-
Notifications
You must be signed in to change notification settings - Fork 520
/
hf_api.py
4124 lines (3568 loc) · 153 KB
/
hf_api.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
# coding=utf-8
# Copyright 2019-present, the HuggingFace Inc. team.
#
# 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 os
import re
import warnings
from dataclasses import dataclass, field
from itertools import islice
from pathlib import Path
from typing import Any, BinaryIO, Dict, Iterable, Iterator, List, Optional, Tuple, Union
from urllib.parse import quote
import requests
from huggingface_hub.utils import EntryNotFoundError, RepositoryNotFoundError
from requests.exceptions import HTTPError
from ._commit_api import (
CommitOperation,
CommitOperationAdd,
CommitOperationDelete,
fetch_upload_modes,
prepare_commit_payload,
upload_lfs_files,
warn_on_overwriting_operations,
)
from ._space_api import SpaceHardware, SpaceRuntime
from .community import (
Discussion,
DiscussionComment,
DiscussionStatusChange,
DiscussionTitleChange,
DiscussionWithDetails,
deserialize_event,
)
from .constants import (
DEFAULT_REVISION,
ENDPOINT,
REGEX_COMMIT_OID,
REPO_TYPE_MODEL,
REPO_TYPES,
REPO_TYPES_MAPPING,
REPO_TYPES_URL_PREFIXES,
SPACES_SDK_TYPES,
)
from .utils import ( # noqa: F401 # imported for backward compatibility
HfFolder,
HfHubHTTPError,
build_hf_headers,
erase_from_credential_store,
filter_repo_objects,
hf_raise_for_status,
logging,
parse_datetime,
read_from_credential_store,
validate_hf_hub_args,
write_to_credential_store,
)
from .utils._deprecation import (
_deprecate_arguments,
_deprecate_list_output,
_deprecate_method,
)
from .utils._pagination import paginate
from .utils._typing import Literal, TypedDict
from .utils.endpoint_helpers import (
AttributeDictionary,
DatasetFilter,
DatasetTags,
ModelFilter,
ModelTags,
_filter_emissions,
)
USERNAME_PLACEHOLDER = "hf_user"
_REGEX_DISCUSSION_URL = re.compile(r".*/discussions/(\d+)$")
logger = logging.get_logger(__name__)
def repo_type_and_id_from_hf_id(
hf_id: str, hub_url: Optional[str] = None
) -> Tuple[Optional[str], Optional[str], str]:
"""
Returns the repo type and ID from a huggingface.co URL linking to a
repository
Args:
hf_id (`str`):
An URL or ID of a repository on the HF hub. Accepted values are:
- https://huggingface.co/<repo_type>/<namespace>/<repo_id>
- https://huggingface.co/<namespace>/<repo_id>
- hf://<repo_type>/<namespace>/<repo_id>
- hf://<namespace>/<repo_id>
- <repo_type>/<namespace>/<repo_id>
- <namespace>/<repo_id>
- <repo_id>
hub_url (`str`, *optional*):
The URL of the HuggingFace Hub, defaults to https://huggingface.co
Returns:
A tuple with three items: repo_type (`str` or `None`), namespace (`str` or
`None`) and repo_id (`str`).
Raises:
- [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
If URL cannot be parsed.
- [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
If `repo_type` is unknown.
