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| # Standalone script to watch the GAIA agent run on one question, with every step | |
| # printed live: which LLM provider handled each call (and which ones failed over), | |
| # the plan, each tool call and its result, the judge's verdict, and the final | |
| # formatted answer. Run it directly: `python test_agent.py "your question here"`. | |
| # | |
| # All of this tracing is built into gaia_agent itself (llm.py, judge.py, | |
| # workflow.py print as they go) -- this script just calls the agent and gets out | |
| # of the way so you see that output as it happens, plus a summary at the end. | |
| import sys | |
| import time | |
| from gaia_agent.adapter import GAIAAgent | |
| DEFAULT_QUESTIONS = [ | |
| "What is the capital of Australia?", | |
| "If a train travels 187.5 miles in 2.5 hours, what is its average speed in miles per hour?", | |
| ] | |
| def run_one(agent: GAIAAgent, question: str, task_id: str | None = None) -> None: | |
| print("=" * 100) | |
| print(f"QUESTION: {question}") | |
| if task_id: | |
| print(f"task_id: {task_id}") | |
| print("-" * 100) | |
| start = time.time() | |
| try: | |
| answer = agent(question, task_id) | |
| elapsed = time.time() - start | |
| print("-" * 100) | |
| print(f"FINAL ANSWER ({elapsed:.1f}s): {answer!r}") | |
| except Exception as e: | |
| elapsed = time.time() - start | |
| print("-" * 100) | |
| print(f"FAILED ({elapsed:.1f}s): {type(e).__name__}: {e}") | |
| def main() -> None: | |
| questions = sys.argv[1:] or DEFAULT_QUESTIONS | |
| agent = GAIAAgent() | |
| for question in questions: | |
| run_one(agent, question) | |
| if __name__ == "__main__": | |
| main() | |