import os import gradio as gr import requests import pandas as pd # --- Constants --- DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space" # --- YOUR AGENT (MODIFIED) --- class BasicAgent: def __init__(self): print("BasicAgent initialized.") def __call__(self, question: str) -> str: q = question.lower() # --- EASY MATH (BIG POINTS) --- try: if any(op in q for op in ["+", "-", "*", "/"]): clean_q = q.replace("what is", "").replace("?", "").strip() return str(eval(clean_q)) except: pass # --- MULTIPLY WORDS --- if "multiply" in q: try: numbers = [int(s) for s in q.split() if s.isdigit()] if len(numbers) >= 2: return str(numbers[0] * numbers[1]) except: pass # --- SIMPLE FACTS --- if "capital of france" in q: return "Paris" if "morocco" in q: return "Rabat" # --- DEFAULT --- return "I don't know" def run_and_submit_all(profile: gr.OAuthProfile | None): space_id = os.getenv("SPACE_ID") if profile: username = f"{profile.username}" print(f"User logged in: {username}") else: return "Please Login to Hugging Face with the button.", None api_url = DEFAULT_API_URL questions_url = f"{api_url}/questions" submit_url = f"{api_url}/submit" # Create agent agent = BasicAgent() agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main" # Fetch questions response = requests.get(questions_url) questions_data = response.json() results_log = [] answers_payload = [] for item in questions_data: task_id = item.get("task_id") question_text = item.get("question") try: answer = agent(question_text) answers_payload.append({ "task_id": task_id, "submitted_answer": answer }) results_log.append({ "Task ID": task_id, "Question": question_text, "Submitted Answer": answer }) except Exception as e: results_log.append({ "Task ID": task_id, "Question": question_text, "Submitted Answer": f"ERROR: {e}" }) submission_data = { "username": username.strip(), "agent_code": agent_code, "answers": answers_payload } response = requests.post(submit_url, json=submission_data) result = response.json() final_status = ( f"Score: {result.get('score')}% | " f"{result.get('correct_count')}/{result.get('total_attempted')} correct" ) return final_status, pd.DataFrame(results_log) # --- UI --- with gr.Blocks() as demo: gr.Markdown("# Basic Agent Evaluation Runner") gr.LoginButton() run_button = gr.Button("Run Evaluation & Submit All Answers") status_output = gr.Textbox(label="Result", lines=5) results_table = gr.DataFrame() run_button.click( fn=run_and_submit_all, outputs=[status_output, results_table] ) if __name__ == "__main__": demo.launch()