File size: 44,913 Bytes
b72ab63
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
"""
This file defines two useful high-level abstractions to build Gradio apps: Interface and TabbedInterface.
"""

from __future__ import annotations

import inspect
import json
import os
import warnings
import weakref
from typing import TYPE_CHECKING, Any, Callable, Literal

from gradio_client.documentation import document

from gradio import Examples, utils, wasm_utils
from gradio.blocks import Blocks
from gradio.components import (
    Button,
    ClearButton,
    Component,
    DuplicateButton,
    Markdown,
    State,
    get_component_instance,
)
from gradio.data_classes import InterfaceTypes
from gradio.events import Dependency, Events, on
from gradio.exceptions import RenderError
from gradio.flagging import CSVLogger, FlaggingCallback, FlagMethod
from gradio.layouts import Accordion, Column, Row, Tab, Tabs
from gradio.pipelines import load_from_js_pipeline, load_from_pipeline
from gradio.themes import ThemeClass as Theme

if TYPE_CHECKING:  # Only import for type checking (is False at runtime).
    from diffusers import DiffusionPipeline  # type: ignore
    from transformers.pipelines.base import Pipeline


@document("launch", "load", "from_pipeline", "integrate", "queue")
class Interface(Blocks):
    """
    Interface is Gradio's main high-level class, and allows you to create a web-based GUI / demo
    around a machine learning model (or any Python function) in a few lines of code.
    You must specify three parameters: (1) the function to create a GUI for (2) the desired input components and
    (3) the desired output components. Additional parameters can be used to control the appearance
    and behavior of the demo.

    Example:
        import gradio as gr

        def image_classifier(inp):
            return {'cat': 0.3, 'dog': 0.7}

        demo = gr.Interface(fn=image_classifier, inputs="image", outputs="label")
        demo.launch()
    Demos: hello_world, hello_world_2, hello_world_3
    Guides: quickstart, key-features, sharing-your-app, interface-state, reactive-interfaces, advanced-interface-features, setting-up-a-gradio-demo-for-maximum-performance
    """

    # stores references to all currently existing Interface instances
    instances: weakref.WeakSet = weakref.WeakSet()

    @classmethod
    def get_instances(cls) -> list[Interface]:
        """
        :return: list of all current instances.
        """
        return list(Interface.instances)

    @classmethod
    def from_pipeline(
        cls, pipeline: Pipeline | DiffusionPipeline, **kwargs
    ) -> Interface:
        """
        Class method that constructs an Interface from a Hugging Face transformers.Pipeline or diffusers.DiffusionPipeline object.
        The input and output components are automatically determined from the pipeline.
        Parameters:
            pipeline: the pipeline object to use.
        Returns:
            a Gradio Interface object from the given Pipeline
        Example:
            import gradio as gr
            from transformers import pipeline
            pipe = pipeline("image-classification")
            gr.Interface.from_pipeline(pipe).launch()
        """
        if wasm_utils.IS_WASM:
            interface_info = load_from_js_pipeline(pipeline)
        else:
            interface_info = load_from_pipeline(pipeline)
        kwargs = dict(interface_info, **kwargs)
        interface = cls(**kwargs)
        return interface

