目前的工作总结来看就是进行AI智能体的开发，组里基于langchain做了一些储备，搭建了内部的一个AI智能体开发平台，支持了知识库、工具调用、多种大模型的配置，但当后来字节的coze、百度的千帆发布，发现AI智能体开发平台真是发展的太快了，相比于coze，丰富的插件工具，稳定的模型，成熟的工作流，分析自己组内的人力情况，根本追不上：组内同学既要全力完成okr，又要每个人开发自己的AI智能体，剩下的精力才能继续完善AI智能体平台。

五一之前，领导在群里扔了一个创业公司基于Dify开发AI应用的介绍。我抱着学习的态度了解了一下Dify：可以称之为开源版的coze！支持多种大模型、插件工具的一键适配，支持知识库自动切割创建索引，支持工具流开发！赞啊，这些功能不正是组内AI智能体开发平台需要添加的功能么。于是马上开始了部署与调试。

先分享dify项目的github：https://github.com/langgenius/dify

“项目由前腾讯云DevOps团队成员创建。我们发现基于OpenAI的API开发GPT应用程序有些麻烦。凭借我们多年在开发者效率工具方面的研发经验，我们希望能够让更多的人使用自然语言开发有趣的应用程序。”

dify由10+全职团队和100+社区贡献者共同维护，迭代非常快，我下载的时候还是0.6.3，现在已经升级为0.6.6，基本上每周都会升级一个版本。这里唠叨两句，对于迭代非常频繁的开源项目，在公司内部使用的时候，咱就先别二次开发了，否则你这边刚开发完一个点，另一边社区升级了，逻辑冲突合不到一块去，尴尬不尴尬。之前听说有个团队基于tensorflow1.x“自研”了深度学习训练框架，多年过去，社区都2.x了，那个团队还在tensorflow1.x上疲于奔命。哈哈哈，扯远了。

说回到本文，标题叫《Agent AI智能体的未来—Dify项目介绍》，其实是有些夸张的，但我认为，了解Dify以及其中依赖的上下游技术、架构，利用Dify快速建立AI智能体demo原型，其实对推进AI智能体开发是有意义的。今天我先简要介绍一下Dify的部署过程，后面的篇幅会具体分享基于Dify的AI智能体开发经验，以及AI智能体开发所依赖的底层技术。

2.docker compose一行命令部署Dify

首先将dify项目下载至服务器上，

git clone https://github.com/langgenius/dify.git

项目主要分为api（后端）和web（前端）两大部分，具体代码后面再分析，进入docker目录

cd docker

目录中包含几个文件，docker-compose.yaml可以通过docker compose直接启动所有服务和依赖，docker-compose.middleware.yaml可以先启动依赖的关系数据库、向量数据库等组件，再单独启动api和web端，隔离做得可以说太棒了。

