"""Configure backend settings for the backend application.""" from pathlib import Path from pydantic import Field from pydantic_settings import BaseSettings, SettingsConfigDict from functools import lru_cache # Keep configuration setup explicit so runtime behavior is easy to reason about. ROOT_DIR = Path(__file__).resolve().parents[3] ROOT_ENV_FILES = ( ROOT_DIR / ".env", ROOT_DIR / ".env.development", ) class Settings(BaseSettings): """Define configuration for settings.""" model_config = SettingsConfigDict( env_file=tuple(str(env_file) for env_file in ROOT_ENV_FILES), env_file_encoding="utf-8", extra="ignore", ) # Keep configuration setup explicit so runtime behavior is easy to reason about. app_name: str = Field(default="AI Regulations Demo", description="Application name") app_version: str = Field(default="0.1.0", description="应用版本") debug: bool = Field(default=False, description="调试模式") # Keep configuration setup explicit so runtime behavior is easy to reason about. milvus_host: str = Field(default="6.86.80.8", description="Milvus服务地址") milvus_port: int = Field(default=19530, description="Milvus服务端口") milvus_collection: str = Field(default="regulations_dense_1024_v2", description="法规向量集合名称") milvus_db_name: str = Field(default="default", description="Milvus数据库名称") # Keep configuration setup explicit so runtime behavior is easy to reason about. embedding_model: str = Field(default="text-embedding-v3", description="嵌入模型名称") embedding_dim: int = Field(default=1024, description="嵌入向量维度") embedding_api_key: str = Field(default="", description="Embedding API密钥") embedding_base_url: str = Field(default="http://6.86.80.4:30080/v1", description="Embedding API地址") embedding_timeout_seconds: int = Field(default=120, description="Embedding API超时时间(秒)") alibaba_access_key_id: str = Field(default="", description="阿里云文档解析 Access Key ID") alibaba_access_key_secret: str = Field(default="", description="阿里云文档解析 Access Key Secret") alibaba_endpoint: str = Field(default="docmind-api.cn-hangzhou.aliyuncs.com", description="阿里云文档解析 endpoint") aliyun_parse_poll_interval_seconds: int = Field(default=5, description="阿里云文档解析轮询间隔(秒)") aliyun_parse_timeout_seconds: int = Field(default=900, description="阿里云文档解析超时时间(秒)") aliyun_parse_layout_step_size: int = Field(default=50, description="阿里云文档解析分页步长") aliyun_llm_enhancement: bool = Field(default=True, description="是否启用阿里云解析增强") aliyun_enhancement_mode: str = Field(default="VLM", description="阿里云解析增强模式") document_parse_artifact_prefix: str = Field(default="artifacts", description="解析产物对象前缀") parser_failure_mode: str = Field(default="fail", description="解析失败策略") # Keep configuration setup explicit so runtime behavior is easy to reason about. minio_endpoint: str = Field(default="6.86.80.8:9000", description="MinIO服务地址") minio_access_key: str = Field(default="minioadmin", description="MinIO访问密钥") minio_secret_key: str = Field(default="minioadmin123", description="MinIO秘密密钥") minio_bucket: str = Field(default="upload-files", description="文档存储桶名称") minio_secure: bool = Field(default=False, description="是否使用HTTPS") # Keep configuration setup explicit so runtime behavior is easy to reason about. redis_host: str = Field(default="6.86.80.8", description="Redis服务地址") redis_port: int = Field(default=6379, description="Redis服务端口") redis_password: str = Field(default="", description="Redis密码") redis_db: int = Field(default=0, description="Redis数据库编号") # Keep configuration setup explicit so runtime behavior is easy to reason about. postgres_host: str = Field(default="6.86.80.8", description="PostgreSQL服务地址") postgres_port: int = Field(default=5432, description="PostgreSQL服务端口") postgres_user: str = Field(default="compliance", description="PostgreSQL用户名") postgres_password: str = Field(default="compliance123", description="PostgreSQL密码") postgres_db: str = Field(default="compliance_db", description="PostgreSQL数据库名称") # Keep configuration setup explicit so runtime behavior is easy to reason about. chunk_size: int = Field(default=512, description="分块大小（字符数）") chunk_overlap: int = Field(default=50, description="分块重叠大小") max_file_size_mb: int = Field(default=100, description="最大文件大小(MB)") document_metadata_path: str = Field(default="backend/data/documents.json", description="文档元数据存储路径") document_processing_metadata_path: str = Field(default="backend/data/document_processing.json", description="文档处理历史存储路径") parser_backend: str = Field(default="aliyun", description="解析后端(local/aliyun)") chunk_backend: str = Field(default="aliyun", description="分块后端(local/aliyun)") document_repository_backend: str = Field(default="json", description="文档元数据存储后端 (json/postgres)") # When