.env.example

# ──────────────────────────────────────────────────────────────────────────────
# GraphRAG – environment variables
# Copy this file to .env and fill in the values. Never commit .env to git.
# ──────────────────────────────────────────────────────────────────────────────

# PostgreSQL credentials (required)
POSTGRES_PASSWORD=changeme_strong_password

# PostgreSQL connection (defaults match docker-compose service names)
POSTGRES_HOST=postgres
POSTGRES_PORT=5432
POSTGRES_DB=graphrag
POSTGRES_USER=graphrag

# Embedding model (HuggingFace model ID)
# BAAI/bge-m3 → 1024-dim, multilingual (100+ languages incl. German)
# Change here AND update vector(1024) in 02_schema.sql if using a different model
EMBEDDING_MODEL=BAAI/bge-m3
EMBEDDING_DEVICE=cuda          # set to "cpu" if no GPU is available
EMBEDDING_BATCH_SIZE=16
EMBEDDING_PRECISION=fp16       # "fp16" halves VRAM usage; use "fp32" if you see NaN embeddings

# Watched docs folder (inside the container; mapped via volume)
DOCS_PATH=/docs
WATCH_RECURSIVE=true

# MCP server
MCP_HOST=0.0.0.0
MCP_PORT=8000
SEARCH_TOP_K=10
SEARCH_MIN_SCORE=0.0

# Docker image tag used in docker-compose.yml when pulling pre-built images
IMAGE_TAG=latest

# Set to your GitHub org/repo for GHCR image names — must be all lowercase
# e.g. for github.com/MyOrg/MyRepo use: myorg/myrepo
GITHUB_REPOSITORY=yourorg/yourrepo

# Optional: HuggingFace cache directory on the host (avoids re-downloading)
# Mount this path as a volume in docker-compose.override.yml if desired
# HF_HOME=/path/to/hf_cache

# ── Enricher (run manually: docker compose exec watcher python -m graphrag.enricher) ──
# OpenAI-compatible endpoint — LiteLLM proxy, vLLM, Ollama, LM Studio, …
ENRICHER_BASE_URL=http://localhost:4000/v1
ENRICHER_API_KEY=dummy
ENRICHER_MODEL=mistral/mistral-small-24b
ENRICHER_CONCURRENCY=4
SIMILAR_TO_THRESHOLD=0.82
SIMILAR_TO_MAX_PER_CHUNK=5