Update app.py

app.py

@@ -731,6 +731,10 @@ async def api_info():
 # ============================================================================
 
 async def generate_welcome_closing_messages(lead_data: Dict[str, Any]) -> Dict[str, str]:
+    class structure(BaseModel):
+        welcome_message: str = Field(description="Welcome message for the candidate")
+        closing_message: str = Field(description="Closing message for the candidate")
+
     """Generate personalized welcome and closing messages using LLM based on candidate details"""
     
     if not LANGCHAIN_AVAILABLE:
@@ -747,6 +751,7 @@ async def generate_welcome_closing_messages(lead_data: Dict[str, Any]) -> Dict[s
             temperature=0.7,
             openai_api_key=openai_api_key
         )
+        str_llm = llm.with_structured_output(structure)
         
         # Extract relevant information from lead data
         first_name = lead_data.get("first_name", "")
@@ -758,7 +763,7 @@ async def generate_welcome_closing_messages(lead_data: Dict[str, Any]) -> Dict[s
         
         # Create a summary of the candidate's background
         candidate_info = f"""
-        Name: {first_name} {last_name}
+        Name: {first_name}
         Company: {company_name}
         Location: {location}
         Title: {title}
@@ -776,13 +781,7 @@ async def generate_welcome_closing_messages(lead_data: Dict[str, Any]) -> Dict[s
         - Reference their specific background/company/role when possible
         - Keep messages concise and engaging
         - Make them feel valued and understood
-        
-        Respond with ONLY a JSON object:
-        {
-            "welcome_message": "Personalized welcome message here",
-            "closing_message": "Personalized closing message here"
-        }
-        
+         
         IMPORTANT: Respond with ONLY valid JSON. No additional text."""
         
         prompt_template = ChatPromptTemplate.from_messages([
@@ -791,22 +790,13 @@ async def generate_welcome_closing_messages(lead_data: Dict[str, Any]) -> Dict[s
         ])
         
         messages = prompt_template.format_messages(candidate_info=candidate_info)
-        response = await llm.ainvoke(messages)
+        response = await str_llm.ainvoke(messages)
         
         try:
-            content = response.content.strip()
-            
-            if content.startswith("```json"):
-                content = content[7:]
-            if content.endswith("```"):
-                content = content[:-3]
-            
-            content = content.strip()
-            parsed_data = json.loads(content)
             
             return {
-                "welcome_message": parsed_data.get("welcome_message", ""),
-                "closing_message": parsed_data.get("closing_message", "")
+                "welcome_message": response.welcome_message,
+                "closing_message": response.closing_message
             }
             
         except Exception as parse_error: