Update app.py

app.py

@@ -7,18 +7,15 @@ from agno.agent import Agent
 from agno.tools.duckduckgo import DuckDuckGoTools
 from agno.models.nvidia import Nvidia
 
-
-# (Keep Constants as is)
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
 # --- Basic Agent Definition ---
-# ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
 class BasicAgent:
     def __init__(self):
         agent=Agent(
-            model=Nvidia(id="meta/llama-3.3-70b-instruct")
-            ,instructions='''
+            model=Nvidia(id="meta/llama-3.3-70b-instruct"),
+            instructions='''
             ## 🚀 Gaia Taskmaster: The Ultimate Agent Efficiency Prompt! 🌍
 
                 You are a high-performance AI agent with a laser focus on completing Gaia tasks with maximum efficiency and precision. Think of yourself as a blend of a master strategist and a productivity guru—always optimizing, always delivering.
@@ -44,24 +41,15 @@ class BasicAgent:
             tools=[DuckDuckGoTools()])
         print("BasicAgent initialized.") 
         
-    def do_web_search(self,question:str)->str:
-        """
-        this would call an API or perform a search.
-        """
-        print(f"Performing web search for: {question}")
-        # Example usage
-        answer=agent.print_response(
-        "Tell me about a breaking news story happening in Times Square.", stream=True
-        )
-        return {answer} 
-     
     def __call__(self, question: str) -> str:
         print(f"Agent received question (first 50 chars): {question[:50]}...")
-        fixed_answer = "This is a default answer."
+        fixed_answer = agent.print_response(
+        question, stream=True
+        )
         print(f"Agent returning fixed answer: {fixed_answer}")
         return fixed_answer
 
-def run_and_submit_all( profile: gr.OAuthProfile | None):
+def run_and_submit_all(profile: gr.OAuthProfile | None):
     """
     Fetches all questions, runs the BasicAgent on them, submits all answers,
     and displays the results.
@@ -86,7 +74,7 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
     except Exception as e:
         print(f"Error instantiating agent: {e}")
         return f"Error initializing agent: {e}", None
-    # In the case of an app running as a hugging Face space, this link points toward your codebase ( usefull for others so please keep it public)
+    # In the case of an app running as a hugging Face space, this link points toward your codebase ( useful for others so please keep it public)
     agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
     print(agent_code)
 
@@ -181,7 +169,6 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
         results_df = pd.DataFrame(results_log)
         return status_message, results_df
 
-
 # --- Build Gradio Interface using Blocks ---
 with gr.Blocks() as demo:
     gr.Markdown("# Basic Agent Evaluation Runner")
@@ -203,7 +190,6 @@ with gr.Blocks() as demo:
     run_button = gr.Button("Run Evaluation & Submit All Answers")
 
     status_output = gr.Textbox(label="Run Status / Submission Result", lines=5, interactive=False)
-    # Removed max_rows=10 from DataFrame constructor
     results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True)
 
     run_button.click(
@@ -232,4 +218,5 @@ if __name__ == "__main__":
 
     print("-"*(60 + len(" App Starting ")) + "\n")
 
-    print("Launching Gradio Interface for Basic Agent Evaluation...")
+    print("Launching Gradio Interface for Basic Agent Evaluation...")
+    demo.launch(debug=True, share=False)