Update app.py

app.py

@@ -2,6 +2,7 @@ import gradio as gr
 import os
 import pandas as pd
 import datasets
+import logging
 
 from smolagents import CodeAgent, OpenAIServerModel
 from tools import DuckDuckGoSearchTool, WeatherInfoTool, HubStatsTool, NewsSearchTool
@@ -10,12 +11,16 @@ from retriever import load_guest_dataset
 # Constants
 SAMPLE_FILE = "sample_guests.csv"
 
+# Set up logging
+logging.basicConfig(level=logging.INFO)
+
 # Generate sample dataset if not already present
 def generate_sample_guest_csv():
     if not os.path.exists(SAMPLE_FILE):
         guest_dataset = datasets.load_dataset("agents-course/unit3-invitees", split="train")
         df = pd.DataFrame(guest_dataset)
         df.to_csv(SAMPLE_FILE, index=False)
+        logging.info(f"Sample dataset saved as {SAMPLE_FILE}")
 
 generate_sample_guest_csv()
 
@@ -71,21 +76,28 @@ with gr.Blocks() as demo:
 
     def run_query(prompt, file):
         global agent_instance
-        agent_instance = build_agent(file_path=file)
-        result = agent_instance.run(prompt)
-
-        # Handle different result types to convert to string for chatbot output
-        if isinstance(result, dict):
-            result = "\n\n".join(f"**{k}**: {v}" for k, v in result.items())
-        elif isinstance(result, list):
-            if all(isinstance(item, dict) and "name" in item and "starter" in item for item in result):
-                result = "\n\n".join(f"{item['name']}: {item['starter']}" for item in result)
+        logging.info(f"Received prompt: {prompt}")
+        logging.info(f"Guest file path: {file}")
+
+        try:
+            agent_instance = build_agent(file_path=file)
+            result = agent_instance.run(prompt)
+
+            # Handle different result types to convert to string for chatbot output
+            if isinstance(result, dict):
+                result = "\n\n".join(f"**{k}**: {v}" for k, v in result.items())
+            elif isinstance(result, list):
+                if all(isinstance(item, dict) and "name" in item and "starter" in item for item in result):
+                    result = "\n\n".join(f"{item['name']}: {item['starter']}" for item in result)
+                else:
+                    result = str(result)
             else:
                 result = str(result)
-        else:
-            result = str(result)
 
-        # Return as list of message dicts for Gradio chatbot type="messages"
+        except Exception as e:
+            logging.error(f"Error running agent: {e}")
+            result = f"⚠️ An error occurred: {str(e)}"
+
         return [
             {"role": "user", "content": prompt},
             {"role": "assistant", "content": result}