- Add SemanticSearchConfig to settings.py with embedding model options
- Update WorldMapper to accept embedding_model parameter
- Update main.py to pass model from config to WorldMapper
- Add documentation for available embedding models:
- sentence-transformers/all-MiniLM-L6-v2 (default, fast)
- sentence-transformers/all-mpnet-base-v2 (better quality)
- google/embeddinggemma-300m (state-of-the-art)
- Update config.yaml and config.example.yaml with new options
Users can now choose the best embedding model for their needs.
- Add comprehensive configuration guide (docs/configuration.md)
- Add development guide with setup instructions (docs/development.md)
- Add complete API reference documentation (docs/api_reference.md)
- Update README.md with new features and project structure
- Update TODO.md to reflect current implementation status
- Add web monitoring dashboard with FastAPI and WebSocket support
- Add tests for sync integration and web monitoring
- Update config example with monitoring settings
The MUD AI Player is now feature-complete with full documentation.
Phase 0 (housekeeping):
- Add .gitignore to protect credentials and runtime files
- Track all project source code, docs, and config
Phase 1 (perception loop):
- Implement pluggable parser architecture (BaseMudParser ABC + ParserFactory)
- Add DeadSoulsParser with regex for HP/MP/SP prompt, room descriptions,
exits (multiple formats), NPC/item detection, and combat events
- Add OutputBuffer for accumulating text between prompts
- Update GameState with SP support and update_from_prompt/room/combat methods
- Rewire main loop to use parser + buffer for real-time game state updates
- Add reconnection logic to TelnetClient (retry with backoff)
- Remove old TextParser (replaced by pluggable system)
- Add mud_type config field for selecting parser at runtime
- Add comprehensive test suite (50 tests, all passing)
truetype