本地容器化快速部署GLM-4-9B-chat教程_chatglm4-9b

本文需要有一定的docker 基础知识，且会修改python代码，不是新手向的教程

第一步：下载官方项目

GitHub - THUDM/GLM-4: GLM-4 series: Open Multilingual Multimodal Chat LMs | 开源多语言多模态对话模型

 然后在官方项目的根目录下，添加dockerfile文件,docker file 文件的内容如下

# 使用nvidia/cuda:12.4.1-devel-ubuntu22.04作为基础镜像
FROM nvidia/cuda:12.4.1-devel-ubuntu22.04 AS dev
 
# 更新包索引并安装Python 3的pip和Git
RUN apt-get update -y \
    && apt-get install -y python3-pip git \
    && rm -rf /var/lib/apt/lists/*
 
# 运行ldconfig命令以确保CUDA库可以被正确找到
RUN ldconfig /usr/local/cuda-12.4/compat/
 
# 设置工作目录
WORKDIR /glm4
 
# 复制文件夹和文件到容器的工作目录
COPY basic_demo /glm4/basic_demo
COPY composite_demo /glm4/composite_demo
COPY finetune_demo /glm4/finetune_demo
COPY LICENSE /glm4/LICENSE
COPY resources /glm4/resources
 
# 进入到/basic_demo目录
WORKDIR /glm4/basic_demo
 
# 安装requirements.txt中指定的Python依赖
RUN python3 -m pip install --no-cache-dir -r requirements.txt -i https://pypi.tuna.tsinghua.edu.cn/simple/
 
# 回到之前的工作目录
WORKDIR /glm4
 
# 声明容器将监听的端口
EXPOSE 8000

然后在项目的根目录下，构建容器

docker build -t you_need_name/glm4-9b:tag .

然后等待容器构建成功。

容器构建成功后，需要提前下载好模型。

下载模型后，需要修改openai_api_server.py文件，修改的位置如下。

修改的内容如下，修改这些内容是为了方便在容器启动时，直接设置模型路径，

MODEL_PATH = os.environ.get('LOCAL_MODEL_PATH','THUDM/glm-4-9b-chat')
MAX_MODEL_LENGTH = os.environ.get('LOCAL_MAX_MODEL_LENGTH','8192')

修改完成后使用如下docker-compose.yml文件，在该文件的目录下运行 ‘docker compose up -d’命令

version: '3.8'
services:
  glm4_vllm_server:
    image: jjck/glm4-9b:20240606
    runtime: nvidia
    ipc: host
    restart: always
    environment:
      - LOCAL_MODEL_PATH=/glm4/glm-4-9b-chat
      - LOCAL_MAX_MODEL_LENGTH=8192
    ports:
      - "8101:8000"
    volumes:
      - "/etc/localtime:/etc/localtime:ro"
      - "/home/aicode/logs/AI_Order/glm-4-9b-chat:/glm4/glm-4-9b-chat"
      - "/home/pythonproject/GLM-4-main/basic_demo:/glm4/basic_demo"
    command: python3 basic_demo/openai_api_server.py
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              device_ids: ['0']
              capabilities: [gpu]

• "/home/aicode/logs/AI_Order/glm-4-9b-chat:/glm4/glm-4-9b-chat" - "/home/pythonproject/GLM-4-main/basic_demo:/glm4/basic_demo"

这两个路径，第一个是模型的存放路径，这个路径根据你的实际情况自行修改。

第二个是代码路径，这个也是根据自身情况自行修改。

或者是这个命令

docker run --runtime nvidia --gpus device=0 \
    --name glm4_vllm_server \
    -p 8101:8000 \
    -v /etc/localtime:/etc/localtime:ro \
    -v /home/aicode/logs/AI_Order/glm-4-9b-chat:/glm4/glm-4-9b-chat \
    -v /home/pythonproject/GLM-4-main/basic_demo:/glm4/basic_demo \
    -itd xxx/glm4-9b:20240606 

我尝试用他们的api_server demo的过程中出现的问题。

用清华官方的这个demo会出现异步线程的问题，导致用户访问异常,异常的日志如下

glm4_vllm_api_server-glm4_vllm_server-1  |   File "/usr/local/lib/python3.10/dist-packages/fastapi/routing.py", line 191, in run_endpoint_function
glm4_vllm_api_server-glm4_vllm_server-1  |     return await dependant.call(**values)
glm4_vllm_api_server-glm4_vllm_server-1  |   File "/glm4/basic_demo/openai_api_server.py", line 344, in create_chat_completion
glm4_vllm_api_server-glm4_vllm_server-1  |     async for response in generate_stream_glm4(gen_params):
glm4_vllm_api_server-glm4_vllm_server-1  |   File "/glm4/basic_demo/openai_api_server.py", line 199, in generate_stream_glm4
glm4_vllm_api_server-glm4_vllm_server-1  |     async for output in engine.generate(inputs=inputs, sampling_params=sampling_params, request_id="glm-4-9b"):
glm4_vllm_api_server-glm4_vllm_server-1  |   File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 662, in generate
glm4_vllm_api_server-glm4_vllm_server-1  |     async for output in self._process_request(
glm4_vllm_api_server-glm4_vllm_server-1  |   File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 756, in _process_request
glm4_vllm_api_server-glm4_vllm_server-1  |     stream = await self.add_request(
glm4_vllm_api_server-glm4_vllm_server-1  |   File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 561, in add_request
glm4_vllm_api_server-glm4_vllm_server-1  |     self.start_background_loop()
glm4_vllm_api_server-glm4_vllm_server-1  |   File "/usr/local/lib/python3.10/dist-packages/vllm/engine/async_llm_engine.py", line 431, in start_background_loop
glm4_vllm_api_server-glm4_vllm_server-1  |     raise AsyncEngineDeadError(
glm4_vllm_api_server-glm4_vllm_server-1  | vllm.engine.async_llm_engine.AsyncEngineDeadError: Background loop has errored already.

所以，不要把demo放在生产环境中使用。需要在生产环境的，等官方适配吧