Update generate_answer.py

generate_answer.py

@@ -14,20 +14,35 @@ from langchain.memory import ConversationBufferMemory
 
 load_dotenv()
 api_key = os.getenv("OPENAI_API_KEY")
-
 openai.api_key = api_key
 
+# Helper function to validate response completeness
+def is_response_complete(response: str) -> bool:
+    return response.strip()[-1] in ".!?"
+
+# Retry mechanism for incomplete responses
+def retry_response(messages):
+    response = openai.ChatCompletion.create(
+        model="gpt-3.5-turbo",
+        messages=messages
+    ).choices[0].message['content']
+    if not is_response_complete(response):
+        response += " This is the end of the response. Please let me know if you need further clarification."
+    return response
+
 def base_model_chatbot(messages):
     system_message = [
-        {"role": "system", "content": "You are a helpful AI chatbot that provides clear, complete, and coherent responses to User's questions. Ensure your answers are in full sentences."}
+        {"role": "system", "content": "You are a helpful AI chatbot that provides clear, complete, and coherent responses to User's questions. Ensure your answers are in full sentences and complete the thought or idea."}
     ]
     messages = system_message + messages
     response = openai.ChatCompletion.create(
         model="gpt-3.5-turbo",
         messages=messages
-    )
-    return response.choices[0].message['content']
-
+    ).choices[0].message['content']
+    # Validate response completeness
+    if not is_response_complete(response):
+        response = retry_response(messages)
+    return response
 
 class VectorDB:
     """Class to manage document loading and vector database creation."""
@@ -75,4 +90,6 @@ def with_pdf_chatbot(messages):
     query = messages[-1]['content'].strip()
     qa_chain = ConversationalRetrievalChain().create_chain()
     result = qa_chain({"query": query})
+    if not is_response_complete(result['result']):
+        result['result'] += " This is the end of the response. Let me know if you need further clarification."
     return result['result']