先看一下docker-compose.yaml的源码


version: '3'
services:
  # API service
  api:
    image: langgenius/dify-api:0.6.6
    restart: always
    environment:
      # Startup mode, 'api' starts the API server.
      MODE: api
      # The log level for the application. Supported values are `DEBUG`, `INFO`, `WARNING`, `ERROR`, `CRITICAL`
      LOG_LEVEL: INFO
      # A secret key that is used for securely signing the session cookie and encrypting sensitive information on the database. You can generate a strong key using `openssl rand -base64 42`.
      SECRET_KEY: sk-9f73s3ljTXVcMT3Blb3ljTqtsKiGHXVcMT3BlbkFJLK7U
      # The base URL of console application web frontend, refers to the Console base URL of WEB service if console domain is
      # different from api or web app domain.
      # example: http://cloud.dify.ai
      CONSOLE_WEB_URL: ''
      # Password for admin user initialization.
      # If left unset, admin user will not be prompted for a password when creating the initial admin account.
      INIT_PASSWORD: ''
      # The base URL of console application api server, refers to the Console base URL of WEB service if console domain is
      # different from api or web app domain.
      # example: http://cloud.dify.ai
      CONSOLE_API_URL: ''
      # The URL prefix for Service API endpoints, refers to the base URL of the current API service if api domain is
      # different from console domain.
      # example: http://api.dify.ai
      SERVICE_API_URL: ''
      # The URL prefix for Web APP frontend, refers to the Web App base URL of WEB service if web app domain is different from
      # console or api domain.
      # example: http://udify.app
      APP_WEB_URL: ''
      # File preview or download Url prefix.
      # used to display File preview or download Url to the front-end or as Multi-model inputs;
      # Url is signed and has expiration time.
      FILES_URL: ''
      # When enabled, migrations will be executed prior to application startup and the application will start after the migrations have completed.
      MIGRATION_ENABLED: 'true'
      # The configurations of postgres database connection.
      # It is consistent with the configuration in the 'db' service below.
      DB_USERNAME: postgres
      DB_PASSWORD: difyai123456
      DB_HOST: db
      DB_PORT: 5432
      DB_DATABASE: dify
      # The configurations of redis connection.
      # It is consistent with the configuration in the 'redis' service below.
      REDIS_HOST: redis
      REDIS_PORT: 6379
      REDIS_USERNAME: ''
      REDIS_PASSWORD: difyai123456
      REDIS_USE_SSL: 'false'
      # use redis db 0 for redis cache
      REDIS_DB: 0
      # The configurations of celery broker.
      # Use redis as the broker, and redis db 1 for celery broker.
      CELERY_BROKER_URL: redis://:difyai123456@redis:6379/1
      # Specifies the allowed origins for cross-origin requests to the Web API, e.g. https://dify.app or * for all origins.
      WEB_API_CORS_ALLOW_ORIGINS: '*'
      # Specifies the allowed origins for cross-origin requests to the console API, e.g. https://cloud.dify.ai or * for all origins.
      CONSOLE_CORS_ALLOW_ORIGINS: '*'
      # CSRF Cookie settings
      # Controls whether a cookie is sent with cross-site requests,
      # providing some protection against cross-site request forgery attacks
      #
      # Default: `SameSite=Lax, Secure=false, HttpOnly=true`
      # This default configuration supports same-origin requests using either HTTP or HTTPS,
      # but does not support cross-origin requests. It is suitable for local debugging purposes.
      #
      # If you want to enable cross-origin support,
      # you must use the HTTPS protocol and set the configuration to `SameSite=None, Secure=true, HttpOnly=true`.
      #
      # The type of storage to use for storing user files. Supported values are `local` and `s3` and `azure-blob` and `google-storage`, Default: `local`
      STORAGE_TYPE: local
