Update app.py

app.py

@@ -127,11 +127,11 @@ class SuperSmartAgent:
         ###################
         def general_reasoning_qa(state):
             question = state["question"]
-            
+        
             # Step 1: Search Wikipedia broadly
             search_results = wikipedia.search(question)
             relevant_pages = search_results[:3]  # get top 3 pages
-            
+        
             context = ""
             for title in relevant_pages:
                 try:
@@ -143,20 +143,21 @@ class SuperSmartAgent:
                 state["response"] = "Sorry, I couldn’t find enough information."
                 return state
         
-            # Step 2: Ask the LLM to reason over the context
+            # Step 2: Use the SuperSmartAgent to reason over the context
+            agent = SuperSmartAgent()
             prompt = f"""
             Based on the following Wikipedia content, answer the question:
-            
+        
             Question: {question}
-            
+        
             Context:
             {context}
-            
+        
             Answer in a single sentence.
             """
-        
-            state["response"] = call_llm(prompt)  # call your preferred LLM method
-            return state
+            state["response"] = agent(prompt)  # Use the SuperSmartAgent to process the prompt
+    return state
+
 
         def check_reasoning_needed(state):
             q = state["question"].lower()
@@ -169,7 +170,7 @@ class SuperSmartAgent:
         def check_wikipedia_suitability(state):
             q = state["question"].lower()
             # Simple heuristic: if it's a "who is", "what is", or named entity
-            triggers = ["who is", "what is", "when did", "where is", "tell me about"]
+            triggers = ["who is", "what is", "when did", "where is", "tell me about", "How many"]
             state["is_wiki"] = any(trigger in q for trigger in triggers)
             print(f"is_wiki: {state['is_wiki']}")
             return state