Update app.py

app.py

@@ -61,12 +61,13 @@ def preprocess_response(response: str) -> str:
 
 def shorten_response(response: str) -> str:
     """Uses the Zephyr model to shorten and refine the response."""
-    messages = [{"role": "system", "content": "Greet, Shorten and refine this response"}, {"role": "user", "content": response}]
-    result = client.chat_completion(messages, max_tokens=512, temperature=0.5, top_p=0.9)
+    messages = [{"role": "system", "content": "Shorten and refine this response"}, {"role": "user", "content": response}]
+    result = client.chat_completion(messages, max_tokens=512, temperature=0.2, top_p=0.9)
     return result.choices[0].message['content'].strip()
-
+    
+#You guide customers through understanding and resolving CAPA-related queries with clarity and expertise. When customers inquire about CAPA information for a specific issue, you provide precise details, including the relevant CAPA ID. Address one query at a time and ask follow-up questions to clarify or deepen understanding, maintaining a supportive and solution-oriented tone throughout. Remember to give CAPA Name, CAPA count, Capa Title and problem summary for each query.
 def respond(message: str, history: List[Tuple[str, str]]):
-    system_message = "You're an experienced and knowledgeable CAPA tickets analyst assistant. You guide customers through understanding and resolving CAPA-related queries with clarity and expertise. When customers inquire about CAPA information for a specific issue, you provide precise details, including the relevant CAPA ID. Address one query at a time and ask follow-up questions to clarify or deepen understanding, maintaining a supportive and solution-oriented tone throughout. Remember to give CAPA Name, CAPA count, Capa Title and problem summary for each query."
+    system_message = "You're an experienced and knowledgeable CAPA tickets analyst assistant. Just give the Summary of the complaint. "
     messages = [{"role": "system", "content": system_message}]
 
     for val in history:
@@ -78,7 +79,7 @@ def respond(message: str, history: List[Tuple[str, str]]):
     messages.append({"role": "user", "content": message})
 
     # RAG - Retrieve relevant documents if the query suggests exercises or specific information
-    if any(keyword in message.lower() for keyword in ["exercise", "technique", "information", "guide", "help", "how to", "freezer","tell me", "how","tell me","how many","capa","department","product","issue","issues","find","which"]):
+    if any(keyword in message.lower() for keyword in ["exercise", "technique", "information", "guide", "help", "how to","tell me", "how","tell me","how many","capa","department","product","issue","issues","find","which"]):
         retrieved_docs = app.search_documents(message)
         context = "\n".join(retrieved_docs)
         if context.strip():