ClickUp Operator
by noahvanhart
- .venv
- Lib
- site-packages
- huggingface_hub
- __pycache__
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) �RepoCard�model�content�ignore_metadata_errorsc � � || _ || _ y)a� Initialize a RepoCard from string content. The content should be a
Markdown file with a YAML block at the beginning and a Markdown body.
Args:
content (`str`): The content of the Markdown file.
Example:
```python
>>> from huggingface_hub.repocard import RepoCard
>>> text = '''
... ---
... language: en
... license: mit
... ---
...
... # My repo
... '''
>>> card = RepoCard(text)
>>> card.data.to_dict()
{'language': 'en', 'license': 'mit'}
>>> card.text
'\n# My repo\n'
```
<Tip>
Raises the following error:
- [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
when the content of the repo card metadata is not a dictionary.
</Tip>
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��Z�L����!2�!2�j�Y]�Ym�Ym�!2�!n� o�pz�o{�{~� @J� K� LP� LU� LU� KV� W� Wr& c � � || _ t j |� }|r]|j d� }||j � d | _ t
j |� }|�i }t |t � s)t d� �t j d� i }|| _ | j di |�d| j i��| _ t! |j# � � | _ y)z Set the content of the RepoCard.� N�)repo card metadata block should be a dictzBRepo card metadata block was not found. Setting CardData to empty.r! � )r- �REGEX_YAML_BLOCK�search�group�endr1 �yaml� safe_load�
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�N�N�_� `��I� �D�I�(�D�(�(�i�9�i�T�Mh�Mh�i�� � #�I�N�N�$4� 5�� r& c � � | j S �N)r )r# s r$ �__str__zRepoCard.__str__s s � ��|�|�r& �filepathc �� � t |� }|j j dd�� t |ddd�� 5 }|j t | � � ddd� y# 1 sw Y yxY w)a{ Save a RepoCard to a file.
Args:
filepath (`Union[Path, str]`): Filepath to the markdown file to save.
Example:
```python
>>> from huggingface_hub.repocard import RepoCard
>>> card = RepoCard("---\nlanguage: en\n---\n# This is a test repo card")
>>> card.save("/tmp/test.md")
```
T)�parents�exist_ok�w� �utf-8��mode�newline�encodingN)r �parent�mkdir�open�write�str)r# rJ �fs r$ �savez
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a� Initialize a RepoCard from a Hugging Face Hub repo's README.md or a local filepath.
Args:
repo_id_or_path (`Union[str, Path]`):
The repo ID associated with a Hugging Face Hub repo or a local filepath.
repo_type (`str`, *optional*):
The type of Hugging Face repo to push to. Defaults to None, which will use use "model". Other options
are "dataset" and "space". Not used when loading from a local filepath. If this is called from a child
class, the default value will be the child class's `repo_type`.
token (`str`, *optional*):
Authentication token, obtained with `huggingface_hub.HfApi.login` method. Will default to the stored token.
ignore_metadata_errors (`str`):
If True, errors while parsing the metadata section will be ignored. Some information might be lost during
the process. Use it at your own risk.
Returns:
[`huggingface_hub.repocard.RepoCard`]: The RepoCard (or subclass) initialized from the repo's
README.md file or filepath.
Example:
```python
>>> from huggingface_hub.repocard import RepoCard
>>> card = RepoCard.load("nateraw/food")
>>> assert card.data.tags == ["generated_from_trainer", "image-classification", "pytorch"]
```
)r] r^ z.Cannot load RepoCard: path not found on disk (z).�rrO rP rQ )r! N) r �existsr< rY r
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j j $ r+}j dk( rt |j � �|�d}~ww xY w)a� Validates card against Hugging Face Hub's card validation logic.
Using this function requires access to the internet, so it is only called
internally by [`huggingface_hub.repocard.RepoCard.push_to_hub`].
Args:
repo_type (`str`, *optional*, defaults to "model"):
The type of Hugging Face repo to push to. Options are "model", "dataset", and "space".
If this function is called from a child class, the default will be the child class's `repo_type`.
<Tip>
Raises the following errors:
- [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
if the card fails validation checks.
- [`HTTPError`](https://requests.readthedocs.io/en/latest/api/#requests.HTTPError)
if the request to the Hub API fails for any other reason.
