服务相关配置文件
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@@ -6,17 +6,58 @@ x-kong-config:
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KONG_PG_DATABASE: kong
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KONG_PG_USER: postgres
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KONG_PG_PASSWORD: 123456
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services:
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fastapi2:
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build: # 在本文件所在目录运行构建 docker compose build --no-cache
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context: ../../
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dockerfile: ./bbit_ai/docker/Dockerfiledev # 开发版 Dockerfile
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container_name: fastapi-dev
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pybackend:
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# 因为每次build都会用缓存 调试起来极不方便,所以索性在外部先构建 在这里直接运行镜像
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# build: # 在本文件所在目录运行构建 docker compose build --no-cache
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# context: ../../bbit_ai/
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# dockerfile: ./Dockerfile_ai_lab # 开发版 Dockerfile
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container_name: ce_pybackend
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image: ce_pybackend:latest
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ports:
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- "13011:13011"
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volumes: # 在本文件所在目录运行
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- ../../bbit_ai/app:/app # 挂载本地代码,实现热更新
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- ../../bbit_ai/docker/:/root/.local/pyzxing # 挂载 jar
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- ./config/bot:/app/data # 配置文件目录
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networks:
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- ce_network
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depends_on:
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- milvus
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bot_server:
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# build: # 在本文件所在目录运行构建 docker compose build --no-cache
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# context: ../../bbit_ai/
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# dockerfile: ./Dockerfile_bot_server
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container_name: ce_bot_server
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image: ce_bot_server:latest
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ports:
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# ws服务端
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- "8000:8000"
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# http服务的端口,用于简单OTA接口(单服务部署),以及视觉分析接口
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- "8003:8003"
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volumes: # 在本文件所在目录运行
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- ../../bbit_ai/app_bot:/app # 挂载本地代码,实现热更新
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# 配置文件目录
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- ./config/bot:/app/data
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# 模型文件挂接,很重要
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- ./config/models/SenseVoiceSmall/model.pt:/app/models/SenseVoiceSmall/model.pt
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networks:
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- ce_network
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bot_mcp:
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# build: # 在本文件所在目录运行构建 docker compose build --no-cache
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# context: ../../bbit_ai/
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# dockerfile: ./Dockerfile_bot_mcp
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image: ce_bot_mcp:latest
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container_name: ce_bot_mcp
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ports:
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- "8004:8004"
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volumes: # 在本文件所在目录运行
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- ../../bbit_ai/app_mcp:/app
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# 配置文件目录
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- ./config/bot:/app/data
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networks:
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- ce_network
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