      # The path to the local storage directory, the directory relative the root path of API service codes or absolute path. Default: `storage` or `/home/john/storage`.
      # only available when STORAGE_TYPE is `local`.
      STORAGE_LOCAL_PATH: storage
      # The S3 storage configurations, only available when STORAGE_TYPE is `s3`.
      S3_ENDPOINT: 'https://xxx.r2.cloudflarestorage.com'
      S3_BUCKET_NAME: 'difyai'
      S3_ACCESS_KEY: 'ak-difyai'
      S3_SECRET_KEY: 'sk-difyai'
      S3_REGION: 'us-east-1'
      # The Azure Blob storage configurations, only available when STORAGE_TYPE is `azure-blob`.
      AZURE_BLOB_ACCOUNT_NAME: 'difyai'
      AZURE_BLOB_ACCOUNT_KEY: 'difyai'
      AZURE_BLOB_CONTAINER_NAME: 'difyai-container'
      AZURE_BLOB_ACCOUNT_URL: 'https://<your_account_name>.blob.core.windows.net'
      # The Google storage configurations, only available when STORAGE_TYPE is `google-storage`.
      GOOGLE_STORAGE_BUCKET_NAME: 'yout-bucket-name'
      GOOGLE_STORAGE_SERVICE_ACCOUNT_JSON_BASE64: 'your-google-service-account-json-base64-string'
      # The type of vector store to use. Supported values are `weaviate`, `qdrant`, `milvus`, `relyt`.
      VECTOR_STORE: weaviate
      # The Weaviate endpoint URL. Only available when VECTOR_STORE is `weaviate`.
      WEAVIATE_ENDPOINT: http://weaviate:8080
      # The Weaviate API key.
      WEAVIATE_API_KEY: WVF5YThaHlkYwhGUSmCRgsX3tD5ngdN8pkih
      # The Qdrant endpoint URL. Only available when VECTOR_STORE is `qdrant`.
      QDRANT_URL: http://qdrant:6333
      # The Qdrant API key.
      QDRANT_API_KEY: difyai123456
      # The Qdrant client timeout setting.
      QDRANT_CLIENT_TIMEOUT: 20
      # The Qdrant client enable gRPC mode.
      QDRANT_GRPC_ENABLED: 'false'
      # The Qdrant server gRPC mode PORT.
      QDRANT_GRPC_PORT: 6334
      # Milvus configuration Only available when VECTOR_STORE is `milvus`.
      # The milvus host.
      MILVUS_HOST: 127.0.0.1
      # The milvus host.
      MILVUS_PORT: 19530
      # The milvus username.
      MILVUS_USER: root
      # The milvus password.
      MILVUS_PASSWORD: Milvus
      # The milvus tls switch.
      MILVUS_SECURE: 'false'
      # relyt configurations
      RELYT_HOST: db
      RELYT_PORT: 5432
      RELYT_USER: postgres
      RELYT_PASSWORD: difyai123456
      RELYT_DATABASE: postgres
      # Mail configuration, support: resend, smtp
      MAIL_TYPE: ''
      # default send from email address, if not specified
      MAIL_DEFAULT_SEND_FROM: 'YOUR EMAIL FROM (eg: no-reply <no-reply@dify.ai>)'
      SMTP_SERVER: ''
      SMTP_PORT: 587
      SMTP_USERNAME: ''
      SMTP_PASSWORD: ''
      SMTP_USE_TLS: 'true'
      # the api-key for resend (https://resend.com)
      RESEND_API_KEY: ''
      RESEND_API_URL: https://api.resend.com
      # The DSN for Sentry error reporting. If not set, Sentry error reporting will be disabled.
      SENTRY_DSN: ''
      # The sample rate for Sentry events. Default: `1.0`
      SENTRY_TRACES_SAMPLE_RATE: 1.0
      # The sample rate for Sentry profiles. Default: `1.0`
      SENTRY_PROFILES_SAMPLE_RATE: 1.0
      # Notion import configuration, support public and internal
      NOTION_INTEGRATION_TYPE: public
      NOTION_CLIENT_SECRET: you-client-secret
      NOTION_CLIENT_ID: you-client-id
      NOTION_INTERNAL_SECRET: you-internal-secret
      # The sandbox service endpoint.
      CODE_EXECUTION_ENDPOINT: "http://sandbox:8194"
      CODE_EXECUTION_API_KEY: dify-sandbox
      CODE_MAX_NUMBER: 9223372036854775807
      CODE_MIN_NUMBER: -9223372036854775808
      CODE_MAX_STRING_LENGTH: 80000
      TEMPLATE_TRANSFORM_MAX_LENGTH: 80000
      CODE_MAX_STRING_ARRAY_LENGTH: 30
      CODE_MAX_OBJECT_ARRAY_LENGTH: 30
      CODE_MAX_NUMBER_ARRAY_LENGTH: 1000
    depends_on:
      - db
      - redis
    volumes:
      # Mount the storage directory to the container, for storing user files.
      - ./volumes/app/storage:/app/api/storage
    # uncomment to expose dify-api port to host
    # ports:
    #   - "5001:5001"
 
