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							- import logging
 
- import time
 
- from typing import Any
 
- from core.rag.datasource.retrieval_service import RetrievalService
 
- from core.rag.models.document import Document
 
- from core.rag.retrieval.retrieval_methods import RetrievalMethod
 
- from extensions.ext_database import db
 
- from models.account import Account
 
- from models.dataset import Dataset, DatasetQuery
 
- default_retrieval_model = {
 
-     "search_method": RetrievalMethod.SEMANTIC_SEARCH.value,
 
-     "reranking_enable": False,
 
-     "reranking_model": {"reranking_provider_name": "", "reranking_model_name": ""},
 
-     "top_k": 2,
 
-     "score_threshold_enabled": False,
 
- }
 
- class HitTestingService:
 
-     @classmethod
 
-     def retrieve(
 
-         cls,
 
-         dataset: Dataset,
 
-         query: str,
 
-         account: Account,
 
-         retrieval_model: Any,  # FIXME drop this any
 
-         external_retrieval_model: dict,
 
-         limit: int = 10,
 
-     ) -> dict:
 
-         if dataset.available_document_count == 0 or dataset.available_segment_count == 0:
 
-             return {
 
-                 "query": {
 
-                     "content": query,
 
-                     "tsne_position": {"x": 0, "y": 0},
 
-                 },
 
-                 "records": [],
 
-             }
 
-         start = time.perf_counter()
 
-         # get retrieval model , if the model is not setting , using default
 
-         if not retrieval_model:
 
-             retrieval_model = dataset.retrieval_model or default_retrieval_model
 
-         all_documents = RetrievalService.retrieve(
 
-             retrieval_method=retrieval_model.get("search_method", "semantic_search"),
 
-             dataset_id=dataset.id,
 
-             query=query,
 
-             top_k=retrieval_model.get("top_k", 2),
 
-             score_threshold=retrieval_model.get("score_threshold", 0.0)
 
-             if retrieval_model["score_threshold_enabled"]
 
-             else 0.0,
 
-             reranking_model=retrieval_model.get("reranking_model", None)
 
-             if retrieval_model["reranking_enable"]
 
-             else None,
 
-             reranking_mode=retrieval_model.get("reranking_mode") or "reranking_model",
 
-             weights=retrieval_model.get("weights", None),
 
-         )
 
-         end = time.perf_counter()
 
-         logging.debug(f"Hit testing retrieve in {end - start:0.4f} seconds")
 
-         dataset_query = DatasetQuery(
 
-             dataset_id=dataset.id, content=query, source="hit_testing", created_by_role="account", created_by=account.id
 
-         )
 
-         db.session.add(dataset_query)
 
-         db.session.commit()
 
-         return cls.compact_retrieve_response(query, all_documents)  # type: ignore
 
-     @classmethod
 
-     def external_retrieve(
 
-         cls,
 
-         dataset: Dataset,
 
-         query: str,
 
-         account: Account,
 
-         external_retrieval_model: dict,
 
-     ) -> dict:
 
-         if dataset.provider != "external":
 
-             return {
 
-                 "query": {"content": query},
 
-                 "records": [],
 
-             }
 
-         start = time.perf_counter()
 
-         all_documents = RetrievalService.external_retrieve(
 
-             dataset_id=dataset.id,
 
-             query=cls.escape_query_for_search(query),
 
-             external_retrieval_model=external_retrieval_model,
 
-         )
 
-         end = time.perf_counter()
 
-         logging.debug(f"External knowledge hit testing retrieve in {end - start:0.4f} seconds")
 
-         dataset_query = DatasetQuery(
 
-             dataset_id=dataset.id, content=query, source="hit_testing", created_by_role="account", created_by=account.id
 
-         )
 
-         db.session.add(dataset_query)
 
-         db.session.commit()
 
-         return dict(cls.compact_external_retrieve_response(dataset, query, all_documents))
 
-     @classmethod
 
-     def compact_retrieve_response(cls, query: str, documents: list[Document]):
 
-         records = RetrievalService.format_retrieval_documents(documents)
 
-         return {
 
-             "query": {
 
-                 "content": query,
 
-             },
 
-             "records": [record.model_dump() for record in records],
 
-         }
 
-     @classmethod
 
-     def compact_external_retrieve_response(cls, dataset: Dataset, query: str, documents: list) -> dict[Any, Any]:
 
-         records = []
 
-         if dataset.provider == "external":
 
-             for document in documents:
 
-                 record = {
 
-                     "content": document.get("content", None),
 
-                     "title": document.get("title", None),
 
-                     "score": document.get("score", None),
 
-                     "metadata": document.get("metadata", None),
 
-                 }
 
-                 records.append(record)
 
-             return {
 
-                 "query": {"content": query},
 
-                 "records": records,
 
-             }
 
-         return {"query": {"content": query}, "records": []}
 
-     @classmethod
 
-     def hit_testing_args_check(cls, args):
 
-         query = args["query"]
 
-         if not query or len(query) > 250:
 
-             raise ValueError("Query is required and cannot exceed 250 characters")
 
-     @staticmethod
 
-     def escape_query_for_search(query: str) -> str:
 
-         return query.replace('"', '\\"')
 
 
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