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from llm_engineering.domain.dataset import DatasetType
MOCKED_RESPONSE_INSTRUCT = """
[
{"instruction": "<mocked generated instruction> 1", "answer": "<mocked generated answer> 1"},
{"instruction": "<mocked generated instruction> 2", "answer": "<mocked generated answer> 2"},
{"instruction": "<mocked generated instruction> 3", "answer": "<mocked generated answer> 3"}
]
"""
MOCKED_RESPONSE_PREFERENCE = """
[
{"instruction": "<mocked generated instruction> 1", "rejected": "<mocked generated answer> 1", "chosen": "Mocked extracted extracted extracted extracted extracted extracted extracted extracted extracted extracted answer 1."},
{"instruction": "<mocked generated instruction> 2", "rejected": "<mocked generated answer> 2", "chosen": "Mocked extracted extracted extracted extracted extracted extracted extracted extracted extracted extracted answer 2."},
{"instruction": "<mocked generated instruction> 3", "rejected": "<mocked generated answer> 3", "chosen": "Mocked extracted answer 3"}
]
"""
def get_mocked_response(dataset_type: DatasetType) -> str:
if dataset_type == DatasetType.INSTRUCTION:
return MOCKED_RESPONSE_INSTRUCT
elif dataset_type == DatasetType.PREFERENCE:
return MOCKED_RESPONSE_PREFERENCE
else:
raise ValueError(f"Invalid dataset type: {dataset_type}")
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