"""
input_hf_id = hf_id
hub_url = re.sub(r"https?://", "", hub_url if hub_url is not None else ENDPOINT)
is_hf_url = hub_url in hf_id and "@" not in hf_id
HFFS_PREFIX = "hf://"
if hf_id.startswith(HFFS_PREFIX): # Remove "hf://" prefix if exists
hf_id = hf_id[len(HFFS_PREFIX) :]
url_segments = hf_id.split("/")
is_hf_id = len(url_segments) <= 3
namespace: Optional[str]
if is_hf_url:
namespace, repo_id = url_segments[-2:]
if namespace == hub_url:
namespace = None
if len(url_segments) > 2 and hub_url not in url_segments[-3]:
repo_type = url_segments[-3]
else:
repo_type = None
elif is_hf_id:
if len(url_segments) == 3:
# Passed <repo_type>/<user>/<model_id> or <repo_type>/<org>/<model_id>
repo_type, namespace, repo_id = url_segments[-3:]
elif len(url_segments) == 2:
# Passed <user>/<model_id> or <org>/<model_id>
namespace, repo_id = hf_id.split("/")[-2:]
repo_type = None
else:
# Passed <model_id>
repo_id = url_segments[0]
namespace, repo_type = None, None
else:
raise ValueError(
f"Unable to retrieve user and repo ID from the passed HF ID: {hf_id}"
)
# Check if repo type is known (mapping "spaces" => "space" + empty value => `None`)
if repo_type in REPO_TYPES_MAPPING:
repo_type = REPO_TYPES_MAPPING[repo_type]
if repo_type == "":
repo_type = None
if repo_type not in REPO_TYPES:
raise ValueError(f"Unknown `repo_type`: '{repo_type}' ('{input_hf_id}')")
return repo_type, namespace, repo_id
class BlobLfsInfo(TypedDict, total=False):
size: int
sha256: str
@dataclass
class CommitInfo:
"""Data structure containing information about a newly created commit.
Returned by [`create_commit`].
Args:
commit_url (`str`):
Url where to find the commit.
commit_message (`str`):
The summary (first line) of the commit that has been created.
commit_description (`str`):
Description of the commit that has been created. Can be empty.
oid (`str`):
Commit hash id. Example: `"91c54ad1727ee830252e457677f467be0bfd8a57"`.
pr_url (`str`, *optional*):
Url to the PR that has been created, if any. Populated when `create_pr=True`
is passed.
pr_revision (`str`, *optional*):
Revision of the PR that has been created, if any. Populated when
`create_pr=True` is passed. Example: `"refs/pr/1"`.
pr_num (`int`, *optional*):
Number of the PR discussion that has been created, if any. Populated when
`create_pr=True` is passed. Can be passed as `discussion_num` in
[`get_discussion_details`]. Example: `1`.
"""
commit_url: str
commit_message: str
commit_description: str
oid: str
pr_url: Optional[str] = None
# Computed from `pr_url` in `__post_init__`
pr_revision: Optional[str] = field(init=False)
pr_num: Optional[str] = field(init=False)
def __post_init__(self):
"""Populate pr-related fields after initialization.
See https://docs.python.org/3.10/library/dataclasses.html#post-init-processing.
"""
if self.pr_url is not None:
self.pr_revision = _parse_revision_from_pr_url(self.pr_url)
self.pr_num = int(self.pr_revision.split("/")[-1])
else:
self.pr_revision = None
self.pr_num = None
class RepoUrl(str):
"""Subclass of `str` describing a repo URL on the Hub.
`RepoUrl` is returned by `HfApi.create_repo`. It inherits from `str` for backward
compatibility. At initialization, the URL is parsed to populate properties:
- endpoint (`str`)
- namespace (`Optional[str]`)
- repo_id (`str`)
- repo_type (`Literal["model", "dataset", "space"]`)
- url (`str`)
Args:
url (`Any`):
String value of the repo url.
endpoint (`str`, *optional*):
Endpoint of the Hub. Defaults to <https://huggingface.co>.
Example:
```py
>>> RepoUrl('https://huggingface.co/gpt2')
RepoUrl('https://huggingface.co/gpt2', endpoint='https://huggingface.co', repo_type='model', repo_id='gpt2')
>>> RepoUrl('https://hub-ci.huggingface.co/datasets/dummy_user/dummy_dataset', endpoint='https://hub-ci.huggingface.co')
RepoUrl('https://hub-ci.huggingface.co/datasets/dummy_user/dummy_dataset', endpoint='https://hub-ci.huggingface.co', repo_type='dataset', repo_id='dummy_user/dummy_dataset')
>>> RepoUrl('hf://datasets/my-user/my-dataset')
RepoUrl('hf://datasets/my-user/my-dataset', endpoint='https://huggingface.co', repo_type='dataset', repo_id='user/dataset')
>>> HfApi.create_repo("dummy_model")
RepoUrl('https://huggingface.co/Wauplin/dummy_model', endpoint='https://huggingface.co', repo_type='model', repo_id='Wauplin/dummy_model')
```
Raises:
- [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
If URL cannot be parsed.
