Update app.py

app.py

@@ -1,8 +1,16 @@
 import chainlit as cl
 from pydantic import BaseModel, Field
+from dotenv import load_dotenv
 import instructor
 from openai import OpenAI
 import os
+import logging
+
+load_dotenv()
+
+# Set up logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
 
 # Patch the OpenAI client with Instructor
 client = instructor.from_openai(OpenAI(api_key=os.environ['OPENAI_API_KEY']))
@@ -48,41 +56,45 @@ def revise_architecture(proposed_architecture: str) -> PropositionWithRevision:
         ],
     )
 
-
 # Define the Chainlit message handler
 @cl.on_message
 async def main(message: cl.Message):
+    try:
+        user_proposal = message.content
 
-    user_proposal = message.content
-
-    user_proposal_details = extract_user_proposal_details(user_proposal)
-    
-    proposed_architecture = generate_proposed_architecture(user_proposal_details.proposal)
-    
-    await cl.Message(
-        content=f"Proposed Architecture:\n{proposed_architecture.proposed_architecture}"
-    ).send()
-
-    feedback_message = await cl.AskUserMessage(content="What do you think about this proposed plan and alleged architecture?", timeout=60).send()
-    if feedback_message:
-        human_feedback_of_proposed_plan = feedback_message["output"]
-    
-        revised_architecture = revise_architecture(proposed_architecture.proposed_architecture)
-    
+        user_proposal_details = extract_user_proposal_details(user_proposal)
+        
+        proposed_architecture = generate_proposed_architecture(user_proposal_details.proposal)
+        
         await cl.Message(
-            content=f"Revised Architecture:\n{revised_architecture.revised_proposed_architecture}"
+            content=f"Proposed Architecture:\n{proposed_architecture.proposed_architecture}"
         ).send()
 
-        with open("output.md", "w") as output_file:
-            output_file.write("# User Proposal\n")
-            output_file.write(user_proposal_details.proposal + "\n\n")
-            output_file.write("# Proposed Architecture\n")
-            output_file.write(proposed_architecture.proposed_architecture + "\n\n")
-            output_file.write("# Revised Architecture\n")
-            output_file.write(revised_architecture.revised_proposed_architecture + "\n")
+        feedback_message = await cl.AskUserMessage(content="What do you think about this proposed plan and alleged architecture?", timeout=60).send()
+        if feedback_message:
+            human_feedback_of_proposed_plan = feedback_message["output"]
+        
+            revised_architecture = revise_architecture(proposed_architecture.proposed_architecture)
+        
+            await cl.Message(
+                content=f"Revised Architecture:\n{revised_architecture.revised_proposed_architecture}"
+            ).send()
+
+            with open("output.md", "w") as output_file:
+                output_file.write("# User Proposal\n")
+                output_file.write(user_proposal_details.proposal + "\n\n")
+                output_file.write("# Proposed Architecture\n")
+                output_file.write(proposed_architecture.proposed_architecture + "\n\n")
+                output_file.write("# Revised Architecture\n")
+                output_file.write(revised_architecture.revised_proposed_architecture + "\n")
 
+            await cl.Message(
+                content="The results have been saved to output.md"
+            ).send()
+    except Exception as e:
+        logger.error(f"An error occurred: {e}")
         await cl.Message(
-            content="The results have been saved to output.md"
+            content="An error occurred while processing your request. Please try again later."
         ).send()
 
 # Load the starters