Update app.py

app.py

@@ -304,95 +304,42 @@ chain_neo4j = (
 
 
 
-# def generate_answer(message, choice, retrieval_mode):
-#     logging.debug(f"generate_answer called with choice: {choice} and retrieval_mode: {retrieval_mode}")
-
-#     # Check if the question is about hotels
-#     if "hotel" in message.lower() and "birmingham" in message.lower():
-#         response = fetch_google_hotels()
-#         return response, extract_addresses(response)
-    
-#     # Check if the question is about restaurants
-#     if "restaurant" in message.lower() and "birmingham" in message.lower():
-#         response = fetch_yelp_restaurants()
-#         return response, extract_addresses(response)
-#     # Check if the question is about flights
-#     if "flight" in message.lower() and ("JFK" in message or "BHM" in message):
-#         response = fetch_google_flights()
-#         return response, extract_addresses(response)
-
-#     prompt_template = QA_CHAIN_PROMPT_1 if choice == "Details" else QA_CHAIN_PROMPT_2
-
-#     if retrieval_mode == "VDB":
-#         qa_chain = RetrievalQA.from_chain_type(
-#             llm=chat_model,
-#             chain_type="stuff",
-#             retriever=retriever,
-#             chain_type_kwargs={"prompt": prompt_template}
-#         )
-#         response = qa_chain({"query": message})
-#         logging.debug(f"Vector response: {response}")
-#         return response['result'], extract_addresses(response['result'])
-#     elif retrieval_mode == "KGF":
-#         response = chain_neo4j.invoke({"question": message})
-#         logging.debug(f"Knowledge-Graph response: {response}")
-#         return response, extract_addresses(response)
-#     else:
-#         return "Invalid retrieval mode selected.", []
-
 def generate_answer(message, choice, retrieval_mode):
     logging.debug(f"generate_answer called with choice: {choice} and retrieval_mode: {retrieval_mode}")
 
-    intro = ""
-    response = ""
+    # Check if the question is about hotels
     if "hotel" in message.lower() and "birmingham" in message.lower():
-        intro = "Here are the top Hotels in Birmingham:\n\n"
         response = fetch_google_hotels()
-    elif "restaurant" in message.lower() and "birmingham" in message.lower():
-        intro = "Here are the top Restaurants in Birmingham:\n\n"
+        return response, extract_addresses(response)
+    
+    # Check if the question is about restaurants
+    if "restaurant" in message.lower() and "birmingham" in message.lower():
         response = fetch_yelp_restaurants()
-    elif "flight" in message.lower() and ("JFK" in message or "BHM" in message):
-        intro = "Here are some available flights for today:\n\n"
+        return response, extract_addresses(response)
+    # Check if the question is about flights
+    if "flight" in message.lower() and "birmingham" in message.lower():
         response = fetch_google_flights()
-    else:
-        prompt_template = QA_CHAIN_PROMPT_1 if choice == "Details" else QA_CHAIN_PROMPT_2
-        if retrieval_mode == "VDB":
-            qa_chain = RetrievalQA.from_chain_type(
-                llm=chat_model,
-                chain_type="stuff",
-                retriever=retriever,
-                chain_type_kwargs={"prompt": prompt_template}
-            )
-            response = qa_chain({"query": message})
-            logging.debug(f"Vector response: {response}")
-            response = response['result']
-        elif retrieval_mode == "KGF":
-            response = chain_neo4j.invoke({"question": message})
-            logging.debug(f"Knowledge-Graph response: {response}")
-        else:
-            response = "Invalid retrieval mode selected."
+        return response, extract_addresses(response)
 
-    # Assign numbers to each item in the response and format it
-    response_lines = response.splitlines()
-    formatted_response = ""
-    item_counter = 1
+    prompt_template = QA_CHAIN_PROMPT_1 if choice == "Details" else QA_CHAIN_PROMPT_2
 
-    for i in range(0, len(response_lines), 7):  # Assuming 7 lines per restaurant/hotel/flight entry
-        formatted_response += f"{item_counter}. {response_lines[i]}\n"  # Number and name
-        if i + 1 < len(response_lines):
-            formatted_response += f"   {response_lines[i + 1]}\n"  # Link and location
-        if i + 2 < len(response_lines):
-            formatted_response += f"   {response_lines[i + 2]}\n"  # Contact number
-        if i + 3 < len(response_lines):
-            formatted_response += f"   {response_lines[i + 3]}\n"  # Rating
-        if i + 4 < len(response_lines):
-            formatted_response += f"   {response_lines[i + 4]}\n"  # Snippet
-        if i + 5 < len(response_lines):
-            formatted_response += f"   {response_lines[i + 5]}\n"  # Divider
-        formatted_response += "\n"  # Extra line between items
-        item_counter += 1
+    if retrieval_mode == "VDB":
+        qa_chain = RetrievalQA.from_chain_type(
+            llm=chat_model,
+            chain_type="stuff",
+            retriever=retriever,
+            chain_type_kwargs={"prompt": prompt_template}
+        )
+        response = qa_chain({"query": message})
+        logging.debug(f"Vector response: {response}")
+        return response['result'], extract_addresses(response['result'])
+    elif retrieval_mode == "KGF":
+        response = chain_neo4j.invoke({"question": message})
+        logging.debug(f"Knowledge-Graph response: {response}")
+        return response, extract_addresses(response)
+    else:
+        return "Invalid retrieval mode selected.", []
 
-    return intro + formatted_response.strip(), extract_addresses(response)
 
 
 
@@ -1143,10 +1090,10 @@ def fetch_google_flights(departure_id="JFK", arrival_id="BHM", outbound_date="20
 
     params = {
       "engine": "google_flights",
-      "departure_id": "PEK",
-      "arrival_id": "AUS",
-      "outbound_date": "2024-08-14",
-      "return_date": "2024-08-20",
+      "departure_id": departure_id,
+      "arrival_id": arrival_id,
+      "outbound_date": outbound_date,
+      "return_date": return_date,
       "currency": "USD",
       "hl": "en",
       "api_key": os.getenv("SERP_API")  # Replace with your actual API key