- [`ValueError`](https://docs.python.org/3/library/exceptions.html#ValueError)
If `repo_type` is unknown.
"""
def __new__(cls, url: Any, endpoint: Optional[str] = None):
return super(RepoUrl, cls).__new__(cls, url)
def __init__(self, url: Any, endpoint: Optional[str] = None) -> None:
super().__init__()
# Parse URL
self.endpoint = endpoint or ENDPOINT
repo_type, namespace, repo_name = repo_type_and_id_from_hf_id(
self, hub_url=self.endpoint
)
# Populate fields
self.namespace = namespace
self.repo_id = repo_name if namespace is None else f"{namespace}/{repo_name}"
self.repo_type = repo_type or REPO_TYPE_MODEL
self.url = str(self) # just in case it's needed
def __repr__(self) -> str:
return (
f"RepoUrl('{self}', endpoint='{self.endpoint}',"
f" repo_type='{self.repo_type}', repo_id='{self.repo_id}')"
)
class RepoFile:
"""
Data structure that represents a public file inside a repo, accessible from
huggingface.co
Args:
rfilename (str):
file name, relative to the repo root. This is the only attribute
that's guaranteed to be here, but under certain conditions there can
certain other stuff.
size (`int`, *optional*):
The file's size, in bytes. This attribute is present when `files_metadata` argument
of [`repo_info`] is set to `True`. It's `None` otherwise.
blob_id (`str`, *optional*):
The file's git OID. This attribute is present when `files_metadata` argument
of [`repo_info`] is set to `True`. It's `None` otherwise.
lfs (`BlobLfsInfo`, *optional*):
The file's LFS metadata. This attribute is present when`files_metadata` argument
of [`repo_info`] is set to `True` and the file is stored with Git LFS. It's `None` otherwise.
"""
def __init__(
self,
rfilename: str,
size: Optional[int] = None,
blobId: Optional[str] = None,
lfs: Optional[BlobLfsInfo] = None,
**kwargs,
):
self.rfilename = rfilename # filename relative to the repo root
# Optional file metadata
self.size = size
self.blob_id = blobId
self.lfs = lfs
# Hack to ensure backward compatibility with future versions of the API.
# See discussion in https://github.com/huggingface/huggingface_hub/pull/951#discussion_r926460408
for k, v in kwargs.items():
setattr(self, k, v)
def __repr__(self):
items = (f"{k}='{v}'" for k, v in self.__dict__.items())
return f"{self.__class__.__name__}({', '.join(items)})"
class ModelInfo:
"""
Info about a model accessible from huggingface.co
Attributes:
modelId (`str`, *optional*):
ID of model repository.
sha (`str`, *optional*):
repo sha at this particular revision
lastModified (`str`, *optional*):
date of last commit to repo
tags (`List[str]`, *optional*):
List of tags.
pipeline_tag (`str`, *optional*):
Pipeline tag to identify the correct widget.
siblings (`List[RepoFile]`, *optional*):
list of ([`huggingface_hub.hf_api.RepoFile`]) objects that constitute the model.
private (`bool`, *optional*, defaults to `False`):
is the repo private
author (`str`, *optional*):
repo author
config (`Dict`, *optional*):
Model configuration information
securityStatus (`Dict`, *optional*):
Security status of the model.
Example: `{"containsInfected": False}`
kwargs (`Dict`, *optional*):
Kwargs that will be become attributes of the class.
"""
def __init__(
self,
*,
modelId: Optional[str] = None,
sha: Optional[str] = None,
lastModified: Optional[str] = None,
tags: Optional[List[str]] = None,
pipeline_tag: Optional[str] = None,
siblings: Optional[List[Dict]] = None,
private: bool = False,
author: Optional[str] = None,
config: Optional[Dict] = None,
securityStatus: Optional[Dict] = None,
**kwargs,
):
self.modelId = modelId
self.sha = sha
self.lastModified = lastModified
self.tags = tags
self.pipeline_tag = pipeline_tag
self.siblings = (
[RepoFile(**x) for x in siblings] if siblings is not None else []
)
self.private = private
self.author = author
self.config = config
self.securityStatus = securityStatus
for k, v in kwargs.items():
setattr(self, k, v)
def __repr__(self):
s = f"{self.__class__.__name__}:" + " {"
for key, val in self.__dict__.items():
s += f"\n\t{key}: {val}"
return s + "\n}"
def __str__(self):
r = f"Model Name: {self.modelId}, Tags: {self.tags}"
if self.pipeline_tag:
r += f", Task: {self.pipeline_tag}"
return r
class DatasetInfo:
"""
Info about a dataset accessible from huggingface.co
Attributes:
id (`str`, *optional*):
ID of dataset repository.
