Update app.py

app.py

@@ -34,33 +34,40 @@ llm = ChatGoogleGenerativeAI(
     google_api_key=os.getenv("GOOGLE_API_KEY")
 )
 
+# Initialize models and APIs
+llm = ChatGoogleGenerativeAI(
+    model="gemini-1.5-flash",
+    google_api_key=os.getenv("GOOGLE_API_KEY")
+)
+
 def space_events_agent():
     """
-    Fetches space events from NASA's EONET API, processes them, and generates a response using LLM.
+    Fetches and formats upcoming space events from NASA's EONET API.
     Returns:
-        dict: A dictionary with the LLM-generated response based on space events.
+        dict: A dictionary with the formatted space events or a message if no events are found.
     Raises:
         HTTPError: If the request to the NASA API fails.
     Note:
-        Requires NASA API key set in the environment variable `NASA_API_KEY`.
+        Requires NASA API key set in the environment variable NASA_API_KEY.
     """
+    import os
+    import requests
+
     base_url = "https://eonet.gsfc.nasa.gov/api/v2.1/events"
     params = {"api_key": os.getenv("NASA_API_KEY")}
     
     try:
-        # Fetching events from NASA's EONET API
         response = requests.get(base_url, params=params)
         response.raise_for_status()
     except Exception as e:
         return {"output": f"🚀 **Space Events Agent:** Error fetching events: {str(e)}"}
     
-    # Processing the events
     events = response.json().get("events", [])
     if events:
-        # Extract event details
         event_details = []
         for event in events:
             title = event.get('title', 'N/A')
+            # Retrieve category using safe defaults
             category = (event.get('categories', [{}])[0]).get('title', 'Unknown Category')
             geometries = event.get('geometries', [])
             if geometries:
@@ -80,14 +87,8 @@ def space_events_agent():
             event_details.append(detail)
         
         formatted_events = "\n".join(event_details)
-        
-        # Generate response using the LLM
-        prompt = f"Here are the upcoming space events:\n{formatted_events}\nCan you provide a summary of these events?"
-        llm_response = llm.chat(messages=[{"role": "system", "content": "You are a space events assistant."}, {"role": "user", "content": prompt}])
-        return {"output": llm_response['message']['content']}
-    
+        return {"output": f"🚀 **Space Events Agent:**\n\n{formatted_events}"}
     else:
-        # If no events are found
         return {"output": "🚀 **Space Events Agent:** No events found at the moment."}