Update app.py

app.py

@@ -1,10 +1,34 @@
-class BasicAgent:
-    def __init__(self):
-        print("BasicAgent initialized.")
-
-    def __call__(self, question: str) -> str:
-        print(f"Agent received question (first 50 chars): {question[:50]}...")
-        # Replace this with your own logic to answer the questions
-        fixed_answer = "This is a default answer."
-        print(f"Agent returning fixed answer: {fixed_answer}")
-        return fixed_answer
+import gradio as gr
+import requests
+import pandas as pd
+from BasicAgent import BasicAgent  # Import BasicAgent class
+
+DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
+
+def run_and_submit_all(profile: gr.OAuthProfile | None):
+    # Your logic for fetching and submitting data here
+    agent = BasicAgent()
+    question = "What is the meaning of life?"  # Example question, you can modify this
+    answer = agent(question)  # Get answer from BasicAgent
+    
+    # Mocking data as if agent has answered some questions
+    data = [{"Task ID": f"task_{i+1}", "Answer": f"Answer to question {i+1}"} for i in range(5)]
+    
+    # You can modify the status and table as per your needs
+    return "Results submitted successfully!", pd.DataFrame(data)
+
+# Initialize Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("# Basic Agent Evaluation Runner")
+    gr.LoginButton()
+    
+    # Add run button and result output fields
+    run_button = gr.Button("Run Evaluation & Submit All Answers")
+    status_output = gr.Textbox(label="Run Status / Submission Result", lines=5, interactive=False)
+    results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True)
+    
+    # Hook up button click to function
+    run_button.click(fn=run_and_submit_all, outputs=[status_output, results_table])
+
+if __name__ == "__main__":
+    demo.launch(debug=True, share=False)