sha (`str`, *optional*):
repo sha at this particular revision
lastModified (`str`, *optional*):
date of last commit to repo
tags (`Listr[str]`, *optional*):
List of tags.
siblings (`List[RepoFile]`, *optional*):
list of [`huggingface_hub.hf_api.RepoFile`] objects that constitute the dataset.
private (`bool`, *optional*, defaults to `False`):
is the repo private
author (`str`, *optional*):
repo author
description (`str`, *optional*):
Description of the dataset
citation (`str`, *optional*):
Dataset citation
cardData (`Dict`, *optional*):
Metadata of the model card as a dictionary.
kwargs (`Dict`, *optional*):
Kwargs that will be become attributes of the class.
"""
def __init__(
self,
*,
id: Optional[str] = None,
sha: Optional[str] = None,
lastModified: Optional[str] = None,
tags: Optional[List[str]] = None,
siblings: Optional[List[Dict]] = None,
private: bool = False,
author: Optional[str] = None,
description: Optional[str] = None,
citation: Optional[str] = None,
cardData: Optional[dict] = None,
**kwargs,
):
self.id = id
self.sha = sha
self.lastModified = lastModified
self.tags = tags
self.private = private
self.author = author
self.description = description
self.citation = citation
self.cardData = cardData
self.siblings = (
[RepoFile(**x) for x in siblings] if siblings is not None else []
)
# Legacy stuff, "key" is always returned with an empty string
# because of old versions of the datasets lib that need this field
kwargs.pop("key", None)
# Store all the other fields returned by the API
for k, v in kwargs.items():
setattr(self, k, v)
def __repr__(self):
s = f"{self.__class__.__name__}:" + " {"
for key, val in self.__dict__.items():
s += f"\n\t{key}: {val}"
return s + "\n}"
def __str__(self):
r = f"Dataset Name: {self.id}, Tags: {self.tags}"
return r
class SpaceInfo:
"""
Info about a Space accessible from huggingface.co
This is a "dataclass" like container that just sets on itself any attribute
passed by the server.
Attributes:
id (`str`, *optional*):
id of space
sha (`str`, *optional*):
repo sha at this particular revision
lastModified (`str`, *optional*):
date of last commit to repo
siblings (`List[RepoFile]`, *optional*):
list of [`huggingface_hub.hf_api.RepoFIle`] objects that constitute the Space
private (`bool`, *optional*, defaults to `False`):
is the repo private
author (`str`, *optional*):
repo author
kwargs (`Dict`, *optional*):
Kwargs that will be become attributes of the class.
"""
def __init__(
self,
*,
id: Optional[str] = None,
sha: Optional[str] = None,
lastModified: Optional[str] = None,
siblings: Optional[List[Dict]] = None,
private: bool = False,
author: Optional[str] = None,
**kwargs,
):
self.id = id
self.sha = sha
self.lastModified = lastModified
self.siblings = (
[RepoFile(**x) for x in siblings] if siblings is not None else []
)
self.private = private
self.author = author
for k, v in kwargs.items():
setattr(self, k, v)
def __repr__(self):
s = f"{self.__class__.__name__}:" + " {"
for key, val in self.__dict__.items():
s += f"\n\t{key}: {val}"
return s + "\n}"
class MetricInfo:
"""
Info about a public metric accessible from huggingface.co
"""
def __init__(
self,
*,
id: Optional[str] = None, # id of metric
description: Optional[str] = None,
citation: Optional[str] = None,
**kwargs,
):
self.id = id
self.description = description
self.citation = citation
# Legacy stuff, "key" is always returned with an empty string
# because of old versions of the datasets lib that need this field
kwargs.pop("key", None)
# Store all the other fields returned by the API
for k, v in kwargs.items():
setattr(self, k, v)
def __repr__(self):
s = f"{self.__class__.__name__}:" + " {"
for key, val in self.__dict__.items():
s += f"\n\t{key}: {val}"
return s + "\n}"
def __str__(self):
r = f"Metric Name: {self.id}"
return r
class ModelSearchArguments(AttributeDictionary):
"""
A nested namespace object holding all possible values for properties of
models currently hosted in the Hub with tab-completion. If a value starts
with a number, it will only exist in the dictionary
Example:
```python
>>> args = ModelSearchArguments()
>>> args.author.huggingface
'huggingface'
>>> args.language.en
'en'
```
<Tip warning={true}>
`ModelSearchArguments` is a legacy class meant for exploratory purposes only. Its
initialization requires listing all models on the Hub which makes it increasingly
slower as the number of repos on the Hub increases.
