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Fix Document Similarity Check with passed Threshold (#6845)
Converting the Similarity obtained in the similarity_search_with_score_by_vector method whilst comparing to the passed threshold. This is because the passed threshold is a number between 0 to 1 and is already in the relevance_score_fn format. As of now, the function is comparing two different scoring parameters and that wouldn't work. Dependencies None Issue: Different scores being compared in similarity_search_with_score_by_vector method in FAISS. Tag maintainer @hwchase17 <!-- Thank you for contributing to LangChain! Replace this comment with: - Description: a description of the change, - Issue: the issue # it fixes (if applicable), - Dependencies: any dependencies required for this change, - Tag maintainer: for a quicker response, tag the relevant maintainer (see below), - Twitter handle: we announce bigger features on Twitter. If your PR gets announced and you'd like a mention, we'll gladly shout you out! If you're adding a new integration, please include: 1. a test for the integration, preferably unit tests that do not rely on network access, 2. an example notebook showing its use. Maintainer responsibilities: - General / Misc / if you don't know who to tag: @dev2049 - DataLoaders / VectorStores / Retrievers: @rlancemartin, @eyurtsev - Models / Prompts: @hwchase17, @dev2049 - Memory: @hwchase17 - Agents / Tools / Toolkits: @vowelparrot - Tracing / Callbacks: @agola11 - Async: @agola11 If no one reviews your PR within a few days, feel free to @-mention the same people again. See contribution guidelines for more information on how to write/run tests, lint, etc: https://github.com/hwchase17/langchain/blob/master/.github/CONTRIBUTING.md --> --------- Co-authored-by: Bagatur <baskaryan@gmail.com>
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@ -698,6 +698,9 @@ class FAISS(VectorStore):
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**kwargs: Any,
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**kwargs: Any,
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) -> List[Tuple[Document, float]]:
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) -> List[Tuple[Document, float]]:
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"""Return docs and their similarity scores on a scale from 0 to 1."""
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"""Return docs and their similarity scores on a scale from 0 to 1."""
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# Pop score threshold so that only relevancy scores, not raw scores, are
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# filtered.
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score_threshold = kwargs.pop("score_threshold", None)
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relevance_score_fn = self._select_relevance_score_fn()
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relevance_score_fn = self._select_relevance_score_fn()
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if relevance_score_fn is None:
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if relevance_score_fn is None:
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raise ValueError(
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raise ValueError(
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@ -711,4 +714,13 @@ class FAISS(VectorStore):
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fetch_k=fetch_k,
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fetch_k=fetch_k,
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**kwargs,
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**kwargs,
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)
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)
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return [(doc, relevance_score_fn(score)) for doc, score in docs_and_scores]
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docs_and_rel_scores = [
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(doc, relevance_score_fn(score)) for doc, score in docs_and_scores
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]
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if score_threshold is not None:
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docs_and_rel_scores = [
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(doc, similarity)
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for doc, similarity in docs_and_rel_scores
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if similarity >= score_threshold
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]
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return docs_and_rel_scores
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