mirror of
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chore(model): Update the default model to glm-4-9b-chat (#1629)
This commit is contained in:
parent
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162e2c9b1c
@ -17,7 +17,7 @@
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#** LLM MODELS **#
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#*******************************************************************#
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# LLM_MODEL, see dbgpt/configs/model_config.LLM_MODEL_CONFIG
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LLM_MODEL=vicuna-13b-v1.5
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LLM_MODEL=glm-4-9b-chat
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## LLM model path, by default, DB-GPT will read the model path from LLM_MODEL_CONFIG based on the LLM_MODEL.
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## Of course you can specify your model path according to LLM_MODEL_PATH
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## In DB-GPT, the priority from high to low to read model path:
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@ -25,7 +25,7 @@ LLM_MODEL=vicuna-13b-v1.5
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## 2. environment variable with key: MODEL_PATH
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## 3. environment variable with key: LLM_MODEL_PATH
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## 4. the config in dbgpt/configs/model_config.LLM_MODEL_CONFIG
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# LLM_MODEL_PATH=/app/models/vicuna-13b-v1.5
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# LLM_MODEL_PATH=/app/models/glm-4-9b-chat
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# LLM_PROMPT_TEMPLATE=vicuna_v1.1
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MODEL_SERVER=http://127.0.0.1:8000
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LIMIT_MODEL_CONCURRENCY=5
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@ -194,7 +194,7 @@ class Config(metaclass=Singleton):
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self.CHAT_HISTORY_STORE_TYPE = os.getenv("CHAT_HISTORY_STORE_TYPE", "db")
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### LLM Model Service Configuration
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self.LLM_MODEL = os.getenv("LLM_MODEL", "vicuna-13b-v1.5")
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self.LLM_MODEL = os.getenv("LLM_MODEL", "glm-4-9b-chat")
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self.LLM_MODEL_PATH = os.getenv("LLM_MODEL_PATH")
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### Proxy llm backend, this configuration is only valid when "LLM_MODEL=proxyllm"
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@ -26,6 +26,8 @@ def baidu_search(
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"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:112.0) "
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"Gecko/20100101 Firefox/112.0"
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}
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if num_results < 8:
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num_results = 8
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url = f"https://www.baidu.com/s?wd={query}&rn={num_results}"
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response = requests.get(url, headers=headers)
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response.encoding = "utf-8"
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@ -24,7 +24,7 @@ services:
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- LOCAL_DB_HOST=db
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- LOCAL_DB_PASSWORD=aa123456
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- ALLOWLISTED_PLUGINS=db_dashboard
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- LLM_MODEL=vicuna-13b-v1.5
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- LLM_MODEL=glm-4-9b-chat
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depends_on:
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- db
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volumes:
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@ -4,7 +4,7 @@ docker run --ipc host --gpus all -d \
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-p 5000:5000 \
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-e LOCAL_DB_TYPE=sqlite \
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-e LOCAL_DB_PATH=data/default_sqlite.db \
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-e LLM_MODEL=vicuna-13b-v1.5 \
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-e LLM_MODEL=glm-4-9b-chat \
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-e LANGUAGE=zh \
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-v /data:/data \
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-v /data/models:/app/models \
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@ -19,7 +19,7 @@ services:
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- 8100:8100/tcp
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llm-worker:
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image: eosphorosai/dbgpt:latest
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command: dbgpt start worker --model_name vicuna-13b-v1.5 --model_path /app/models/vicuna-13b-v1.5 --port 8001 --controller_addr http://controller:8000
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command: dbgpt start worker --model_name glm-4-9b-chat --model_path /app/models/glm-4-9b-chat --port 8001 --controller_addr http://controller:8000
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environment:
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- DBGPT_LOG_LEVEL=DEBUG
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depends_on:
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@ -66,7 +66,7 @@ services:
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- LOCAL_DB_PATH=data/default_sqlite.db
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- LOCAL_DB_TYPE=sqlite
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- ALLOWLISTED_PLUGINS=db_dashboard
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- LLM_MODEL=vicuna-13b-v1.5
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- LLM_MODEL=glm-4-9b-chat
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- MODEL_SERVER=http://controller:8000
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depends_on:
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- controller
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@ -38,7 +38,7 @@ Chat
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curl http://127.0.0.1:8100/api/v1/chat/completions \
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-H "Authorization: Bearer EMPTY" \
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-H "Content-Type: application/json" \
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-d '{"model": "vicuna-13b-v1.5", "messages": [{"role": "user", "content": "hello"}]}'
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-d '{"model": "glm-4-9b-chat", "messages": [{"role": "user", "content": "hello"}]}'
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```
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:::tip
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@ -61,7 +61,7 @@ curl http://127.0.0.1:8100/api/v1/embeddings \
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import openai
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openai.api_key = "EMPTY"
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openai.api_base = "http://127.0.0.1:8100/api/v1"
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model = "vicuna-13b-v1.5"
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model = "glm-4-9b-chat"
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completion = openai.ChatCompletion.create(
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model=model,
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@ -4,15 +4,17 @@ DB-GPT supports [vLLM](https://github.com/vllm-project/vllm) inference, a fast a
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## Install dependencies
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`vLLM` is an optional dependency in DB-GPT. You can install it manually through the following command.