    def __init__(
        self,
        fn: Callable,
        inputs: str | Component | list[str | Component] | None,
        outputs: str | Component | list[str | Component] | None,
        examples: list[Any] | list[list[Any]] | str | None = None,
        cache_examples: bool | Literal["lazy"] | None = None,
        examples_per_page: int = 10,
        live: bool = False,
        title: str | None = None,
        description: str | None = None,
        article: str | None = None,
        thumbnail: str | None = None,
        theme: Theme | str | None = None,
        css: str | None = None,
        allow_flagging: Literal["never"]
        | Literal["auto"]
        | Literal["manual"]
        | None = None,
        flagging_options: list[str] | list[tuple[str, str]] | None = None,
        flagging_dir: str = "flagged",
        flagging_callback: FlaggingCallback | None = None,
        analytics_enabled: bool | None = None,
        batch: bool = False,
        max_batch_size: int = 4,
        api_name: str | Literal[False] | None = "predict",
        _api_mode: bool = False,
        allow_duplication: bool = False,
        concurrency_limit: int | None | Literal["default"] = "default",
        js: str | None = None,
        head: str | None = None,
        additional_inputs: str | Component | list[str | Component] | None = None,
        additional_inputs_accordion: str | Accordion | None = None,
        *,
        submit_btn: str | Button = "Submit",
        stop_btn: str | Button = "Stop",
        clear_btn: str | Button | None = "Clear",
        delete_cache: tuple[int, int] | None = None,
        **kwargs,
    ):
        """
        Parameters:
            fn: The function to wrap an interface around. Often a machine learning model's prediction function. Each parameter of the function corresponds to one input component, and the function should return a single value or a tuple of values, with each element in the tuple corresponding to one output component.
            inputs: A single Gradio component, or list of Gradio components. Components can either be passed as instantiated objects, or referred to by their string shortcuts. The number of input components should match the number of parameters in fn. If set to None, then only the output components will be displayed.
            outputs: A single Gradio component, or list of Gradio components. Components can either be passed as instantiated objects, or referred to by their string shortcuts. The number of output components should match the number of values returned by fn. If set to None, then only the input components will be displayed.
            examples: Sample inputs for the function; if provided, appear below the UI components and can be clicked to populate the interface. Should be nested list, in which the outer list consists of samples and each inner list consists of an input corresponding to each input component. A string path to a directory of examples can also be provided, but it should be within the directory with the python file running the gradio app. If there are multiple input components and a directory is provided, a log.csv file must be present in the directory to link corresponding inputs.
            cache_examples: If True, caches examples in the server for fast runtime in examples. If "lazy", then examples are cached after their first use. If `fn` is a generator function, then the last yielded value will be used as the output. Can also be set by the GRADIO_CACHE_EXAMPLES environment variable, which takes a case-insensitive value, one of: {"true", "false", "lazy"}. The default option in HuggingFace Spaces is True. The default option elsewhere is False.
            examples_per_page: If examples are provided, how many to display per page.
            live: Whether the interface should automatically rerun if any of the inputs change.
            title: A title for the interface; if provided, appears above the input and output components in large font. Also used as the tab title when opened in a browser window.
            description: A description for the interface; if provided, appears above the input and output components and beneath the title in regular font. Accepts Markdown and HTML content.
            article: An expanded article explaining the interface; if provided, appears below the input and output components in regular font. Accepts Markdown and HTML content. If it is an HTTP(S) link to a downloadable remote file, the content of this file is displayed.
            thumbnail: This parameter has been deprecated and has no effect.
            theme: A Theme object or a string representing a theme. If a string, will look for a built-in theme with that name (e.g. "soft" or "default"), or will attempt to load a theme from the Hugging Face Hub (e.g. "gradio/monochrome"). If None, will use the Default theme.
            css: Custom css as a string or path to a css file. This css will be included in the demo webpage.
            allow_flagging: One of "never", "auto", or "manual". If "never" or "auto", users will not see a button to flag an input and output. If "manual", users will see a button to flag. If "auto", every input the user submits will be automatically flagged, along with the generated output. If "manual", both the input and outputs are flagged when the user clicks flag button. This parameter can be set with environmental variable GRADIO_ALLOW_FLAGGING; otherwise defaults to "manual".
            flagging_options: If provided, allows user to select from the list of options when flagging. Only applies if allow_flagging is "manual". Can either be a list of tuples of the form (label, value), where label is the string that will be displayed on the button and value is the string that will be stored in the flagging CSV; or it can be a list of strings ["X", "Y"], in which case the values will be the list of strings and the labels will ["Flag as X", "Flag as Y"], etc.
            flagging_dir: What to name the directory where flagged data is stored.
            flagging_callback: None or an instance of a subclass of FlaggingCallback which will be called when a sample is flagged. If set to None, an instance of gradio.flagging.CSVLogger will be created and logs will be saved to a local CSV file in flagging_dir. Default to None.
            analytics_enabled: Whether to allow basic telemetry. If None, will use GRADIO_ANALYTICS_ENABLED environment variable if defined, or default to True.
            batch: If True, then the function should process a batch of inputs, meaning that it should accept a list of input values for each parameter. The lists should be of equal length (and be up to length `max_batch_size`). The function is then *required* to return a tuple of lists (even if there is only 1 output component), with each list in the tuple corresponding to one output component.
            max_batch_size: Maximum number of inputs to batch together if this is called from the queue (only relevant if batch=True)
            api_name: Defines how the endpoint appears in the API docs. Can be a string, None, or False. If set to a string, the endpoint will be exposed in the API docs with the given name. If None, the name of the prediction function will be used as the API endpoint. If False, the endpoint will not be exposed in the API docs and downstream apps (including those that `gr.load` this app) will not be able to use this event.
            allow_duplication: If True, then will show a 'Duplicate Spaces' button on Hugging Face Spaces.
            concurrency_limit: If set, this is the maximum number of this event that can be running simultaneously. Can be set to None to mean no concurrency_limit (any number of this event can be running simultaneously). Set to "default" to use the default concurrency limit (defined by the `default_concurrency_limit` parameter in `.queue()`, which itself is 1 by default).
            js: Custom js as a string or path to a js file. The custom js should be in the form of a single js function. This function will automatically be executed when the page loads. For more flexibility, use the head parameter to insert js inside <script> tags.
            head: Custom html to insert into the head of the demo webpage. This can be used to add custom meta tags, scripts, stylesheets, etc. to the page.
            additional_inputs: A single Gradio component, or list of Gradio components. Components can either be passed as instantiated objects, or referred to by their string shortcuts. These components will be rendered in an accordion below the main input components. By default, no additional input components will be displayed.
            additional_inputs_accordion: If a string is provided, this is the label of the `gr.Accordion` to use to contain additional inputs. A `gr.Accordion` object can be provided as well to configure other properties of the container holding the additional inputs. Defaults to a `gr.Accordion(label="Additional Inputs", open=False)`. This parameter is only used if `additional_inputs` is provided.
            submit_btn: The button to use for submitting inputs. Defaults to a `gr.Button("Submit", variant="primary")`. This parameter does not apply if the Interface is output-only, in which case the submit button always displays "Generate". Can be set to a string (which becomes the button label) or a `gr.Button` object (which allows for more customization).
            stop_btn: The button to use for stopping the interface. Defaults to a `gr.Button("Stop", variant="stop", visible=False)`. Can be set to a string (which becomes the button label) or a `gr.Button` object (which allows for more customization).
            clear_btn: The button to use for clearing the inputs. Defaults to a `gr.Button("Clear", variant="secondary")`. Can be set to a string (which becomes the button label) or a `gr.Button` object (which allows for more customization). Can be set to None, which hides the button.
            delete_cache: A tuple corresponding [frequency, age] both expressed in number of seconds. Every `frequency` seconds, the temporary files created by this Blocks instance will be deleted if more than `age` seconds have passed since the file was created. For example, setting this to (86400, 86400) will delete temporary files every day. The cache will be deleted entirely when the server restarts. If None, no cache deletion will occur.
        """
        super().__init__(
            analytics_enabled=analytics_enabled,
            mode="interface",
            css=css,
            title=title or "Gradio",
            theme=theme,
            js=js,
            head=head,
            delete_cache=delete_cache,
            **kwargs,
        )
        self.api_name: str | Literal[False] | None = api_name
        self.interface_type = InterfaceTypes.STANDARD
        if (inputs is None or inputs == []) and (outputs is None or outputs == []):
            raise ValueError("Must provide at least one of `inputs` or `outputs`")
        elif outputs is None or outputs == []:
            outputs = []
            self.interface_type = InterfaceTypes.INPUT_ONLY
        elif inputs is None or inputs == []:
            inputs = []
            self.interface_type = InterfaceTypes.OUTPUT_ONLY
        if additional_inputs is None:
            additional_inputs = []

