Update app.py

app.py

@@ -1,11 +1,15 @@
 import os
 import faiss
+import logging
 import streamlit as st
 from langchain.embeddings import HuggingFaceEmbeddings
 from langchain.vectorstores import FAISS
 from langchain.chains import RetrievalQA
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
 
+# Configure logging
+logging.basicConfig(level=logging.DEBUG)
+
 def load_faiss_index(index_path):
     """
     Load a FAISS index from a specified path.
@@ -17,14 +21,18 @@ def load_faiss_index(index_path):
     - faiss.Index: Loaded FAISS index object.
     """
     if not os.path.exists(index_path):
+        logging.error(f"FAISS index not found at {index_path}. Please create the index first.")
         st.error(f"FAISS index not found at {index_path}. Please create the index first.")
         raise FileNotFoundError(f"FAISS index not found at {index_path}.")
     
     try:
+        logging.info(f"Attempting to load FAISS index from {index_path}.")
         index = faiss.read_index(index_path)
+        logging.info("FAISS index loaded successfully.")
         st.success("FAISS index loaded successfully.")
         return index
     except Exception as e:
+        logging.error(f"Failed to load FAISS index: {e}")
         st.error(f"Failed to load FAISS index: {e}")
         raise
 
@@ -72,6 +80,7 @@ def process_answer(question):
         answer = result['result']
         return answer, result
     except Exception as e:
+        logging.error(f"An error occurred while processing the answer: {e}")
         st.error(f"An error occurred while processing the answer: {e}")
         return "An error occurred while processing your request.", {}