abadesalex's picture
Update to Qdrant db
47b5f0c
from fastapi import Depends, Request
from transformers import (AutoModel, AutoModelForMaskedLM, AutoTokenizer,
pipeline)
from app.infrastructure.repository.query_search_repository import \
QuerySearchRepository
from app.modules.denseEmbeddings.denseEmbeddings import DenseEmbeddings
from app.modules.hybridSearcher.hybridSearcher import HybridSearcher
from app.modules.querySearch.controllers.querySearch_controller import \
QuerySearchController
from app.modules.querySearch.features.querySearch_feature import \
QuerySearchFeature
from app.modules.questionAnswer.questionAnswer import QuestionAnswering
from app.qdrant import QdrantConnectionDb
def get_qdrant_connection_db() -> QdrantConnectionDb:
return QdrantConnectionDb()
def get_query_search_repository(
qdrant_connection_db: QdrantConnectionDb = Depends(get_qdrant_connection_db),
):
return QuerySearchRepository(qdrant_connection_db)
def get_dense_model(request: Request) -> AutoModel:
return request.scope["state"]["dense_model"]
def get_sparse_model(request: Request) -> AutoModelForMaskedLM:
return request.scope["state"]["sparse_model"]
def get_dense_tokenizer(request: Request) -> AutoTokenizer:
return request.scope["state"]["dense_tokenizer"]
def get_sparse_tokenizer(request: Request) -> AutoTokenizer:
return request.scope["state"]["sparse_tokenizer"]
def get_dense_embeddings(
dense_model: AutoModel = Depends(get_dense_model),
dense_tokenizer: AutoTokenizer = Depends(get_dense_tokenizer),
sparse_model: AutoModelForMaskedLM = Depends(get_sparse_model),
sparse_tokenizer: AutoTokenizer = Depends(get_sparse_tokenizer),
):
return DenseEmbeddings(
dense_model=dense_model,
dense_tokenizer=dense_tokenizer,
sparse_model=sparse_model,
sparse_tokenizer=sparse_tokenizer,
)
def get_qa_pipeline(request: Request):
return request.scope["state"]["qa_pipeline"]
def get_question_ansering(qa_pipline: pipeline = Depends(get_qa_pipeline)):
return QuestionAnswering(qa_pipline)
def get_hybrid_searcher(
dense_embeddings: DenseEmbeddings = Depends(get_dense_embeddings),
query_search_repository: QuerySearchRepository = Depends(
get_query_search_repository
),
):
return HybridSearcher(dense_embeddings, query_search_repository)
def get_query_search_feature(
qa_pipeline: pipeline = Depends(get_qa_pipeline),
hybrid_searcher: HybridSearcher = Depends(get_hybrid_searcher),
question_answering: QuestionAnswering = Depends(get_question_ansering),
):
return QuerySearchFeature(qa_pipeline, hybrid_searcher, question_answering)
def get_query_search_controller(
query_search_feature: QuerySearchFeature = Depends(get_query_search_feature),
):
return QuerySearchController(query_search_feature)