51 lines
1.8 KiB
Python
51 lines
1.8 KiB
Python
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"""
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环境变量集中管理模块
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所有配置项统一定义，避免散落在各个文件中
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"""
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import os
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# ========== Graph 执行追踪配置 ==========
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# 是否启用 Graph 流转追踪（通过环境变量控制）
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ENABLE_GRAPH_TRACE = os.getenv("ENABLE_GRAPH_TRACE", "true").lower() == "true"
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# ========== 记忆提取配置 ==========
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# 记忆提取间隔：每 N 轮对话生成一次摘要
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MEMORY_SUMMARIZE_INTERVAL = int(os.getenv("MEMORY_SUMMARIZE_INTERVAL", "10"))
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# ========== Mem0 记忆层配置 ==========
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# Qdrant 向量数据库地址
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QDRANT_URL = os.getenv("QDRANT_URL", "http://127.0.0.1:6333")
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QDRANT_COLLECTION_NAME = os.getenv("QDRANT_COLLECTION_NAME", "mem0_user_memories")
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QDRANT_API_KEY = os.getenv("QDRANT_API_KEY", "your-qdrant-api-key")
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# ========== llm 配置 ==========
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# LLM 模型配置
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VLLM_BASE_URL = os.getenv("VLLM_BASE_URL", "http://127.0.0.1:8081/v1")
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LLM_API_KEY = os.getenv("LLM_API_KEY", "your-ai-api-key")
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# llama.cpp Embedding 服务地址 (用于 Mem0 的向量化)
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LLAMACPP_EMBEDDING_URL = os.getenv("LLAMACPP_EMBEDDING_URL", "http://127.0.0.1:8082/v1")
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LLAMACPP_API_KEY = os.getenv("LLAMACPP_API_KEY", "your-llamacpp-api-key")
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# ========== 后端服务配置 ==========
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# 数据库连接字符串
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DB_URI = os.getenv(
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"DB_URI",
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"postgresql://postgres:huang1998@ai-postgres:5432/langgraph_db?sslmode=disable"
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)
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# 后端服务端口
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BACKEND_PORT = int(os.getenv("BACKEND_PORT", "8079"))
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# ========== 日志配置 ==========
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LOG_LEVEL = os.getenv("LOG_LEVEL", "INFO").upper()
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DEBUG = os.getenv("DEBUG", "false").lower() == "true"
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# ========== Reranker 服务配置 ==========
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LLAMACPP_RERANKER_URL = os.getenv("LLAMACPP_RERANKER_URL", "http://127.0.0.1:8083")
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# ========== 第三方 API 密钥 ==========
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ZHIPUAI_API_KEY = os.getenv("ZHIPUAI_API_KEY", "")
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DEEPSEEK_API_KEY = os.getenv("DEEPSEEK_API_KEY", "")
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