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To install Gradio from main, run the following command:
pip install https://gradio-builds.s3.amazonaws.com/ecbc363ee094a73535f53a612c2f6bd1b2154d83/gradio-4.34.0-py3-none-any.whl*Note: Setting share=True in
launch() will not work.
Interface
gradio.Interface(···)Description
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 Usage
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()Initialization
| Parameter | Description |
|---|---|
fn Callable required | 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 str | Component | list[str | Component] | None required | 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 str | Component | list[str | Component] | None required | 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 list[Any] | list[list[Any]] | str | None default: None | 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 bool | Literal['lazy'] | None default: None | If True, caches examples in the server for fast runtime in examples. If "lazy", then examples are cached after their first use. If |
examples_per_page int default: 10 | If examples are provided, how many to display per page. |
live bool default: False | Whether the interface should automatically rerun if any of the inputs change. |
title str | None default: None | 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 str | None default: None | 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 str | None default: None | 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 str | None default: None | This parameter has been deprecated and has no effect. |
theme Theme | str | None default: None | 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 str | None default: None | Custom css as a string or path to a css file. This css will be included in the demo webpage. |
allow_flagging Literal['never'] | Literal['auto'] | Literal['manual'] | None default: None | 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 list[str] | list[tuple[str, str]] | None default: None | 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 str default: "flagged" | What to name the directory where flagged data is stored. |
flagging_callback FlaggingCallback | None default: None | 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 bool | None default: None | Whether to allow basic telemetry. If None, will use GRADIO_ANALYTICS_ENABLED environment variable if defined, or default to True. |
batch bool default: False | 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 int default: 4 | Maximum number of inputs to batch together if this is called from the queue (only relevant if batch=True) |
api_name str | Literal[False] | None default: "predict" | 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 |
allow_duplication bool default: False | If True, then will show a 'Duplicate Spaces' button on Hugging Face Spaces. |
concurrency_limit int | None | Literal['default'] default: "default" | 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 |
js str | None default: None | 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 str | None default: None | 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 str | Component | list[str | Component] | None default: None | 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 str | Accordion | None default: None | If a string is provided, this is the label of the |
submit_btn str | Button default: "Submit" | The button to use for submitting inputs. Defaults to a |
stop_btn str | Button default: "Stop" | The button to use for stopping the interface. Defaults to a |
clear_btn str | Button | None default: "Clear" | The button to use for clearing the inputs. Defaults to a |
delete_cache tuple[int, int] | None default: None | A tuple corresponding [frequency, age] both expressed in number of seconds. Every |
Demos
Methods
launch %20Copyright%202022%20Fonticons,%20Inc.%20--%3e%3cpath%20d='M172.5%20131.1C228.1%2075.51%20320.5%2075.51%20376.1%20131.1C426.1%20181.1%20433.5%20260.8%20392.4%20318.3L391.3%20319.9C381%20334.2%20361%20337.6%20346.7%20327.3C332.3%20317%20328.9%20297%20339.2%20282.7L340.3%20281.1C363.2%20249%20359.6%20205.1%20331.7%20177.2C300.3%20145.8%20249.2%20145.8%20217.7%20177.2L105.5%20289.5C73.99%20320.1%2073.99%20372%20105.5%20403.5C133.3%20431.4%20177.3%20435%20209.3%20412.1L210.9%20410.1C225.3%20400.7%20245.3%20404%20255.5%20418.4C265.8%20432.8%20262.5%20452.8%20248.1%20463.1L246.5%20464.2C188.1%20505.3%20110.2%20498.7%2060.21%20448.8C3.741%20392.3%203.741%20300.7%2060.21%20244.3L172.5%20131.1zM467.5%20380C411%20436.5%20319.5%20436.5%20263%20380C213%20330%20206.5%20251.2%20247.6%20193.7L248.7%20192.1C258.1%20177.8%20278.1%20174.4%20293.3%20184.7C307.7%20194.1%20311.1%20214.1%20300.8%20229.3L299.7%20230.9C276.8%20262.1%20280.4%20306.9%20308.3%20334.8C339.7%20366.2%20390.8%20366.2%20422.3%20334.8L534.5%20222.5C566%20191%20566%20139.1%20534.5%20108.5C506.7%2080.63%20462.7%2076.99%20430.7%2099.9L429.1%20101C414.7%20111.3%20394.7%20107.1%20384.5%2093.58C374.2%2079.2%20377.5%2059.21%20391.9%2048.94L393.5%2047.82C451%206.731%20529.8%2013.25%20579.8%2063.24C636.3%20119.7%20636.3%20211.3%20579.8%20267.7L467.5%20380z'/%3e%3c/svg%3e)
gradio.Interface.launch(···)Description
Launches a simple web server that serves the demo. Can also be used to create a public link used by anyone to access the demo from their browser by setting share=True. <br>
Example Usage
import gradio as gr
def reverse(text):
return text[::-1]
demo = gr.Interface(reverse, "text", "text")
demo.launch(share=True, auth=("username", "password"))Arguments
| Parameter | Description |
|---|---|
inline bool | None default: None | whether to display in the gradio app inline in an iframe. Defaults to True in python notebooks; False otherwise. |
inbrowser bool default: False | whether to automatically launch the gradio app in a new tab on the default browser. |