  # worker service
  # The Celery worker for processing the queue.
  worker:
    image: langgenius/dify-api:0.6.6
    restart: always
    environment:
      # Startup mode, 'worker' starts the Celery worker for processing the queue.
      MODE: worker
 
      # --- All the configurations below are the same as those in the 'api' service. ---
 
      # The log level for the application. Supported values are `DEBUG`, `INFO`, `WARNING`, `ERROR`, `CRITICAL`
      LOG_LEVEL: INFO
      # A secret key that is used for securely signing the session cookie and encrypting sensitive information on the database. You can generate a strong key using `openssl rand -base64 42`.
      # same as the API service
      SECRET_KEY: sk-9f73s3ljTXVcMT3Blb3ljTqtsKiGHXVcMT3BlbkFJLK7U
      # The configurations of postgres database connection.
      # It is consistent with the configuration in the 'db' service below.
      DB_USERNAME: postgres
      DB_PASSWORD: difyai123456
      DB_HOST: db
      DB_PORT: 5432
      DB_DATABASE: dify
      # The configurations of redis cache connection.
      REDIS_HOST: redis
      REDIS_PORT: 6379
      REDIS_USERNAME: ''
      REDIS_PASSWORD: difyai123456
      REDIS_DB: 0
      REDIS_USE_SSL: 'false'
      # The configurations of celery broker.
      CELERY_BROKER_URL: redis://:difyai123456@redis:6379/1
      # The type of storage to use for storing user files. Supported values are `local` and `s3` and `azure-blob`, Default: `local`
      STORAGE_TYPE: local
      STORAGE_LOCAL_PATH: storage
      # The S3 storage configurations, only available when STORAGE_TYPE is `s3`.
      S3_ENDPOINT: 'https://xxx.r2.cloudflarestorage.com'
      S3_BUCKET_NAME: 'difyai'
      S3_ACCESS_KEY: 'ak-difyai'
      S3_SECRET_KEY: 'sk-difyai'
      S3_REGION: 'us-east-1'
      # The Azure Blob storage configurations, only available when STORAGE_TYPE is `azure-blob`.
      AZURE_BLOB_ACCOUNT_NAME: 'difyai'
      AZURE_BLOB_ACCOUNT_KEY: 'difyai'
      AZURE_BLOB_CONTAINER_NAME: 'difyai-container'
      AZURE_BLOB_ACCOUNT_URL: 'https://<your_account_name>.blob.core.windows.net'
      # The type of vector store to use. Supported values are `weaviate`, `qdrant`, `milvus`, `relyt`.
      VECTOR_STORE: weaviate
      # The Weaviate endpoint URL. Only available when VECTOR_STORE is `weaviate`.
      WEAVIATE_ENDPOINT: http://weaviate:8080
      # The Weaviate API key.
      WEAVIATE_API_KEY: WVF5YThaHlkYwhGUSmCRgsX3tD5ngdN8pkih
      # The Qdrant endpoint URL. Only available when VECTOR_STORE is `qdrant`.
      QDRANT_URL: http://qdrant:6333
      # The Qdrant API key.
      QDRANT_API_KEY: difyai123456
      # The Qdrant clinet timeout setting.
      QDRANT_CLIENT_TIMEOUT: 20
      # The Qdrant client enable gRPC mode.
      QDRANT_GRPC_ENABLED: 'false'
      # The Qdrant server gRPC mode PORT.
      QDRANT_GRPC_PORT: 6334
      # Milvus configuration Only available when VECTOR_STORE is `milvus`.
      # The milvus host.
      MILVUS_HOST: 127.0.0.1
      # The milvus host.
      MILVUS_PORT: 19530
      # The milvus username.
      MILVUS_USER: root
      # The milvus password.
      MILVUS_PASSWORD: Milvus
      # The milvus tls switch.
      MILVUS_SECURE: 'false'
      # Mail configuration, support: resend
      MAIL_TYPE: ''
      # default send from email address, if not specified
      MAIL_DEFAULT_SEND_FROM: 'YOUR EMAIL FROM (eg: no-reply <no-reply@dify.ai>)'
      # the api-key for resend (https://resend.com)
      RESEND_API_KEY: ''
      RESEND_API_URL: https://api.resend.com
      # relyt configurations
      RELYT_HOST: db
      RELYT_PORT: 5432
      RELYT_USER: postgres
      RELYT_PASSWORD: difyai123456
      RELYT_DATABASE: postgres
      # Notion import configuration, support public and internal
      NOTION_INTEGRATION_TYPE: public
      NOTION_CLIENT_SECRET: you-client-secret
      NOTION_CLIENT_ID: you-client-id
      NOTION_INTERNAL_SECRET: you-internal-secret
    depends_on:
      - db
      - redis
    volumes:
      # Mount the storage directory to the container, for storing user files.
      - ./volumes/app/storage:/app/api/storage
 
  # Frontend web application.
  web:
    image: langgenius/dify-web:0.6.6
    restart: always
    environment:
      # The base URL of console application api server, refers to the Console base URL of WEB service if console domain is
      # different from api or web app domain.
      # example: http://cloud.dify.ai
      CONSOLE_API_URL: ''
      # The URL for Web APP api server, refers to the Web App base URL of WEB service if web app domain is different from
      # console or api domain.
      # example: http://udify.app
      APP_API_URL: ''
      # The DSN for Sentry error reporting. If not set, Sentry error reporting will be disabled.
      SENTRY_DSN: ''
    # uncomment to expose dify-web port to host
    # ports:
    #   - "3000:3000"
 
