�
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e2ef d eddfd �Z5dd ddddd!�d"e2d#e2d$e2d%e2d&e2d'ed(e2d)e2d*ee2 d+e6d,ee2 d-ee2 d.ee2 d/ee2 def d0�Z7e$dd ddddd dd1�d2e2d3ed4ee2 d5e6d6ee2 d7ee2 d8ee2 d9ee2 d:e6d;ee2 de2fd<�� � Z8dS )=� N)�Path)�Any�Dict�Literal�Optional�Type�Union)�hf_hub_download)� upload_file)�CardData�DatasetCardData�
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ModelCardData�
SpaceCardData�eval_results_to_model_index�model_index_to_eval_results)� get_session�is_jinja_available� yaml_dump� )� constants)�EntryNotFoundError)�SoftTemporaryDirectory�logging�validate_hf_hub_args� templateszmodelcard_template.mdzdatasetcard_template.mdz1^(\s*---[\r\n]+)([\S\s]*?)([\r\n]+---(\r\n|\n|$))c �� � e Zd ZeZeZdZd dede fd�Z
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ee dee dee dee dee dee fd�Ze d dedee dee fd�� � Zd S )!�RepoCard�modelF�content�ignore_metadata_errorsc �" � || _ || _ dS )a� Initialize a RepoCard from string content. The content should be a
Markdown file with a YAML block at the beginning and a Markdown body.
Args:
content (`str`): The content of the Markdown file.
Example:
```python
>>> from huggingface_hub.repocard import RepoCard
>>> text = '''
... ---
... language: en
... license: mit
... ---
...
... # My repo
... '''
>>> card = RepoCard(text)
>>> card.data.to_dict()
{'language': 'en', 'license': 'mit'}
>>> card.text
'\n# My repo\n'
```
<Tip>
Raises the following error:
- [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
when the content of the repo card metadata is not a dictionary.
</Tip>
N)r! r )�selfr r! s �h/home/asafur/pinokio/api/open-webui.git/app/env/lib/python3.11/site-packages/huggingface_hub/repocard.py�__init__zRepoCard.__init__+ s � �H '=��#� �� � � � c � � t | j � � pd}d|� | j � || j �� � � |� d|� | j � �S )zLThe content of the RepoCard, including the YAML block and the Markdown body.�
�---)�
line_break�original_order)�_detect_line_ending�_content�data�to_yaml�_original_order�text)r# r* s r$ r zRepoCard.contentR s� � � )�� �7�7�?�4�
� W�Z� W���!2�!2�j�Y]�Ym�!2�!n�!n� W�pz� W� W� @J� W� LP� LU� W� W� Wr& c �� � || _ t � |� � }|rs|� d� � }||� � � d� | _ t
j |� � }|�i }t |t � � st d� � �n#t � d� � i }|| _ | j
di |�d| j i��| _ t! |� � � � � | _ dS )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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� �'�'��0�0�� � � ���Q� � �J� �� � � � �
�
�.�D�I� ��z�2�2�I�� � � � �i��.�.�
N� �!L�M�M�M�
N�
�N�N�_� `� `� `��I� �D�I�(�D�(�i�i�9�i�i�T�Mh�i�i�i�� � #�I�N�N�$4�$4� 5� 5�� � � r& c � � | j S �N)r )r# s r$ �__str__zRepoCard.__str__s s
� ��|�r& �filepathc �� � t |� � }|j � dd�� � t |ddd�� � 5 }|� t | � � � � ddd� � dS # 1 swxY w Y dS )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
RepoCard.savev s� � � ��>�>���� � �d�T� �:�:�:�
�(��b�7�
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�G�G�C��I�I� � � � � � � � � � � � � � � ���� � � � � � s �#A/�/A3�6A3N�repo_id_or_path� repo_type�tokenc � � t |� � � � � rt |� � }nZt |t � � r2t t |t
j |p| j |�� � � � }nt d|� d�� � �|� ddd�� � 5 } | |�
� � |�� � cd d d � � S # 1 swxY w Y d S )
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 �is_filer< rY r
r �
REPOCARD_NAMEr] r> rW �read)�clsr\ r] r^ r! � card_pathrZ s r$ �loadz
RepoCard.load� sB � �H �� � � (� (� *� *� c� �_�-�-�I�I�
���
-�
-�
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C�
C� P�q��3�q�v�v�x�x�8N�O�O�O� P� P� P� P� P� P� P� P� P� P� P� P���� P� P� P� P� P� Ps �$ C�C�Cc �0 � |p| j }|t | � � d�}ddi} t � � � d||�� � }|� � � dS # t
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
text/plainz(https://huggingface.co/api/validate-yaml)�headersi� N) r] rY r �post�raise_for_status�requests�
exceptions� HTTPError� status_coder> r1 )r# r] �bodyrj r` �excs r$ �validatezRepoCard.validate� s� � �, �/�� � � "��4�y�y�
�
�� �\�*�� ��
�
�"�"�#M�t�]d�"�e�e�A�
� � � � � � � ���"�,� � � ��}��#�#� ���(�(�(�� ����� ���s �8A �B�/!B�B�repo_id�commit_message�commit_description�revision� create_pr�
parent_commitc
�l � |p| j }| � |�� � t � � 5 } t | � � t j z }
|
� t | � � � � t t |
� � t j ||||||||��
�
} ddd� � n # 1 swxY w Y | S )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.
