feat: Configure KuzuDB Docker deployment with persistent storage
- Update docker-compose-kuzu.yml to use persistent volume by default - Set KUZU_DB to /data/graphiti.kuzu for persistent storage - Increase max concurrent queries from 1 to 10 for better performance - Add dedicated config-docker-kuzu.yaml for Docker deployments - Create README-kuzu.md with usage instructions and troubleshooting - Configure volume with local driver for data persistence The setup now provides: - Automatic data persistence across container restarts - No external database dependencies - Simple backup/restore procedures - Lower resource usage compared to Neo4j 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
Daniel Chalef
parent
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commit
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3 changed files with 222 additions and 10 deletions
90
mcp_server/config/config-docker-kuzu.yaml
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90
mcp_server/config/config-docker-kuzu.yaml
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# Graphiti MCP Server Configuration for Docker with KuzuDB
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# This configuration is optimized for running with docker-compose-kuzu.yml
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# It uses persistent KuzuDB storage at /data/graphiti.kuzu
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server:
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transport: "sse" # SSE for HTTP access from Docker
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host: "0.0.0.0"
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port: 8000
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llm:
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provider: "openai" # Options: openai, azure_openai, anthropic, gemini, groq
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model: "gpt-4o"
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temperature: 0.0
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max_tokens: 4096
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providers:
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openai:
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api_key: ${OPENAI_API_KEY}
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api_url: ${OPENAI_API_URL:https://api.openai.com/v1}
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organization_id: ${OPENAI_ORGANIZATION_ID:}
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azure_openai:
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api_key: ${AZURE_OPENAI_API_KEY}
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api_url: ${AZURE_OPENAI_ENDPOINT}
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api_version: ${AZURE_OPENAI_API_VERSION:2024-10-21}
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deployment_name: ${AZURE_OPENAI_DEPLOYMENT}
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use_azure_ad: ${USE_AZURE_AD:false}
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anthropic:
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api_key: ${ANTHROPIC_API_KEY}
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api_url: ${ANTHROPIC_API_URL:https://api.anthropic.com}
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max_retries: 3
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gemini:
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api_key: ${GOOGLE_API_KEY}
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project_id: ${GOOGLE_PROJECT_ID:}
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location: ${GOOGLE_LOCATION:us-central1}
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groq:
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api_key: ${GROQ_API_KEY}
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api_url: ${GROQ_API_URL:https://api.groq.com/openai/v1}
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embedder:
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provider: "openai" # Options: openai, azure_openai, gemini, voyage
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model: "text-embedding-ada-002"
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dimensions: 1536
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providers:
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openai:
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api_key: ${OPENAI_API_KEY}
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api_url: ${OPENAI_API_URL:https://api.openai.com/v1}
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organization_id: ${OPENAI_ORGANIZATION_ID:}
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azure_openai:
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api_key: ${AZURE_OPENAI_API_KEY}
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api_url: ${AZURE_OPENAI_EMBEDDINGS_ENDPOINT}
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api_version: ${AZURE_OPENAI_API_VERSION:2024-10-21}
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deployment_name: ${AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT}
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use_azure_ad: ${USE_AZURE_AD:false}
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gemini:
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api_key: ${GOOGLE_API_KEY}
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project_id: ${GOOGLE_PROJECT_ID:}
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location: ${GOOGLE_LOCATION:us-central1}
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voyage:
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api_key: ${VOYAGE_API_KEY}
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api_url: ${VOYAGE_API_URL:https://api.voyageai.com/v1}
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model: "voyage-3"
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database:
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provider: "kuzu" # Using KuzuDB for this configuration
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providers:
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kuzu:
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# Use environment variable if set, otherwise use persistent storage at /data
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db: ${KUZU_DB:/data/graphiti.kuzu}
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max_concurrent_queries: ${KUZU_MAX_CONCURRENT_QUERIES:10}
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graphiti:
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group_id: ${GRAPHITI_GROUP_ID:main}
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episode_id_prefix: ${EPISODE_ID_PREFIX:}
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user_id: ${USER_ID:mcp_user}
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entity_types:
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- name: "Requirement"
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description: "Represents a requirement"
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- name: "Preference"
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description: "User preferences and settings"
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- name: "Procedure"
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description: "Standard operating procedures"
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122
mcp_server/docker/README-kuzu.md
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122
mcp_server/docker/README-kuzu.md
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# Running MCP Server with KuzuDB
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This guide explains how to run the Graphiti MCP server with KuzuDB as the graph database backend using Docker Compose.
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## Why KuzuDB?
