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import logging
import time
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, DocumentSegment
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: dict,
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=cls.escape_query_for_search(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(dataset, query, all_documents)
@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 cls.compact_external_retrieve_response(dataset, query, all_documents)
@classmethod
def compact_retrieve_response(cls, dataset: Dataset, query: str, documents: list[Document]):
records = []
for document in documents:
index_node_id = document.metadata["doc_id"]
segment = (
db.session.query(DocumentSegment)
.filter(
DocumentSegment.dataset_id == dataset.id,
DocumentSegment.enabled == True,
DocumentSegment.status == "completed",
DocumentSegment.index_node_id == index_node_id,
)
.first()
)
if not segment:
continue
record = {
"segment": segment,
"score": document.metadata.get("score", None),
}
records.append(record)
return {
"query": {
"content": query,
},
"records": records,
}
@classmethod
def compact_external_retrieve_response(cls, dataset: Dataset, query: str, documents: list):
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,
}
@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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