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122 lines
4.2 KiB
Python
122 lines
4.2 KiB
Python
# SPDX-License-Identifier: AGPL-3.0-only
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# Copyright 2026-present the Unsloth AI Inc. team. All rights reserved. See /studio/LICENSE.AGPL-3.0
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from __future__ import annotations
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import json
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from pathlib import Path
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from utils.paths import recipe_datasets_root, resolve_dataset_path
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_DATA_DESIGNER_FOOTER = (
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'<sub style="white-space: nowrap;">Made with ❤️ using 🎨 '
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'<a href="https://github.com/NVIDIA-NeMo/DataDesigner">NeMo Data Designer</a></sub>'
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)
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_UNSLOTH_STUDIO_FOOTER = (
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'<sub style="white-space: nowrap;">Made with ❤️ using 🦥 ' "Unsloth Studio</sub>"
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)
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class RecipeDatasetPublishError(ValueError):
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"""Raised when a recipe dataset cannot be published to Hugging Face."""
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def _resolve_recipe_artifact_path(artifact_path: str) -> Path:
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root = recipe_datasets_root().expanduser().resolve()
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candidate = resolve_dataset_path(artifact_path).expanduser()
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resolved = candidate.resolve(strict = False)
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try:
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resolved.relative_to(root)
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except ValueError as exc:
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raise RecipeDatasetPublishError(
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"This execution artifact is outside the Recipe Studio dataset storage."
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) from exc
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if not resolved.exists():
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raise RecipeDatasetPublishError("Execution artifacts are no longer available.")
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if not resolved.is_dir():
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raise RecipeDatasetPublishError("Execution artifact path is not a dataset folder.")
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return resolved
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def publish_recipe_dataset(
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*,
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artifact_path: str,
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repo_id: str,
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description: str,
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hf_token: str | None = None,
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private: bool = False,
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) -> str:
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dataset_path = _resolve_recipe_artifact_path(artifact_path)
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try:
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from data_designer.engine.storage.artifact_storage import (
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FINAL_DATASET_FOLDER_NAME,
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METADATA_FILENAME,
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PROCESSORS_OUTPUTS_FOLDER_NAME,
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SDG_CONFIG_FILENAME,
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)
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from data_designer.integrations.huggingface.client import (
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HuggingFaceHubClient,
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HuggingFaceHubClientUploadError,
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)
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from data_designer.integrations.huggingface.dataset_card import (
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DataDesignerDatasetCard,
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)
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except ImportError as exc:
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raise RecipeDatasetPublishError(
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"NeMo Data Designer Hugging Face integration is not installed."
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) from exc
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try:
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client = HuggingFaceHubClient(token = hf_token)
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client._validate_repo_id(repo_id = repo_id)
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client._validate_dataset_path(base_dataset_path = dataset_path)
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client._create_or_get_repo(repo_id = repo_id, private = private)
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metadata_path = dataset_path / METADATA_FILENAME
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builder_config_path = dataset_path / SDG_CONFIG_FILENAME
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with metadata_path.open(encoding = "utf-8") as fh:
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metadata = json.load(fh)
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builder_config = None
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if builder_config_path.exists():
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with builder_config_path.open(encoding = "utf-8") as fh:
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builder_config = json.load(fh)
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card = DataDesignerDatasetCard.from_metadata(
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metadata = metadata,
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builder_config = builder_config,
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repo_id = repo_id,
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description = description,
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tags = None,
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)
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card.text = card.text.replace(_DATA_DESIGNER_FOOTER, _UNSLOTH_STUDIO_FOOTER)
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# Data Designer drops the explicit token, so push the card ourselves to keep auth request-local.
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card.push_to_hub(repo_id, token = hf_token, repo_type = "dataset")
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client._upload_main_dataset_files(
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repo_id = repo_id,
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parquet_folder = dataset_path / FINAL_DATASET_FOLDER_NAME,
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)
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client._upload_images_folder(
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repo_id = repo_id,
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images_folder = dataset_path / "images",
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)
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client._upload_processor_files(
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repo_id = repo_id,
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processors_folder = dataset_path / PROCESSORS_OUTPUTS_FOLDER_NAME,
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)
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client._upload_config_files(
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repo_id = repo_id,
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metadata_path = metadata_path,
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builder_config_path = builder_config_path,
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)
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return f"https://huggingface.co/datasets/{repo_id}"
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except HuggingFaceHubClientUploadError as exc:
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raise RecipeDatasetPublishError(str(exc)) from exc
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