init. project

rag-web-ui/backend/app/core/config.py

@@ -0,0 +1,123 @@
+import os
+from typing import List, Optional
+
+from pydantic_settings import BaseSettings
+
+
+class Settings(BaseSettings):
+    PROJECT_NAME: str = "RAG Web UI"  # Project name
+    VERSION: str = "0.1.0"  # Project version
+    API_V1_STR: str = "/api"  # API version string
+
+    # MySQL settings
+    MYSQL_SERVER: str = os.getenv("MYSQL_SERVER", "localhost")
+    MYSQL_PORT: int = int(os.getenv("MYSQL_PORT", "3306"))
+    MYSQL_USER: str = os.getenv("MYSQL_USER", "ragagent")
+    MYSQL_PASSWORD: str = os.getenv("MYSQL_PASSWORD", "ragagent")
+    MYSQL_DATABASE: str = os.getenv("MYSQL_DATABASE", "ragagent")
+    SQLALCHEMY_DATABASE_URI: Optional[str] = None
+
+    @property
+    def get_database_url(self) -> str:
+        if self.SQLALCHEMY_DATABASE_URI:
+            return self.SQLALCHEMY_DATABASE_URI
+        return (
+            f"mysql+mysqlconnector://{self.MYSQL_USER}:{self.MYSQL_PASSWORD}"
+            f"@{self.MYSQL_SERVER}:{self.MYSQL_PORT}/{self.MYSQL_DATABASE}"
+        )
+
+    # JWT settings
+    SECRET_KEY: str = os.getenv("SECRET_KEY", "your-secret-key-here")
+    ALGORITHM: str = "HS256"
+    ACCESS_TOKEN_EXPIRE_MINUTES: int = int(os.getenv("ACCESS_TOKEN_EXPIRE_MINUTES", "10080"))
+
+    # Chat Provider settings
+    CHAT_PROVIDER: str = os.getenv("CHAT_PROVIDER", "openai")
+
+    # Embeddings settings
+    EMBEDDINGS_PROVIDER: str = os.getenv("EMBEDDINGS_PROVIDER", "openai")
+
+    # MinIO settings
+    MINIO_ENDPOINT: str = os.getenv("MINIO_ENDPOINT", "localhost:9000")
+    MINIO_ACCESS_KEY: str = os.getenv("MINIO_ACCESS_KEY", "minioadmin")
+    MINIO_SECRET_KEY: str = os.getenv("MINIO_SECRET_KEY", "minioadmin")
+    MINIO_BUCKET_NAME: str = os.getenv("MINIO_BUCKET_NAME", "documents")
+
+    # Shared model API key fallback
+    API_KEY: str = os.getenv("API_KEY", "")
+
+    # OpenAI settings
+    OPENAI_API_BASE: str = os.getenv("OPENAI_API_BASE", "https://api.openai.com/v1")
+    OPENAI_API_KEY: str = os.getenv(
+        "OPENAI_API_KEY", os.getenv("API_KEY", "your-openai-api-key-here")
+    )
+    OPENAI_MODEL: str = os.getenv("OPENAI_MODEL", "gpt-4")
+    OPENAI_EMBEDDINGS_MODEL: str = os.getenv("OPENAI_EMBEDDINGS_MODEL", "text-embedding-ada-002")
+
+    # DashScope settings
+    DASH_SCOPE_API_KEY: str = os.getenv(
+        "DASH_SCOPE_API_KEY",
+        os.getenv("DASHSCOPE_API_KEY", os.getenv("API_KEY", "")),
+    )
+    DASH_SCOPE_API_BASE: str = os.getenv(
+        "DASH_SCOPE_API_BASE", "https://dashscope.aliyuncs.com/compatible-mode/v1"
+    )