        if not isinstance(inputs, (str, list, Component)):
            raise TypeError(
                f"inputs must be a string, list, or Component, not {inputs}"
            )
        if not isinstance(outputs, (str, list, Component)):
            raise TypeError(
                f"outputs must be a string, list, or Component, not {outputs}"
            )

        if not isinstance(inputs, list):
            inputs = [inputs]
        if not isinstance(outputs, list):
            outputs = [outputs]
        if not isinstance(additional_inputs, list):
            additional_inputs = [additional_inputs]

        self.cache_examples = cache_examples

        state_input_indexes = [
            idx for idx, i in enumerate(inputs) if i == "state" or isinstance(i, State)
        ]
        state_output_indexes = [
            idx for idx, o in enumerate(outputs) if o == "state" or isinstance(o, State)
        ]

        if len(state_input_indexes) == 0 and len(state_output_indexes) == 0:
            pass
        elif len(state_input_indexes) != 1 or len(state_output_indexes) != 1:
            raise ValueError(
                "If using 'state', there must be exactly one state input and one state output."
            )
        else:
            state_input_index = state_input_indexes[0]
            state_output_index = state_output_indexes[0]
            if inputs[state_input_index] == "state":
                default = utils.get_default_args(fn)[state_input_index]
                state_variable = State(value=default)  # type: ignore
            else:
                state_variable = inputs[state_input_index]

            inputs[state_input_index] = state_variable
            outputs[state_output_index] = state_variable

