CodeGraph CLI MCP Server

# CodeGraph Configuration Example # Copy this file to .env and update the values for your environment # ============================================================================ # CodeGraph Core Configuration (Simplified Setup) # ============================================================================ # Minimal Setup - Auto-detect embedding provider (ONNX, Ollama, or OpenAI) CODEGRAPH_EMBEDDING_PROVIDER=auto # That's it for basic usage! CodeGraph will auto-detect everything else. # Uncomment and customize the settings below if you need more control. # Embedding Provider Configuration # ---------------------------------- # Provider options: "auto", "onnx", "ollama", "openai", or "lmstudio" # CODEGRAPH_EMBEDDING_PROVIDER=auto # ONNX: Specify model path (or leave empty for auto-detection from HuggingFace cache) # CODEGRAPH_LOCAL_MODEL=/path/to/your/onnx/model # Ollama: Specify embedding model name # CODEGRAPH_EMBEDDING_MODEL=all-minilm:latest # CODEGRAPH_OLLAMA_URL=http://localhost:11434 # LM Studio: Best for MLX + Flash Attention 2 (recommended on macOS) # Default: jina-code-embeddings-1.5b (1536 dimensions) # CODEGRAPH_EMBEDDING_PROVIDER=lmstudio # CODEGRAPH_EMBEDDING_MODEL=jinaai/jina-embeddings-v3 # CODEGRAPH_LMSTUDIO_URL=http://localhost:1234 # CODEGRAPH_EMBEDDING_DIMENSION=1536 # OpenAI: Model name (API key configured below in Security section) # CODEGRAPH_EMBEDDING_MODEL=text-embedding-3-small # LLM Configuration (for local insights generation) # -------------------------------------------------- # Leave empty to use context-only mode (fastest, recommended for agents like Claude/GPT-4) # Set to enable local LLM insights generation # LM Studio with DeepSeek Coder v2 Lite Instruct (recommended) # Superior MLX support and Flash Attention 2 on macOS # CODEGRAPH_LLM_PROVIDER=lmstudio # CODEGRAPH_MODEL=lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF/DeepSeek-Coder-V2-Lite-Instruct-Q4_K_M.gguf # CODEGRAPH_LMSTUDIO_URL=http://localhost:1234 # CODEGRAPH_CONTEXT_WINDOW=32000 # CODEGRAPH_TEMPERATURE=0.1 # Ollama (alternative) # LLM model (e.g., "qwen2.5-coder:14b", "codellama:13b") # CODEGRAPH_MODEL=qwen2.5-coder:14b # CODEGRAPH_OLLAMA_URL=http://localhost:11434 # LLM context window size (tokens) # CODEGRAPH_CONTEXT_WINDOW=32000 # LLM temperature (0.0 = deterministic, 1.0 = creative) # CODEGRAPH_TEMPERATURE=0.1 # Logging # ------- # Log level: trace, debug, info, warn, error # Use "warn" during indexing for clean TUI output (recommended) # Use "info" for development/debugging RUST_LOG=warn # ============================================================================ # Security Configuration (for production deployments) # ============================================================================ # JWT Authentication JWT_SECRET=replace_with_secure_random_secret_minimum_32_characters_long JWT_EXPIRY_HOURS=24 # API Key Configuration API_KEY_PREFIX=cgk # Server Configuration HOST=127.0.0.1 PORT=8080 ENVIRONMENT=development # TLS/HTTPS Configuration (for production) # TLS_CERT_PATH=/path/to/certificate.pem # TLS_KEY_PATH=/path/to/private-key.pem # REQUIRE_TLS=true # Database Configuration # DATABASE_URL=postgresql://user:password@localhost/codegraph # REDIS_URL=redis://localhost:6379 # Rate Limiting RATE_LIMIT_ANONYMOUS=60 RATE_LIMIT_USER=1000 RATE_LIMIT_PREMIUM=5000 RATE_LIMIT_ADMIN=10000 # Security Settings MAX_REQUEST_SIZE=10485760 # 10MB SESSION_TIMEOUT_HOURS=24 PASSWORD_MIN_LENGTH=12 # Logging (see RUST_LOG above for CodeGraph core logging) # LOG_LEVEL=info # For application-level logging SECURITY_LOG_LEVEL=warn LOG_FORMAT=json # Monitoring METRICS_ENABLED=true PROMETHEUS_PORT=9090 # OpenAI API (if using external AI services) # OPENAI_API_KEY=your_openai_api_key_here # OPENAI_ORG_ID=your_org_id_here # External Services # SENTRY_DSN=https://your-sentry-dsn # ANALYTICS_KEY=your_analytics_key # Development/Testing Only DEV_MODE=true DISABLE_AUTH=false # Never set to true in production! ENABLE_DEBUG_ENDPOINTS=false