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构建并部署 AI Agent 服务 / deploy (push) Has been cancelled
问题： - 没有指定 env_file，导致无法读取 docker/.env 文件 - DB_PASSWORD 被硬编码了 修复： - 添加 env_file: .env 配置 - DB_PASSWORD 改为从环境变量读取
106 lines
4.3 KiB
YAML
106 lines
4.3 KiB
YAML
services:
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backend:
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build:
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context: .. # 构建上下文为项目根目录
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dockerfile: docker/backend/Dockerfile
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container_name: ai-backend
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env_file:
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- .env # 读取 docker/.env 文件
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environment:
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# =========================================================================
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# ⭐ 敏感密钥配置 - 必须配置（本地：.env 文件 | CI/CD：Secrets）
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# =========================================================================
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- ZHIPUAI_API_KEY=${ZHIPUAI_API_KEY} # ⭐ 敏感密钥配置
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- DEEPSEEK_API_KEY=${DEEPSEEK_API_KEY} # ⭐ 敏感密钥配置
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- LLAMACPP_API_KEY=${LLAMACPP_API_KEY} # ⭐ 敏感密钥配置
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# =========================================================================
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# PostgreSQL 数据库配置
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# =========================================================================
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- DB_HOST=${DB_HOST}
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- DB_PORT=${DB_PORT}
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- DB_USER=${DB_USER}
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- DB_PASSWORD=${DB_PASSWORD}
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- DB_NAME=${DB_NAME}
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- DB_URI=${DB_URI}
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# =========================================================================
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# Qdrant 向量数据库配置（URL + API密钥 配对）
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# =========================================================================
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- QDRANT_URL=http://115.190.121.151:6333
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- QDRANT_API_KEY=${QDRANT_API_KEY:?请配置 QDRANT_API_KEY（本地：.env 文件 | CI/CD：Secrets）} # ⭐ 敏感密钥配置
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- QDRANT_COLLECTION_NAME=mem0_user_memories
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# =========================================================================
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# llama.cpp 服务配置（URL + API密钥 配对）
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# =========================================================================
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# 主 LLM 服务 (Gemma-4-E2B GGUF) - Docker host 端口 18000
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- VLLM_BASE_URL=http://host.docker.internal:18000/v1
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# Embedding 服务 (Qwen3-Embedding-0.6B GGUF) - Docker host 端口 18001
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- LLAMACPP_EMBEDDING_URL=http://host.docker.internal:18001/v1
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# Reranker 服务 (bge-reranker-v2-m3) - Docker host 端口 18002
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- LLAMACPP_RERANKER_URL=http://host.docker.internal:18002/v1
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# =========================================================================
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# RAG 索引构建配置（非敏感）
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# =========================================================================
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- RAG_COLLECTION_NAME=rag_documents
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- RAG_CHUNK_SIZE=500
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- RAG_CHUNK_OVERLAP=50
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- RAG_PARENT_CHUNK_SIZE=1000
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- RAG_CHILD_CHUNK_SIZE=200
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- RAG_PARENT_CHUNK_OVERLAP=100
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- RAG_CHILD_CHUNK_OVERLAP=20
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- RAG_STRATEGY=parent-child
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- RAG_STORAGE_TYPE=postgres
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# =========================================================================
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# 日志调试配置（可通过 .env 覆盖）
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# =========================================================================
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- LOG_LEVEL=${LOG_LEVEL:-WARNING}
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- DEBUG=${DEBUG:-false}
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- ENABLE_GRAPH_TRACE=${ENABLE_GRAPH_TRACE:-false}
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# =========================================================================
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# 应用行为配置
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# =========================================================================
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- BACKEND_PORT=8079
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- MEMORY_SUMMARIZE_INTERVAL=${MEMORY_SUMMARIZE_INTERVAL:-10}
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# =========================================================================
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# 前端通信地址（Docker 内部网络）
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# =========================================================================
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- API_URL=http://backend:8079/chat
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volumes:
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- ../data/user_docs:/app/data/user_docs # 挂载文档目录
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- ../logs:/app/logs
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networks:
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- ai-network
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# ⭐ 移除对 postgres 和 qdrant 的依赖（使用远程服务）
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restart: unless-stopped
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ports:
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- "8079:8079"
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frontend:
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build:
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context: ..
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dockerfile: docker/frontend/Dockerfile
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container_name: ai-frontend
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environment:
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# Docker 内部网络使用服务名 'backend' 解析后端服务
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- API_URL=http://backend:8079/chat
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# volumes:
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# - ../frontend/src:/app/src # 挂载源代码目录，修改立即生效
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ports:
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- "8501:8501"
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networks:
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- ai-network
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depends_on:
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- backend
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restart: unless-stopped
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networks:
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ai-network:
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driver: bridge
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