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```python
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$ pip install -e ".[vllm]"
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```bash
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pip install -e ".[vllm]"
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```
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## Modify configuration file
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In the `.env` configuration file, modify the inference type of the model to start `vllm` inference.
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```python
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LLM_MODEL=vicuna-13b-v1.5
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```bash
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LLM_MODEL=glm-4-9b-chat
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MODEL_TYPE=vllm
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# modify the following configuration if you possess GPU resources
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# gpu_memory_utilization=0.8
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```
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For more information about the list of models supported by `vLLM`, please refer to the [vLLM supported model document](https://docs.vllm.ai/en/latest/models/supported_models.html#supported-models).
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@ -5,15 +5,15 @@
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There are two ways to prepare a Docker image. 1. Pull from the official image 2. Build locally. You can **choose any one** during actual use.
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1.Pulled from the official image repository, [Eosphoros AI Docker Hub](https://hub.docker.com/u/eosphorosai)
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```python
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```bash
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docker pull eosphorosai/dbgpt:latest
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```
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2.local build(optional)
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```python
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```bash
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bash docker/build_all_images.sh
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```
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Check the Docker image
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```python
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```bash
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# command
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docker images | grep "eosphorosai/dbgpt"
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@ -24,12 +24,12 @@ eosphorosai/dbgpt latest eb3cdc5b4ead About a minute ago 1
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```
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`eosphorosai/dbgpt` is the base image, which contains project dependencies and the sqlite database. The `eosphorosai/dbgpt-allinone` image is built from `eosphorosai/dbgpt`, which contains a MySQL database. Of course, in addition to pulling the Docker image, the project also provides Dockerfile files, which can be built directly through scripts in DB-GPT. Here are the build commands:
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```python
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```bash
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bash docker/build_all_images.sh
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```
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When using it, you need to specify specific parameters. The following is an example of specifying parameter construction:
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```python
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```bash
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bash docker/build_all_images.sh \
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--base-image nvidia/cuda:11.8.0-runtime-ubuntu22.04 \
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--pip-index-url https://pypi.tuna.tsinghua.edu.cn/simple \
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@ -42,12 +42,12 @@ You can view the specific usage through the command `bash docker/build_all_image
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### Run through Sqlite database
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```python
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```bash
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docker run --ipc host --gpus all -d \
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-p 5670:5670 \
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-e LOCAL_DB_TYPE=sqlite \
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-e LOCAL_DB_PATH=data/default_sqlite.db \
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-e LLM_MODEL=vicuna-13b-v1.5 \
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-e LLM_MODEL=glm-4-9b-chat \
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-e LANGUAGE=zh \
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-v /data/models:/app/models \
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--name dbgpt \
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@ -55,23 +55,23 @@ eosphorosai/dbgpt
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```
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Open the browser and visit [http://localhost:5670](http://localhost:5670)
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- `-e LLM_MODEL=vicuna-13b-v1.5`, which means the base model uses `vicuna-13b-v1.5`. For more model usage, you can view the configuration in `/pilot/configs/model_config.LLM_MODEL_CONFIG`.
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- `-e LLM_MODEL=glm-4-9b-chat`, which means the base model uses `glm-4-9b-chat`. For more model usage, you can view the configuration in `/pilot/configs/model_config.LLM_MODEL_CONFIG`.
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- `-v /data/models:/app/models`, specifies the model file to be mounted. The directory `/data/models` is mounted in `/app/models` of the container. Of course, it can be replaced with other paths.