            if cache_examples:
                warnings.warn(
                    "Cache examples cannot be used with state inputs and outputs."
                    "Setting cache_examples to False."
                )
            self.cache_examples = False

        self.main_input_components = [
            get_component_instance(i, unrender=True)
            for i in inputs  # type: ignore
        ]
        self.additional_input_components = [
            get_component_instance(i, unrender=True)
            for i in additional_inputs  # type: ignore
        ]
        if additional_inputs_accordion is None:
            self.additional_inputs_accordion_params = {
                "label": "Additional Inputs",
                "open": False,
            }
        elif isinstance(additional_inputs_accordion, str):
            self.additional_inputs_accordion_params = {
                "label": additional_inputs_accordion
            }
        elif isinstance(additional_inputs_accordion, Accordion):
            self.additional_inputs_accordion_params = (
                additional_inputs_accordion.recover_kwargs(
                    additional_inputs_accordion.get_config()
                )
            )
        else:
            raise ValueError(
                f"The `additional_inputs_accordion` parameter must be a string or gr.Accordion, not {type(additional_inputs_accordion)}"
            )
        self.input_components = (
            self.main_input_components + self.additional_input_components
        )
        self.output_components = [
            get_component_instance(o, unrender=True)
            for o in outputs  # type: ignore
        ]

        for component in self.input_components + self.output_components:
            if not (isinstance(component, Component)):
                raise ValueError(
                    f"{component} is not a valid input/output component for Interface."
                )

        if len(self.input_components) == len(self.output_components):
            same_components = [
                i is o for i, o in zip(self.input_components, self.output_components)
            ]
            if all(same_components):
                self.interface_type = InterfaceTypes.UNIFIED

        if self.interface_type in [
            InterfaceTypes.STANDARD,
            InterfaceTypes.OUTPUT_ONLY,
        ]:
            for o in self.output_components:
                if not isinstance(o, Component):
                    raise TypeError(
                        f"Output component must be a Component, not {type(o)}"
                    )
                if o.interactive is None:
                    # Unless explicitly otherwise specified, force output components to
                    # be non-interactive
                    o.interactive = False

        self.api_mode = _api_mode
        self.fn = fn
        self.fn_durations = [0, 0]
        self.__name__ = getattr(fn, "__name__", "fn")
        self.live = live
        self.title = title

        self.simple_description = utils.remove_html_tags(description)
        self.description = description
        if article is not None:
            article = utils.download_if_url(article)
        self.article = article

        self.thumbnail = thumbnail

        self.examples = examples
        self.examples_per_page = examples_per_page

        if isinstance(submit_btn, Button):
            self.submit_btn_parms = submit_btn.recover_kwargs(submit_btn.get_config())
        elif isinstance(submit_btn, str):
            self.submit_btn_parms = {
                "value": submit_btn,
                "variant": "primary",
            }
        else:
            raise ValueError(
                f"The submit_btn parameter must be a gr.Button or string, not {type(submit_btn)}"
            )

        if isinstance(stop_btn, Button):
            self.stop_btn_parms = stop_btn.recover_kwargs(stop_btn.get_config())
        elif isinstance(stop_btn, str):
            self.stop_btn_parms = {
                "value": stop_btn,
                "variant": "stop",
                "visible": False,
            }
        else:
            raise ValueError(
                f"The stop_btn parameter must be a gr.Button or string, not {type(stop_btn)}"
            )

        if clear_btn is None:
            self.clear_btn_params = {
                "visible": False,
                "variant": "secondary",
            }
        elif isinstance(clear_btn, Button):
            self.clear_btn_params = clear_btn.recover_kwargs(clear_btn.get_config())
        elif isinstance(clear_btn, str):
            self.clear_btn_params = {
                "value": clear_btn,
                "variant": "secondary",
            }
        else:
            raise ValueError(
                f"The clear_btn parameter must be a gr.Button, a string, or None, not {type(clear_btn)}"
            )

