backend/semantic_search.py

# import time
# import logging
# from qdrant_haystack import QdrantDocumentStore
# from haystack.nodes import EmbeddingRetriever
# from pathlib import Path
#
# # Setting up the logging
# logging.basicConfig(level=logging.INFO)
# logger = logging.getLogger(__name__)
#
# # Start the timer for loading the QdrantDocumentStore
# start_time = time.perf_counter()
#
# proj_dir = Path(__file__).parents[1]
# qd_document_store = QdrantDocumentStore(path=str(proj_dir/'Qdrant'), index='RAGDemo')
#
# # Log the time taken to load the QdrantDocumentStore
# document_store_loading_time = time.perf_counter() - start_time
# logger.info(f"Time taken to load QdrantDocumentStore: {document_store_loading_time:.6f} seconds")
#
# # Start the timer for loading the EmbeddingRetriever
# start_time = time.perf_counter()
#
# qd_retriever = EmbeddingRetriever(document_store=qd_document_store,
#                                   embedding_model="BAAI/bge-base-en-v1.5",
#                                   model_format="sentence_transformers",
#                                   use_gpu=False)
#
# # Log the time taken to load the EmbeddingRetriever
# retriever_loading_time = time.perf_counter() - start_time
# logger.info(f"Time taken to load EmbeddingRetriever: {retriever_loading_time:.6f} seconds")

qd_retriever = None