share bool | None default: None | whether to create a publicly shareable link for the gradio app. Creates an SSH tunnel to make your UI accessible from anywhere. If not provided, it is set to False by default every time, except when running in Google Colab. When localhost is not accessible (e.g. Google Colab), setting share=False is not supported. Can be set by environment variable GRADIO_SHARE=True. |
debug bool default: False | if True, blocks the main thread from running. If running in Google Colab, this is needed to print the errors in the cell output. |
max_threads int default: 40 | the maximum number of total threads that the Gradio app can generate in parallel. The default is inherited from the starlette library (currently 40). |
auth Callable | tuple[str, str] | list[tuple[str, str]] | None default: None | If provided, username and password (or list of username-password tuples) required to access app. Can also provide function that takes username and password and returns True if valid login. |
auth_message str | None default: None | If provided, HTML message provided on login page. |
prevent_thread_lock bool default: False | By default, the gradio app blocks the main thread while the server is running. If set to True, the gradio app will not block and the gradio server will terminate as soon as the script finishes. |
show_error bool default: False | If True, any errors in the gradio app will be displayed in an alert modal and printed in the browser console log |
server_name str | None default: None | to make app accessible on local network, set this to "0.0.0.0". Can be set by environment variable GRADIO_SERVER_NAME. If None, will use "127.0.0.1". |
server_port int | None default: None | will start gradio app on this port (if available). Can be set by environment variable GRADIO_SERVER_PORT. If None, will search for an available port starting at 7860. |
height int default: 500 | The height in pixels of the iframe element containing the gradio app (used if inline=True) |
width int | str default: "100%" | The width in pixels of the iframe element containing the gradio app (used if inline=True) |
favicon_path str | None default: None | If a path to a file (.png, .gif, or .ico) is provided, it will be used as the favicon for the web page. |
ssl_keyfile str | None default: None | If a path to a file is provided, will use this as the private key file to create a local server running on https. |
ssl_certfile str | None default: None | If a path to a file is provided, will use this as the signed certificate for https. Needs to be provided if ssl_keyfile is provided. |
ssl_keyfile_password str | None default: None | If a password is provided, will use this with the ssl certificate for https. |
ssl_verify bool default: True | If False, skips certificate validation which allows self-signed certificates to be used. |
quiet bool default: False | If True, suppresses most print statements. |
show_api bool default: True | If True, shows the api docs in the footer of the app. Default True. |
allowed_paths list[str] | None default: None | List of complete filepaths or parent directories that gradio is allowed to serve. Must be absolute paths. Warning: if you provide directories, any files in these directories or their subdirectories are accessible to all users of your app. |
blocked_paths list[str] | None default: None | List of complete filepaths or parent directories that gradio is not allowed to serve (i.e. users of your app are not allowed to access). Must be absolute paths. Warning: takes precedence over `allowed_paths` and all other directories exposed by Gradio by default. |
root_path str | None default: None | The root path (or "mount point") of the application, if it's not served from the root ("/") of the domain. Often used when the application is behind a reverse proxy that forwards requests to the application. For example, if the application is served at "https://example.com/myapp", the `root_path` should be set to "/myapp". A full URL beginning with http:// or https:// can be provided, which will be used as the root path in its entirety. Can be set by environment variable GRADIO_ROOT_PATH. Defaults to "". |
app_kwargs dict[str, Any] | None default: None | Additional keyword arguments to pass to the underlying FastAPI app as a dictionary of parameter keys and argument values. For example, `{"docs_url": "/docs"}` |
state_session_capacity int default: 10000 | The maximum number of sessions whose information to store in memory. If the number of sessions exceeds this number, the oldest sessions will be removed. Reduce capacity to reduce memory usage when using gradio.State or returning updated components from functions. Defaults to 10000. |
share_server_address str | None default: None | Use this to specify a custom FRP server and port for sharing Gradio apps (only applies if share=True). If not provided, will use the default FRP server at https://gradio.live. See https://github.com/huggingface/frp for more information. |
share_server_protocol Literal[('http', 'https')] | None default: None | Use this to specify the protocol to use for the share links. Defaults to "https", unless a custom share_server_address is provided, in which case it defaults to "http". If you are using a custom share_server_address and want to use https, you must set this to "https". |
auth_dependency Callable[[fastapi.Request], str | None] | None default: None | A function that takes a FastAPI request and returns a string user ID or None. If the function returns None for a specific request, that user is not authorized to access the app (they will see a 401 Unauthorized response). To be used with external authentication systems like OAuth. Cannot be used with `auth`. |
max_file_size str | int | None default: None | The maximum file size in bytes that can be uploaded. Can be a string of the form "<value><unit>", where value is any positive integer and unit is one of "b", "kb", "mb", "gb", "tb". If None, no limit is set. |
load
gradio.Interface.load(block, ···)Description
This listener is triggered when the Interface initially loads in the browser.
