Update app.py

app.py

@@ -68,41 +68,60 @@ SYSTEM_PROMPT = (
 
 class BasicAgent:
     """
-    Agente simples baseado em smolagents, mas agora com ferramenta de busca:
-    - Usa InferenceClientModel (Inference API da Hugging Face)
-    - Usa DuckDuckGoSearchTool para buscar informações na web
-    - Retorna uma string já limpa para EXACT MATCH
+    Agente smolagents com DuckDuckGoSearchTool,
+    otimizado para GAIA EXACT MATCH.
     """
 
     def __init__(self):
-        print("Initializing smolagents BasicAgent with web search...")
+        print("Initializing improved GAIA agent with search...")
 
-        # Ferramenta de busca (DuckDuckGo)
         self.search_tool = DuckDuckGoSearchTool()
 
-        # Modelo remoto via Inference API (usa HF_TOKEN configurado no Space)
-        # Passamos o SYSTEM_PROMPT aqui
+        # Prompt especializado
         self.model = InferenceClientModel(
-            system_prompt=SYSTEM_PROMPT
+            system_prompt=(
+                "You are a GAIA evaluation agent that must answer EXACTLY the final answer.\n"
+                "You MUST use the search tool to retrieve verified information.\n"
+                "When you use search, read the results and extract ONLY the exact required answer.\n"
+                "RULES:\n"
+                " - Output MUST be a SINGLE short string.\n"
+                " - NO explanations.\n"
+                " - NO reasoning.\n"
+                " - NO multi-sentence output.\n"
+                " - NO citations or URLs.\n"
+                " - NO extra words.\n"
+                "Examples of valid outputs:\n"
+                "   '2002'\n"
+                "   '7'\n"
+                "   'egalitarian'\n"
+                "   'Mercedes Sosa'\n"
+                "INVALID OUTPUTS:\n"
+                "   'The final answer is 7.'\n"
+                "   'According to Wikipedia, the answer is 2002.'\n"
+                "   'After checking, I think it is 3.'\n"
+                "Your response MUST be only the exact final answer.\n"
+            )
         )
 
-        # CodeAgent com ferramenta de busca
+        # CodeAgent com raciocínio guiado
         self.agent = CodeAgent(
             model=self.model,
             tools=[self.search_tool],
-            max_steps=5,   # permite alguns passos (pensar + buscar + responder)
+            max_steps=8,    # permite buscar e refinar
         )
 
     def __call__(self, question: str) -> str:
-        print(f"Agent received question (first 80 chars): {question[:80]}...")
+        print(f"Processing: {question[:80]}...")
         try:
-            raw_answer = self.agent.run(question)
-            fixed_answer = clean_answer(raw_answer)
-            print(f"Agent returning cleaned answer: {fixed_answer}")
-            return fixed_answer
+            raw = self.agent.run(
+                f"Answer this question using search:\n{question}\n"
+                "Return ONLY the exact final answer."
+            )
+            final = clean_answer(raw)
+            print(f"Final cleaned answer: {final}")
+            return final
         except Exception as e:
-            print(f"Error inside BasicAgent.__call__: {e}")
-            # Em caso de erro, devolve string vazia (melhor do que quebrar tudo)
+            print(f"Error: {e}")
             return ""