</Tip>
)�repoTyper �Acceptz
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} ddd� | S # 1 sw Y S xY w)aA Push a RepoCard to a Hugging Face Hub repo.
Args:
repo_id (`str`):
The repo ID of the Hugging Face Hub repo to push to. Example: "nateraw/food".
token (`str`, *optional*):
Authentication token, obtained with `huggingface_hub.HfApi.login` method. Will default to
the stored token.
repo_type (`str`, *optional*, defaults to "model"):
The type of Hugging Face repo to push to. Options are "model", "dataset", and "space". If this
function is called by a child class, it will default to the child class's `repo_type`.
commit_message (`str`, *optional*):
The summary / title / first line of the generated commit.
commit_description (`str`, *optional*)
The description of the generated commit.
revision (`str`, *optional*):
The git revision to commit from. Defaults to the head of the `"main"` branch.
create_pr (`bool`, *optional*):
Whether or not to create a Pull Request with this commit. Defaults to `False`.
parent_commit (`str`, *optional*):
The OID / SHA of the parent commit, as a hexadecimal string. Shorthands (7 first characters) are also supported.
If specified and `create_pr` is `False`, the commit will fail if `revision` does not point to `parent_commit`.
If specified and `create_pr` is `True`, the pull request will be created from `parent_commit`.
Specifying `parent_commit` ensures the repo has not changed before committing the changes, and can be
especially useful if the repo is updated / committed to concurrently.
Returns:
`str`: URL of the commit which updated the card metadata.
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| j � j � }|j |� } |j dd|j � i|��} | |� S )a' Initialize a RepoCard from a template. By default, it uses the default template.
Templates are Jinja2 templates that can be customized by passing keyword arguments.
Args:
card_data (`huggingface_hub.CardData`):
A huggingface_hub.CardData instance containing the metadata you want to include in the YAML
header of the repo card on the Hugging Face Hub.
template_path (`str`, *optional*):
A path to a markdown file with optional Jinja template variables that can be filled
in with `template_kwargs`. Defaults to the default template.
Returns:
[`huggingface_hub.repocard.RepoCard`]: A RepoCard instance with the specified card data and content from the
template.
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Initialize a ModelCard from a template. By default, it uses the default template, which can be found here:
https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md
Templates are Jinja2 templates that can be customized by passing keyword arguments.
Args:
card_data (`huggingface_hub.ModelCardData`):
A huggingface_hub.ModelCardData instance containing the metadata you want to include in the YAML
header of the model card on the Hugging Face Hub.
template_path (`str`, *optional*):
A path to a markdown file with optional Jinja template variables that can be filled
in with `template_kwargs`. Defaults to the default template.
Returns:
[`huggingface_hub.ModelCard`]: A ModelCard instance with the specified card data and content from the
template.
Example:
```python
>>> from huggingface_hub import ModelCard, ModelCardData, EvalResult
>>> # Using the Default Template
>>> card_data = ModelCardData(
... language='en',
... license='mit',
... library_name='timm',
... tags=['image-classification', 'resnet'],
... datasets=['beans'],
... metrics=['accuracy'],
... )
>>> card = ModelCard.from_template(
... card_data,
... model_description='This model does x + y...'
... )
>>> # Including Evaluation Results
>>> card_data = ModelCardData(
... language='en',
... tags=['image-classification', 'resnet'],
... eval_results=[
... EvalResult(
... task_type='image-classification',
... dataset_type='beans',
... dataset_name='Beans',
... metric_type='accuracy',
... metric_value=0.9,
... ),
... ],
... model_name='my-cool-model',
... )
>>> card = ModelCard.from_template(card_data)
>>> # Using a Custom Template
>>> card_data = ModelCardData(
... language='en',
... tags=['image-classification', 'resnet']
... )
>>> card = ModelCard.from_template(
... card_data=card_data,
... template_path='./src/huggingface_hub/templates/modelcard_template.md',
... custom_template_var='custom value', # will be replaced in template if it exists
... )
```
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� Z � xZ S )� DatasetCard�datasetr� r� r� c �( �� t �| � |||fi |��S )a� Initialize a DatasetCard from a template. By default, it uses the default template, which can be found here:
https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md
Templates are Jinja2 templates that can be customized by passing keyword arguments.
