MAJOR CHANGES:
- Replace complex uv-based Dockerfile with simple pip-only approach
- Add requirements.txt for standard Python dependency management
- Remove all uv commands that might trigger cache mount behavior
- Add .dockerignore for clean Railway build context
- Add nixpacks.toml to force Dockerfile usage (disable auto-detection)
- Update railway.json with explicit Docker configuration
PROBLEM SOLVED:
Railway 'Cache mount ID is not prefixed with cache key' error should be resolved
by eliminating all potential sources of cache mount directives.
DEPLOYMENT STRATEGY:
- Single-stage Docker build using standard pip
- Install graphiti-core from source with 'pip install .'
- Install MCP dependencies with 'pip install -r requirements.txt'
- No complex build tools or caching mechanisms
- Explicit Railway Docker configuration
🚀 Generated with Claude Code (https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Fix Docker cache mount issues that caused Railway build failures
- Add port argument support to MCP server for Railway compatibility
- Create Railway-optimized Dockerfile without cache mounts
- Add railway.json configuration for proper deployment
- Create comprehensive deployment and ChatGPT integration guides
- Add environment variable templates for Railway deployment
- Support Railway's PORT environment variable handling
- Ready for ChatGPT MCP SSE integration
🚀 Generated with Claude Code (https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