        self.simple_server = None

        # For allow_flagging: (1) first check for parameter,
        # (2) check for env variable, (3) default to True/"manual"
        if allow_flagging is None:
            allow_flagging = os.getenv("GRADIO_ALLOW_FLAGGING", "manual")  # type: ignore
        if allow_flagging is True:
            warnings.warn(
                "The `allow_flagging` parameter in `Interface` now"
                "takes a string value ('auto', 'manual', or 'never')"
                ", not a boolean. Setting parameter to: 'manual'."
            )
            self.allow_flagging = "manual"
        elif allow_flagging == "manual":
            self.allow_flagging = "manual"
        elif allow_flagging is False:
            warnings.warn(
                "The `allow_flagging` parameter in `Interface` now"
                "takes a string value ('auto', 'manual', or 'never')"
                ", not a boolean. Setting parameter to: 'never'."
            )
            self.allow_flagging = "never"
        elif allow_flagging == "never":
            self.allow_flagging = "never"
        elif allow_flagging == "auto":
            self.allow_flagging = "auto"
        else:
            raise ValueError(
                "Invalid value for `allow_flagging` parameter."
                "Must be: 'auto', 'manual', or 'never'."
            )

        if flagging_options is None:
            self.flagging_options = [("Flag", "")]
        elif not (isinstance(flagging_options, list)):
            raise ValueError(
                "flagging_options must be a list of strings or list of (string, string) tuples."
            )
        elif all(isinstance(x, str) for x in flagging_options):
            self.flagging_options = [(f"Flag as {x}", x) for x in flagging_options]
        elif all(isinstance(x, tuple) for x in flagging_options):
            self.flagging_options = flagging_options
        else:
            raise ValueError(
                "flagging_options must be a list of strings or list of (string, string) tuples."
            )

        if flagging_callback is None:
            flagging_callback = CSVLogger()

        self.flagging_callback = flagging_callback
        self.flagging_dir = flagging_dir

        self.batch = batch
        self.max_batch_size = max_batch_size
        self.allow_duplication = allow_duplication
        self.concurrency_limit: int | None | Literal["default"] = concurrency_limit

        self.share = None
        self.share_url = None
        self.local_url = None

        self.favicon_path = None
        Interface.instances.add(self)

        param_types = utils.get_type_hints(self.fn)
        # param_names = inspect.getfullargspec(self.fn)[0]
        param_names = []
        try:
            param_names = inspect.getfullargspec(self.fn)[0]
            if len(param_names) > 0 and inspect.ismethod(self.fn):
                param_names = param_names[1:]
            for param_name in param_names.copy():
                if utils.is_special_typed_parameter(param_name, param_types):
                    param_names.remove(param_name)
        except (TypeError, ValueError):
            param_names = utils.default_input_labels()
        for component, param_name in zip(self.input_components, param_names):
            if not isinstance(component, Component):
                raise TypeError(
                    f"Input component must be a Component, not {type(component)}"
                )
            if component.label is None:
                component.label = param_name
        for i, component in enumerate(self.output_components):
            if not isinstance(component, Component):
                raise TypeError(
                    f"Output component must be a Component, not {type(component)}"
                )
            if component.label is None:
                if len(self.output_components) == 1:
                    component.label = "output"
                else:
                    component.label = f"output {i}"

        if self.allow_flagging != "never":
            if self.interface_type == InterfaceTypes.UNIFIED:
                self.flagging_callback.setup(self.input_components, self.flagging_dir)  # type: ignore
            elif self.interface_type == InterfaceTypes.INPUT_ONLY:
                pass
            else:
                self.flagging_callback.setup(
                    self.input_components + self.output_components,
                    self.flagging_dir,  # type: ignore
                )

        # Render the Gradio UI
        with self:
            self.render_title_description()

            _submit_btn, _clear_btn, _stop_btn, flag_btns, duplicate_btn = (
                None,
                None,
                None,
                None,
                None,
            )  # type: ignore
            input_component_column = None

            with Row(equal_height=False):
                if self.interface_type in [
                    InterfaceTypes.STANDARD,
                    InterfaceTypes.INPUT_ONLY,
                    InterfaceTypes.UNIFIED,
                ]:
                    (
                        _submit_btn,
                        _clear_btn,
                        _stop_btn,
                        flag_btns,
                        input_component_column,
                    ) = self.render_input_column()  # type: ignore
                if self.interface_type in [
                    InterfaceTypes.STANDARD,
                    InterfaceTypes.OUTPUT_ONLY,
                ]:
                    (
                        _submit_btn_out,
                        _clear_btn_2_out,
                        duplicate_btn,
                        _stop_btn_2_out,
                        flag_btns_out,
                    ) = self.render_output_column(_submit_btn)
                    _submit_btn = _submit_btn or _submit_btn_out
                    _clear_btn = _clear_btn or _clear_btn_2_out
                    _stop_btn = _stop_btn or _stop_btn_2_out
                    flag_btns = flag_btns or flag_btns_out

            if _clear_btn is None:
                raise RenderError("Clear button not rendered")

