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@ -59,7 +59,7 @@ class AnnotationReplyFeature:
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documents = vector.search_by_vector(
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query=query,
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k=1,
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top_k=1,
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score_threshold=score_threshold,
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filter={
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'group_id': [dataset.id]
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@ -101,7 +101,7 @@ class RetrievalService:
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documents = keyword.search(
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query,
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k=top_k
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top_k=top_k
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)
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all_documents.extend(documents)
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@ -121,7 +121,7 @@ class RetrievalService:
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documents = vector.search_by_vector(
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query,
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search_type='similarity_score_threshold',
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k=top_k,
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top_k=top_k,
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score_threshold=score_threshold,
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filter={
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'group_id': [dataset.id]
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@ -133,8 +133,9 @@ class HitTestingService:
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if embedding_length <= 1:
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return [{'x': 0, 'y': 0}]
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concatenate_data = np.array(embeddings).reshape(embedding_length, -1)
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# concatenate_data = np.concatenate(embeddings)
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noise = np.random.normal(0, 1e-4, np.array(embeddings).shape)
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concatenate_data = np.array(embeddings) + noise
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concatenate_data = concatenate_data.reshape(embedding_length, -1)
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perplexity = embedding_length / 2 + 1
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if perplexity >= embedding_length:
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