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| """ | |
| DocuMind AI — Centralized Configuration | |
| Loads all settings from environment variables via .env file. | |
| """ | |
| from dotenv import load_dotenv | |
| load_dotenv() | |
| from pydantic import field_validator | |
| from pydantic_settings import BaseSettings, SettingsConfigDict | |
| from pathlib import Path | |
| class Settings(BaseSettings): | |
| """All application settings — loaded from .env file.""" | |
| model_config = SettingsConfigDict(env_file=".env", env_file_encoding="utf-8", case_sensitive=False) | |
| # ── LLM ─────────────────────────────────────────────────────────────────── | |
| GROQ_API_KEY: str = "" | |
| llm_model: str = "openai/gpt-oss-20b" | |
| # Reasoning models spend part of this budget on hidden thinking, so keep it generous. | |
| llm_max_tokens: int = 4096 | |
| # ── Embeddings ──────────────────────────────────────────────────────────── | |
| embedding_model: str = "all-MiniLM-L6-v2" | |
| # ── Storage paths ───────────────────────────────────────────────────────── | |
| vectorstore_path: str = "./data/vectorstore" | |
| upload_folder: str = "./data/uploads" | |
| # ── Chunking ────────────────────────────────────────────────────────────── | |
| # all-MiniLM-L6-v2 reads at most 256 tokens, so keep chunks safely below that. | |
| chunk_size: int = 200 | |
| chunk_overlap: int = 30 | |
| chunk_unit: str = "tokens" | |
| # ── Retrieval ───────────────────────────────────────────────────────────── | |
| top_k_results: int = 5 | |
| retrieval_threshold: float = 0.20 | |
| grounding_overlap_threshold: float = 0.30 | |
| # "faiss": FAISS does the similarity search (Chroma stores text + metadata). | |
| # "chroma": Chroma's own HNSW index does the search. Falls back to chroma if faiss-cpu is missing. | |
| vector_backend: str = "faiss" | |
| hybrid_search: bool = False | |
| enable_rerank: bool = False | |
| enable_faithfulness_check: bool = False | |
| api_key: str = "" | |
| allowed_origins: str = "http://localhost:8000" | |
| torch_threads: int = 1 | |
| # ── API ─────────────────────────────────────────────────────────────────── | |
| host: str = "0.0.0.0" | |
| port: int = 8000 | |
| debug: bool = False | |
| def _ignore_placeholder_keys(cls, value): | |
| """Treat template values such as 'replace_with_your_key' as 'not configured'.""" | |
| if isinstance(value, str) and value.strip().lower().startswith("replace_with"): | |
| return "" | |
| return value.strip() if isinstance(value, str) else value | |
| def _check_vector_backend(cls, value): | |
| value = str(value).strip().lower() | |
| if value not in {"faiss", "chroma"}: | |
| raise ValueError("VECTOR_BACKEND must be 'faiss' or 'chroma'") | |
| return value | |
| def cors_origins(self) -> list[str]: | |
| return [origin.strip() for origin in self.allowed_origins.split(",") if origin.strip()] | |
| # ── App Meta ────────────────────────────────────────────────────────────── | |
| app_name: str = "DocuMind AI" | |
| app_version: str = "1.0.0" | |
| app_description: str = "RAG-powered document intelligence system" | |
| def ensure_directories(self): | |
| """Create required directories if they don't exist.""" | |
| Path(self.vectorstore_path).mkdir(parents=True, exist_ok=True) | |
| Path(self.upload_folder).mkdir(parents=True, exist_ok=True) | |
| # Singleton instance — import this everywhere | |
| settings = Settings() | |
| settings.ensure_directories() | |