| @@ -24,7 +24,7 @@ default_retrieval_model = { | |||
| "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, | |||
| } | |||
| @@ -304,7 +304,7 @@ class CouchbaseVector(BaseVector): | |||
| return docs | |||
| def search_by_full_text(self, query: str, **kwargs: Any) -> list[Document]: | |||
| top_k = kwargs.get("top_k", 2) | |||
| top_k = kwargs.get("top_k", 4) | |||
| try: | |||
| CBrequest = search.SearchRequest.create(search.QueryStringQuery("text:" + query)) | |||
| search_iter = self._scope.search( | |||
| @@ -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, | |||
| @@ -181,7 +181,7 @@ class DatasetMultiRetrieverTool(DatasetRetrieverBaseTool): | |||
| retrieval_method="keyword_search", | |||
| dataset_id=dataset.id, | |||
| query=query, | |||
| top_k=retrieval_model.get("top_k") or 2, | |||
| top_k=retrieval_model.get("top_k") or 4, | |||
| ) | |||
| if documents: | |||
| all_documents.extend(documents) | |||
| @@ -192,7 +192,7 @@ class DatasetMultiRetrieverTool(DatasetRetrieverBaseTool): | |||
| 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, | |||
| @@ -13,7 +13,7 @@ class DatasetRetrieverBaseTool(BaseModel, ABC): | |||
| name: str = "dataset" | |||
| description: str = "use this to retrieve a dataset. " | |||
| tenant_id: str | |||
| top_k: int = 2 | |||
| top_k: int = 4 | |||
| score_threshold: Optional[float] = None | |||
| hit_callbacks: list[DatasetIndexToolCallbackHandler] = [] | |||
| return_resource: bool | |||
| @@ -78,7 +78,7 @@ default_retrieval_model = { | |||
| "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, | |||
| } | |||
| @@ -1149,7 +1149,7 @@ class DocumentService: | |||
| "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, | |||
| } | |||
| @@ -1612,7 +1612,7 @@ class DocumentService: | |||
| search_method=RetrievalMethod.SEMANTIC_SEARCH.value, | |||
| reranking_enable=False, | |||
| reranking_model=RerankingModel(reranking_provider_name="", reranking_model_name=""), | |||
| top_k=2, | |||
| top_k=4, | |||
| score_threshold_enabled=False, | |||
| ) | |||
| # save dataset | |||
| @@ -18,7 +18,7 @@ default_retrieval_model = { | |||
| "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, | |||
| } | |||
| @@ -66,7 +66,7 @@ class HitTestingService: | |||
| retrieval_method=retrieval_model.get("search_method", "semantic_search"), | |||
| dataset_id=dataset.id, | |||
| query=query, | |||
| top_k=retrieval_model.get("top_k", 2), | |||
| top_k=retrieval_model.get("top_k", 4), | |||
| score_threshold=retrieval_model.get("score_threshold", 0.0) | |||
| if retrieval_model["score_threshold_enabled"] | |||
| else 0.0, | |||
| @@ -28,7 +28,7 @@ const ExternalKnowledgeBaseCreate: React.FC<ExternalKnowledgeBaseCreateProps> = | |||
| external_knowledge_api_id: '', | |||
| external_knowledge_id: '', | |||
| external_retrieval_model: { | |||
| top_k: 2, | |||
| top_k: 4, | |||
| score_threshold: 0.5, | |||
| score_threshold_enabled: false, | |||
| }, | |||
| @@ -49,7 +49,7 @@ const TextAreaWithButton = ({ | |||
| const { t } = useTranslation() | |||
| const [isSettingsOpen, setIsSettingsOpen] = useState(false) | |||
| const [externalRetrievalSettings, setExternalRetrievalSettings] = useState({ | |||
| top_k: 2, | |||
| top_k: 4, | |||
| score_threshold: 0.5, | |||
| score_threshold_enabled: false, | |||
| }) | |||
| @@ -233,7 +233,7 @@ const DebugConfigurationContext = createContext<IDebugConfiguration>({ | |||
| reranking_provider_name: '', | |||
| reranking_model_name: '', | |||
| }, | |||
| top_k: 2, | |||
| top_k: 4, | |||
| score_threshold_enabled: false, | |||
| score_threshold: 0.7, | |||
| datasets: { | |||