</Tip>
"""
def __init__(self, api: Optional["HfApi"] = None):
self._api = api if api is not None else HfApi()
tags = self._api.get_model_tags()
super().__init__(tags)
self._process_models()
def _process_models(self):
def clean(s: str) -> str:
return s.replace(" ", "").replace("-", "_").replace(".", "_")
models = self._api.list_models()
author_dict, model_name_dict = AttributeDictionary(), AttributeDictionary()
for model in models:
if "/" in model.modelId:
author, name = model.modelId.split("/")
author_dict[author] = clean(author)
else:
name = model.modelId
model_name_dict[name] = clean(name)
self["model_name"] = model_name_dict
self["author"] = author_dict
class DatasetSearchArguments(AttributeDictionary):
"""
A nested namespace object holding all possible values for properties of
datasets currently hosted in the Hub with tab-completion. If a value starts
with a number, it will only exist in the dictionary
Example:
```python
>>> args = DatasetSearchArguments()
>>> args.author.huggingface
'huggingface'
>>> args.language.en
'language:en'
```
<Tip warning={true}>
`DatasetSearchArguments` is a legacy class meant for exploratory purposes only. Its
initialization requires listing all datasets on the Hub which makes it increasingly
slower as the number of repos on the Hub increases.
</Tip>
"""
def __init__(self, api: Optional["HfApi"] = None):
self._api = api if api is not None else HfApi()
tags = self._api.get_dataset_tags()
super().__init__(tags)
self._process_models()
def _process_models(self):
def clean(s: str):
return s.replace(" ", "").replace("-", "_").replace(".", "_")
datasets = self._api.list_datasets()
author_dict, dataset_name_dict = AttributeDictionary(), AttributeDictionary()
for dataset in datasets:
if "/" in dataset.id:
author, name = dataset.id.split("/")
author_dict[author] = clean(author)
else:
name = dataset.id
dataset_name_dict[name] = clean(name)
self["dataset_name"] = dataset_name_dict
self["author"] = author_dict
@dataclass
class GitRefInfo:
"""
Contains information about a git reference for a repo on the Hub.
Args:
name (`str`):
Name of the reference (e.g. tag name or branch name).
ref (`str`):
Full git ref on the Hub (e.g. `"refs/heads/main"` or `"refs/tags/v1.0"`).
target_commit (`str`):
OID of the target commit for the ref (e.g. `"e7da7f221d5bf496a48136c0cd264e630fe9fcc8"`)
"""
name: str
ref: str
target_commit: str
def __init__(self, data: Dict) -> None:
self.name = data["name"]
self.ref = data["ref"]
self.target_commit = data["targetCommit"]
@dataclass
class GitRefs:
"""
Contains information about all git references for a repo on the Hub.
Object is returned by [`list_repo_refs`].
Args:
branches (`List[GitRefInfo]`):
A list of [`GitRefInfo`] containing information about branches on the repo.
converts (`List[GitRefInfo]`):
A list of [`GitRefInfo`] containing information about "convert" refs on the repo.
Converts are refs used (internally) to push preprocessed data in Dataset repos.
tags (`List[GitRefInfo]`):
A list of [`GitRefInfo`] containing information about tags on the repo.
"""
branches: List[GitRefInfo]
converts: List[GitRefInfo]
tags: List[GitRefInfo]
@dataclass
class UserLikes:
"""
Contains information about a user likes on the Hub.
