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fix score_threshold_enabled name (#1626)

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Co-authored-by: jyong <jyong@dify.ai>
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Jyong 2023-11-27 15:34:45 +08:00 • committed by GitHub
commit 74b2260ba6
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8 changed files with 19 additions and 19 deletions
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4
api/core/tool/dataset_multi_retriever_tool.py
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@ -24,7 +24,7 @@ default_retrieval_model = {
'reranking_model_name': ''
},
'top_k': 2,
'score_threshold_enable': False
'score_threshold_enabled': False
}
@ -216,7 +216,7 @@ class DatasetMultiRetrieverTool(BaseTool):
'embeddings': embeddings,
'score_threshold': retrieval_model[
'score_threshold'] if retrieval_model[
'score_threshold_enable'] else None,
'score_threshold_enabled'] else None,
'top_k': self.top_k,
'reranking_model': retrieval_model[
'reranking_model'] if retrieval_model[

8
api/core/tool/dataset_retriever_tool.py
View file

@ -25,7 +25,7 @@ default_retrieval_model = {
'reranking_model_name': ''
},
'top_k': 2,
'score_threshold_enable': False
'score_threshold_enabled': False
}
@ -110,7 +110,7 @@ class DatasetRetrieverTool(BaseTool):
'query': query,
'top_k': self.top_k,
'score_threshold': retrieval_model['score_threshold'] if retrieval_model[
'score_threshold_enable'] else None,
'score_threshold_enabled'] else None,
'reranking_model': retrieval_model['reranking_model'] if retrieval_model[
'reranking_enable'] else None,
'all_documents': documents,
@ -129,7 +129,7 @@ class DatasetRetrieverTool(BaseTool):
'search_method': retrieval_model['search_method'],
'embeddings': embeddings,
'score_threshold': retrieval_model['score_threshold'] if retrieval_model[
'score_threshold_enable'] else None,
'score_threshold_enabled'] else None,
'top_k': self.top_k,
'reranking_model': retrieval_model['reranking_model'] if retrieval_model[
'reranking_enable'] else None,
@ -148,7 +148,7 @@ class DatasetRetrieverTool(BaseTool):
model_name=retrieval_model['reranking_model']['reranking_model_name']
)
documents = hybrid_rerank.rerank(query, documents,
retrieval_model['score_threshold'] if retrieval_model['score_threshold_enable'] else None,
retrieval_model['score_threshold'] if retrieval_model['score_threshold_enabled'] else None,
self.top_k)
else:
documents = []