# Copyright (c) 2025, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import json
import shutil
from pathlib import Path
import yaml
from datasets import load_dataset
from huggingface_hub import HfApi, hf_hub_download
from huggingface_hub.utils import HfHubHTTPError
from scripts.update_resource_servers import visit_resource_server
from nemo_gym.config_types import DownloadJsonlDatasetHuggingFaceConfig, UploadJsonlDatasetHuggingFaceConfig
[docs]
def create_huggingface_client(token: str) -> HfApi: # pragma: no cover
client = HfApi(token=token)
return client
[docs]
def download_hf_dataset_as_jsonl(
config: DownloadJsonlDatasetHuggingFaceConfig,
) -> None: # pragma: no cover
"""
Download a HF dataset and save as JSONL.
If `artifact_fpath` is provided, downloads that specific file using `hf_hub_download`.
Otherwise, uses datasets.load_dataset() to handle structured datasets.
"""
try:
# artifact_fpath - download raw jsonl file
if config.artifact_fpath:
downloaded_path = hf_hub_download(
repo_id=config.repo_id,
filename=config.artifact_fpath,
repo_type="dataset",
token=config.hf_token,
)
output_file = (
Path(config.output_fpath or config.output_dirpath) / Path(config.artifact_fpath).name
if config.output_dirpath
else Path(config.output_fpath)
)
output_file.parent.mkdir(parents=True, exist_ok=True)
# We copy the downloaded file from the cache to the target path
# to allow renaming (e.g., artifact_fpath="something.jsonl" -> output_fpath="train.jsonl")
shutil.copy(downloaded_path, output_file)
print(f"[Nemo-Gym] - Downloaded {config.artifact_fpath} to: {output_file}")
return
# no artifact_fpath - use load_dataset() with split (if provided)
if config.output_fpath:
# Exact output path specified
output_file = Path(config.output_fpath)
output_file.parent.mkdir(parents=True, exist_ok=True)
ds = load_dataset(config.repo_id, split=config.split, token=config.hf_token)
ds.to_json(str(output_file))
print(f"[Nemo-Gym] - Downloaded {config.split} split to: {output_file}")
else:
# Output directory specified
output_dir = Path(config.output_dirpath)
output_dir.mkdir(parents=True, exist_ok=True)
if config.split:
ds = load_dataset(config.repo_id, split=config.split, token=config.hf_token)
output_file = output_dir / f"{config.split}.jsonl"
ds.to_json(str(output_file))
print(f"[Nemo-Gym] - Downloaded {config.split} split to: {output_file}")
else:
# Download all
ds = load_dataset(config.repo_id, token=config.hf_token)
for split_name, split_data in ds.items():
output_file = output_dir / f"{split_name}.jsonl"
split_data.to_json(str(output_file))
print(f"[Nemo-Gym] - Downloaded {split_name} split to: {output_file}")
except Exception as e:
print(f"[Nemo-Gym] - Error downloading/converting dataset: {e}")
raise
[docs]
def upload_jsonl_dataset(
config: UploadJsonlDatasetHuggingFaceConfig,
) -> None: # pragma: no cover
client = create_huggingface_client(config.hf_token)
with open(config.resource_config_path, "r") as f:
data = yaml.safe_load(f)
domain = d.lower() + "-" if (d := visit_resource_server(data).to_dict().get("domain")) else ""
resource_server = config.resource_config_path.split("/")[1]
dataset_name = config.dataset_name or resource_server
prefix = config.hf_dataset_prefix + "-" if config.hf_dataset_prefix else ""
collection_id = (
f"{config.hf_organization}/{config.hf_collection_name.lower().replace(' ', '-')}-{config.hf_collection_slug}"
)
repo_id = f"{config.hf_organization}/{prefix}{domain}{dataset_name}"
# Dataset format check - only strict check for training data
is_training = config.split.lower() == "train"
if is_training and not check_jsonl_format(config.input_jsonl_fpath):
print("[Nemo-Gym] - JSONL file format check failed.")
return
# Repo creation
try:
client.create_repo(repo_id=repo_id, token=config.hf_token, repo_type="dataset", private=True, exist_ok=True)
print(f"[Nemo-Gym] - Repo '{repo_id}' is ready for use")
except HfHubHTTPError as e:
if config.create_pr and "403" in str(e):
print(f"[Nemo-Gym] - Repo '{repo_id}' exists (no create permission, will create PR)")
else:
print(f"[Nemo-Gym] - Error creating repo: {e}")
raise
# Collection id + addition
try:
collection = client.get_collection(collection_id)
if any(item.item_id.lower() == repo_id.lower() and item.item_type == "dataset" for item in collection.items):
print(
f"[Nemo-Gym] - Dataset '{dataset_name}' under Repo '{repo_id}' is already in Collection '{collection_id}'"
)
else:
client.add_collection_item(collection_slug=collection_id, item_id=repo_id, item_type="dataset")
print(f"[Nemo-Gym] - Dataset '{repo_id}' added to collection '{collection_id}'")
except HfHubHTTPError as e:
print(f"[Nemo-Gym] - Error adding to collection: {e}")
raise
# File upload
try:
commit_info = client.upload_file(
path_or_fileobj=config.input_jsonl_fpath,
path_in_repo=Path(config.input_jsonl_fpath).name,
repo_id=repo_id,
token=config.hf_token,
repo_type="dataset",
create_pr=config.create_pr,
revision=config.revision,
commit_message=config.commit_message,
commit_description=config.commit_description,
)
if config.create_pr:
print(f"[Nemo-Gym] - Pull Request created: {commit_info.pr_url}")
else:
print("[Nemo-Gym] - Dataset upload successful")
except HfHubHTTPError as e:
print(f"[Nemo-Gym] - Error uploading file: {e}")
raise