+    DASH_SCOPE_CHAT_MODEL: str = os.getenv("DASH_SCOPE_CHAT_MODEL", "qwen3-max")
+    DASH_SCOPE_EMBEDDINGS_MODEL: str = os.getenv("DASH_SCOPE_EMBEDDINGS_MODEL", "")
+
+    # Vector Store settings
+    VECTOR_STORE_TYPE: str = os.getenv("VECTOR_STORE_TYPE", "chroma")
+
+    # External reranker settings
+    RERANKER_API_URL: str = os.getenv("RERANKER_API_URL", "")
+    RERANKER_API_KEY: str = os.getenv(
+        "RERANKER_API_KEY",
+        os.getenv(
+            "DASH_SCOPE_API_KEY",
+            os.getenv("DASHSCOPE_API_KEY", os.getenv("API_KEY", "")),
+        ),
+    )
+    RERANKER_MODEL: str = os.getenv("RERANKER_MODEL", "")
+    RERANKER_TIMEOUT_SECONDS: float = float(os.getenv("RERANKER_TIMEOUT_SECONDS", "8"))
+    RERANKER_WEIGHT: float = float(os.getenv("RERANKER_WEIGHT", "0.75"))
+
+    # GraphRAG settings
+    GRAPHRAG_ENABLED: bool = os.getenv("GRAPHRAG_ENABLED", "false").lower() == "true"
+    GRAPHRAG_WORKING_DIR: str = os.getenv("GRAPHRAG_WORKING_DIR", "./graphrag_cache")
+    GRAPHRAG_GRAPH_STORAGE: str = os.getenv("GRAPHRAG_GRAPH_STORAGE", "neo4j")
+    GRAPHRAG_QUERY_LEVEL: int = int(os.getenv("GRAPHRAG_QUERY_LEVEL", "2"))
+    GRAPHRAG_LOCAL_TOP_K: int = int(os.getenv("GRAPHRAG_LOCAL_TOP_K", "20"))
+    GRAPHRAG_ENTITY_EXTRACT_MAX_GLEANING: int = int(os.getenv("GRAPHRAG_ENTITY_EXTRACT_MAX_GLEANING", "1"))
+    GRAPHRAG_EMBEDDING_DIM: int = int(os.getenv("GRAPHRAG_EMBEDDING_DIM", "1024"))
+    GRAPHRAG_EMBEDDING_MAX_TOKEN_SIZE: int = int(os.getenv("GRAPHRAG_EMBEDDING_MAX_TOKEN_SIZE", "8192"))
+
+    # Neo4j settings
+    NEO4J_URL: str = os.getenv("NEO4J_URL", "bolt://localhost:7687")
+    NEO4J_USERNAME: str = os.getenv("NEO4J_USERNAME", "neo4j")
+    NEO4J_PASSWORD: str = os.getenv("NEO4J_PASSWORD", "neo4j")
+
+    # Chroma DB settings
+    CHROMA_DB_HOST: str = os.getenv("CHROMA_DB_HOST", "chromadb")
+    CHROMA_DB_PORT: int = int(os.getenv("CHROMA_DB_PORT", "8000"))
+
+    # Qdrant DB settings
+    QDRANT_URL: str = os.getenv("QDRANT_URL", "http://localhost:6333")
+    QDRANT_PREFER_GRPC: bool = os.getenv("QDRANT_PREFER_GRPC", "true").lower() == "true"
+
+    # Deepseek settings
+    DEEPSEEK_API_KEY: str = ""
+    DEEPSEEK_API_BASE: str = "https://api.deepseek.com/v1"  # 默认 API 地址
+    DEEPSEEK_MODEL: str = "deepseek-chat"  # 默认模型名称
+
+    # Ollama settings
+    OLLAMA_API_BASE: str = "http://localhost:11434"
+    OLLAMA_MODEL: str = "deepseek-r1:7b"
+    OLLAMA_EMBEDDINGS_MODEL: str = os.getenv(
+        "OLLAMA_EMBEDDINGS_MODEL", "nomic-embed-text"
+    )  # Added this line
+
+    class Config:
+        env_file = ".env"
+
+
+settings = Settings()