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After the container is started, you can view the logs through the following command
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```python
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```bash
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docker logs dbgpt -f
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```
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### Run through MySQL database
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```python
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```bash
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docker run --ipc host --gpus all -d -p 3306:3306 \
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-p 5670:5670 \
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-e LOCAL_DB_HOST=127.0.0.1 \
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-e LOCAL_DB_PASSWORD=aa123456 \
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-e MYSQL_ROOT_PASSWORD=aa123456 \
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-e LLM_MODEL=vicuna-13b-v1.5 \
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-e LLM_MODEL=glm-4-9b-chat \
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-e LANGUAGE=zh \
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-v /data/models:/app/models \
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--name db-gpt-allinone \
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@ -79,16 +79,16 @@ db-gpt-allinone
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```
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Open the browser and visit [http://localhost:5670](http://localhost:5670)
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- `-e LLM_MODEL=vicuna-13b-v1.5`, which means the base model uses `vicuna-13b-v1.5`. For more model usage, you can view the configuration in `/pilot/configs/model_config.LLM_MODEL_CONFIG`.
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- `-e LLM_MODEL=glm-4-9b-chat`, which means the base model uses `glm-4-9b-chat`. For more model usage, you can view the configuration in `/pilot/configs/model_config.LLM_MODEL_CONFIG`.
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- `-v /data/models:/app/models`, specifies the model file to be mounted. The directory `/data/models` is mounted in `/app/models` of the container. Of course, it can be replaced with other paths.
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After the container is started, you can view the logs through the following command
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```python
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```bash
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docker logs db-gpt-allinone -f
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```
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### Run through the OpenAI proxy model
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```python
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```bash
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PROXY_API_KEY="You api key"
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PROXY_SERVER_URL="https://api.openai.com/v1/chat/completions"
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docker run --gpus all -d -p 3306:3306 \
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@ -25,12 +25,12 @@ By default, `Model Server` will start on port `8000`
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## Start Model Worker
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:::tip
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Start `chatglm2-6b` model Worker
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Start `glm-4-9b-chat` model Worker
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:::
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```shell
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dbgpt start worker --model_name chatglm2-6b \
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--model_path /app/models/chatglm2-6b \
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dbgpt start worker --model_name glm-4-9b-chat \
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--model_path /app/models/glm-4-9b-chat \
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--port 8001 \
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--controller_addr http://127.0.0.1:8000
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```
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@ -92,7 +92,7 @@ $ dbgpt model list
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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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| chatglm2-6b | llm | 172.17.0.2 | 8001 | True | True | | 2023-09-12T23:04:31.287654 |
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| glm-4-9b-chat | llm | 172.17.0.2 | 8001 | True | True | | 2023-09-12T23:04:31.287654 |
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| WorkerManager | service | 172.17.0.2 | 8001 | True | True | | 2023-09-12T23:04:31.286668 |
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| WorkerManager | service | 172.17.0.2 | 8003 | True | True | | 2023-09-12T23:04:29.845617 |
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| WorkerManager | service | 172.17.0.2 | 8002 | True | True | | 2023-09-12T23:04:24.598439 |
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@ -124,7 +124,7 @@ MODEL_SERVER=http://127.0.0.1:8000
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Or it can be started directly by command to formulate the model.
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```shell
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LLM_MODEL=chatglm2-6b dbgpt start webserver --light
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LLM_MODEL=glm-4-9b-chat dbgpt start webserver --light
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```
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## Command line usage
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@ -1,26 +1,26 @@
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# Stand-alone Deployment
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## Preparation
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```python
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```bash
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# download source code
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$ git clone https://github.com/eosphoros-ai/DB-GPT.git
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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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cd DB-GPT
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```
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## Environment installation
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```python
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```bash
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# create a virtual environment
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$ conda create -n dbgpt_env python=3.10
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conda create -n dbgpt_env python=3.10
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# activate virtual environment
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$ conda activate dbgpt_env
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conda activate dbgpt_env
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```
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## Install dependencies
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```python
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```bash
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pip install -e ".[default]"
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```
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@ -34,11 +34,11 @@ Download LLM and Embedding model
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:::
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```python
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$ mkdir models && cd models
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```bash
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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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git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese
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```
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:::tip
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@ -46,7 +46,7 @@ $ git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese
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Set up proxy API and modify `.env`configuration
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:::
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```python
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```bash
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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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@ -58,23 +58,23 @@ PROXY_SERVER_URL=https://api.openai.com/v1/chat/completions
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⚠️ If you have GPU resources, you can use local models to deploy
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:::
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```python
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$ mkdir models && cd models
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```bash
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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: glm-4-9b-chat or
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git clone https://huggingface.co/THUDM/glm-4-9b-chat
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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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git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese
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$ popd
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popd
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```
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## Command line startup
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```python
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LLM_MODEL=vicuna-13b-v1.5
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```bash
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LLM_MODEL=glm-4-9b-chat
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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` through a single Python process. In the above command, port `6006` is specified.
