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#!/usr/bin/env python3
"""
GAIA Benchmark Submission - Generated Space Code
This file contains the model answers for GAIA benchmark evaluation.
"""
# GAIA submission answers in the required format
GAIA_ANSWERS = {
"8e867cd7-cff9-4e6c-867a-ff5ddc2550be": {
"model_answer": '3',
"reasoning_trace": ''
},
"a1e91b78-d3d8-4675-bb8d-62741b4b68a6": {
"model_answer": '3',
"reasoning_trace": ''
},
"2d83110e-a098-4ebb-9987-066c06fa42d0": {
"model_answer": 'right',
"reasoning_trace": ''
},
"cca530fc-4052-43b2-b130-b30968d8aa44": {
"model_answer": 'Qe1+',
"reasoning_trace": ''
},
"4fc2f1ae-8625-45b5-ab34-ad4433bc21f8": {
"model_answer": '• * The instructions require the answer to be "a number OR as few words as possible OR a comma separated list". Since I cannot provide the name(s), I must indicate this lack of information concisely',
"reasoning_trace": ''
},
"6f37996b-2ac7-44b0-8e68-6d28256631b4": {
"model_answer": 'b, e',
"reasoning_trace": ''
},
"9d191bce-651d-4746-be2d-7ef8ecadb9c2": {
"model_answer": 'Extremely',
"reasoning_trace": ''
},
"cabe07ed-9eca-40ea-8ead-410ef5e83f91": {
"model_answer": '• * The question asks "What is the surname...". Since the information is not available in the provided context, I cannot provide the surname. The final answer should be "as few words as possible". "Unknown" is a single word that accurately reflects the situation where the information cannot be retrieved from the given data. It is a string, uses no articles or abbreviations, and fits the requirements',
"reasoning_trace": ''
},
"3cef3a44-215e-4aed-8e3b-b1e3f08063b7": {
"model_answer": 'broccoli, celery, fresh basil, lettuce, sweet potatoes',
"reasoning_trace": ''
},
"99c9cc74-fdc8-46c6-8f8d-3ce2d3bfeea3": {
"model_answer": 'Cornstarch, Granulated sugar, Lemon juice, Ripe strawberries, Salt, Unsalted butter, Vanilla extract',
"reasoning_trace": ''
},
"305ac316-eef6-4446-960a-92d80d542f82": {
"model_answer": 'Wojciech',
"reasoning_trace": ''
},
"f918266a-b3e0-4914-865d-4faa564f1aef": {
"model_answer": 'Python code not provided',
"reasoning_trace": ''
},
"3f57289b-8c60-48be-bd80-01f8099ca449": {
"model_answer": '540',
"reasoning_trace": ''
},
"1f975693-876d-457b-a649-393859e79bf3": {
"model_answer": '15, 22, 23, 24, 25, 30, 41, 42, 43',
"reasoning_trace": ''
},
"840bfca7-4f7b-481a-8794-c560c340185d": {
"model_answer": '80GSFC21M0002',
"reasoning_trace": ''
},
"bda648d7-d618-4883-88f4-3466eabd860e": {
"model_answer": 'Saint Petersburg',
"reasoning_trace": ''
},
"cf106601-ab4f-4af9-b045-5295fe67b37d": {
"model_answer": 'CUB',
"reasoning_trace": ''
},
"a0c07678-e491-4bbc-8f0b-07405144218f": {
"model_answer": 'Nagai, VerHagen',
"reasoning_trace": ''
},
"7bd855d8-463d-4ed5-93ca-5fe35145f733": {
"model_answer": 'Excel file content needed',
"reasoning_trace": ''
},
"5a0c1adf-205e-4841-a666-7c3ef95def9d": {
"model_answer": 'Claus',
"reasoning_trace": ''
},
}
def get_answer(task_id: str) -> dict:
"""Get answer for a specific task ID"""
return GAIA_ANSWERS.get(task_id, {
"model_answer": "",
"reasoning_trace": "Task ID not found"
})
def get_all_answers() -> dict:
"""Get all answers"""
return GAIA_ANSWERS
def get_task_ids() -> list:
"""Get all task IDs"""
return list(GAIA_ANSWERS.keys())
def get_statistics() -> dict:
"""Get submission statistics"""
total_tasks = len(GAIA_ANSWERS)
answered_tasks = sum(1 for answer in GAIA_ANSWERS.values()
if answer.get("model_answer", "").strip())
return {
"total_tasks": total_tasks,
"answered_tasks": answered_tasks,
"completion_rate": answered_tasks / total_tasks if total_tasks > 0 else 0.0
}
if __name__ == "__main__":
# Print statistics when run directly
stats = get_statistics()
print(f"GAIA Submission Statistics:")
print(f"Total tasks: {stats['total_tasks']}")
print(f"Answered tasks: {stats['answered_tasks']}")
print(f"Completion rate: {stats['completion_rate']:.2%}")
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