# ===== LLM Configuration =====
# Any OpenAI-compatible API is supported
LLM_API_KEY=your_api_key_here
LLM_BASE_URL=https://dashscope.aliyuncs.com/compatible-mode/v1
LLM_MODEL_NAME=qwen-plus

# --- Gemini (Google AI Studio) ---
# Set LLM_PROVIDER=gemini to auto-configure the Google AI Studio endpoint.
# Get a free API key at: https://aistudio.google.com/
# LLM_PROVIDER=gemini
# LLM_API_KEY=AIza...
# LLM_MODEL_NAME=gemini-3.1-flash-lite-preview

# ===== Graph Backend =====
# GRAPH_BACKEND=zep      (default) — Zep Cloud managed memory graph
# GRAPH_BACKEND=graphiti — Self-hosted Neo4j + Graphiti (requires graphiti extras)
GRAPH_BACKEND=zep

# --- Zep Cloud (default backend) ---
# Free tier available: https://app.getzep.com/
ZEP_API_KEY=your_zep_api_key_here

# --- Graphiti + Neo4j (alternative backend) ---
# Install extras: pip install "mirofish-backend[graphiti]"
# NEO4J_URI=bolt://localhost:7687
# NEO4J_USER=neo4j
# NEO4J_PASSWORD=your_neo4j_password_here
# GRAPHITI_BATCH_SIZE=10  # chunks per bulk call; higher = faster but more LLM parallelism

# --- Embedding LLM (used by Graphiti for vector indexing) ---
# Falls back to LLM_API_KEY / LLM_BASE_URL if not set.
# Use a dedicated embedding deployment when your LLM_BASE_URL points to a generative model.
# LLM_EMBED_API_KEY=your_embed_api_key_here
# LLM_EMBED_BASE_URL=https://<resource>.cognitiveservices.azure.com/openai/deployments/<embed-deployment>/embeddings?api-version=2024-05-01-preview
# LLM_EMBED_MODEL_NAME=text-embedding-3-small

# --- Small/fast LLM (used by Graphiti for reranking and lightweight tasks) ---
# Falls back to LLM_API_KEY / LLM_BASE_URL / LLM_MODEL_NAME if not set.
# Use a cheaper model (e.g. gpt-4o-mini, gpt-5-mini) to reduce costs.
# LLM_SMALL_API_KEY=your_small_api_key_here
# LLM_SMALL_BASE_URL=https://<resource>.cognitiveservices.azure.com/openai/deployments/<small-model>/chat/completions?api-version=2024-05-01-preview
# LLM_SMALL_MODEL_NAME=gpt-4o-mini

# ===== Ontology limits =====
# ONTOLOGY_MAX_ENTITY_TYPES=12  # total entity types (specific + 2 fallback); Zep Cloud max is 10 specific + 2 = 12
# ONTOLOGY_MAX_EDGE_TYPES=10    # max relationship types; Zep Cloud max is 10

# ===== Boost LLM (optional) =====
# Secondary faster LLM — omit these lines entirely if not used
LLM_BOOST_API_KEY=your_api_key_here
LLM_BOOST_BASE_URL=your_base_url_here
LLM_BOOST_MODEL_NAME=your_model_name_here

# ===== Authentication =====
# Password for the "demo" user — REQUIRED in production
# Empty default = login disabled until set
DEMO_PASSWORD=

# Flask secret key — used to sign JWT tokens
# Generate with: python -c "import secrets; print(secrets.token_hex(32))"
SECRET_KEY=your-secret-key-here