Args:
card_data (`huggingface_hub.DatasetCardData`):
A huggingface_hub.DatasetCardData instance containing the metadata you want to include in the YAML
header of the dataset card on the Hugging Face Hub.
template_path (`str`, *optional*):
A path to a markdown file with optional Jinja template variables that can be filled
in with `template_kwargs`. Defaults to the default template.
Returns:
[`huggingface_hub.DatasetCard`]: A DatasetCard instance with the specified card data and content from the
template.
Example:
```python
>>> from huggingface_hub import DatasetCard, DatasetCardData
>>> # Using the Default Template
>>> card_data = DatasetCardData(
... language='en',
... license='mit',
... annotations_creators='crowdsourced',
... task_categories=['text-classification'],
... task_ids=['sentiment-classification', 'text-scoring'],
... multilinguality='monolingual',
... pretty_name='My Text Classification Dataset',
... )
>>> card = DatasetCard.from_template(
... card_data,
... pretty_name=card_data.pretty_name,
... )
>>> # Using a Custom Template
>>> card_data = DatasetCardData(
... language='en',
... license='mit',
... )
>>> card = DatasetCard.from_template(
... card_data=card_data,
... template_path='./src/huggingface_hub/templates/datasetcard_template.md',
... custom_template_var='custom value', # will be replaced in template if it exists
... )
```
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r( �
Nc � � | j d� }| j d� }| j d� }||z dk( ry||k( r||k( ry||kD ryy)z�Detect the line ending of a string. Used by RepoCard to avoid making huge diff on newlines.
Uses same implementation as in Hub server, keep it in sync.
Returns:
str: The detected line ending of the string.
r� r( r� r N)�count)r �cr�lf�crlfs r$ r, r, � sY � �
� � �t� �B� � � �t� �B� �=�=�� �D� �B�w�!�|�� �r�z�d�b�j�� �B�w��r& �
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��~�~�j�)�� �<�:�d�D�1��K��D�E�E�r& r. c � � d}d}t j j | � rxt | ddd�� 5 }|j � }t |j t � r|j d }n&t |j t � r |j }ddd� t | ddd�� 5 }t |d |�
� }t j |� }|r3|d|j � d |� |� d |� �z ||j � d z }n d |� |� d |� |� �}|j |� |j � ddd� y# 1 sw Y ��xY w# 1 sw Y yxY w) a&
Save the metadata dict in the upper YAML part Trying to preserve newlines as
in the existing file. Docs about open() with newline="" parameter:
https://docs.python.org/3/library/functions.html?highlight=open#open Does
not work with "^M" linebreaks, which are replaced by
r( rO r` �utf8)rS rT r NrN F)� sort_keysr* r) )�os�pathra rW rc r< �newlines�tuplerY r r6 r7 �startr9 rX �close)r� r. r* r �readme� data_yamlrD �outputs r$ �
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dataset_idr� r� r� r� r� r� c �N � dt | t ||||||||| |
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Creates a metadata dict with the result from a model evaluated on a dataset.
Args:
model_pretty_name (`str`):
The name of the model in natural language.
task_pretty_name (`str`):
The name of a task in natural language.
task_id (`str`):
Example: automatic-speech-recognition. A task id.
metrics_pretty_name (`str`):
A name for the metric in natural language. Example: Test WER.
metrics_id (`str`):
Example: wer. A metric id from https://hf.co/metrics.
metrics_value (`Any`):
The value from the metric. Example: 20.0 or "20.0 ± 1.2".
dataset_pretty_name (`str`):
The name of the dataset in natural language.
dataset_id (`str`):
Example: common_voice. A dataset id from https://hf.co/datasets.
metrics_config (`str`, *optional*):
The name of the metric configuration used in `load_metric()`.
