AndyMik90
268 lines
10 KiB
Bash
268 lines
10 KiB
Bash
# Auto Claude Environment Variables
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# Copy this file to .env and fill in your values
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# Claude Code OAuth Token (REQUIRED)
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# Get this by running: claude setup-token
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CLAUDE_CODE_OAUTH_TOKEN=your-oauth-token-here
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# Model override (OPTIONAL)
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# Default: claude-opus-4-5-20251101
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# AUTO_BUILD_MODEL=claude-opus-4-5-20251101
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# =============================================================================
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# DEBUG MODE (OPTIONAL)
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# =============================================================================
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# Enable debug logging for development and troubleshooting.
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# Shows detailed information about runner execution, agent calls, file operations.
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# Enable debug mode (default: false)
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# DEBUG=true
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# Debug log level: 1=basic, 2=detailed, 3=verbose (default: 1)
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# DEBUG_LEVEL=1
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# Log to file instead of stdout (OPTIONAL)
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# DEBUG_LOG_FILE=auto-claude/debug.log
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# =============================================================================
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# LINEAR INTEGRATION (OPTIONAL)
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# =============================================================================
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# Enable Linear integration for real-time progress tracking in Linear.
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# Get your API key from: https://linear.app/YOUR-TEAM/settings/api
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# Linear API Key (OPTIONAL - enables Linear integration)
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# LINEAR_API_KEY=lin_api_xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
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# Pre-configured Team ID (OPTIONAL - will auto-detect if not set)
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# LINEAR_TEAM_ID=
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# Pre-configured Project ID (OPTIONAL - will create project if not set)
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# LINEAR_PROJECT_ID=
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# =============================================================================
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# UI SETTINGS (OPTIONAL)
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# =============================================================================
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# Enable fancy terminal UI with icons, colors, and interactive menus.
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# Set to "false" to use plain text output (useful for CI/CD or log files).
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# Enable fancy UI (default: true)
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# ENABLE_FANCY_UI=true
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# =============================================================================
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# GRAPHITI MEMORY INTEGRATION V2 (OPTIONAL)
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# =============================================================================
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# Enable Graphiti-based persistent memory layer for cross-session context
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# retention. Uses FalkorDB as the graph database backend.
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#
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# V2 supports multiple LLM and embedder providers:
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# - OpenAI (default)
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# - Anthropic (LLM only, use with Voyage for embeddings)
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# - Azure OpenAI
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# - Ollama (local, fully offline)
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#
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# Prerequisites:
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# 1. Start FalkorDB: docker-compose up -d falkordb
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# 2. Install Graphiti: pip install graphiti-core[falkordb]
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# 3. Configure your chosen provider (see below)
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# Enable Graphiti integration (default: false)
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# GRAPHITI_ENABLED=true
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# =============================================================================
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# GRAPHITI: Provider Selection
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# =============================================================================
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# Choose which providers to use for LLM and embeddings.
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# Default is "openai" for both.
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# LLM provider: openai | anthropic | azure_openai | ollama
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# GRAPHITI_LLM_PROVIDER=openai
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# Embedder provider: openai | voyage | azure_openai | ollama
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# GRAPHITI_EMBEDDER_PROVIDER=openai
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# =============================================================================
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# GRAPHITI: OpenAI Provider (Default)
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# =============================================================================
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# Use OpenAI for both LLM and embeddings. This is the simplest setup.
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# Required: OPENAI_API_KEY
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# OpenAI API Key
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# OPENAI_API_KEY=sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
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# OpenAI Model for LLM (default: gpt-5-mini)
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# OPENAI_MODEL=gpt-5-mini
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# OpenAI Model for embeddings (default: text-embedding-3-small)
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# Available: text-embedding-3-small (1536 dim), text-embedding-3-large (3072 dim)
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# OPENAI_EMBEDDING_MODEL=text-embedding-3-small
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# =============================================================================
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# GRAPHITI: Anthropic Provider (LLM only)
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# =============================================================================
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# Use Anthropic for LLM. Requires separate embedder (use Voyage or OpenAI).
