Source code for oumi.datasets.sft.magpie

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# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
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#     http://www.apache.org/licenses/LICENSE-2.0
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from typing import Union

import pandas as pd

from oumi.core.datasets import BaseSftDataset
from oumi.core.registry import register_dataset
from oumi.core.types.conversation import Conversation, Message, Role




@register_dataset("argilla/magpie-ultra-v0.1")
class ArgillaMagpieUltraDataset(BaseSftDataset):
    """Dataset class for the argilla/magpie-ultra-v0.1 dataset."""

    default_dataset = "argilla/magpie-ultra-v0.1"



    def transform_conversation(self, example: Union[dict, pd.Series]) -> Conversation:
        """Transform a dataset example into a Conversation object."""
        instruction: str = example.get("instruction", None) or ""
        response: str = example.get("response", None) or ""

        messages = [
            Message(role=Role.USER, content=instruction),
            Message(role=Role.ASSISTANT, content=response),
        ]

        return Conversation(messages=messages)






@register_dataset("Magpie-Align/Llama-3-Magpie-Pro-1M-v0.1")
@register_dataset("Magpie-Align/Magpie-Pro-300K-Filtered")
class MagpieProDataset(BaseSftDataset):
    """Dataset class for the Magpie-Align/Llama-3-Magpie-Pro-1M-v0.1 dataset."""

    default_dataset = "Magpie-Align/Llama-3-Magpie-Pro-1M-v0.1"



    def transform_conversation(self, example: Union[dict, pd.Series]) -> Conversation:
        """Transform a dataset example into a Conversation object."""
        conversation = example.get("conversations")

        if conversation is None:
            raise ValueError("Conversation is None")

        messages = []
        for message in conversation:
            if message["from"] == "human":
                role = Role.USER
            elif message["from"] == "gpt":
                role = Role.ASSISTANT
            else:
                raise ValueError(f"Unknown role: {message['from']}")
            content = message.get("value", "")
            messages.append(Message(role=role, content=content))
        return Conversation(messages=messages)