Example: bleurt-large-512 in `load_metric("bleurt", "bleurt-large-512")`.
metrics_verified (`bool`, *optional*, defaults to `False`):
Indicates whether the metrics originate from Hugging Face's [evaluation service](https://huggingface.co/spaces/autoevaluate/model-evaluator) or not. Automatically computed by Hugging Face, do not set.
dataset_config (`str`, *optional*):
Example: fr. The name of the dataset configuration used in `load_dataset()`.
dataset_split (`str`, *optional*):
Example: test. The name of the dataset split used in `load_dataset()`.
dataset_revision (`str`, *optional*):
Example: 5503434ddd753f426f4b38109466949a1217c2bb. The name of the dataset dataset revision
used in `load_dataset()`.
metrics_verification_token (`bool`, *optional*):
A JSON Web Token that is used to verify whether the metrics originate from Hugging Face's [evaluation service](https://huggingface.co/spaces/autoevaluate/model-evaluator) or not.
Returns:
`dict`: a metadata dict with the result from a model evaluated on a dataset.
Example:
```python
>>> from huggingface_hub import metadata_eval_result
>>> results = metadata_eval_result(
... model_pretty_name="RoBERTa fine-tuned on ReactionGIF",
... task_pretty_name="Text Classification",
... task_id="text-classification",
... metrics_pretty_name="Accuracy",
... metrics_id="accuracy",
... metrics_value=0.2662102282047272,
... dataset_pretty_name="ReactionJPEG",
... dataset_id="julien-c/reactionjpeg",
... dataset_config="default",
... dataset_split="test",
... )
>>> results == {
... 'model-index': [
... {
... 'name': 'RoBERTa fine-tuned on ReactionGIF',
... 'results': [
... {
... 'task': {
... 'type': 'text-classification',
... 'name': 'Text Classification'
... },
... 'dataset': {
... 'name': 'ReactionJPEG',
... 'type': 'julien-c/reactionjpeg',
... 'config': 'default',
... 'split': 'test'
... },
... 'metrics': [
... {
... 'type': 'accuracy',
... 'value': 0.2662102282047272,
... 'name': 'Accuracy',
... 'verified': False
... }
... ]
... }
... ]
... }
... ]
... }
True
```
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Updates the metadata in the README.md of a repository on the Hugging Face Hub.
If the README.md file doesn't exist yet, a new one is created with metadata and an
the default ModelCard or DatasetCard template. For `space` repo, an error is thrown
as a Space cannot exist without a `README.md` file.
Args:
repo_id (`str`):
The name of the repository.
metadata (`dict`):
A dictionary containing the metadata to be updated.
repo_type (`str`, *optional*):
Set to `"dataset"` or `"space"` if updating to a dataset or space,
`None` or `"model"` if updating to a model. Default is `None`.
overwrite (`bool`, *optional*, defaults to `False`):
If set to `True` an existing field can be overwritten, otherwise
attempting to overwrite an existing field will cause an error.
token (`str`, *optional*):
The Hugging Face authentication token.
commit_message (`str`, *optional*):
The summary / title / first line of the generated commit. Defaults to
`f"Update metadata with huggingface_hub"`
commit_description (`str` *optional*)
The description of the generated commit
revision (`str`, *optional*):
The git revision to commit from. Defaults to the head of the
`"main"` branch.
create_pr (`boolean`, *optional*):
Whether or not to create a Pull Request from `revision` with that commit.
Defaults to `False`.
parent_commit (`str`, *optional*):
The OID / SHA of the parent commit, as a hexadecimal string. Shorthands (7 first characters) are also supported.
If specified and `create_pr` is `False`, the commit will fail if `revision` does not point to `parent_commit`.
If specified and `create_pr` is `True`, the pull request will be created from `parent_commit`.
Specifying `parent_commit` ensures the repo has not changed before committing the changes, and can be
especially useful if the repo is updated / committed to concurrently.
Returns:
`str`: URL of the commit which updated the card metadata.
Example:
```python
>>> from huggingface_hub import metadata_update
>>> metadata = {'model-index': [{'name': 'RoBERTa fine-tuned on ReactionGIF',
... 'results': [{'dataset': {'name': 'ReactionGIF',
... 'type': 'julien-c/reactiongif'},
... 'metrics': [{'name': 'Recall',
... 'type': 'recall',
... 'value': 0.7762102282047272}],
... 'task': {'name': 'Text Classification',
... 'type': 'text-classification'}}]}]}
>>> url = metadata_update("hf-internal-testing/reactiongif-roberta-card", metadata)
```
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