            _submit_event = self.attach_submit_events(_submit_btn, _stop_btn)
            self.attach_clear_events(_clear_btn, input_component_column)
            if duplicate_btn is not None:
                duplicate_btn.activate()

            self.attach_flagging_events(flag_btns, _clear_btn, _submit_event)
            self.render_examples()
            self.render_article()

        self.config = self.get_config_file()

    def render_title_description(self) -> None:
        if self.title:
            Markdown(
                f"<h1 style='text-align: center; margin-bottom: 1rem'>{self.title}</h1>"
            )
        if self.description:
            Markdown(self.description)

    def render_flag_btns(self) -> list[Button]:
        return [Button(label) for label, _ in self.flagging_options]

    def render_input_column(
        self,
    ) -> tuple[
        Button | None,
        ClearButton | None,
        Button | None,
        list[Button] | None,
        Column,
    ]:
        _submit_btn, _clear_btn, _stop_btn, flag_btns = None, None, None, None

        with Column(variant="panel"):
            input_component_column = Column()
            with input_component_column:
                for component in self.main_input_components:
                    component.render()
                if self.additional_input_components:
                    with Accordion(**self.additional_inputs_accordion_params):  # type: ignore
                        for component in self.additional_input_components:
                            component.render()
            with Row():
                if self.interface_type in [
                    InterfaceTypes.STANDARD,
                    InterfaceTypes.INPUT_ONLY,
                ]:
                    _clear_btn = ClearButton(**self.clear_btn_params)  # type: ignore
                    if not self.live:
                        _submit_btn = Button(**self.submit_btn_parms)  # type: ignore
                        # Stopping jobs only works if the queue is enabled
                        # We don't know if the queue is enabled when the interface
                        # is created. We use whether a generator function is provided
                        # as a proxy of whether the queue will be enabled.
                        # Using a generator function without the queue will raise an error.
                        if inspect.isgeneratorfunction(
                            self.fn
                        ) or inspect.isasyncgenfunction(self.fn):
                            _stop_btn = Button(**self.stop_btn_parms)
                elif self.interface_type == InterfaceTypes.UNIFIED:
                    _clear_btn = ClearButton(**self.clear_btn_params)  # type: ignore
                    _submit_btn = Button(**self.submit_btn_parms)  # type: ignore
                    if (
                        inspect.isgeneratorfunction(self.fn)
                        or inspect.isasyncgenfunction(self.fn)
                    ) and not self.live:
                        _stop_btn = Button(**self.stop_btn_parms)
                    if self.allow_flagging == "manual":
                        flag_btns = self.render_flag_btns()
                    elif self.allow_flagging == "auto":
                        flag_btns = [_submit_btn]
        return (
            _submit_btn,
            _clear_btn,
            _stop_btn,
            flag_btns,
            input_component_column,
        )

    def render_output_column(
        self,
        _submit_btn_in: Button | None,
    ) -> tuple[
        Button | None,
        ClearButton | None,
        DuplicateButton | None,
        Button | None,
        list | None,
    ]:
        _submit_btn = _submit_btn_in
        _clear_btn, duplicate_btn, flag_btns, _stop_btn = (
            None,
            None,
            None,
            None,
        )

        with Column(variant="panel"):
            for component in self.output_components:
                if not (isinstance(component, State)):
                    component.render()
            with Row():
                if self.interface_type == InterfaceTypes.OUTPUT_ONLY:
                    _clear_btn = ClearButton(**self.clear_btn_params)  # type: ignore
                    _submit_btn = Button("Generate", variant="primary")
                    if (
                        inspect.isgeneratorfunction(self.fn)
                        or inspect.isasyncgenfunction(self.fn)
                    ) and not self.live:
                        # Stopping jobs only works if the queue is enabled
                        # We don't know if the queue is enabled when the interface
                        # is created. We use whether a generator function is provided
                        # as a proxy of whether the queue will be enabled.
                        # Using a generator function without the queue will raise an error.
                        _stop_btn = Button(**self.stop_btn_parms)
                if self.allow_flagging == "manual":
                    flag_btns = self.render_flag_btns()
                elif self.allow_flagging == "auto":
                    if _submit_btn is None:
                        raise RenderError("Submit button not rendered")
                    flag_btns = [_submit_btn]

                if self.allow_duplication:
                    duplicate_btn = DuplicateButton(scale=1, size="lg", _activate=False)

        return (
            _submit_btn,
            _clear_btn,
            duplicate_btn,
            _stop_btn,
            flag_btns,
        )

    def render_article(self):
        if self.article:
            Markdown(self.article)