  # The postgres database.
  db:
    image: postgres:15-alpine
    restart: always
    environment:
      PGUSER: postgres
      # The password for the default postgres user.
      POSTGRES_PASSWORD: difyai123456
      # The name of the default postgres database.
      POSTGRES_DB: dify
      # postgres data directory
      PGDATA: /var/lib/postgresql/data/pgdata
    volumes:
      - ./volumes/db/data:/var/lib/postgresql/data
    # uncomment to expose db(postgresql) port to host
    # ports:
    #   - "5432:5432"
    healthcheck:
      test: [ "CMD", "pg_isready" ]
      interval: 1s
      timeout: 3s
      retries: 30
 
  # The redis cache.
  redis:
    image: redis:6-alpine
    restart: always
    volumes:
      # Mount the redis data directory to the container.
      - ./volumes/redis/data:/data
    # Set the redis password when startup redis server.
    command: redis-server --requirepass difyai123456
    healthcheck:
      test: [ "CMD", "redis-cli", "ping" ]
    # uncomment to expose redis port to host
    # ports:
    #   - "6379:6379"
 
  # The Weaviate vector store.
  weaviate:
    image: semitechnologies/weaviate:1.19.0
    restart: always
    volumes:
      # Mount the Weaviate data directory to the container.
      - ./volumes/weaviate:/var/lib/weaviate
    environment:
      # The Weaviate configurations
      # You can refer to the [Weaviate](https://weaviate.io/developers/weaviate/config-refs/env-vars) documentation for more information.
      QUERY_DEFAULTS_LIMIT: 25
      AUTHENTICATION_ANONYMOUS_ACCESS_ENABLED: 'false'
      PERSISTENCE_DATA_PATH: '/var/lib/weaviate'
      DEFAULT_VECTORIZER_MODULE: 'none'
      CLUSTER_HOSTNAME: 'node1'
      AUTHENTICATION_APIKEY_ENABLED: 'true'
      AUTHENTICATION_APIKEY_ALLOWED_KEYS: 'WVF5YThaHlkYwhGUSmCRgsX3tD5ngdN8pkih'
      AUTHENTICATION_APIKEY_USERS: 'hello@dify.ai'
      AUTHORIZATION_ADMINLIST_ENABLED: 'true'
      AUTHORIZATION_ADMINLIST_USERS: 'hello@dify.ai'
    # uncomment to expose weaviate port to host
    # ports:
    #  - "8080:8080"
 
  # The DifySandbox
  sandbox:
    image: langgenius/dify-sandbox:0.1.0
    restart: always
    cap_add:
    # Why is sys_admin permission needed?
    # https://docs.dify.ai/getting-started/install-self-hosted/install-faq#id-16.-why-is-sys_admin-permission-needed
      - SYS_ADMIN
    environment:
      # The DifySandbox configurations
      API_KEY: dify-sandbox
      GIN_MODE: release
      WORKER_TIMEOUT: 15
 
  # Qdrant vector store.
  # uncomment to use qdrant as vector store.
  # (if uncommented, you need to comment out the weaviate service above,
  # and set VECTOR_STORE to qdrant in the api & worker service.)
  # qdrant:
  #   image: langgenius/qdrant:v1.7.3
  #   restart: always
  #   volumes:
  #     - ./volumes/qdrant:/qdrant/storage
  #   environment:
  #     QDRANT_API_KEY: 'difyai123456'
  #   # uncomment to expose qdrant port to host
  #   # ports:
  #   #  - "6333:6333"
  #   #  - "6334:6334"
 
  # The nginx reverse proxy.
  # used for reverse proxying the API service and Web service.
  nginx:
    image: nginx:latest
    restart: always
    volumes:
      - ./nginx/nginx.conf:/etc/nginx/nginx.conf
      - ./nginx/proxy.conf:/etc/nginx/proxy.conf
      - ./nginx/conf.d:/etc/nginx/conf.d
      #- ./nginx/ssl:/etc/ssl
    depends_on:
      - api
      - web
    ports:
      - "80:80"
      #- "443:443"

