Update app.py

app.py

@@ -1,11 +1,8 @@
 import sys
 from pathlib import Path
 
-
 sys.path.insert(0, str(Path(__file__).parent))
 
-
-
 import chainlit as cl
 
 from src.components.model_nlp_intent import predict_intent
@@ -13,9 +10,11 @@ from src.components.model_nlp_ner import extract_entities_pipeline
 from src.components.model_risk_predictor import predict_risk
 from src.components.recommendation_engine import generate_recommendation
 
+
 @cl.on_chat_start
 async def welcome():
-    await cl.Message(
+    """Welcome message displayed when chat starts"""
+    welcome_msg = cl.Message(
         content=(
             "# 🌐 Welcome to AI-Powered Supply Chain Risk Advisor\n\n"
             "I provide **real-time risk analysis** and **mitigation strategies** "
@@ -30,118 +29,144 @@ async def welcome():
             "- \"Are there weather problems affecting shipments to Germany?\"\n"
             "- \"Risk level for Mumbai to Singapore route?\"\n\n"
             "**Ask me anything about your supply chain risks!** 🚀"
-        ),
-        author="Risk Advisor Bot"
-    ).send()
+        )
+    )
+    await welcome_msg.send()
 
 
 @cl.on_message
 async def handle_message(msg: cl.Message):
+    """Handle incoming messages and provide risk analysis"""
     query = msg.content
-    session = cl.user_session
-
-    
-    intent_result = predict_intent(query)
-    intent = intent_result["intent"]
-    confidence = intent_result["confidence"]
-
-  
-    entities = extract_entities_pipeline(query)
-
-   
-    region = None
-    origin = None
-    destination = None
-    
-    if entities.get("location"):
-        locations = entities["location"]
-        if isinstance(locations, list) and len(locations) > 0:
-            region = locations[0]
-            
-            if len(locations) > 1:
-                origin = locations[0]
-                destination = locations[1]
-        else:
-            region = locations
-    
-    if not region:
-        region = "Mumbai"
-
-    
-    incidents = []
-    event_type = None
     