Arguments
| Parameter | Description |
|---|---|
block Block | None required | |
fn Callable | None | Literal['decorator'] default: "decorator" | the function to call when this event is triggered. 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 Component | list[Component] | set[Component] | None default: None | List of gradio.components to use as inputs. If the function takes no inputs, this should be an empty list. |
outputs Block | list[Block] | list[Component] | None default: None | List of gradio.components to use as outputs. If the function returns no outputs, this should be an empty list. |
api_name str | None | Literal[False] default: None | 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 (default), the name of the 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. |
scroll_to_output bool default: False | If True, will scroll to output component on completion |
show_progress Literal[('full', 'minimal', 'hidden')] default: "full" | If True, will show progress animation while pending |
queue bool default: True | If True, will place the request on the queue, if the queue has been enabled. If False, will not put this event on the queue, even if the queue has been enabled. If None, will use the queue setting of the gradio app. |
batch bool default: False | 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 int default: 4 | Maximum number of inputs to batch together if this is called from the queue (only relevant if batch=True) |
preprocess bool default: True | If False, will not run preprocessing of component data before running 'fn' (e.g. leaving it as a base64 string if this method is called with the `Image` component). |
postprocess bool default: True | If False, will not run postprocessing of component data before returning 'fn' output to the browser. |
cancels dict[str, Any] | list[dict[str, Any]] | None default: None | A list of other events to cancel when this listener is triggered. For example, setting cancels=[click_event] will cancel the click_event, where click_event is the return value of another components .click method. Functions that have not yet run (or generators that are iterating) will be cancelled, but functions that are currently running will be allowed to finish. |
every float | None default: None | Run this event 'every' number of seconds while the client connection is open. Interpreted in seconds. |
trigger_mode Literal[('once', 'multiple', 'always_last')] | None default: None | If "once" (default for all events except `.change()`) would not allow any submissions while an event is pending. If set to "multiple", unlimited submissions are allowed while pending, and "always_last" (default for `.change()` and `.key_up()` events) would allow a second submission after the pending event is complete. |
js str | None default: None | Optional frontend js method to run before running 'fn'. Input arguments for js method are values of 'inputs' and 'outputs', return should be a list of values for output components. |
concurrency_limit int | None | Literal['default'] default: "default" | 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 `Blocks.queue()`, which itself is 1 by default). |
concurrency_id str | None default: None | If set, this is the id of the concurrency group. Events with the same concurrency_id will be limited by the lowest set concurrency_limit. |
show_api bool default: True | whether to show this event in the "view API" page of the Gradio app, or in the ".view_api()" method of the Gradio clients. Unlike setting api_name to False, setting show_api to False will still allow downstream apps as well as the Clients to use this event. If fn is None, show_api will automatically be set to False. |
from_pipeline
gradio.Interface.from_pipeline(pipeline, ···)Description
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.
Example Usage
import gradio as gr
from transformers import pipeline
pipe = pipeline("image-classification")
gr.Interface.from_pipeline(pipe).launch()Arguments
| Parameter | Description |
|---|---|
pipeline Pipeline | DiffusionPipeline required | the pipeline object to use. |
integrate
gradio.Interface.integrate(···)Description
A catch-all method for integrating with other libraries. This method should be run after launch()
Arguments
| Parameter | Description |
|---|---|
comet_ml <class 'inspect._empty'> default: None | If a comet_ml Experiment object is provided, will integrate with the experiment and appear on Comet dashboard |
wandb ModuleType | None default: None | If the wandb module is provided, will integrate with it and appear on WandB dashboard |
mlflow ModuleType | None default: None | If the mlflow module is provided, will integrate with the experiment and appear on ML Flow dashboard |
queue
gradio.Interface.queue(···)Description
By enabling the queue you can control when users know their position in the queue, and set a limit on maximum number of events allowed.
Example Usage
demo = gr.Interface(image_generator, gr.Textbox(), gr.Image())
demo.queue(max_size=20)
demo.launch()Arguments
| Parameter | Description |
|---|---|
status_update_rate float | Literal['auto'] default: "auto" | If "auto", Queue will send status estimations to all clients whenever a job is finished. Otherwise Queue will send status at regular intervals set by this parameter as the number of seconds. |
api_open bool | None default: None | If True, the REST routes of the backend will be open, allowing requests made directly to those endpoints to skip the queue. |
max_size int | None default: None | The maximum number of events the queue will store at any given moment. If the queue is full, new events will not be added and a user will receive a message saying that the queue is full. If None, the queue size will be unlimited. |
concurrency_count int | None default: None | Deprecated. Set the concurrency_limit directly on event listeners e.g. btn.click(fn, ..., concurrency_limit=10) or gr.Interface(concurrency_limit=10). If necessary, the total number of workers can be configured via `max_threads` in launch(). |
default_concurrency_limit int | None | Literal['not_set'] default: "not_set" | The default value of `concurrency_limit` to use for event listeners that don't specify a value. Can be set by environment variable GRADIO_DEFAULT_CONCURRENCY_LIMIT. Defaults to 1 if not set otherwise. |