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@ -86,16 +86,16 @@ By default, the `dbgpt start webserver command` will start the `webserver`, `mod
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:::tip
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view and display all model services
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:::
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```python
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```bash
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dbgpt model list
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```
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```python
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```bash
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# result
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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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| glm-4-9b-chat | 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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@ -105,14 +105,14 @@ Where `WorkerManager` is the management process of `Model Workers`
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:::tip
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check and verify model serving
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:::
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```python
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dbgpt model chat --model_name vicuna-13b-v1.5
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```bash
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dbgpt model chat --model_name glm-4-9b-chat
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```
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The above command will launch an interactive page that allows you to talk to the model through the terminal.
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```python
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Chatbot started with model vicuna-13b-v1.5. Type 'exit' to leave the chat.
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```bash
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Chatbot started with model glm-4-9b-chat. Type 'exit' to leave the chat.
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You: Hello
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|
@ -20,7 +20,7 @@ Download DB-GPT
|
||||
|
||||
|
||||
|
||||
```python
|
||||
```bash
|
||||
git clone https://github.com/eosphoros-ai/DB-GPT.git
|
||||
```
|
||||
|
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@ -32,7 +32,7 @@ git clone https://github.com/eosphoros-ai/DB-GPT.git
|
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Create a Python virtual environment
|
||||
:::
|
||||
|
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```python
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```bash
|
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python >= 3.10
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conda create -n dbgpt_env python=3.10
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conda activate dbgpt_env
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@ -44,7 +44,7 @@ pip install -e ".[default]"
|
||||
:::tip
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Copy environment variables
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||||
:::
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```python
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```bash
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cp .env.template .env
|
||||
```
|
||||
|
||||
@ -56,7 +56,7 @@ DB-GPT can be deployed on servers with lower hardware through proxy model, or as
|
||||
:::info note
|
||||
|
||||
⚠️ You need to ensure that git-lfs is installed
|
||||
```python
|
||||
```bash
|
||||
● CentOS installation: yum install git-lfs
|
||||
● Ubuntu installation: apt-get install git-lfs
|
||||
● MacOS installation: brew install git-lfs
|
||||
@ -79,13 +79,13 @@ import TabItem from '@theme/TabItem';
|
||||
<TabItem value="openai" label="open ai">