-    if entities.get("event"):
-        events = entities["event"]
-        if isinstance(events, list):
-            incidents = events
-            event_type = events[0] if events else None
+    # Show a loading message
+    loading_msg = cl.Message(content="🔄 Analyzing your query...")
+    await loading_msg.send()
+
+    try:
+        # Predict intent
+        intent_result = predict_intent(query)
+        intent = intent_result["intent"]
+        confidence = intent_result["confidence"]
+
+        # Extract entities
+        entities = extract_entities_pipeline(query)
+
+        # Extract location information
+        region = None
+        origin = None
+        destination = None
+        
+        if entities.get("location"):
+            locations = entities["location"]
+            if isinstance(locations, list) and len(locations) > 0:
+                region = locations[0]
+                
+                if len(locations) > 1:
+                    origin = locations[0]
+                    destination = locations[1]
+            else:
+                region = locations
+        
+        if not region:
+            region = "Mumbai"
+
+        # Extract event information
+        incidents = []
+        event_type = None
+        
+        if entities.get("event"):
+            events = entities["event"]
+            if isinstance(events, list):
+                incidents = events
+                event_type = events[0] if events else None
+            else:
+                incidents = [events]
+                event_type = events
+        
+        # Predict risk
+        risk_score = predict_risk(
+            region=region,
+            days=5,
+            origin=origin,
+            destination=destination,
+            event_type=event_type,
+            incidents=incidents
+        )
+
+        # Generate recommendation
+        recent_incidents = incidents if incidents else ["port strike", "supplier outage"]
+        weather_alert = "Typhoon warning" if region.lower() == "shanghai" else None
+        
+        advice = generate_recommendation(
+            risk_score=risk_score,
+            region=region,
+            recent_incidents=recent_incidents,
+            weather_alert=weather_alert,
+            intent=intent
+        )
+
+        # Determine risk level
+        if risk_score >= 0.7:
+            risk_emoji = "🔴"
+            risk_level = "High"
+        elif risk_score >= 0.4:
+            risk_emoji = "🟡"
+            risk_level = "Medium"
         else:
-            incidents = [events]
-            event_type = events
-    
-   
-    risk_score = predict_risk(
-        region=region,
-        days=5,
-        origin=origin,              
-        destination=destination,
-        event_type=event_type,
-        incidents=incidents
-    )
-
-  
-    recent_incidents = incidents if incidents else ["port strike", "supplier outage"]
-    weather_alert = "Typhoon warning" if region == "Shanghai" else None
-    
-    advice = generate_recommendation(
-        risk_score=risk_score,
-        region=region,
-        recent_incidents=recent_incidents,
-        weather_alert=weather_alert,
-        intent=intent
-    )
-
-
-    if risk_score >= 0.7:
-        risk_emoji = "🔴"
-        risk_level = "High"
-    elif risk_score >= 0.4:
-        risk_emoji = "🟡"
-        risk_level = "Medium"
-    else:
-        risk_emoji = "🟢"
-        risk_level = "Low"
-
-    
-    response = (
-        f"### 📊 Supply Chain Risk Analysis\n\n"
-        f"**Region:** {region}\n"
-        f"**Intent:** {intent} (Confidence: {confidence:.2%})\n"
-        f"**Entities:** {entities}\n"
-    )
-    
- 
-    if origin and destination:
-        response += f"**Route:** {origin} → {destination}\n"
-    
-   
-    if incidents:
-        response += f"**⚠️ Detected Events:** {', '.join(incidents)}\n"
-    
-    response += f"**Risk Score:** {risk_emoji} **{risk_level}** ({risk_score:.2f})\n\n"
-    response += f"**💡 Recommendation:**\n{advice['message']}\n"
-
-    await cl.Message(
-        content=response,
-        author="Supply Chain Risk Analysis"
-    ).send()
-
-    # Send Alert Level
-    alert_emoji = "🚨" if risk_score >= 0.7 else "⚠️" if risk_score >= 0.4 else "✅"
-    await cl.Message(
-        content=f"{alert_emoji} **Alert Level:** {advice['action'].upper()}",
-        author="Alert Level"
-    ).send()
-
-
+            risk_emoji = "🟢"
+            risk_level = "Low"
+
+        # Build response
+        response = (
+            f"### 📊 Supply Chain Risk Analysis\n\n"
+            f"**Region:** {region}\n"
+            f"**Intent:** {intent} (Confidence: {confidence:.2%})\n"
+            f"**Entities:** {entities}\n"
+        )
+        
+        if origin and destination:
+            response += f"**Route:** {origin} → {destination}\n"
+        
+        if incidents:
+            response += f"**⚠️ Detected Events:** {', '.join(incidents)}\n"
+        
+        response += f"**Risk Score:** {risk_emoji} **{risk_level}** ({risk_score:.2f})\n\n"
+        response += f"**💡 Recommendation:**\n{advice['message']}\n"
+
+        # Remove loading message
+        await loading_msg.remove()
+
+        # Send main response
+        await cl.Message(content=response).send()
+
+        # Send alert level
+        alert_emoji = "🚨" if risk_score >= 0.7 else "⚠️" if risk_score >= 0.4 else "✅"
+        await cl.Message(
+            content=f"{alert_emoji} **Alert Level:** {advice['action'].upper()}"
+        ).send()
+
+    except Exception as e:
+        # Log the error for debugging
+        print(f"Error processing query: {str(e)}")
+        import traceback
+        traceback.print_exc()
+        
+        # Remove loading message if it exists
+        try:
+            await loading_msg.remove()
+        except:
+            pass
+        
+        # Send user-friendly error message
+        await cl.Message(
+            content=(
+                f"❌ **Error:** An error occurred while processing your request.\n\n"
+                f"**Details:** {str(e)}\n\n"
+                f"Please try:\n"
+                f"- Rephrasing your question\n"
+                f"- Being more specific about locations\n"
+                f"- Asking a different question\n\n"
+                f"Example: \"What is the risk level for shipments from Mumbai to Singapore?\""
+            )
+        ).send()