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# Example: GRAPHITI_LLM_PROVIDER=anthropic, GRAPHITI_EMBEDDER_PROVIDER=voyage
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#
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# Required: ANTHROPIC_API_KEY
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# Anthropic API Key
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# ANTHROPIC_API_KEY=sk-ant-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
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# Anthropic Model (default: claude-sonnet-4-5-latest)
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# GRAPHITI_ANTHROPIC_MODEL=claude-sonnet-4-5-latest
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# =============================================================================
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# GRAPHITI: Voyage AI Provider (Embeddings only)
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# =============================================================================
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# Use Voyage AI for embeddings. Commonly paired with Anthropic LLM.
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# Get API key from: https://www.voyageai.com/
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#
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# Required: VOYAGE_API_KEY
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# Voyage AI API Key
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# VOYAGE_API_KEY=pa-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
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# Voyage Embedding Model (default: voyage-3)
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# Available: voyage-3 (1024 dim), voyage-3-lite (512 dim)
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# VOYAGE_EMBEDDING_MODEL=voyage-3
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# =============================================================================
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# GRAPHITI: Azure OpenAI Provider
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# =============================================================================
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# Use Azure OpenAI for both LLM and embeddings.
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# Requires Azure OpenAI deployment with appropriate models.
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#
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# Required: AZURE_OPENAI_API_KEY, AZURE_OPENAI_BASE_URL
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# Azure OpenAI API Key
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# AZURE_OPENAI_API_KEY=xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
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# Azure OpenAI Base URL (your Azure endpoint)
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# AZURE_OPENAI_BASE_URL=https://your-resource.openai.azure.com/openai/deployments/your-deployment
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# Azure OpenAI Deployment Names
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# AZURE_OPENAI_LLM_DEPLOYMENT=gpt-5
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# AZURE_OPENAI_EMBEDDING_DEPLOYMENT=text-embedding-3-small
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# =============================================================================
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# GRAPHITI: Ollama Provider (Local/Offline)
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# =============================================================================
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# Use Ollama for fully offline operation. No API keys required.
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# Requires Ollama running locally with appropriate models pulled.
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#
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# Prerequisites:
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# 1. Install Ollama: https://ollama.ai/
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# 2. Pull models: ollama pull deepseek-r1:7b && ollama pull nomic-embed-text
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# 3. Start Ollama server (usually auto-starts)
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#
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# Required: OLLAMA_LLM_MODEL, OLLAMA_EMBEDDING_MODEL, OLLAMA_EMBEDDING_DIM
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# Ollama Server URL (default: http://localhost:11434)
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# OLLAMA_BASE_URL=http://localhost:11434
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# Ollama LLM Model
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# Popular choices: deepseek-r1:7b, llama3.2:3b, mistral:7b, phi3:medium
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# OLLAMA_LLM_MODEL=deepseek-r1:7b
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# Ollama Embedding Model
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# Popular choices: nomic-embed-text (768 dim), mxbai-embed-large (1024 dim)
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# OLLAMA_EMBEDDING_MODEL=nomic-embed-text
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# Ollama Embedding Dimension (REQUIRED for Ollama embeddings)
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# Must match your embedding model's output dimension
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# Common values: nomic-embed-text=768, mxbai-embed-large=1024, all-minilm=384
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# OLLAMA_EMBEDDING_DIM=768
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# =============================================================================
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# GRAPHITI MCP SERVER (OPTIONAL - Agent-accessible knowledge graph)
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# =============================================================================
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# Enable Graphiti MCP server for direct agent access to knowledge graph.
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# This is SEPARATE from GRAPHITI_ENABLED (Python library integration).
