llama-index

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from llama_index.legacy.llm_predictor.base import BaseLLMPredictor, LLMPredictor
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from llama_index.legacy.llm_predictor.mock import MockLLMPredictor
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from llama_index.legacy.llm_predictor.structured import StructuredLLMPredictor
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from llama_index.legacy.llm_predictor.vellum.predictor import VellumPredictor
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def load_predictor(data: dict) -> BaseLLMPredictor:
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    """Load predictor by class name."""
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    if isinstance(data, BaseLLMPredictor):
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        return data
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    predictor_name = data.get("class_name", None)
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    if predictor_name is None:
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        raise ValueError("Predictor loading requires a class_name")
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    if predictor_name == LLMPredictor.class_name():
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        return LLMPredictor.from_dict(data)
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    elif predictor_name == StructuredLLMPredictor.class_name():
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        return StructuredLLMPredictor.from_dict(data)
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    elif predictor_name == MockLLMPredictor.class_name():
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        return MockLLMPredictor.from_dict(data)
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    elif predictor_name == VellumPredictor.class_name():
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        return VellumPredictor.from_dict(data)
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    else:
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        raise ValueError(f"Invalid predictor name: {predictor_name}")
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