|
||||
Install dependencies
|
||||
|
||||
```python
|
||||
```bash
|
||||
pip install -e ".[openai]"
|
||||
```
|
||||
|
||||
Download embedding model
|
||||
|
||||
```python
|
||||
```bash
|
||||
cd DB-GPT
|
||||
mkdir models and cd models
|
||||
git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese
|
||||
@ -93,7 +93,7 @@ git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese
|
||||
|
||||
Configure the proxy and modify LLM_MODEL, PROXY_API_URL and API_KEY in the `.env`file
|
||||
|
||||
```python
|
||||
```bash
|
||||
# .env
|
||||
LLM_MODEL=chatgpt_proxyllm
|
||||
PROXY_API_KEY={your-openai-sk}
|
||||
@ -105,13 +105,13 @@ PROXY_SERVER_URL=https://api.openai.com/v1/chat/completions
|
||||
<TabItem value="qwen" label="通义千问">
|
||||
Install dependencies
|
||||
|
||||
```python
|
||||
```bash
|
||||
pip install dashscope
|
||||
```
|
||||
|
||||
Download embedding model
|
||||
|
||||
```python
|
||||
```bash
|
||||
cd DB-GPT
|
||||
mkdir models and cd models
|
||||
|
||||
@ -123,7 +123,7 @@ git clone https://huggingface.co/moka-ai/m3e-large
|
||||
|
||||
Configure the proxy and modify LLM_MODEL, PROXY_API_URL and API_KEY in the `.env`file
|
||||
|
||||
```python
|
||||
```bash
|
||||
# .env
|
||||
# Aliyun tongyiqianwen
|
||||
LLM_MODEL=tongyi_proxyllm
|
||||
@ -134,13 +134,13 @@ PROXY_SERVER_URL={your_service_url}
|
||||
<TabItem value="chatglm" label="chatglm" >
|
||||
Install dependencies
|
||||
|
||||
```python
|
||||
```bash
|
||||
pip install zhipuai
|
||||
```
|
||||
|
||||
Download embedding model
|
||||
|
||||
```python
|
||||
```bash
|
||||
cd DB-GPT
|
||||
mkdir models and cd models
|
||||
|
||||
@ -152,7 +152,7 @@ git clone https://huggingface.co/moka-ai/m3e-large
|
||||
|
||||
Configure the proxy and modify LLM_MODEL, PROXY_API_URL and API_KEY in the `.env`file
|
||||
|
||||
```python
|
||||
```bash
|
||||
# .env
|
||||
LLM_MODEL=zhipu_proxyllm
|
||||
PROXY_SERVER_URL={your_service_url}
|
||||
@ -165,7 +165,7 @@ ZHIPU_PROXY_API_KEY={your-zhipu-sk}
|
||||
|
||||
Download embedding model
|
||||
|
||||
```python
|
||||
```bash
|
||||
cd DB-GPT
|
||||
mkdir models and cd models
|
||||
|
||||
@ -177,7 +177,7 @@ git clone https://huggingface.co/moka-ai/m3e-large
|
||||
|
||||
Configure the proxy and modify LLM_MODEL, MODEL_VERSION, API_KEY and API_SECRET in the `.env`file
|
||||
|
||||
```python
|
||||
```bash
|
||||
# .env
|
||||
LLM_MODEL=wenxin_proxyllm
|
||||
WEN_XIN_MODEL_VERSION={version} # ERNIE-Bot or ERNIE-Bot-turbo
|
||||
@ -190,7 +190,7 @@ WEN_XIN_API_SECRET={your-wenxin-sct}
|
||||
|
||||
Yi's API is compatible with OpenAI's API, so you can use the same dependencies as OpenAI's API.
|
||||
|
||||
```python
|
||||
```bash
|
||||
pip install -e ".[openai]"
|
||||
```
|
||||
|
||||
@ -225,9 +225,9 @@ YI_API_KEY={your-yi-api-key}
|
||||
<Tabs
|
||||
defaultValue="vicuna"
|
||||
values={[
|
||||
{label: 'ChatGLM', value: 'chatglm'},
|
||||
{label: 'Vicuna', value: 'vicuna'},
|
||||
{label: 'Baichuan', value: 'baichuan'},
|
||||
{label: 'ChatGLM', value: 'chatglm'},
|
||||
]}>
|
||||
<TabItem value="vicuna" label="vicuna">
|
||||
|
||||
@ -241,7 +241,7 @@ YI_API_KEY={your-yi-api-key}
|
||||
|
||||
##### Download LLM
|
||||
|
||||
```python
|
||||
```bash
|
||||
cd DB-GPT
|
||||
mkdir models and cd models
|
||||
|
||||
@ -255,7 +255,7 @@ git clone https://huggingface.co/lmsys/vicuna-13b-v1.5
|
||||
|
||||
```
|
||||
##### Environment variable configuration, configure the LLM_MODEL parameter in the `.env` file
|
||||
```python
|
||||
```bash
|
||||
# .env
|
||||
LLM_MODEL=vicuna-13b-v1.5
|
||||
```
|
||||
@ -274,7 +274,7 @@ LLM_MODEL=vicuna-13b-v1.5
|
||||
##### Download LLM
|
||||
|
||||
|
||||
```python
|
||||
```bash
|
||||
cd DB-GPT
|
||||
mkdir models and cd models
|
||||
|
||||
@ -290,7 +290,7 @@ git clone https://huggingface.co/baichuan-inc/Baichuan2-13B-Chat
|
||||
|
||||
```
|
||||
##### Environment variable configuration, configure the LLM_MODEL parameter in the `.env` file
|
||||
```python
|
||||
```bash
|
||||
# .env
|
||||
LLM_MODEL=baichuan2-13b
|
||||
```
|
||||
@ -299,16 +299,17 @@ LLM_MODEL=baichuan2-13b
