feat: add matching retrieval utilities and model integration#123
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zerolovesea
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Jun 1, 2026
zerolovesea
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- Introduced EmbeddingTable and FaissVectorIndex for managing embeddings and similarity searches.
- Implemented methods for saving/loading embedding tables in CSV and Parquet formats.
- Enhanced compute_pair_scores function to utilize feature data loaders for batch processing.
- Added tests for embedding table functionality, including roundtrip serialization and model integration.
- Developed tests for FAISS index operations, ensuring correct behavior for search and streaming exports.
- Integrated new matching models with existing prediction APIs and added relevant tests for their functionality.
- Introduced EmbeddingTable and FaissVectorIndex for managing embeddings and similarity searches. - Implemented methods for saving/loading embedding tables in CSV and Parquet formats. - Enhanced compute_pair_scores function to utilize feature data loaders for batch processing. - Added tests for embedding table functionality, including roundtrip serialization and model integration. - Developed tests for FAISS index operations, ensuring correct behavior for search and streaming exports. - Integrated new matching models with existing prediction APIs and added relevant tests for their functionality.
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