Update app.py

app.py

@@ -135,26 +135,31 @@ class BasicAgent:
         return text.strip()
 
     def _generate_answer(self, state: AgentState) -> AgentState:
-        # Format search results for better LLM consumption
-        search_results = []
-        for item in state["history"]:
-            if item.get("step") == "search" and "results" in item:
-                for i, result in enumerate(item["results"], 1):
-                    search_results.append(f"Result {i}:\n{result}\n")
+        # Get the last search results
+        search_block = "\n".join(state["history"][-1]["results"])  # last search step
         
-        history_text = "\n".join(search_results) if search_results else "No search results found."
+        prompt = f"""
+You are an expert fact-extractor. Using ONLY the text below, answer the question.
+
+Question:
+{state['question']}
+
+Search snippets (bold terms are highlighted):
+{search_block}
+
+Think step-by-step. Quote exact numbers/names if needed.
+END EACH STEP with ➤.  After reasoning, output:
+
+ANSWER: <the short answer here>
+
+No other text.
+"""
+        raw = self._call_llm(prompt, 300)
+        answer = raw.splitlines()[-1].replace("ANSWER:", "").strip()
         
-        prompt = (
-            f"Answer the user question as directly as possible using the search results below.\n"
-            f"Question: {state['question']}\n\n"
-            f"Search Results:\n{history_text}\n\n"
-            "Give ONLY the final answer without extra formatting or explanation.\n"
-            "If you cannot find a definitive answer in the search results, say 'I cannot find a definitive answer to this question.'"
-        )
-        answer = self._call_llm(prompt, max_tokens=150)
-        state["final_answer"] = answer.strip()
-        state["history"].append({"step": "answer", "output": answer})
-        state["logs"]["final_answer"] = {"prompt": prompt, "response": answer}
+        state["final_answer"] = answer
+        state["history"].append({"step": "answer", "output": raw})  # Store full response for debugging
+        state["logs"]["final_answer"] = {"prompt": prompt, "response": raw}
         state["current_step"] = "done"
         return state