True, document processing is enqueued to Celery workers via Redis. # When False (default), processing runs in a FastAPI BackgroundTask in the same process — # no external worker needed. Switch to True only when a Celery worker is running. use_celery_worker: bool = Field(default=False, description="使用 Celery Worker 异步处理文档 (需要 Worker 运行中)") # ── Perception crawl ────────────────────────────────────────────────────── perception_crawl_timeout_seconds: int = Field( default=120, description="HTTP timeout for regulatory source crawlers." ) perception_max_events_per_source: int = Field( default=100, description="Maximum events fetched per source per crawl run." ) perception_diff_similarity_threshold: float = Field( default=0.85, description="Cosine similarity below which a paragraph is flagged as changed.", ) # Keep configuration setup explicit so runtime behavior is easy to reason about. api_host: str = Field(default="0.0.0.0", description="API服务地址") api_port: int = Field(default=8000, description="API服务端口") # Keep configuration setup explicit so runtime behavior is easy to reason about. llm_provider: str = Field(default="deepseek", description="LLM提供商 (deepseek/qwen/qwen_vl)") llm_model: str = Field(default="deepseek-v4-flash", description="LLM模型名称") llm_max_tokens: int = Field(default=4096, description="LLM最大输出token数") llm_temperature: float = Field(default=0.7, description="LLM温度参数") # Keep configuration setup explicit so runtime behavior is easy to reason about. deepseek_api_key: str = Field(default="", description="DeepSeek API密钥") deepseek_base_url: str = Field(default="http://6.86.80.4:30080/v1", description="DeepSeek API地址") deepseek_model: str = Field(default="deepseek-v4-flash", description="DeepSeek模型") # Keep configuration setup explicit so runtime behavior is easy to reason about. qwen_api_key: str = Field(default="", description="Qwen API密钥") qwen_base_url: str = Field(default="http://6.86.80.4:30080/v1", description="Qwen API地址") qwen_model: str = Field(default="qwen3.5-flash", description="Qwen文本模型") qwen_vl_model: str = Field(default="qwen3-vl-plus", description="Qwen视觉模型") # Keep configuration setup explicit so runtime behavior is easy to reason about. rag_top_k: int = Field(default=5, description="检索召回数量") rag_retrieval_top_k: int = Field(default=20, description="精排前召回候选数量（reranker 启用时生效）") rag_max_context_tokens: int = Field(default=2000, description="RAG最大上下文token数") rag_summary_max_tokens: int = Field(default=10240, description="文档摘要最大token数") rag_skills_max_tokens: int = Field(default=2048, description="技能类 RAG 最大 token 数") reranker_enabled: bool = Field(default=False, description="是否启用 Cross-Encoder 精排") reranker_base_url: str = Field(default="", description="Reranker API 地址") reranker_model: str = Field(default="BAAI/bge-reranker-v2-m3", description="Reranker 模型名称") reranker_api_key: str = Field(default="", description="Reranker API 密钥") reranker_top_k: int = Field(default=5, description="精排后保留的最终结果数量") # Keep configuration setup explicit so runtime behavior is easy to reason about. milvus_index_type: str = Field(default="IVF_FLAT", description="Milvus索引类型") milvus_nlist: int = Field(default=128, description="Milvus nlist参数") milvus_nprobe: int = Field(default=16, description="Milvus nprobe参数") # Keep configuration setup explicit so runtime behavior is easy to reason about. session_max_sessions: int = Field(default=100, description="最大会话数量") session_timeout_minutes: int = Field(default=30, description="会话超时时间(分钟)") session_backend: str = Field( default="memory", description="会话存储后端 (memory | redis)。redis 需要 Redis 可用。", ) # ── Auth ────────────────────────────────────────────────────────────────── # Generate a strong secret: python -c "import secrets; print(secrets.token_hex(32))" auth_secret_key: str = Field( default="change-me-in-production-must-be-32-or-more-characters-long", description="JWT signing secret. MUST be changed in production.", ) auth_algorithm: str = Field(default="HS256", description="JWT signing algorithm.") auth_token_expire_minutes: int = Field(default=480, description="JWT TTL in minutes (default 8 hours).") auth_enabled: bool = Field(default=True, description="Set False to bypass auth (development only).") # ── CORS ────────────────────────────────────────────────────────────────── cors_allow_origins: str = Field( default="http://localhost:5173", description="Comma-separated allowed CORS origins. Never use * in production.", ) @lru_cache def get_settings() -> Settings: """Return settings.""" return Settings() # Keep configuration setup explicit so runtime behavior is easy to reason about. settings = get_settings()