    def attach_submit_events(
        self, _submit_btn: Button | None, _stop_btn: Button | None
    ) -> Dependency:
        if self.live:
            if self.interface_type == InterfaceTypes.OUTPUT_ONLY:
                if _submit_btn is None:
                    raise RenderError("Submit button not rendered")
                super().load(self.fn, None, self.output_components)
                # For output-only interfaces, the user probably still want a "generate"
                # button even if the Interface is live
                return _submit_btn.click(
                    self.fn,
                    None,
                    self.output_components,
                    api_name=self.api_name,
                    preprocess=not (self.api_mode),
                    postprocess=not (self.api_mode),
                    batch=self.batch,
                    max_batch_size=self.max_batch_size,
                )
            else:
                events: list[Callable] = []
                streaming_event = False
                for component in self.input_components:
                    if component.has_event("stream") and component.streaming:  # type: ignore
                        events.append(component.stream)  # type: ignore
                        streaming_event = True
                    elif component.has_event("change"):
                        events.append(component.change)  # type: ignore
                return on(
                    events,
                    self.fn,
                    self.input_components,
                    self.output_components,
                    api_name=self.api_name,
                    preprocess=not (self.api_mode),
                    postprocess=not (self.api_mode),
                    show_progress="hidden" if streaming_event else "full",
                    trigger_mode="always_last",
                )
        else:
            if _submit_btn is None:
                raise RenderError("Submit button not rendered")
            fn = self.fn
            extra_output = []

            triggers = [_submit_btn.click] + [
                component.submit  # type: ignore
                for component in self.input_components
                if component.has_event(Events.submit)
            ]

            if _stop_btn:
                extra_output = [_submit_btn, _stop_btn]

                async def cleanup():
                    return [Button(visible=True), Button(visible=False)]

                predict_event = on(
                    triggers,
                    utils.async_lambda(
                        lambda: (
                            Button(visible=False),
                            Button(visible=True),
                        )
                    ),
                    inputs=None,
                    outputs=[_submit_btn, _stop_btn],
                    queue=False,
                    show_api=False,
                ).then(
                    self.fn,
                    self.input_components,
                    self.output_components,
                    api_name=self.api_name,
                    scroll_to_output=True,
                    preprocess=not (self.api_mode),
                    postprocess=not (self.api_mode),
                    batch=self.batch,
                    max_batch_size=self.max_batch_size,
                    concurrency_limit=self.concurrency_limit,
                )

                final_event = predict_event.then(
                    cleanup,
                    inputs=None,
                    outputs=extra_output,  # type: ignore
                    queue=False,
                    show_api=False,
                )

                _stop_btn.click(
                    cleanup,
                    inputs=None,
                    outputs=[_submit_btn, _stop_btn],
                    cancels=predict_event,
                    queue=False,
                    show_api=False,
                )
                return final_event
            else:
                return on(
                    triggers,
                    fn,
                    self.input_components,
                    self.output_components,
                    api_name=self.api_name,
                    scroll_to_output=True,
                    preprocess=not (self.api_mode),
                    postprocess=not (self.api_mode),
                    batch=self.batch,
                    max_batch_size=self.max_batch_size,
                    concurrency_limit=self.concurrency_limit,
                )

    def attach_clear_events(
        self,
        _clear_btn: ClearButton,
        input_component_column: Column | None,
    ):
        _clear_btn.add(self.input_components + self.output_components)
        _clear_btn.click(
            None,
            [],
            ([input_component_column] if input_component_column else []),  # type: ignore
            js=f"""() => {json.dumps(

                    [{'variant': None, 'visible': True, '__type__': 'update'}]
                    if self.interface_type
                       in [
                           InterfaceTypes.STANDARD,
                           InterfaceTypes.INPUT_ONLY,
                           InterfaceTypes.UNIFIED,
                       ]
                    else []

