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doc:deploy doc

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17
docs/getting_started/faq/llm/llm_faq.md
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@@ -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.

43
docs/getting_started/install/deploy/deploy.md
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@@ -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