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fix:hard-coded top-k fallback issue. (#24879)

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Frederick2313072
2025-09-01 15:46:37 +08:00
committed by GitHub
parent d41d4deaac
commit 5b3cc560d5
11 changed files with 16 additions and 16 deletions
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6
api/core/rag/retrieval/dataset_retrieval.py
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@ -65,7 +65,7 @@ default_retrieval_model: dict[str, Any] = {
"search_method": RetrievalMethod.SEMANTIC_SEARCH.value,
"reranking_enable": False,
"reranking_model": {"reranking_provider_name": "", "reranking_model_name": ""},
"top_k": 2,
"top_k": 4,
"score_threshold_enabled": False,
}
@ -647,7 +647,7 @@ class DatasetRetrieval:
retrieval_method=retrieval_model["search_method"],
dataset_id=dataset.id,
query=query,
top_k=retrieval_model.get("top_k") or 2,
top_k=retrieval_model.get("top_k") or 4,
score_threshold=retrieval_model.get("score_threshold", 0.0)
if retrieval_model["score_threshold_enabled"]
else 0.0,
@ -743,7 +743,7 @@ class DatasetRetrieval:
tool = DatasetMultiRetrieverTool.from_dataset(
dataset_ids=[dataset.id for dataset in available_datasets],
tenant_id=tenant_id,
top_k=retrieve_config.top_k or 2,
top_k=retrieve_config.top_k or 4,
score_threshold=retrieve_config.score_threshold,
hit_callbacks=[hit_callback],
return_resource=return_resource,