主要包含如下几个模块及docker镜像

api：langgenius/dify-api:0.6.6
worker：langgenius/dify-api:0.6.6
web：langgenius/dify-web:0.6.6
db：postgres:15-alpine
redis：redis:6-alpine
weaviate：semitechnologies/weaviate:1.19.0
sandbox：langgenius/dify-sandbox:0.1.0
nginx：nginx:latest

docker compose一键部署安装

docker compose up -d

从dockerhub逐个pulling依赖镜像，感觉还挺爽的

等待镜像下载部署完成后，打开webui：123.123.123.123:80，默认占用80端口，可以在docker compose配置文件中更改nignx端口。

经过账号初始化等工作后，欢迎来到Dify工作界面，就是这么丝滑

3.Dify主要特色

3.1多种大语言模型集成

相较于fastGPT+oneApi的方案，集成度更高：

大模型厂商模型：仅需到大模型厂商注册账号，申请鉴权apikey，即可快速体验比较每个大模型厂商的优劣，项目还贴心的附带了每个厂商的注册跳转链接，每个厂商基本都会给几百万的token用于测试。
本地部署模型：支持Xinference，Ollama，OpenLLM，LocalAI等推理框架部署的模型一键接入
HuggingFace开源模型：只需配置APIKEY和模型名字即可接入，不过要求服务器能翻墙噢
OpenAI-API-compatible：接入兼容OpenAI规范的API，目前Xinference，OpenLLM等很多推理框架，都是直接支持OpenAI API接口规范的，但对于每家大模型厂商，一般都要设计自己的规范，可能是想构建生态，或者是与众不同？这里多说一下：对于国内互联网中小厂，如果不自建大模型，可能要试用或买入多加公司的大模型，多加大模型给多个业务部门使用，就要有一个代理平台专门计算成本，这个平台最好对业务暴露的是兼容OpenAI的API接口，如果不是的话，当接入Dify平台时，就需要包一层与OpenAI兼容的API接口。

3.2丰富工具内置+自定义工具支持

Dify内置了包含搜索引擎、天气预报、维基百科、SD等工具，同时自定义工具的配置化接入，团队成员一人接入，全组复用，高效！

3.3工作流

只需连接各个节点，既能在几分钟内快速完成AI智能体创作，且逻辑非常清晰。

3.4Agent 编排

编写提示词，导入知识库，添加工具，选择模型，运行测试，发布为API，一条龙创作！

还有很多特色，在此不再赘述了，附上一张官方的表格吧

4.总结

临下班了，本来只是想参加个话题活动，洋洋洒洒几千字。可能加入了太多感慨吧。希望感兴趣的朋友可以关注我、点赞、收藏和评论，您的鼓励是我持续码字的动力。

本文首先结合自己的工作写了一些对Agent AI智能体的见解，接着介绍了Dify框架快捷部署的过程，最后阐述了Dify框架的特点。个人认为Dify的发展会让Agent AI智能体开发提效，涌现更多有趣有价值的AI应用。

最后，写一下我对未来AI智能体发展的看法吧，从流量与用户来看，2000年-2004年，以新浪、搜狐、网易为代表的门户网站是流量入口，2004年-2014年，以百度为代表的搜索引擎是流量入口，2014-2024，以抖音、快手、微博、小红书为代表的移动互联网推荐系统是流量入口，抓住了流量入口就抓住了用户，抓住了用户就抓住了商业变现。2024-未来，极大的可能出现一家基于AI的平台型企业，通过AI智能体抓住流量，比如你要去哪玩，AI智能体在为你做出规划的过程中，夹杂酒店、航班的广告私货，你想吃什么，AI智能体夹杂着饭店的广告私货。

AI领域，乾坤未定，你我皆是黑马。

如果对AI感兴趣，可以接着看看我的其他文章：

《AI—工程篇》

AI智能体研发之路-工程篇（一）：Docker助力AI智能体开发提效

AI智能体研发之路-工程篇（二）：Dify智能体开发平台一键部署

AI智能体研发之路-工程篇（三）：大模型推理服务框架Ollama一键部署

AI智能体研发之路-工程篇（四）：大模型推理服务框架Xinference一键部署

AI智能体研发之路-工程篇（五）：大模型推理服务框架LocalAI一键部署

《AI—模型篇》

AI智能体研发之路-模型篇（一）：大模型训练框架LLaMA-Factory在国内网络环境下的安装、部署及使用

AI智能体研发之路-模型篇（二）：DeepSeek-V2-Chat 训练与推理实战

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