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#
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# With MCP server enabled, Claude agents can directly:
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# - Search for relevant context (search_nodes, search_facts)
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# - Add discoveries to the graph (add_episode)
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# - Retrieve recent sessions (get_episodes)
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#
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# Quick Start (uses docker-compose.yml in project root):
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# 1. Set OPENAI_API_KEY in your .env file (or export it)
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# 2. Run: docker-compose up -d
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# 3. Set GRAPHITI_MCP_URL below
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#
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# Manual Docker (alternative):
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# docker run -d -p 8000:8000 \
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# -e DATABASE_TYPE=falkordb \
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# -e OPENAI_API_KEY=$OPENAI_API_KEY \
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# -e FALKORDB_URI=redis://host.docker.internal:6379 \
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# falkordb/graphiti-knowledge-graph-mcp
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#
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# See: https://docs.falkordb.com/agentic-memory/graphiti-mcp-server.html
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# Graphiti MCP Server URL (setting this enables MCP integration)
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# GRAPHITI_MCP_URL=http://localhost:8000/mcp/
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# Graphiti MCP Server Port (for docker-compose, default: 8000)
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# GRAPHITI_MCP_PORT=8000
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# Optional: Override model settings for MCP server
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# GRAPHITI_MODEL_NAME=gpt-4o-mini
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# GRAPHITI_EMBEDDING_MODEL=text-embedding-3-small
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# =============================================================================
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# GRAPHITI: FalkorDB Connection Settings
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# =============================================================================
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# Configure the FalkorDB graph database connection.
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# Start FalkorDB: docker run -p 6379:6379 falkordb/falkordb:latest
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# FalkorDB Host (default: localhost)
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# GRAPHITI_FALKORDB_HOST=localhost
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# FalkorDB Port (default: 6379)
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# GRAPHITI_FALKORDB_PORT=6379
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# FalkorDB Password (default: empty)
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# GRAPHITI_FALKORDB_PASSWORD=
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# Graph Database Name (default: auto_claude_memory)
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# GRAPHITI_DATABASE=auto_claude_memory
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# =============================================================================
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# GRAPHITI: Miscellaneous Settings
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# =============================================================================
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# Disable Graphiti telemetry (default: true)
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# GRAPHITI_TELEMETRY_ENABLED=false
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# =============================================================================
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# GRAPHITI: Example Configurations
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# =============================================================================
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#
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# --- Example 1: OpenAI (simplest) ---
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# GRAPHITI_ENABLED=true
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# GRAPHITI_LLM_PROVIDER=openai
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# GRAPHITI_EMBEDDER_PROVIDER=openai
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# OPENAI_API_KEY=sk-xxxxxxxx
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#
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# --- Example 2: Anthropic + Voyage (high quality) ---
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# GRAPHITI_ENABLED=true
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# GRAPHITI_LLM_PROVIDER=anthropic
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# GRAPHITI_EMBEDDER_PROVIDER=voyage
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# ANTHROPIC_API_KEY=sk-ant-xxxxxxxx
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# VOYAGE_API_KEY=pa-xxxxxxxx
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#
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# --- Example 3: Ollama (fully offline) ---
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# GRAPHITI_ENABLED=true
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# GRAPHITI_LLM_PROVIDER=ollama
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# GRAPHITI_EMBEDDER_PROVIDER=ollama
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# OLLAMA_LLM_MODEL=deepseek-r1:7b
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# OLLAMA_EMBEDDING_MODEL=nomic-embed-text
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# OLLAMA_EMBEDDING_DIM=768
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#
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# --- Example 4: Azure OpenAI (enterprise) ---
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# GRAPHITI_ENABLED=true
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# GRAPHITI_LLM_PROVIDER=azure_openai
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# GRAPHITI_EMBEDDER_PROVIDER=azure_openai
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# AZURE_OPENAI_API_KEY=xxxxxxxx
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# AZURE_OPENAI_BASE_URL=https://your-resource.openai.azure.com/...
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# AZURE_OPENAI_LLM_DEPLOYMENT=gpt-5
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# AZURE_OPENAI_EMBEDDING_DEPLOYMENT=text-embedding-3-small
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