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fix(rag): Fix CrossEncoderRanker bug of EmbeddingRetriever (#1504)
Co-authored-by: aries_ckt <916701291@qq.com>
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@ -219,7 +219,7 @@ class CrossEncoderRanker(Ranker):
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rank_scores = self._model.predict(sentences=query_content_pairs)
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for candidate, score in zip(candidates_with_scores, rank_scores):
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candidate.score = score
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candidate.score = float(score)
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new_candidates_with_scores = sorted(
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candidates_with_scores, key=lambda x: x.score, reverse=True
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@ -82,7 +82,7 @@ class ChromaStore(VectorStoreBase):
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# client_settings=chroma_settings,
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client=client,
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collection_metadata=collection_metadata,
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)
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) # type: ignore
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def similar_search(
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self, text, topk, filters: Optional[MetadataFilters] = None
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@ -93,7 +93,8 @@ class PGVectorStore(VectorStoreBase):
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List[str]: chunk ids.
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"""
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lc_documents = [Chunk.chunk2langchain(chunk) for chunk in chunks]
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return self.vector_store_client.from_documents(lc_documents)
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self.vector_store_client.from_documents(lc_documents)
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return [str(chunk.chunk_id) for chunk in lc_documents]
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def delete_vector_name(self, vector_name: str):
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"""Delete vector by name.
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@ -109,4 +110,5 @@ class PGVectorStore(VectorStoreBase):
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Args:
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ids(str): vector ids, separated by comma.
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"""
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return self.vector_store_client.delete(ids)
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delete_ids = ids.split(",")
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return self.vector_store_client.delete(delete_ids)
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