|
||||
<TabItem value="chatglm" label="chatglm">
|
||||
|
||||
##### Hardware requirements description
|
||||
| Model | Quantize | VRAM Size |
|
||||
|------------------ |--------------|----------------|
|
||||
|ChatGLM-6b | 4-bit | 7GB |
|
||||
|ChatGLM-6b | 8-bit | 9GB |
|
||||
|ChatGLM-6b | FP16 | 14GB |
|
||||
| Model | Quantize | VRAM Size |
|
||||
|--------------------|-------------|----------------|
|
||||
| glm-4-9b-chat | Not support | 16GB |
|
||||
| ChatGLM-6b | 4-bit | 7GB |
|
||||
| ChatGLM-6b | 8-bit | 9GB |
|
||||
| ChatGLM-6b | FP16 | 14GB |
|
||||
|
||||
|
||||
##### Download LLM
|
||||
|
||||
```python
|
||||
```bash
|
||||
cd DB-GPT
|
||||
mkdir models and cd models
|
||||
|
||||
@ -318,13 +319,13 @@ or
|
||||
git clone https://huggingface.co/moka-ai/m3e-large
|
||||
|
||||
# llm model
|
||||
git clone https://huggingface.co/THUDM/chatglm2-6b
|
||||
git clone https://huggingface.co/THUDM/glm-4-9b-chat
|
||||
|
||||
```
|
||||
##### Environment variable configuration, configure the LLM_MODEL parameter in the `.env` file
|
||||
```python
|
||||
```bash
|
||||
# .env
|
||||
LLM_MODEL=chatglm2-6b
|
||||
LLM_MODEL=glm-4-9b-chat
|
||||
```
|
||||
</TabItem>
|
||||
|
||||
@ -347,7 +348,7 @@ Method 1: Download the converted model
|
||||
:::
|
||||
|
||||
If you want to use [Vicuna-13b-v1.5](https://huggingface.co/lmsys/vicuna-13b-v1.5), you can download the converted file [TheBloke/vicuna-13B-v1.5-GGUF](https://huggingface.co/TheBloke/vicuna-13B-v1.5-GGUF), only this one file is needed. Download the file and put it in the model path. You need to rename the model to: `ggml-model-q4_0.gguf`.
|
||||
```python
|
||||
```bash
|
||||
wget https://huggingface.co/TheBloke/vicuna-13B-v1.5-GGUF/resolve/main/vicuna-13b-v1.5.Q4_K_M.gguf -O models/ggml-model-q4_0.gguf
|
||||
```
|
||||
|
||||
@ -360,7 +361,7 @@ During use, you can also convert the model file yourself according to the instru
|
||||
#### Install dependencies
|
||||
llama.cpp is an optional installation item in DB-GPT. You can install it with the following command.
|
||||
|
||||
```python
|
||||
```bash
|
||||
pip install -e ".[llama_cpp]"
|
||||
```
|
||||
|
||||
@ -410,13 +411,13 @@ After version 0.4.7, we removed the automatic generation of MySQL database Schem
|
||||
|
||||
1. Frist, execute MySQL script to create database and tables.
|
||||
|
||||
```python
|
||||
```bash
|
||||
$ mysql -h127.0.0.1 -uroot -p{your_password} < ./assets/schema/dbgpt.sql
|
||||
```
|
||||
|
||||
2. Second, set DB-GPT MySQL database settings in `.env` file.
|
||||
|
||||
```python
|
||||
```bash
|
||||
LOCAL_DB_TYPE=mysql
|
||||
LOCAL_DB_USER= {your username}
|
||||
LOCAL_DB_PASSWORD={your_password}
|
||||
@ -432,19 +433,19 @@ LOCAL_DB_PORT=3306
|
||||
The DB-GPT project has a part of test data built-in by default, which can be loaded into the local database for testing through the following command
|
||||
- **Linux**
|
||||
|
||||
```python
|
||||
```bash
|
||||
bash ./scripts/examples/load_examples.sh
|
||||
|
||||
```
|
||||
- **Windows**
|
||||
|
||||
```python
|
||||
```bash
|
||||
.\scripts\examples\load_examples.bat
|
||||
```
|
||||
|
||||
## Run service
|
||||
The DB-GPT service is packaged into a server, and the entire DB-GPT service can be started through the following command.
|
||||
```python
|
||||
```bash
|
||||
python dbgpt/app/dbgpt_server.py
|
||||
```
|
||||
:::info NOTE
|
||||
@ -452,9 +453,17 @@ python dbgpt/app/dbgpt_server.py
|
||||
|
||||
If you are running version v0.4.3 or earlier, please start with the following command:
|
||||
|
||||
```python
|
||||
```bash
|
||||
python pilot/server/dbgpt_server.py
|
||||
```
|
||||
### Run DB-GPT with command `dbgpt`
|
||||
|
||||
If you want to run DB-GPT with the command `dbgpt`:
|
||||
|
||||
```bash
|
||||
dbgpt start webserver
|
||||
```
|
||||
|
||||
:::
|
||||
|
||||
## Visit website
|
||||
|
@ -7,7 +7,7 @@ DB-GPT supports the installation and use of a variety of open source and closed
|
||||
|
||||
:::info note
|
||||
- Detailed installation and deployment tutorials can be found in [Installation](/docs/installation).
