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Improve weaviate vectorstore docs (#5201)

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# Improve weaviate vectorstore docs
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Shukri 2023-05-25 00:31:48 +08:00 committed by GitHub
parent fd866d1801
commit b00c77dc62
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2 changed files with 175 additions and 94 deletions
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234
docs/modules/indexes/vectorstores/examples/weaviate.ipynb
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35
langchain/vectorstores/weaviate.py
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@ -322,12 +322,24 @@ class Weaviate(VectorStore):
if kwargs.get("search_distance"): if kwargs.get("search_distance"):
content["certainty"] = kwargs.get("search_distance") content["certainty"] = kwargs.get("search_distance")
query_obj = self._client.query.get(self._index_name, self._query_attrs) query_obj = self._client.query.get(self._index_name, self._query_attrs)
result = (
query_obj.with_near_text(content) if not self._by_text:
.with_limit(k) embedding = self._embedding.embed_query(query)
.with_additional("vector") vector = {"vector": embedding}
.do() result = (
) query_obj.with_near_vector(vector)
.with_limit(k)
.with_additional("vector")
.do()
)
else:
result = (
query_obj.with_near_text(content)
.with_limit(k)
.with_additional("vector")
.do()
)
if "errors" in result: if "errors" in result:
raise ValueError(f"Error during query: {result['errors']}") raise ValueError(f"Error during query: {result['errors']}")
@ -436,6 +448,15 @@ class Weaviate(VectorStore):
batch.flush() batch.flush()
relevance_score_fn = kwargs.get("relevance_score_fn")
by_text: bool = kwargs.get("by_text", False)
return cls( return cls(
client, index_name, text_key, embedding=embedding, attributes=attributes client,
index_name,
text_key,
embedding=embedding,
attributes=attributes,
relevance_score_fn=relevance_score_fn,
by_text=by_text,
) )