Update app.py

app.py

@@ -295,58 +295,64 @@ def respond(message, history, model, temperature, num_calls, use_web_search, sel
     logging.info(f"User Query: {message}")
     logging.info(f"Model Used: {model}")
     logging.info(f"Search Type: {'Web Search' if use_web_search else 'PDF Search'}")
-
     logging.info(f"Selected Documents: {selected_docs}")
 
     try:
         if use_web_search:
+            logging.info("Entering web search flow")
             for main_content, sources in get_response_with_search(message, model, num_calls=num_calls, temperature=temperature):
                 response = f"{main_content}\n\n{sources}"
-                first_line = response.split('\n')[0] if response else ''
-#                logging.info(f"Generated Response (first line): {first_line}")
+                logging.info(f"Generated Response (first 100 chars): {response[:100]}...")
                 yield response
         else:
+            logging.info("Entering PDF search flow")
             embed = get_embeddings()
             if os.path.exists("faiss_database"):
+                logging.info("FAISS database exists, loading it")
                 database = FAISS.load_local("faiss_database", embed, allow_dangerous_deserialization=True)
                 retriever = database.as_retriever()
                 
+                logging.info("Attempting to retrieve relevant documents")
+                try:
+                    relevant_docs = retriever.invoke(message)
+                    logging.info(f"Retrieved {len(relevant_docs)} relevant documents")
+                except Exception as e:
+                    logging.error(f"Error retrieving relevant documents: {str(e)}")
+                    yield f"An error occurred while retrieving relevant documents: {str(e)}"
+                    return
+                
                 # Filter relevant documents based on user selection
-                all_relevant_docs = retriever.get_relevant_documents(message)
-                relevant_docs = [doc for doc in all_relevant_docs if doc.metadata["source"] in selected_docs]
+                filtered_docs = [doc for doc in relevant_docs if doc.metadata["source"] in selected_docs]
+                logging.info(f"Filtered to {len(filtered_docs)} documents based on user selection")
                 
-                if not relevant_docs:
+                if not filtered_docs:
+                    logging.warning("No relevant information found in the selected documents")
                     yield "No relevant information found in the selected documents. Please try selecting different documents or rephrasing your query."
                     return
 
-                context_str = "\n".join([doc.page_content for doc in relevant_docs])
+                context_str = "\n".join([doc.page_content for doc in filtered_docs])
+                logging.info(f"Total context length: {len(context_str)}")
             else:
+                logging.warning("No FAISS database found")
                 context_str = "No documents available."
                 yield "No documents available. Please upload PDF documents to answer questions."
                 return
             
             if model == "@cf/meta/llama-3.1-8b-instruct":
-                # Use Cloudflare API
+                logging.info("Using Cloudflare API")
                 for partial_response in get_response_from_cloudflare(prompt="", context=context_str, query=message, num_calls=num_calls, temperature=temperature, search_type="pdf"):
-                    first_line = partial_response.split('\n')[0] if partial_response else ''
-                    logging.info(f"Generated Response (first line): {first_line}")
+                    logging.info(f"Generated Response (first 100 chars): {partial_response[:100]}...")
                     yield partial_response
             else:
-                # Use Hugging Face API
+                logging.info("Using Hugging Face API")
                 for partial_response in get_response_from_pdf(message, model, selected_docs, num_calls=num_calls, temperature=temperature):
-                    first_line = partial_response.split('\n')[0] if partial_response else ''
-                    logging.info(f"Generated Response (first line): {first_line}")
+                    logging.info(f"Generated Response (first 100 chars): {partial_response[:100]}...")
                     yield partial_response
     except Exception as e:
-        logging.error(f"Error with {model}: {str(e)}")
-        if "microsoft/Phi-3-mini-4k-instruct" in model:
-            logging.info("Falling back to Mistral model due to Phi-3 error")
-            fallback_model = "mistralai/Mistral-7B-Instruct-v0.3"
-            yield from respond(message, history, fallback_model, temperature, num_calls, use_web_search, selected_docs)
-        else:
-            yield f"An error occurred with the {model} model: {str(e)}. Please try again or select a different model."
+        logging.error(f"Unexpected error in respond function: {str(e)}")
+        yield f"An unexpected error occurred: {str(e)}"
 
-logging.basicConfig(level=logging.DEBUG)
+    logging.info("Finished respond function")
 
 def get_response_from_cloudflare(prompt, context, query, num_calls=3, temperature=0.2, search_type="pdf"):
     headers = {