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KuzuDB is an embedded graph database that provides several advantages:
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- **No external dependencies**: Unlike Neo4j, KuzuDB runs embedded within the application
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- **Persistent storage**: Data is stored in a single file/directory
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- **High performance**: Optimized for analytical workloads
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- **Low resource usage**: Minimal memory and CPU requirements
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## Quick Start
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1. **Set up environment variables**:
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Create a `.env` file in the `docker` directory:
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```bash
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OPENAI_API_KEY=your-api-key-here
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# Optional: Override default settings
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GRAPHITI_GROUP_ID=my-group
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KUZU_MAX_CONCURRENT_QUERIES=20
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```
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2. **Start the server**:
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```bash
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docker-compose -f docker-compose-kuzu.yml up
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```
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3. **Access the MCP server**:
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The server will be available at `http://localhost:8000`
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## Configuration
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### Persistent Storage
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By default, KuzuDB data is stored in a Docker volume at `/data/graphiti.kuzu`. This ensures your data persists across container restarts.
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To use a different location, set the `KUZU_DB` environment variable:
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```bash
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KUZU_DB=/data/my-custom-db.kuzu
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```
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### In-Memory Mode
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For testing or temporary usage, you can run KuzuDB in memory-only mode:
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```bash
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KUZU_DB=:memory:
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```
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Note: Data will be lost when the container stops.
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### Performance Tuning
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Adjust the maximum number of concurrent queries:
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```bash
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KUZU_MAX_CONCURRENT_QUERIES=20 # Default is 10
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```
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## Data Management
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### Backup
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To backup your KuzuDB data:
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```bash
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# Create a backup of the volume
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docker run --rm -v mcp_server_kuzu_data:/data -v $(pwd):/backup alpine tar czf /backup/kuzu-backup.tar.gz -C /data .
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```
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### Restore
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To restore from a backup:
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```bash
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# Restore from backup
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docker run --rm -v mcp_server_kuzu_data:/data -v $(pwd):/backup alpine tar xzf /backup/kuzu-backup.tar.gz -C /data
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```
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### Clear Data
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To completely clear the KuzuDB data:
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```bash
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# Stop the container
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docker-compose -f docker-compose-kuzu.yml down
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# Remove the volume
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docker volume rm docker_kuzu_data
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# Restart (will create fresh volume)
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docker-compose -f docker-compose-kuzu.yml up
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```
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## Switching from Neo4j
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If you're migrating from Neo4j to KuzuDB:
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1. Export your data from Neo4j (if needed)
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2. Stop the Neo4j-based setup: `docker-compose down`
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3. Start the KuzuDB setup: `docker-compose -f docker-compose-kuzu.yml up`
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4. Re-import your data through the MCP API
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## Troubleshooting
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### Container won't start
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- Check that port 8000 is not in use: `lsof -i :8000`
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- Verify your `.env` file has valid API keys
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### Data not persisting
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- Ensure the volume is properly mounted: `docker volume ls`
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- Check volume permissions: `docker exec graphiti-mcp ls -la /data`
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### Performance issues
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- Increase `KUZU_MAX_CONCURRENT_QUERIES` for better parallelism
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- Monitor container resources: `docker stats graphiti-mcp`
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## Comparison with Neo4j Setup
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| Feature | KuzuDB | Neo4j |
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|---------|--------|-------|
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| External Database | No | Yes |
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| Memory Usage | Low (~100MB) | High (~512MB min) |
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| Startup Time | Instant | 30+ seconds |
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| Persistent Storage | Single file | Multiple files |
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| Docker Services | 1 | 2 |
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| Default Port | 8000 (MCP only) | 8000, 7474, 7687 |
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- path: .env
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required: false # Makes the file optional. Default value is 'true'
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environment:
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# Database configuration for KuzuDB
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- KUZU_DB=${KUZU_DB:-:memory:}
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- KUZU_MAX_CONCURRENT_QUERIES=${KUZU_MAX_CONCURRENT_QUERIES:-1}
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# Database configuration for KuzuDB - using persistent storage
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- KUZU_DB=${KUZU_DB:-/data/graphiti.kuzu}
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- KUZU_MAX_CONCURRENT_QUERIES=${KUZU_MAX_CONCURRENT_QUERIES:-10}
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# LLM provider configurations
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- OPENAI_API_KEY=${OPENAI_API_KEY}
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- ANTHROPIC_API_KEY=${ANTHROPIC_API_KEY}
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@ -29,14 +29,14 @@ services:
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- CONFIG_PATH=/app/config/config.yaml
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- PATH=/root/.local/bin:${PATH}
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volumes:
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- ./config.yaml:/app/config/config.yaml:ro
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# Optional: If you want to persist KuzuDB data, uncomment the following line
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# and change KUZU_DB to /data/kuzu.db
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# - kuzu_data:/data
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- ../config/config-docker-kuzu.yaml:/app/config/config.yaml:ro
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# Persistent KuzuDB data storage
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- kuzu_data:/data
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ports:
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- "8000:8000" # Expose the MCP server via HTTP for SSE transport
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command: ["uv", "run", "graphiti_mcp_server.py", "--transport", "sse", "--config", "/app/config/config.yaml"]
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# Optional: Volume for persistent KuzuDB storage
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# volumes:
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# kuzu_data:
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# Volume for persistent KuzuDB storage
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volumes:
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kuzu_data:
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driver: local
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