)r] )
�path_or_fileobj� path_in_report r^ r] ru rv rx rw ry N) r] rs r r r rb �
write_textrY r ) r# rt r^ r] ru rv rw rx ry �tmpdir�tmp_path�urls r$ � push_to_hubzRepoCard.push_to_hub� s� � �R �/�� � �
�
�
� �
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�
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template_path� template_strc �� � t � � rddl}nt d� � �|� � � � � � }|� |� � |�!t
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| j � � � � � }|� |� � } |j
dd|� � � 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.
r NzjUsing RepoCard.from_template requires Jinja2 to be installed. Please install it with `pip install Jinja2`.r� r5 ) r �jinja2� ImportError�to_dict�copy�updater � read_text�default_template_path�Template�renderr/ ) rd r� r� r� �template_kwargsr� �kwargs�templater s r$ �
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� � Z � xZ S )� ModelCardr Nr� r� r� c �< �� t � � j |||fi |��S )a�
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
... )
```
��superr� �rd r� r� r� r� � __class__s �r$ r� zModelCard.from_templateW s) �� �R %�u�w�w�$�Y�
�|�_�_��_�_�_r& r� )
r� r� r� r rA r� r� r] r� r rY r� �
__classcell__�r� s @r$ r� r� R s� �� � � � � �#�O� 3���I�� (,�&*� H`� H`� �H`� ��}�H`� �s�m� H`� H`� H`� H`� H`� �[�H`� H`� H`� H`� H`r& r� c �f � � e Zd ZeZeZdZe ddede e
de e
f� fd�
� � Z � xZ S )� DatasetCard�datasetNr� r� r� c �< �� t � � j |||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
... )
```
r� r� s �r$ r� zDatasetCard.from_template� s) �� �r %�u�w�w�$�Y�
�|�_�_��_�_�_r& r� )
r� r� r� r
rA �TEMPLATE_DATASETCARD_PATHr� r] r� r rY r� r� r� s @r$ r� r� � s� �� � � � � �%�O� 5���I�� (,�&*� 8`� 8`�"�8`� ��}�8`� �s�m� 8`� 8`� 8`� 8`� 8`� �[�8`� 8`� 8`� 8`� 8`r& r� c � � e Zd ZeZeZdZdS )� SpaceCard�spaceN)r� r� r� r rA r� r� r] r5 r& r$ r� r� � s � � � � � �#�O� 3���I�I�Ir& r� r �return)�
r( �
Nc �� � | � d� � }| � d� � }| � d� � }||z dk rdS ||k r||k rdS ||k rdS dS )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, � sr � �
� � �t� � �B� � � �t� � �B� �=�=�� � �D� �B�w�!�|�|��t� �r�z�z�d�b�j�j��v� �B�w�w��t��tr& �
local_pathc �" � t | � � � � � }t � |� � }|rQ|� d� � }t j |� � }|�t |t � � r|S t d� � �d S )Nr3 r4 )
r r� r6 r7 r8 r: r; r< r= r> )r� r rD rE r. s r$ �
metadata_loadr� � s� � ��:� � �(�(�*�*�G� � #� #�G� ,� ,�E� � ��[�[��^�^�
��~�j�)�)�� �<�:�d�D�1�1�<��K��D�E�E�E��tr& r. c � � d}d}t j � | � � r�t | ddd�� � 5 }|� � � }t |j t � � r|j d }n!t |j t � � r|j }ddd� � n # 1 swxY w Y t | ddd�� � 5 }t |d |�
� � }t � |� � }|rE|d|� � � � d |� |� d |� �z ||�
� � d� z }n d |� |� d |� |� �}|� |� � |� � � ddd� � dS # 1 swxY w Y dS ) 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
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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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