|
||||
- This page only introduces deployment based on ChatGPT proxy and local Vicuna model.
|
||||
- This page only introduces deployment based on ChatGPT proxy and local glm model.
|
||||
:::
|
||||
|
||||
## Environmental preparation
|
||||
@ -20,7 +20,7 @@ Download DB-GPT
|
||||
|
||||
|
||||
|
||||
```python
|
||||
```bash
|
||||
git clone https://github.com/eosphoros-ai/DB-GPT.git
|
||||
```
|
||||
|
||||
@ -32,7 +32,7 @@ git clone https://github.com/eosphoros-ai/DB-GPT.git
|
||||
Create a Python virtual environment
|
||||
:::
|
||||
|
||||
```python
|
||||
```bash
|
||||
python >= 3.10
|
||||
conda create -n dbgpt_env python=3.10
|
||||
conda activate dbgpt_env
|
||||
@ -44,7 +44,7 @@ pip install -e ".[default]"
|
||||
:::tip
|
||||
Copy environment variables
|
||||
:::
|
||||
```python
|
||||
```bash
|
||||
cp .env.template .env
|
||||
```
|
||||
|
||||
@ -61,8 +61,8 @@ import TabItem from '@theme/TabItem';
|
||||
<Tabs
|
||||
defaultValue="openai"
|
||||
values={[
|
||||
{label: 'Open AI', value: 'openai'},
|
||||
{label: 'Vicuna', value: 'vicuna'},
|
||||
{label: 'Open AI(Proxy LLM)', value: 'openai'},
|
||||
{label: 'glm-4(Local LLM)', value: 'glm-4'},
|
||||
]}>
|
||||
|
||||
<TabItem value="openai" label="openai">
|
||||
@ -70,7 +70,7 @@ import TabItem from '@theme/TabItem';
|
||||
:::info note
|
||||
|
||||
⚠️ You need to ensure that git-lfs is installed
|
||||
```python
|
||||
```bash
|
||||
● CentOS installation: yum install git-lfs
|
||||
● Ubuntu installation: apt-get install git-lfs
|
||||
● MacOS installation: brew install git-lfs
|
||||
@ -79,13 +79,13 @@ import TabItem from '@theme/TabItem';
|
||||
|
||||
#### Install dependencies
|
||||
|
||||
```python
|
||||
```bash
|
||||
pip install -e ".[openai]"
|
||||
```
|
||||
|
||||
#### Download embedding model
|
||||
|
||||
```python
|
||||
```bash
|
||||
cd DB-GPT
|
||||
mkdir models and cd models
|
||||
git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese
|
||||
@ -93,7 +93,7 @@ git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese
|
||||
|
||||
#### Configure the proxy and modify LLM_MODEL, PROXY_API_URL and API_KEY in the `.env`file
|
||||
|
||||
```python
|
||||
```bash
|
||||
# .env
|
||||
LLM_MODEL=chatgpt_proxyllm
|
||||
PROXY_API_KEY={your-openai-sk}
|
||||
@ -101,35 +101,32 @@ PROXY_SERVER_URL=https://api.openai.com/v1/chat/completions
|
||||
```
|
||||
</TabItem>
|
||||
|
||||
<TabItem value="vicuna" label="vicuna">
|
||||
<TabItem value="glm-4" label="glm-4">
|
||||
|
||||
#### Hardware requirements description
|
||||
| Model | Quantize | VRAM Size |
|
||||
|:----------------------------------------:|--------------:|---------------|
|
||||
|Vicuna-7b | 4-bit | 8GB |
|
||||
|Vicuna-7b | 8-bit | 12GB |
|
||||
|Vicuna-13b | 4-bit | 12GB |
|
||||
|Vicuna-13b | 8-bit | 20GB |
|
||||
| Model | GPU VRAM Size |
|
||||
|:--------------:|-------------------|
|
||||
| glm-4-9b | 16GB |
|
||||
|
||||
#### Download LLM
|
||||
|
||||
```python
|
||||
```bash
|
||||
cd DB-GPT
|
||||
mkdir models and cd models
|
||||
|
||||
# embedding model
|
||||
git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese
|
||||
or
|
||||
git clone https://huggingface.co/moka-ai/m3e-large
|
||||
# also you can use m3e-large model, you can choose one of them according to your needs
|
||||
# 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
|
||||