Args:
user (`str`):
Name of the user for which we fetched the likes.
total (`int`):
Total number of likes.
datasets (`List[str]`):
List of datasets liked by the user (as repo_ids).
models (`List[str]`):
List of models liked by the user (as repo_ids).
spaces (`List[str]`):
List of spaces liked by the user (as repo_ids).
"""
# Metadata
user: str
total: int
# User likes
datasets: List[str]
models: List[str]
spaces: List[str]
class HfApi:
def __init__(
self,
endpoint: Optional[str] = None,
token: Optional[str] = None,
library_name: Optional[str] = None,
library_version: Optional[str] = None,
user_agent: Union[Dict, str, None] = None,
) -> None:
"""Create a HF client to interact with the Hub via HTTP.
The client is initialized with some high-level settings used in all requests
made to the Hub (HF endpoint, authentication, user agents...). Using the `HfApi`
client is preferred but not mandatory as all of its public methods are exposed
directly at the root of `huggingface_hub`.
Args:
endpoint (`str`, *optional*):
Hugging Face Hub base url. Will default to https://huggingface.co/. To
be set if you are using a private hub. Otherwise, one can set the
`HF_ENDPOINT` environment variable.
token (`str`, *optional*):
Hugging Face token. Will default to the locally saved token if
not provided.
library_name (`str`, *optional*):
The name of the library that is making the HTTP request. Will be added to
the user-agent header. Example: `"transformers"`.
library_version (`str`, *optional*):
The version of the library that is making the HTTP request. Will be added
to the user-agent header. Example: `"4.24.0"`.
user_agent (`str`, `dict`, *optional*):
The user agent info in the form of a dictionary or a single string. It will
be completed with information about the installed packages.
"""
self.endpoint = endpoint if endpoint is not None else ENDPOINT
self.token = token
self.library_name = library_name
self.library_version = library_version
self.user_agent = user_agent
def whoami(self, token: Optional[str] = None) -> Dict:
"""
Call HF API to know "whoami".
Args:
token (`str`, *optional*):
Hugging Face token. Will default to the locally saved token if
not provided.
"""
r = requests.get(
f"{self.endpoint}/api/whoami-v2",
headers=self._build_hf_headers(
# If `token` is provided and not `None`, it will be used by default.
# Otherwise, the token must be retrieved from cache or env variable.
token=(token or self.token or True),
),
)
try:
hf_raise_for_status(r)
except HTTPError as e:
raise HTTPError(
"Invalid user token. If you didn't pass a user token, make sure you "
"are properly logged in by executing `huggingface-cli login`, and "
"if you did pass a user token, double-check it's correct."
) from e
return r.json()
def _is_valid_token(self, token: str) -> bool:
"""
Determines whether `token` is a valid token or not.
Args:
token (`str`):
The token to check for validity.
Returns:
`bool`: `True` if valid, `False` otherwise.
"""
try:
self.whoami(token=token)
return True
except HTTPError:
return False
@staticmethod
@_deprecate_method(
version="0.14",
message=(
"`HfApi.set_access_token` is deprecated as it is very ambiguous. Use"
" `login` or `set_git_credential` instead."
),
)
def set_access_token(access_token: str):
"""
Saves the passed access token so git can correctly authenticate the
user.
Args:
access_token (`str`):
The access token to save.
"""
write_to_credential_store(USERNAME_PLACEHOLDER, access_token)
@staticmethod
@_deprecate_method(
version="0.14",
message=(
"`HfApi.unset_access_token` is deprecated as it is very ambiguous. Use"
" `login` or `unset_git_credential` instead."
),
)
def unset_access_token():
"""
Resets the user's access token.
"""
erase_from_credential_store(USERNAME_PLACEHOLDER)
def get_model_tags(self) -> ModelTags:
"Gets all valid model tags as a nested namespace object"
path = f"{self.endpoint}/api/models-tags-by-type"
r = requests.get(path)
hf_raise_for_status(r)
d = r.json()
return ModelTags(d)
def get_dataset_tags(self) -> DatasetTags:
"""
Gets all valid dataset tags as a nested namespace object.
