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| import aiohttp | |
| import asyncio | |
| from graph import graph | |
| from state import JARVISState | |
| from pydantic import BaseModel | |
| from typing import List | |
| import json | |
| import os | |
| from dotenv import load_dotenv | |
| # Load environment variables | |
| load_dotenv() | |
| # Debug: Verify environment variables | |
| print(f"OPENAI_API_KEY loaded: {'set' if os.getenv('OPENAI_API_KEY') else 'not set'}") | |
| print(f"LANGFUSE_PUBLIC_KEY loaded: {'set' if os.getenv('LANGFUSE_PUBLIC_KEY') else 'not set'}") | |
| # Verify critical environment variables | |
| required_env_vars = ["OPENAI_API_KEY", "LANGFUSE_PUBLIC_KEY", "LANGFUSE_SECRET_KEY"] | |
| for var in required_env_vars: | |
| if not os.getenv(var): | |
| raise ValueError(f"Environment variable {var} is not set") | |
| # Pydantic Models for Submission | |
| class Answer(BaseModel): | |
| task_id: str | |
| submitted_answer: str | |
| class Submission(BaseModel): | |
| username: str | |
| agent_code: str | |
| answers: List[Answer] | |
| async def fetch_questions() -> List[dict]: | |
| async with aiohttp.ClientSession() as session: | |
| async with session.get("https://api.gaia-benchmark.com/questions") as resp: | |
| return await resp.json() | |
| async def download_file(task_id: str, file_path: str) -> bool: | |
| async with aiohttp.ClientSession() as session: | |
| async with session.get(f"https://api.gaia-benchmark.com/files/{task_id}") as resp: | |
| if resp.status == 200: | |
| with open(file_path, "wb") as f: | |
| f.write(await resp.read()) | |
| return True | |
| return False | |
| async def process_question(question: dict) -> Answer: | |
| # Determine file type based on question context | |
| file_type = "jpg" if "image" in question["question"].lower() else "txt" | |
| if "menu" in question["question"].lower() or "report" in question["question"].lower() or "document" in question["question"].lower(): | |
| file_type = "pdf" # Prioritize PDF for reports/documents | |
| elif "data" in question["question"].lower(): | |
| file_type = "csv" | |
| file_path = f"temp_{question['task_id']}.{file_type}" | |
| await download_file(question["task_id"], file_path) | |
| state = JARVISState( | |
| task_id=question["task_id"], | |
| question=question["question"], | |
| tools_needed=[], | |
| web_results=[], | |
| file_results="", | |
| image_results="", | |
| calculation_results="", | |
| document_results="", | |
| messages=[], | |
| answer="" | |
| ) | |
| # Use unique thread_id for memory | |
| result = await graph.ainvoke(state, config={"thread_id": question["task_id"]}) | |
| return Answer(task_id=question["task_id"], submitted_answer=result["answer"]) | |
| async def submit_answers(answers: List[Answer], username: str, agent_code: str): | |
| submission = Submission( | |
| username=username, | |
| agent_code=agent_code, | |
| answers=answers | |
| ) | |
| async with aiohttp.ClientSession() as session: | |
| async with session.post("https://api.gaia-benchmark.com/submit", json=submission.dict()) as resp: | |
| return await resp.json() | |
| async def main(): | |
| username = "onisj" # Your Hugging Face username | |
| agent_code = "https://huggingface.co/spaces/onisj/jarvis_gaia_agent/tree/main" | |
| questions = await fetch_questions() | |
| answers = [] | |
| for question in questions[:20]: # Process 20 questions | |
| answer = await process_question(question) | |
| answers.append(answer) | |
| result = await submit_answers(answers, username, agent_code) | |
| print("Submission result:", json.dumps(result, indent=2)) | |
| if __name__ == "__main__": | |
| asyncio.run(main()) |