Undoing debug

app.py

@@ -31,17 +31,16 @@ def bot(history, system_prompt=""):
     top_k = 5
     query = history[-1][0]
 
-    # logger.warning('Retrieving documents...')
-    # # Retrieve documents relevant to query
-    # document_start = perf_counter()
-    # documents = qd_retriever.retrieve(query, top_k=top_k)
-    # document_time = document_start - perf_counter()
-    # logger.warning('Finished Retrieving documents...')
-    #
-    # # Create Prompt
-    # prompt = template.render(documents=documents, query=query)
-    # prompt_html = template_html.render(documents=documents, query=query)
-    prompt = query
+    logger.warning('Retrieving documents...')
+    # Retrieve documents relevant to query
+    document_start = perf_counter()
+    documents = qd_retriever.retrieve(query, top_k=top_k)
+    document_time = document_start - perf_counter()
+    logger.warning(f'Finished Retrieving documents in {round(document_time, 2)} seconds...')
+
+    # Create Prompt
+    prompt = template.render(documents=documents, query=query)
+    prompt_html = template_html.render(documents=documents, query=query)
     logger.warning(prompt)
 
     history[-1][1] = ""

backend/semantic_search.py

@@ -1,33 +1,31 @@
-# 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")
+import time
+import logging
+from qdrant_haystack import QdrantDocumentStore
+from haystack.nodes import EmbeddingRetriever
+from pathlib import Path
 
-qd_retriever = None
+# 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")

requirements.txt

@@ -3,4 +3,6 @@ farm-haystack[inference]==1.20.1
 qdrant-haystack==1.0.10
 ipywidgets==8.1.1
 tqdm==4.66.1
-aiohttp==3.8.6
+aiohttp==3.8.6
+huggingface-hub==0.17.3
+transformers==4.34.1