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import os
import gradio as gr
import requests
import pandas as pd
from smolagents import (
CodeAgent,
DuckDuckGoSearchTool,
InferenceClientModel
)
# -----------------------------
# Constants
# -----------------------------
DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
# -----------------------------
# Smart Agent
# -----------------------------
class BasicAgent:
def __init__(self):
print("Initializing Smart Agent...")
# Web Search Tool
search_tool = DuckDuckGoSearchTool()
# Free Hugging Face Model
model = InferenceClientModel(
model_id="meta-llama/Llama-3.1-8B-Instruct"
)
# Main Agent
self.agent = CodeAgent(
tools=[search_tool],
model=model,
add_base_tools=True,
max_steps=5
)
def __call__(self, question: str) -> str:
print(f"Question: {question}")
prompt = f"""
You are a GAIA benchmark assistant.
IMPORTANT RULES:
- Return ONLY the final answer
- Do NOT explain your reasoning
- Do NOT write 'FINAL ANSWER'
- Keep answers short and exact
- If the answer is a number, return only the number
- If the answer is text, return only the text
Question:
{question}
"""
try:
response = self.agent.run(prompt)
answer = str(response).strip()
print(f"Agent answer: {answer}")
return answer
except Exception as e:
print(f"Error while solving question: {e}")
return "Error"
# -----------------------------
# Main Evaluation Function
# -----------------------------
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 with Hugging Face first.", None
api_url = DEFAULT_API_URL
questions_url = f"{api_url}/questions"
submit_url = f"{api_url}/submit"
# -----------------------------
# Create Agent
# -----------------------------
try:
agent = BasicAgent()
except Exception as e:
return f"Error initializing agent: {e}", None
# -----------------------------
# Space Code URL
# -----------------------------
agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
print(agent_code)
# -----------------------------
# Fetch Questions
# -----------------------------
try:
response = requests.get(
questions_url,
timeout=30
)
response.raise_for_status()
questions_data = response.json()
print(f"Fetched {len(questions_data)} questions")
except Exception as e:
return f"Error fetching questions: {e}", None
# -----------------------------
# Run Agent
# -----------------------------
results_log = []
answers_payload = []
for item in questions_data:
task_id = item.get("task_id")
question_text = item.get("question")
if not task_id or question_text is None:
continue
try:
submitted_answer = agent(question_text)
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"ERROR: {e}"
})
# -----------------------------
# Submit Answers
# -----------------------------
submission_data = {
"username": username.strip(),
"agent_code": agent_code,
"answers": answers_payload
}
try:
response = requests.post(
submit_url,
json=submission_data,
timeout=120
)
response.raise_for_status()
result_data = response.json()
final_status = (
f"Submission Successful!\n\n"
f"User: {result_data.get('username')}\n"
f"Score: {result_data.get('score')}%\n"
f"Correct: {result_data.get('correct_count')}/"
f"{result_data.get('total_attempted')}\n\n"
f"Message: {result_data.get('message')}"
)
results_df = pd.DataFrame(results_log)
return final_status, results_df
except Exception as e:
results_df = pd.DataFrame(results_log)
return f"Submission Failed: {e}", results_df
# -----------------------------
# Gradio UI
# -----------------------------
with gr.Blocks() as demo:
gr.Markdown("# GAIA Agent Evaluation")
gr.Markdown(
"""
Login with Hugging Face and run your AI agent on GAIA questions.
"""
)
gr.LoginButton()
run_button = gr.Button(
"Run Evaluation & Submit All Answers"
)
status_output = gr.Textbox(
label="Status",
lines=8
)
results_table = gr.DataFrame(
label="Agent Results"
)
run_button.click(
fn=run_and_submit_all,
outputs=[
status_output,
results_table
]
)
# -----------------------------
# Launch App
# -----------------------------
if __name__ == "__main__":
print("Starting GAIA Agent App...")
demo.launch(
debug=True,
share=False
)