            )}
            """,
        )

    def attach_flagging_events(
        self,
        flag_btns: list[Button] | None,
        _clear_btn: ClearButton,
        _submit_event: Dependency,
    ):
        if not (
            flag_btns
            and self.interface_type
            in (
                InterfaceTypes.STANDARD,
                InterfaceTypes.OUTPUT_ONLY,
                InterfaceTypes.UNIFIED,
            )
        ):
            return

        if self.allow_flagging == "auto":
            flag_method = FlagMethod(
                self.flagging_callback, "", "", visual_feedback=False
            )
            _submit_event.success(
                flag_method,
                inputs=self.input_components + self.output_components,
                outputs=None,
                preprocess=False,
                queue=False,
                show_api=False,
            )
            return

        if self.interface_type == InterfaceTypes.UNIFIED:
            flag_components = self.input_components
        else:
            flag_components = self.input_components + self.output_components

        for flag_btn, (label, value) in zip(flag_btns, self.flagging_options):
            if not isinstance(value, str):
                raise TypeError(
                    f"Flagging option value must be a string, not {value!r}"
                )
            flag_method = FlagMethod(self.flagging_callback, label, value)
            flag_btn.click(
                utils.async_lambda(
                    lambda: Button(value="Saving...", interactive=False)
                ),
                None,
                flag_btn,
                queue=False,
                show_api=False,
            )
            flag_btn.click(
                flag_method,
                inputs=flag_components,
                outputs=flag_btn,
                preprocess=False,
                queue=False,
                show_api=False,
            )
            _clear_btn.click(
                utils.async_lambda(flag_method.reset),
                None,
                flag_btn,
                queue=False,
                show_api=False,
            )

    def render_examples(self):
        if self.examples:
            non_state_inputs = [
                c for c in self.input_components if not isinstance(c, State)
            ]
            non_state_outputs = [
                c for c in self.output_components if not isinstance(c, State)
            ]
            self.examples_handler = Examples(
                examples=self.examples,
                inputs=non_state_inputs,  # type: ignore
                outputs=non_state_outputs,  # type: ignore
                fn=self.fn,
                cache_examples=self.cache_examples,  # type: ignore
                examples_per_page=self.examples_per_page,
                _api_mode=self.api_mode,
                batch=self.batch,
            )

    def __str__(self):
        return self.__repr__()

    def __repr__(self):
        repr = f"Gradio Interface for: {self.__name__}"
        repr += f"\n{'-' * len(repr)}"
        repr += "\ninputs:"
        for component in self.input_components:
            repr += f"\n|-{component}"
        repr += "\noutputs:"
        for component in self.output_components:
            repr += f"\n|-{component}"
        return repr


@document()
class TabbedInterface(Blocks):
    """
    A TabbedInterface is created by providing a list of Interfaces or Blocks, each of which gets
    rendered in a separate tab. Only the components from the Interface/Blocks will be rendered in the tab.
    Certain high-level attributes of the Blocks (e.g. custom `css`, `js`, and `head` attributes) will not be loaded.

    Demos: tabbed_interface_lite
    """

    def __init__(
        self,
        interface_list: list[Interface],
        tab_names: list[str] | None = None,
        title: str | None = None,
        theme: Theme | str | None = None,
        analytics_enabled: bool | None = None,
        css: str | None = None,
        js: str | None = None,
        head: str | None = None,
    ):
        """
        Parameters:
            interface_list: A list of Interfaces (or Blocks) to be rendered in the tabs.
            tab_names: A list of tab names. If None, the tab names will be "Tab 1", "Tab 2", etc.
            title: The tab title to display when this demo is opened in a browser window.
            theme: A Theme object or a string representing a theme. If a string, will look for a built-in theme with that name (e.g. "soft" or "default"), or will attempt to load a theme from the Hugging Face Hub (e.g. "gradio/monochrome"). If None, will use the Default theme.
            analytics_enabled: Whether to allow basic telemetry. If None, will use GRADIO_ANALYTICS_ENABLED environment variable or default to True.
            css: Custom css as a string or path to a css file. This css will be included in the demo webpage.
            js: Custom js as a string or path to a js file. The custom js should in the form of a single js function. This function will automatically be executed when the page loads. For more flexibility, use the head parameter to insert js inside <script> tags.
            head: Custom html to insert into the head of the demo webpage. This can be used to add custom meta tags, multiple scripts, stylesheets, etc. to the page.
        Returns:
            a Gradio Tabbed Interface for the given interfaces
        """
        super().__init__(
            title=title or "Gradio",
            theme=theme,
            analytics_enabled=analytics_enabled,
            mode="tabbed_interface",
            css=css,
            js=js,
            head=head,
        )
        if tab_names is None:
            tab_names = [f"Tab {i}" for i in range(len(interface_list))]
        with self:
            if title:
                Markdown(
                    f"<h1 style='text-align: center; margin-bottom: 1rem'>{title}</h1>"
                )
            with Tabs():
                for interface, tab_name in zip(interface_list, tab_names):
                    with Tab(label=tab_name):
                        interface.render()


def close_all(verbose: bool = True) -> None:
    for io in Interface.get_instances():
        io.close(verbose)