- 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.
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