Update app.py

app.py

@@ -10,6 +10,7 @@ load_dotenv()
 
 # Configure 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']))
@@ -116,7 +117,6 @@ def format_template(template, **kwargs):
 
 # Define functions
 def llm_call(user_prompt, system_prompt=None):
-
     messages = [
         {"role": "user", "content": user_prompt}
     ] if system_prompt is None else [
@@ -125,62 +125,72 @@ def llm_call(user_prompt, system_prompt=None):
     ]
 
     try:
-        return client.chat.completions.create(
+        response = client.chat.completions.create(
             model="gpt-4-turbo-preview",
             response_model=None,
             messages=messages,
         )
+        return response
     except Exception as e:
-        logging.error(f"Error during LLM call: {e}")
+        logger.error(f"Error during LLM call: {e}")
         return None
 
-# Define the Chainlit message handler
 @cl.on_chat_start
 async def start():
-
-    # Welcome message
-    wel_msg = cl.Message(content="Welcome to Build Advisor!\n\nBuild Advisor creates plan, production requirement spec and implementation for your AI application idea.\nQuickly create a PoC so you can determine whether an idea is worth starting, worth investing time and/or money in.")
-    await wel_msg.send()
-
-    # Ask user for AI application / business idea
-    res = await cl.AskUserMessage(content="What is your AI application/business idea?", timeout=30).send()
-    if res:
-        await wel_msg.remove()
-        await cl.Message(
-            content=f"User Proposal: {res['output']}.\n\nStarting...",
-        ).send()
-
-        user_proposal = res['output']
-
-        prd_sys1 = format_template(PRD_PROMPT_TEMPLATE, user_proposal=user_proposal) # system message to create PRD
-        prd_response = llm_call(user_prompt=user_proposal, system_prompt=prd_sys1)
-        
-        if prd_response:
-            prd_response_raw = prd_response.choices[0].message.content
-
-            # send PRD output to UI
-            prd_msg = cl.Message(content=prd_response_raw)
-            await prd_msg.send()
-
-            prd_json = json.dumps({"objective_goal": "Develop a chatbot...", "features": [], "ux_flow_design_notes": "...", "system_environment_requirements": "...", "assumptions": [], "constraints": [], "dependencies": [], "prompt_engineering_practices": "...", "task_composability": "...", "review_approval_process": "..."})
-            designer_prompt = format_template(DESIGNER_PROMPT_TEMPLATE, prd_response_raw=prd_response_raw, prd_json=prd_json, user_proposal=user_proposal)
-            designer_response = llm_call(designer_prompt)
-
-            if designer_response:
-                designer_output = designer_response.choices[0].message.content
-
-                designer_output_msg = cl.Message(content=designer_output)
-                await designer_output_msg.send()
-
-                # update outputs in UI
-                for secs in [1, 5, 10, 20]:
-                    await cl.sleep(secs)
-                    await prd_msg.update()
-                    await designer_output_msg.update()
+    try:
+        # Welcome message
+        wel_msg = cl.Message(content="Welcome to Build Advisor!\n\nBuild Advisor creates plan, production requirement spec and implementation for your AI application idea.\nQuickly create a PoC so you can determine whether an idea is worth starting, worth investing time and/or money in.")
+        await wel_msg.send()
+
+        # Ask user for AI application / business idea
+        res = await cl.AskUserMessage(content="What is your AI application/business idea?", timeout=30).send()
+        if res:
+            await wel_msg.remove()
+            await cl.Message(
+                content=f"User Proposal: {res['output']}.\n\nStarting...",
+            ).send()
+
+            user_proposal = res['output']
+
+            prd_sys1 = format_template(PRD_PROMPT_TEMPLATE, user_proposal=user_proposal) # system message to create PRD
+            prd_response = llm_call(user_prompt=user_proposal, system_prompt=prd_sys1)
+
+            if prd_response:
+                prd_response_raw = prd_response.choices[0].message.content
+
+                # send PRD output to UI
+                prd_msg = cl.Message(content=prd_response_raw)
+                await prd_msg.send()
+
+                prd_json = json.dumps({
+                    "objective_goal": "Develop a chatbot...", 
+                    "features": [], 
+                    "ux_flow_design_notes": "...", 
+                    "system_environment_requirements": "...", 
+                    "assumptions": [], 
+                    "constraints": [], 
+                    "dependencies": [], 
+                    "prompt_engineering_practices": "...", 
+                    "task_composability": "...", 
+                    "review_approval_process": "..."
+                })
+                designer_prompt = format_template(DESIGNER_PROMPT_TEMPLATE, prd_response_raw=prd_response_raw, prd_json=prd_json, user_proposal=user_proposal)
+                designer_response = llm_call(designer_prompt)
+
+                if designer_response:
+                    designer_output = designer_response.choices[0].message.content
+
+                    designer_output_msg = cl.Message(content=designer_output)
+                    await designer_output_msg.send()
+
+                    # update outputs in UI
+                    for secs in [1, 5, 10, 20]:
+                        await cl.sleep(secs)
+                        await prd_msg.update()
+                        await designer_output_msg.update()
+                else:
+                    await cl.Message(content="Error generating designer output. Please try again.").send()
             else:
-                await cl.Message(content="Error generating designer output. Please try again.").send()
-        else:
-            await cl.Message(content="Error generating PRD. Please try again.").send()
-
-# Load the starters ... overrided by on_chat_start
-import starters
+                await cl.Message(content="Error generating PRD. Please try again.").send()
+    except Exception as e:
+        logger.error(f"Error during chat start: {e}")