# LLM (OpenAI-SDK-compatible — Qwen via Dashscope is the documented default).
# For Qwen via Dashscope:
#   LLM_BASE_URL=https://dashscope.aliyuncs.com/compatible-mode/v1
#   LLM_MODEL_NAME=qwen-plus
LLM_API_KEY=
LLM_BASE_URL=https://dashscope.aliyuncs.com/compatible-mode/v1
LLM_MODEL_NAME=qwen-plus

# Optional: pick the Graphiti provider explicitly. "openai" is the default and
# works for any OpenAI-compatible endpoint (Qwen, GLM, OpenAI itself). Set to
# "gemini" to use Google Gemini directly.
# GRAPHITI_LLM_PROVIDER=openai

# Optional: dedicated embedder credentials. Default to the LLM_* values above.
# Useful when chat is Dashscope/Qwen (no OpenAI-compatible embeddings exposed)
# but you want to point the embedder at OpenAI directly.
# EMBEDDING_API_KEY=
# EMBEDDING_BASE_URL=
EMBEDDING_MODEL=text-embedding-3-small

# Local embeddings via Ollama (run: ollama pull mxbai-embed-large).
# mxbai-embed-large is 1024-dim, matching Graphiti's default EMBEDDING_DIM.
# 768-dim models (e.g. nomic-embed-text) are NOT supported until EMBEDDING_DIM
# becomes configurable. Use host.docker.internal in Docker, localhost in host mode.
# EMBEDDING_BASE_URL=http://host.docker.internal:11434/v1
# EMBEDDING_API_KEY=ollama
# EMBEDDING_MODEL=mxbai-embed-large

# Knowledge graph — Neo4j (default works for both Docker and host modes).
# Docker compose overrides NEO4J_URI to bolt://neo4j:7687 inside the stack.
NEO4J_URI=bolt://localhost:7687
NEO4J_USER=neo4j
NEO4J_PASSWORD=mirofish123

# Optional: accelerated LLM for high-volume calls (omit if not used).
# LLM_BOOST_API_KEY=
# LLM_BOOST_BASE_URL=
# LLM_BOOST_MODEL_NAME=

# Deprecated — kept for backwards compatibility only.
ZEP_API_KEY=