"""
path = f"{self.endpoint}/api/datasets-tags-by-type"
r = requests.get(path)
hf_raise_for_status(r)
d = r.json()
return DatasetTags(d)
@_deprecate_list_output(version="0.14")
@validate_hf_hub_args
def list_models(
self,
*,
filter: Union[ModelFilter, str, Iterable[str], None] = None,
author: Optional[str] = None,
search: Optional[str] = None,
emissions_thresholds: Optional[Tuple[float, float]] = None,
sort: Union[Literal["lastModified"], str, None] = None,
direction: Optional[Literal[-1]] = None,
limit: Optional[int] = None,
full: Optional[bool] = None,
cardData: bool = False,
fetch_config: bool = False,
token: Optional[Union[bool, str]] = None,
) -> List[ModelInfo]:
"""
Get the list of all the models on huggingface.co
Args:
filter ([`ModelFilter`] or `str` or `Iterable`, *optional*):
A string or [`ModelFilter`] which can be used to identify models
on the Hub.
author (`str`, *optional*):
A string which identify the author (user or organization) of the
returned models
search (`str`, *optional*):
A string that will be contained in the returned models Example
usage:
emissions_thresholds (`Tuple`, *optional*):
A tuple of two ints or floats representing a minimum and maximum
carbon footprint to filter the resulting models with in grams.
sort (`Literal["lastModified"]` or `str`, *optional*):
The key with which to sort the resulting models. Possible values
are the properties of the [`huggingface_hub.hf_api.ModelInfo`] class.
direction (`Literal[-1]` or `int`, *optional*):
Direction in which to sort. The value `-1` sorts by descending
order while all other values sort by ascending order.
limit (`int`, *optional*):
The limit on the number of models fetched. Leaving this option
to `None` fetches all models.
full (`bool`, *optional*):
Whether to fetch all model data, including the `lastModified`,
the `sha`, the files and the `tags`. This is set to `True` by
default when using a filter.
cardData (`bool`, *optional*):
Whether to grab the metadata for the model as well. Can contain
useful information such as carbon emissions, metrics, and
datasets trained on.
fetch_config (`bool`, *optional*):
Whether to fetch the model configs as well. This is not included
in `full` due to its size.
token (`bool` or `str`, *optional*):
A valid authentication token (see https://huggingface.co/settings/token).
If `None` or `True` and machine is logged in (through `huggingface-cli login`
or [`~huggingface_hub.login`]), token will be retrieved from the cache.
If `False`, token is not sent in the request header.
Returns:
`List[ModelInfo]`: a list of [`huggingface_hub.hf_api.ModelInfo`] objects.
To anticipate future pagination, please consider the return value to be a
simple iterator.
Example usage with the `filter` argument:
```python
>>> from huggingface_hub import HfApi
>>> api = HfApi()
>>> # List all models
>>> api.list_models()
>>> # Get all valid search arguments
>>> args = ModelSearchArguments()
>>> # List only the text classification models
>>> api.list_models(filter="text-classification")
>>> # Using the `ModelFilter`
>>> filt = ModelFilter(task="text-classification")
>>> # With `ModelSearchArguments`
>>> filt = ModelFilter(task=args.pipeline_tags.TextClassification)
>>> api.list_models(filter=filt)
>>> # Using `ModelFilter` and `ModelSearchArguments` to find text classification in both PyTorch and TensorFlow
>>> filt = ModelFilter(
... task=args.pipeline_tags.TextClassification,
... library=[args.library.PyTorch, args.library.TensorFlow],
... )
>>> api.list_models(filter=filt)
>>> # List only models from the AllenNLP library
>>> api.list_models(filter="allennlp")
>>> # Using `ModelFilter` and `ModelSearchArguments`
>>> filt = ModelFilter(library=args.library.allennlp)
```
Example usage with the `search` argument:
```python
>>> from huggingface_hub import HfApi
>>> api = HfApi()
>>> # List all models with "bert" in their name
>>> api.list_models(search="bert")
>>> # List all models with "bert" in their name made by google
>>> api.list_models(search="bert", author="google")
```
"""
path = f"{self.endpoint}/api/models"
headers = self._build_hf_headers(token=token)
params = {}
if filter is not None: