部署自己的对话大模型,使用Ollama + Qwen2 +FastGPT 实现

部署资源

  • AUTODL 使用最小3080Ti 资源,cuda > 12.0
  • 使用云服务器,部署fastGPT oneAPI,M3E 模型

操作步骤

  1. 配置代理
    export HF_ENDPOINT=https://hf-mirror.com

  2. 下载qwen2模型 - 如何下载huggingface
    huggingface-cli download Qwen/Qwen2-7B-Instruct-GGUF qwen2-7b-instruct-q5_k_m.gguf --local-dir . --local-dir-use-symlinks False

  3. 创建模型文件

    FROM qwen2-7b-instruct-q5_k_m.gguf
    
    # set the temperature to 1 [higher is more creative, lower is more coherent]
    PARAMETER temperature 0.7
    PARAMETER top_p 0.8
    PARAMETER repeat_penalty 1.05
    TEMPLATE """{{ if and .First .System }}<|im_start|>system
    {{ .System }}<|im_end|>
    {{ end }}<|im_start|>user
    {{ .Prompt }}<|im_end|>
    <|im_start|>assistant
    {{ .Response }}"""
    # set the system message
    SYSTEM """
    You are a helpful assistant.
    """
    
  4. 导入模型
    ollama create qwen2:7b -f Modelfile

  5. 运行qwen2客户端
    ollama run qwen2-7b

  6. 运行m3e RAG模型

    version: '3'
    services:
      m3e_api:
        container_name: m3e_api
     
        environment:
          TZ: Asia/Shanghai
     
        image: registry.cn-hangzhou.aliyuncs.com/fastgpt_docker/m3e-large-api:latest
     
        restart: always
     
     
        ports:
          - "6200:6008"
    
  7. 运行fastAPI + oneAPI

    version: '3.3'
    services:
      # db
      pg:
        image: pgvector/pgvector:0.7.0-pg15 # docker hub
        # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/pgvector:v0.7.0 # 阿里云
        container_name: pg
        restart: always
        ports: # 生产环境建议不要暴露
          - 5432:5432
        networks:
          - fastgpt
        environment:
          # 这里的配置只有首次运行生效。修改后,重启镜像是不会生效的。需要把持久化数据删除再重启,才有效果
          - POSTGRES_USER=username
          - POSTGRES_PASSWORD=password
          - POSTGRES_DB=postgres
        volumes:
          - ./pg/data:/var/lib/postgresql/data
      mongo:
        image: mongo:5.0.18 # dockerhub
        # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/mongo:5.0.18 # 阿里云
        # image: mongo:4.4.29 # cpu不支持AVX时候使用
        container_name: mongo
        restart: always
        ports:
          - 27017:27017
        networks:
          - fastgpt
        command: mongod --keyFile /data/mongodb.key --replSet rs0
        environment:
          - MONGO_INITDB_ROOT_USERNAME=myusername
          - MONGO_INITDB_ROOT_PASSWORD=mypassword
        volumes:
          - ./mongo/data:/data/db
        entrypoint:
          - bash
          - -c
          - |
            openssl rand -base64 128 > /data/mongodb.key
            chmod 400 /data/mongodb.key
            chown 999:999 /data/mongodb.key
            echo 'const isInited = rs.status().ok === 1
            if(!isInited){
              rs.initiate({
                  _id: "rs0",
                  members: [
                      { _id: 0, host: "mongo:27017" }
                  ]
              })
            }' > /data/initReplicaSet.js
            # 启动MongoDB服务
            exec docker-entrypoint.sh "$$@" &
    
            # 等待MongoDB服务启动
            until mongo -u myusername -p mypassword --authenticationDatabase admin --eval "print('waited for connection')" > /dev/null 2>&1; do
              echo "Waiting for MongoDB to start..."
              sleep 2
            done
    
            # 执行初始化副本集的脚本
            mongo -u myusername -p mypassword --authenticationDatabase admin /data/initReplicaSet.js
    
            # 等待docker-entrypoint.sh脚本执行的MongoDB服务进程
            wait $$!
    
      # fastgpt
      sandbox:
        container_name: sandbox
        image: ghcr.io/labring/fastgpt-sandbox:latest # git
        # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt-sandbox:latest # 阿里云
        networks:
          - fastgpt
        restart: always
      fastgpt:
        container_name: fastgpt
        image: ghcr.io/labring/fastgpt:v4.8.9 # git
        # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/fastgpt:v4.8.9 # 阿里云
        ports:
          - 3200:3000
        networks:
          - fastgpt
        depends_on:
          - mongo
          - pg
          - sandbox
        restart: always
        environment:
          # root 密码,用户名为: root。如果需要修改 root 密码,直接修改这个环境变量,并重启即可。
          - DEFAULT_ROOT_PSW=1234
          # AI模型的API地址哦。务必加 /v1。这里默认填写了OneApi的访问地址。
          - OPENAI_BASE_URL=http://oneapi:3000/v1
          # AI模型的API Key。(这里默认填写了OneAPI的快速默认key,测试通后,务必及时修改)
          - CHAT_API_KEY=sk-fastgpt
          # 数据库最大连接数
          - DB_MAX_LINK=30
          # 登录凭证密钥
          - TOKEN_KEY=any
          # root的密钥,常用于升级时候的初始化请求
          - ROOT_KEY=root_key
          # 文件阅读加密
          - FILE_TOKEN_KEY=filetoken
          # MongoDB 连接参数. 用户名myusername,密码mypassword。
          - MONGODB_URI=mongodb://myusername:mypassword@mongo:27017/fastgpt?authSource=admin
          # pg 连接参数
          - PG_URL=postgresql://username:password@pg:5432/postgres
          # sandbox 地址
          - SANDBOX_URL=http://sandbox:3000
          # 日志等级: debug, info, warn, error
          - LOG_LEVEL=info
          - STORE_LOG_LEVEL=warn
        volumes:
          - ./config.json:/app/data/config.json
    
