Refactor logging for vector similarity search with configurable threshold
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@@ -139,9 +139,6 @@ class NanoVectorDBStorage(BaseVectorStorage):
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async def query(self, query: str, top_k=5):
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embedding = await self.embedding_func([query])
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embedding = embedding[0]
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logger.info(
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f"Query: {query}, top_k: {top_k}, cosine: {self.cosine_better_than_threshold}"
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)
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results = self._client.query(
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query=embedding,
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top_k=top_k,
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