# 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/THUDM/glm-4-9b-chat
|
||||
|
||||
```
|
||||
#### Environment variable configuration, configure the LLM_MODEL parameter in the `.env` file
|
||||
```python
|
||||
```bash
|
||||
# .env
|
||||
LLM_MODEL=vicuna-13b-v1.5
|
||||
LLM_MODEL=glm-4-9b-chat
|
||||
```
|
||||
</TabItem>
|
||||
|
||||
@ -140,38 +137,49 @@ LLM_MODEL=vicuna-13b-v1.5
|
||||
Load default test data into SQLite database
|
||||
- **Linux**
|
||||
|
||||
```python
|
||||
```bash
|
||||
bash ./scripts/examples/load_examples.sh
|
||||
```
|
||||
- **Windows**
|
||||
|
||||
```python
|
||||
```bash
|
||||
.\scripts\examples\load_examples.bat
|
||||
```
|
||||
|
||||
## Run service
|
||||
|
||||
```python
|
||||
```bash
|
||||
python dbgpt/app/dbgpt_server.py
|
||||
```
|
||||
|
||||
:::info NOTE
|
||||
### Run service
|
||||
### Run old service
|
||||
|
||||
If you are running version v0.4.3 or earlier, please start with the following command:
|
||||
|
||||
```python
|
||||
```bash
|
||||
python pilot/server/dbgpt_server.py
|
||||
```
|
||||
|
||||
### Run DB-GPT with command `dbgpt`
|
||||
|
||||
If you want to run DB-GPT with the command `dbgpt`:
|
||||
|
||||
```bash
|
||||
dbgpt start webserver
|
||||
```
|
||||
:::
|
||||
|
||||
## Visit website
|
||||
|
||||
#### 1. Production model:
|
||||
Open the browser and visit [`http://localhost:5670`](http://localhost:5670)
|
||||
|
||||
#### 2. Development mode:
|
||||
```
|
||||
|
||||
### (Optional) Run web front-end separately
|
||||
|
||||
On the other hand, you can also run the web front-end separately.
|
||||
|
||||
```bash
|
||||
cd web & npm install
|
||||
cp .env.template .env
|
||||
// set the API_BASE_URL to your DB-GPT server address, it usually is http://localhost:5670
|
||||
|
@ -19,6 +19,10 @@ logging.basicConfig(
|
||||
@tool
|
||||
def simple_calculator(first_number: int, second_number: int, operator: str) -> float:
|
||||
"""Simple calculator tool. Just support +, -, *, /."""
|
||||
if isinstance(first_number, str):
|
||||
first_number = int(first_number)
|
||||
if isinstance(second_number, str):
|
||||
second_number = int(second_number)
|
||||
if operator == "+":
|
||||
return first_number + second_number
|
||||
elif operator == "-":
|
||||
|
@ -34,15 +34,15 @@ install_sys_packages() {
|
||||
clone_repositories() {
|
||||
cd /root && git clone https://github.com/eosphoros-ai/DB-GPT.git
|
||||
mkdir -p /root/DB-GPT/models && cd /root/DB-GPT/models
|
||||
git clone https://huggingface.co/GanymedeNil/text2vec-large-chinese
|
||||
git clone https://huggingface.co/Qwen/Qwen-1_8B-Chat
|
||||
git clone https://www.modelscope.cn/Jerry0/text2vec-large-chinese.git
|
||||
git clone https://www.modelscope.cn/qwen/Qwen2-0.5B-Instruct.git
|
||||
rm -rf /root/DB-GPT/models/text2vec-large-chinese/.git
|
||||
rm -rf /root/DB-GPT/models/Qwen-1_8B-Chat/.git
|
||||
rm -rf /root/DB-GPT/models/Qwen2-0.5B-Instruct/.git
|
||||
}
|
||||
|
||||
install_dbgpt_packages() {
|
||||
conda activate dbgpt && cd /root/DB-GPT && pip install -e ".[default]" && pip install transformers_stream_generator einops
|
||||
cp .env.template .env && sed -i 's/LLM_MODEL=vicuna-13b-v1.5/LLM_MODEL=qwen-1.8b-chat/' .env
|
||||
cp .env.template .env && sed -i 's/LLM_MODEL=glm-4-9b-chat/LLM_MODEL=qwen2-0.5b-instruct/' .env
|
||||
}
|
||||
|
||||
clean_up() {
|
||||
|
Loading…
Reference in New Issue
Block a user