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RAG Document Server

by jaimeferj
settings.py1.53 kB
"""Application settings and configuration.""" from pydantic_settings import BaseSettings, SettingsConfigDict class Settings(BaseSettings): """Application settings loaded from environment variables.""" # Google AI Studio API Key google_api_key: str # RAG Configuration chunk_size: int = 1000 chunk_overlap: int = 200 top_k_results: int = 5 # Qdrant Configuration use_qdrant_server: bool = True qdrant_url: str = "http://localhost:6333" qdrant_path: str = "./qdrant_storage" qdrant_collection_name: str = "documents" # Server Configuration fastapi_host: str = "0.0.0.0" fastapi_port: int = 8000 # Google AI Models embedding_model: str = "text-embedding-004" llm_model: str = "gemini-1.5-flash" # Rate Limiting Configuration google_api_rpm_limit: int = 15 # Requests per minute google_api_tpm_limit: int = 250000 # Tokens per minute google_api_rpd_limit: int = 1000 # Requests per day rate_limit_db_path: str = "./rate_limits.db" # Dagster Repository dagster_repo_path: str = "/home/ubuntu/dagster" # Code Index code_index_path: str = "./code_index.db" enable_code_index: bool = True # OpenAI-Compatible API enable_openai_api: bool = True openai_api_key: str = "" # Optional API key for authentication model_config = SettingsConfigDict( env_file=".env", env_file_encoding="utf-8", case_sensitive=False, ) # Global settings instance settings = Settings()

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