Update app.py

app.py

@@ -29,33 +29,49 @@ class BasicAgent:
 
 
         model = TransformersModel(
-            # model_id="microsoft/phi-2",   # ✅ small, reliable
-            model_id="TinyLlama/TinyLlama-1.1B-Chat-v1.0",
-            max_new_tokens=1024,
-            temperature=0.0,
+            # model_id="TinyLlama/TinyLlama-1.1B-Chat-v1.0",
+            # model_id="mistralai/Mistral-7B-Instruct-v0.2",
+            model_id="Qwen/Qwen2.5-Coder-7B-Instruct",
+            max_new_tokens=128,
+            temperature=0.1,
         )
 
         with open("prompts.yaml", 'r') as stream:
             prompt_templates = yaml.safe_load(stream)
 
-        agent = CodeAgent(
+        prompt_templates["final_answer"] = {
+            "pre_messages": """You have reached the end of the task.
+        
+        Review your reasoning and ensure that your result is correct.
+        You must now return the final answer using the `final_answer()` tool.
+        
+        Do not output plain text — only use the tool.""",
+        
+            "post_messages": """Write Python code that calls:
+        
+        final_answer(result)
+        
+        Where `result` is the final answer to the task.
+        
+        Do not print anything else.
+        Do not return explanations.
+        Only call `final_answer` and do a final reason to make sure that you answer the question clearly and directly without additional information if not requested."""
+        }
+
+        agent_with_tools = CodeAgent(
             model=model,
-            # tools=[DuckDuckGoSearchTool()],
-            tools=[],
+            tools=[DuckDuckGoSearchTool(),],
             max_steps=5,
             verbosity_level=1,
-            grammar=None,
-            planning_interval=None,
-            name=None,
-            description=None,
-            prompt_templates=prompt_templates
+            additional_authorized_imports=["pandas", "wiki", 'random', 'time', 'itertools', 'statistics', 'queue', 'math', 'collections', 'datetime', 'unicodedata', 're', 'stat'],
+            prompt_templates=prompt_templates,
         )
 
         agent_answer = agent.run(question)
 
-        print(f"Agent Answer: {agent_answer}")
+        # print(f"Agent Answer: {agent_answer}")
 
-        return fixed_answer
+        return agent_answer
 
 def run_and_submit_all( profile: gr.OAuthProfile | None):
     """