Added detailed documentation for SEMAPHORE_LIMIT configuration to help users optimize episode processing concurrency based on their LLM provider's rate limits.
Changes:
1. **graphiti_mcp_server.py**
- Expanded inline comments from 3 lines to 26 lines
- Added provider-specific tuning guidelines (OpenAI, Anthropic, Azure, Ollama)
- Documented symptoms of too-high/too-low settings
- Added monitoring recommendations
2. **README.md**
- Expanded "Concurrency and LLM Provider 429 Rate Limit Errors" section
- Added tier-specific recommendations for each provider
- Explained relationship between episode concurrency and LLM request rates
- Added troubleshooting symptoms and monitoring guidance
- Included example .env configuration
3. **config.yaml**
- Added header comment referencing detailed documentation
- Noted default value and suitable use case
4. **.env.example**
- Added SEMAPHORE_LIMIT with inline tuning guidelines
- Quick reference for all major LLM provider tiers
- Cross-reference to README for full details
Benefits:
- Users can now make informed decisions about concurrency settings
- Reduces likelihood of 429 rate limit errors from misconfiguration
- Helps users maximize throughput within their rate limits
- Provides clear troubleshooting guidance
Addresses PR #1024 review comment about magic number documentation.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
BREAKING CHANGE: Kuzu is no longer supported. FalkorDB is now the default.
- Renamed Dockerfile.falkordb-combined to Dockerfile (default)
- Renamed docker-compose-falkordb-combined.yml to docker-compose.yml (default)
- Updated config.yaml to use FalkorDB with localhost:6379 as default
- Removed Kuzu from pyproject.toml dependencies (now only falkordb extra)
- Updated Dockerfile to use graphiti-core[falkordb] instead of [kuzu,falkordb]
- Completely removed all Kuzu references from README
- Updated README to document FalkorDB combined container as default
- Docker Compose now starts single container with FalkorDB + MCP server
- Prerequisites now require Docker instead of Python for default setup
- Removed old Kuzu docker-compose files
Running from command line now requires external FalkorDB instance at localhost:6379
Replace outdated text-embedding-ada-002 with the newer, more efficient
text-embedding-3-small model as the default embedder. The new model
offers better performance and is more cost-effective.
Updated:
- config/config.yaml: Changed default model
- README.md: Updated documentation to reflect new default
Changed the default LLM model from gpt-4o-mini to gpt-4.1 as requested.
This is the latest GPT-4 series model.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Changed the default LLM model from gpt-4o to gpt-4o-mini across all
configuration files for better cost efficiency while maintaining quality.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Changed default transport to 'http' as SSE is deprecated
- Updated all configuration files to use HTTP transport
- Updated Docker compose commands to use HTTP transport
- Updated comments to reflect HTTP transport usage
This change ensures the MCP server uses the recommended HTTP transport
instead of the deprecated SSE transport.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Fix API key detection: Remove hardcoded OpenAI checks, let factories handle provider-specific validation
- Fix .env file loading: Search for .env in mcp_server directory first
- Change default transport to SSE for broader compatibility (was stdio)
- Add proper error handling with warnings for failed client initialization
- Model already defaults to gpt-4o as requested
These changes ensure the MCP server properly loads API keys from .env files
and creates the appropriate LLM/embedder clients based on configuration.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
This is a major refactoring of the MCP Server to support multiple providers
through a YAML-based configuration system with factory pattern implementation.
## Key Changes
### Architecture Improvements
- Modular configuration system with YAML-based settings
- Factory pattern for LLM, Embedder, and Database providers
- Support for multiple database backends (Neo4j, FalkorDB, KuzuDB)
- Clean separation of concerns with dedicated service modules
### Provider Support
- **LLM**: OpenAI, Anthropic, Gemini, Groq
- **Embedders**: OpenAI, Voyage, Gemini, Anthropic, Sentence Transformers
- **Databases**: Neo4j, FalkorDB, KuzuDB (new default)
- Azure OpenAI support with AD authentication
### Configuration
- YAML configuration with environment variable expansion
- CLI argument overrides for runtime configuration
- Multiple pre-configured Docker Compose setups
- Proper boolean handling in environment variables
### Testing & CI
- Comprehensive test suite with unit and integration tests
- GitHub Actions workflows for linting and testing
- Multi-database testing support
### Docker Support
- Updated Docker images with multi-stage builds
- Database-specific docker-compose configurations
- Persistent volume support for all databases
### Bug Fixes
- Fixed KuzuDB connectivity checks
- Corrected Docker command paths
- Improved error handling and logging
- Fixed boolean environment variable expansion
Co-authored-by: Claude <noreply@anthropic.com>
