.env.example

# --- App ---
APP_HOST=0.0.0.0
APP_PORT=8000

# --- Auth (local JWT — see the advanced tier for Azure AD SSO on top of this) ---
JWT_SECRET=change-me-before-deploying
JWT_ALGORITHM=HS256
JWT_EXPIRY_MINUTES=480

# --- Storage ---
DATA_DIR=./data
SQLITE_PATH=./data/app.sqlite3

# --- Vector store: "faiss" or "chroma" — see api/utils/README.md for when to pick which ---
VECTOR_STORE=chroma
FAISS_INDEX_DIR=./data/faiss
CHROMA_DIR=./data/chroma

# --- Chunking ---
CHUNK_SIZE=1000
CHUNK_OVERLAP=150
RETRIEVAL_TOP_K=5

# --- Embeddings: "local" (offline) or "huggingface" (HF Inference API) ---
EMBEDDING_PROVIDER=local
# Must match your embedding model's output dimension (all-MiniLM-L6-v2 = 384).
# Only used by the FAISS store, to size the index. Update this if you change models.
EMBEDDING_DIM=384
LOCAL_EMBEDDING_MODEL=all-MiniLM-L6-v2
HF_EMBEDDING_MODEL=sentence-transformers/all-MiniLM-L6-v2
HF_API_TOKEN=

# --- LLM generation: "openai" or "bedrock" ---
LLM_PROVIDER=openai
OPENAI_API_KEY=
OPENAI_MODEL=gpt-4o-mini
AWS_REGION=us-east-1
BEDROCK_MODEL_ID=

# --- Uploads ---
ALLOWED_EXTENSIONS=.pdf,.txt,.md,.docx