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import os
import gradio as gr
import requests
import pandas as pd
from smolagents import CodeAgent, DuckDuckGoSearchTool, OpenAIServerModel
# --- Constants ---
DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
# --- Enhanced Agent Definition ---
class GAIAAgent:
def __init__(self):
print("GAIAAgent initialized.")
model = OpenAIServerModel(model_id="gpt-4o")
search_tool = DuckDuckGoSearchTool()
self.agent = CodeAgent(model=model, tools=[search_tool])
def format_prompt(self, question: str, file_content: str = None) -> str:
prompt = (
"You are a helpful AI agent solving a question from the GAIA benchmark. "
"Respond only with the final answer."
)
if file_content:
prompt += f"\nAttached File Content:\n{file_content}\n"
prompt += f"\nQuestion: {question}\nAnswer:"
return prompt
def read_file(self, filename: str) -> str:
filepath = os.path.join("./", filename)
if filename.endswith(".txt") and os.path.exists(filepath):
with open(filepath, "r") as file:
return file.read()[:1000] # limit to 1000 chars
return ""
def __call__(self, question: str, file_name: str = None) -> str:
file_content = self.read_file(file_name) if file_name else None
prompt = self.format_prompt(question, file_content)
result = self.agent.run(prompt)
return result.strip()
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:
print("User not logged in.")
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"
try:
agent = GAIAAgent()
except Exception as e:
return f"Error initializing agent: {e}", None
agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
try:
response = requests.get(questions_url, timeout=15)
response.raise_for_status()
questions_data = response.json()
except Exception as e:
return f"Error fetching questions: {e}", None
results_log = []
answers_payload = []
for item in questions_data:
task_id = item.get("task_id")
question_text = item.get("question")
file_name = item.get("file_name")
if not task_id or question_text is None:
continue
try:
submitted_answer = agent(question_text, file_name)
answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": submitted_answer})
except Exception as e:
results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": f"AGENT ERROR: {e}"})
if not answers_payload:
return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
submission_data = {"username": username.strip(), "agent_code": agent_code, "answers": answers_payload}
try:
response = requests.post(submit_url, json=submission_data, timeout=60)
response.raise_for_status()
result_data = response.json()
final_status = (
f"Submission Successful!\n"
f"User: {result_data.get('username')}\n"
f"Overall Score: {result_data.get('score', 'N/A')}% "
f"({result_data.get('correct_count', '?')}/{result_data.get('total_attempted', '?')} correct)\n"
f"Message: {result_data.get('message', 'No message received.')}"
)
return final_status, pd.DataFrame(results_log)
except Exception as e:
return f"Submission Failed: {e}", pd.DataFrame(results_log)
with gr.Blocks() as demo:
gr.Markdown("# GAIA Agent Evaluation Runner")
gr.Markdown("""
**Instructions:**
1. Log in to your Hugging Face account.
2. Click the button to run the agent and submit answers.
3. Your score will be printed below.
""")
gr.LoginButton()
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)
run_button.click(
fn=run_and_submit_all,
outputs=[status_output, results_table]
)
if __name__ == "__main__":
print("Launching GAIA agent app...")
demo.launch(debug=True, share=False)