      # oneapi
      mysql:
        # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/mysql:8.0.36 # 阿里云
        image: mysql:8.0.36
        container_name: mysql
        restart: always
        ports:
          - 3306:3306
        networks:
          - fastgpt
        command: --default-authentication-plugin=mysql_native_password
        environment:
          # 默认root密码,仅首次运行有效
          MYSQL_ROOT_PASSWORD: oneapimmysql
          MYSQL_DATABASE: oneapi
        volumes:
          - ./mysql:/var/lib/mysql
      oneapi:
        container_name: oneapi
        image: ghcr.io/songquanpeng/one-api:v0.6.7
        # image: registry.cn-hangzhou.aliyuncs.com/fastgpt/one-api:v0.6.6 # 阿里云
        ports:
          - 3001:3000
        depends_on:
          - mysql
        networks:
          - fastgpt
        restart: always
        environment:
          # mysql 连接参数
          - SQL_DSN=root:oneapimmysql@tcp(mysql:3306)/oneapi
          # 登录凭证加密密钥
          - SESSION_SECRET=oneapikey
          # 内存缓存
          - MEMORY_CACHE_ENABLED=true
          # 启动聚合更新,减少数据交互频率
          - BATCH_UPDATE_ENABLED=true
          # 聚合更新时长
          - BATCH_UPDATE_INTERVAL=10
          # 初始化的 root 密钥(建议部署完后更改,否则容易泄露)
          - INITIAL_ROOT_TOKEN=fastgpt
        volumes:
          - ./oneapi:/data
    networks:
      fastgpt:
    
  8. 编辑fastGPT 的模型配置

    {
    "feConfigs": {
    "lafEnv": "https://laf.dev"
    },
    "systemEnv": {
    "vectorMaxProcess": 15,
    "qaMaxProcess": 15,
    "pgHNSWEfSearch": 100
    },
    "llmModels":[
    {
    "model": "qwen2:7b",
    "name": "qwen2",
    "avatar": "/imgs/model/openai.svg",
    "maxContext": 125000,
    "maxResponse": 4000,
    "quoteMaxToken": 120000,
    "maxTemperature": 1.2,
    "charsPointsPrice": 0,
    "censor": false,
    "vision": true,
    "datasetProcess": false,
    "usedInClassify": true,
    "usedInExtractFields": true,
    "usedInToolCall": true,
    "usedInQueryExtension": true,
    "toolChoice": true,
    "functionCall": false,
    "customCQPrompt": "",
    "customExtractPrompt": "",
    "defaultSystemChatPrompt": "",
    "defaultConfig": {}
    }
    ],
    "vectorModels": [
    {
    "model": "mxbai-embed-large",
    "name": "mxbai",
    "avatar": "/imgs/model/openai.svg",
    "charsPointsPrice": 0,
    "defaultToken": 512,
    "maxToken": 3000,
    "weight": 100
    },
    {
    "model": "m3e",
    "name": "M3E",
    "price": 0.1,
    "defaultToken": 500,
    "maxToken": 1800
    }
    ],
    "reRankModels": [],
    "audioSpeechModels": [
    {
    "model": "tts-1",
    "name": "OpenAI TTS1",
    "charsPointsPrice": 0,
    "voices": [
    { "label": "Alloy", "value": "alloy", "bufferId": "openai-Alloy" },
    { "label": "Echo", "value": "echo", "bufferId": "openai-Echo" },
    { "label": "Fable", "value": "fable", "bufferId": "openai-Fable" },
    { "label": "Onyx", "value": "onyx", "bufferId": "openai-Onyx" },
    { "label": "Nova", "value": "nova", "bufferId": "openai-Nova" },
    { "label": "Shimmer", "value": "shimmer", "bufferId": "openai-Shimmer" }
    ]
    }
    ],
    "whisperModel": {
    "model": "whisper-1",
    "name": "Whisper1",
    "charsPointsPrice": 0
    }
    }

  9. 打开oneapi http://ip:3001, 初始密码 root 1234, 配置qwen2 模型以及M3E模型

  10. 点击测试

    • 注:M3E 点击测试后提示404是正常的
  11. 重启fastgpt 和 oneapi
    docker-compose restart fastgpt oneapi

  12. 在fastgpt 中创建一个应用进行测试


  13. 大功告成!!!

从huggingface中直接下载,使用python直接部署为服务

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