# RA-H OS Configuration
# Copy to .env.local: cp .env.example .env.local

# OpenAI API Key (optional, default supported AI path)
# Enables: auto-descriptions, extraction summaries, edge inference, embeddings, and semantic search
# Get one at: https://platform.openai.com/api-keys
OPENAI_API_KEY=

# AI profiles are selected during setup because embedding dimensions shape
# the sqlite-vec tables. Use one:
#
#   npm run setup:local -- --profile openai
#   npm run setup:local -- --profile qwen-local
#
# OpenAI profile:
# LLM_PROFILE=openai
# LLM_MODEL=gpt-4o-mini
# EMBEDDING_PROFILE=openai
# EMBEDDING_MODEL=text-embedding-3-small
# EMBEDDING_DIMENSIONS=1536
# VECTOR_BACKEND=sqlite-vec

# Supported local profile: point RA-H at OpenAI-compatible local endpoints.
# Example Ollama:
# LLM_PROFILE=openai-compatible
# LLM_BASE_URL=http://127.0.0.1:11434/v1
# LLM_MODEL=qwen3:4b
# EMBEDDING_PROFILE=openai-compatible
# EMBEDDING_BASE_URL=http://127.0.0.1:11434/v1
# EMBEDDING_MODEL=qwen3-embedding:0.6b
# EMBEDDING_DIMENSIONS=1024
#
# Example Qdrant sidecar, only needed when sqlite-vec is unavailable or unreliable:
# VECTOR_BACKEND=qdrant
# QDRANT_URL=http://localhost:6333

# Database/vector paths are auto-detected for macOS, Windows, and Linux.
# Override only if you intentionally want a custom location.
# SQLITE_DB_PATH=/absolute/path/to/rah.sqlite
# SQLITE_VEC_EXTENSION_PATH=/absolute/path/to/vec0.<dylib|dll|so>

# App config (no changes needed)
NODE_ENV=development
PORT=3000
NEXT_PUBLIC_APP_URL=http://localhost:3000
NEXT_PUBLIC_DEPLOYMENT_MODE=local