- Create Dockerfile.standalone for MCP server without embedded FalkorDB
- Supports both Neo4j and FalkorDB via DATABASE_PROVIDER build arg
- Update docker-compose-neo4j.yml to use standalone Dockerfile
- Update docker-compose-falkordb.yml to use standalone Dockerfile
- Fixes issue where Neo4j compose was starting embedded FalkorDB
- Separate images: standalone-neo4j and standalone-falkordb
- Changed status check to use graphiti_service.config.database.provider
- Ensures status reports the actual running database, not potentially stale global
- Fixes issue where status always reported falkordb regardless of config
- Remove dead code checking for 'kuzu' provider (was removed)
- Simplify status check to use configured database provider directly
- Status now correctly reports neo4j or falkordb based on config
- Catch Redis/database connection errors during initialization
- Provide clear, formatted error messages with startup instructions
- Include provider-specific guidance (FalkorDB vs Neo4j)
- Improves developer experience when database is not running
- Change episode_id_prefix type to str | None to accept None from YAML
- Add model_post_init to convert None to empty string for backward compatibility
- Change default config path from 'config.yaml' to 'config/config.yaml'
- Fix env var expansion to return None for empty strings instead of False
- Prevents validation errors when optional string fields have unset env vars
Added comprehensive model reference section documenting valid model names for OpenAI, Anthropic, and Google Gemini as of January 2025.
OpenAI Models:
- GPT-5 family (reasoning models): gpt-5-mini, gpt-5-nano
- GPT-4.1 family (standard models): gpt-4.1, gpt-4.1-mini, gpt-4.1-nano
- Legacy models: gpt-4o, gpt-4o-mini
Anthropic Models:
- Claude 3.7 family (latest)
- Claude 3.5 family
- Legacy Claude 3 models
Google Gemini Models:
- Gemini 2.5 family (latest)
- Gemini 2.0 family (experimental)
- Gemini 1.5 family (stable)
This documents that model names like gpt-5-mini, gpt-4.1, and gpt-4.1-mini used throughout the codebase are valid OpenAI model identifiers, not errors.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
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>
Fixed high-impact issues from PR #1024 code review:
1. **Boolean conversion bug (schema.py)**
- Fixed _expand_env_vars returning strings 'true'/'false' instead of booleans
- Now properly converts boolean-like strings (true/false/1/0/yes/no/on/off) to actual booleans
- Simplified logic by removing redundant string-to-string conversions
- Added support for common boolean string variations
2. **Dependency management (pyproject.toml)**
- Removed pytest from main dependencies (now only in dev dependencies)
- Moved azure-identity to optional dependencies under new [azure] group
- Prevents forcing Azure and testing dependencies on all users
3. **Conditional Azure imports (utils.py)**
- Made azure-identity import conditional in create_azure_credential_token_provider()
- Raises helpful ImportError with installation instructions if not available
- Follows lazy-import pattern for optional dependencies
4. **Documentation fix (graphiti_mcp_server.py)**
- Fixed confusing JSON escaping in add_memory docstring example
- Changed from triple-backslash escaping to standard JSON string
- Updated comment to clarify standard JSON escaping is used
Issues verified as already fixed:
- Docker build context (all docker-compose files use context: ..)
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
Fixed pyright type error where temperature parameter (float | None) was being passed directly to Anthropic's messages.create() method which expects (float | Omit).
Changes:
- Build message creation parameters as a dictionary
- Conditionally include temperature only when not None
- Use dictionary unpacking to pass parameters
This allows temperature to be properly omitted when None, rather than passing None as a value.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <noreply@anthropic.com>
