msgid "1.Run db-gpt server"
+#: ../../getting_started/install/deploy/deploy.md:125
+#: 819be2bb22044440ae00c2e7687ea249
+#, fuzzy
+msgid "Run db-gpt server"
 msgstr "1.Run db-gpt server"
 
-#: ../../getting_started/install/deploy/deploy.md:127
-#: 62aafb652df8478281ab633d8d082e7f
+#: ../../getting_started/install/deploy/deploy.md:131
+#: 5ba6d7c9bf9146c797036ab4b9b4f59e
 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:130
-#: cff18fc20ffd4716bc7cf377730dd5ec
-msgid "If you want to access an external LLM service, you need to"
-msgstr ""
-
-#: ../../getting_started/install/deploy/deploy.md:132
-#: f27c3aa9e627480a96cd04fcd4bfdaec
-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/install/deploy/deploy.md:134
-#: e05a395f67924514929cd025fab67e44
-msgid "2.execute dbgpt_server.py in light mode"
-msgstr ""
-
-#: ../../getting_started/install/deploy/deploy.md:137
-#: a5d7fcb46ba446bf9913646b28b036ed
-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"
-
-#: ../../getting_started/install/deploy/deploy.md:143
-#: 90c614e7744c4a7f843adb8968b58c78
+#: be3a2729ef3b4742a403017b31bda7e3
 #, fuzzy
 msgid "Multiple GPUs"
 msgstr "4. Multiple GPUs"
 
-#: ../../getting_started/install/deploy/deploy.md:145
-#: 7b72e7cbd9d246299de5986772df4825
+#: ../../getting_started/install/deploy/deploy.md:136
+#: 00ffa1cc145e4afa830c592a629246f9
 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:147
-#: b7e2f7bbf625464489b3fd9aedb0ed59
+#: ../../getting_started/install/deploy/deploy.md:138
+#: bde32a5a8fea4350868be579e9ee6baa
 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:157
-#: 69fd2183a143428fb77949f58381d455
+#: ../../getting_started/install/deploy/deploy.md:148
+#: 791ed2db2cff44c48342a7828cbd4c45
 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:159
-#: 6cd03b9728f943a4a632aa9b061931f0
+#: ../../getting_started/install/deploy/deploy.md:150
+#: f86b37c8943e4f5595610706e75b4add
 #, fuzzy
 msgid "Not Enough Memory"
 msgstr "5. Not Enough Memory"
 
-#: ../../getting_started/install/deploy/deploy.md:161
-#: 4837aba4c80b42819c1a6345de0aa820
+#: ../../getting_started/install/deploy/deploy.md:152
+#: 8a7bd02cbeca497aa8eecaaf1910a6ad
 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:163
-#: c1a701e9bc4c4439adfb930d0e953cec
+#: ../../getting_started/install/deploy/deploy.md:154
+#: 5ad49b99fe774ba79c50de0cd694807c
 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:165
-#: 205c101f1f774130a5853dd9b7373d36
+#: ../../getting_started/install/deploy/deploy.md:156
+#: b9c80e92137447da91eb944443144c69
 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."
@@ -508,3 +496,29 @@ msgstr ""
 #~ 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"
+