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| import os | |
| import re | |
| import requests | |
| import pandas as pd | |
| import gradio as gr | |
| from smolagents import CodeAgent, InferenceClientModel, DuckDuckGoSearchTool, VisitWebpageTool | |
| API = "https://agents-course-unit4-scoring.hf.space" | |
| INSTRUCTIONS = """You are answering GAIA benchmark questions. Use tools when needed. | |
| Reply with ONLY the final answer, no explanation and no 'FINAL ANSWER' prefix. | |
| - Numbers: plain digits, no commas, no units unless asked. | |
| - Strings: no articles or abbreviations unless asked. | |
| - Lists: comma-separated, in the order requested. | |
| Answers are graded by exact match.""" | |
| class BasicAgent: | |
| def __init__(self): | |
| model = InferenceClientModel( | |
| model_id="Qwen/Qwen2.5-Coder-32B-Instruct", | |
| token=os.getenv("HF_TOKEN"), | |
| ) | |
| self.agent = CodeAgent( | |
| tools=[DuckDuckGoSearchTool(), VisitWebpageTool()], | |
| model=model, | |
| additional_authorized_imports=["pandas", "numpy", "requests", "re", "json", "datetime", "openpyxl"], | |
| instructions=INSTRUCTIONS, | |
| max_steps=10, | |
| ) | |
| def __call__(self, question, task_id=None, file_name=None): | |
| prompt = question | |
| if file_name: | |
| try: | |
| r = requests.get(f"{API}/files/{task_id}", timeout=30) | |
| path = f"/tmp/{file_name}" | |
| with open(path, "wb") as f: | |
| f.write(r.content) | |
| prompt += f"\n\nA file is attached at: {path}" | |
| except Exception: | |
| pass | |
| try: | |
| ans = str(self.agent.run(prompt)).strip() | |
| ans = re.sub(r"^(final answer:?\s*)", "", ans, flags=re.I).strip() | |
| return ans.rstrip(".") | |
| except Exception: | |
| return "unknown" | |
| def run_and_submit_all(profile: gr.OAuthProfile | None): | |
| if not profile: | |
| return "Please log in to Hugging Face first.", None | |
| username = profile.username | |
| space_id = os.getenv("SPACE_ID") | |
| agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main" | |
| try: | |
| agent = BasicAgent() | |
| except Exception as e: | |
| return f"Error creating agent: {e}", None | |
| try: | |
| questions = requests.get(f"{API}/questions", timeout=30).json() | |
| except Exception as e: | |
| return f"Error fetching questions: {e}", None | |
| answers, log = [], [] | |
| for item in questions: | |
| tid = item["task_id"] | |
| try: | |
| ans = agent(item["question"], tid, item.get("file_name")) | |
| except Exception as e: | |
| ans = "unknown" | |
| answers.append({"task_id": tid, "submitted_answer": ans}) | |
| log.append({"Task ID": tid, "Question": item["question"], "Answer": ans}) | |
| payload = {"username": username.strip(), "agent_code": agent_code, "answers": answers} | |
| try: | |
| res = requests.post(f"{API}/submit", json=payload, timeout=120).json() | |
| status = ( | |
| f"Submission successful!\nUser: {res.get('username')}\n" | |
| f"Score: {res.get('score')}% " | |
| f"({res.get('correct_count')}/{res.get('total_attempted')} correct)\n" | |
| f"{res.get('message', '')}" | |
| ) | |
| except Exception as e: | |
| status = f"Submission failed: {e}" | |
| return status, pd.DataFrame(log) | |
| with gr.Blocks() as demo: | |
| gr.Markdown("# GAIA Agent - Final Assignment") | |
| gr.LoginButton() | |
| btn = gr.Button("Run Evaluation & Submit All Answers") | |
| status = gr.Textbox(label="Status", lines=6, interactive=False) | |
| table = gr.DataFrame(label="Questions and Answers", wrap=True) | |
| btn.click(run_and_submit_all, outputs=[status, table]) | |
| if __name__ == "__main__": | |
| demo.launch() |