Gradio Blocks Docs

New to Gradio? Start here: Getting Started

Blocks

with gradio.Blocks():

Description

Blocks is Gradio's low-level API that allows you to create more custom web applications and demos than Interfaces (yet still entirely in Python).

Compared to the Interface class, Blocks offers more flexibility and control over: (1) the layout of components (2) the events that trigger the execution of functions (3) data flows (e.g. inputs can trigger outputs, which can trigger the next level of outputs). Blocks also offers ways to group together related demos such as with tabs.

The basic usage of Blocks is as follows: create a Blocks object, then use it as a context (with the "with" statement), and then define layouts, components, or events within the Blocks context. Finally, call the launch() method to launch the demo.

Example Usage

import gradio as gr
def update(name):
    return f"Welcome to Gradio, {name}!"

with gr.Blocks() as demo:
    gr.Markdown("Start typing below and then click **Run** to see the output.")
    with gr.Row():
        inp = gr.Textbox(placeholder="What is your name?")
        out = gr.Textbox()
    btn = gr.Button("Run")
    btn.click(fn=update, inputs=inp, outputs=out)

demo.launch()

Initialization

Parameter	Description
`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.
`analytics_enabled` bool \| None default: None	Whether to allow basic telemetry. If None, will use GRADIO_ANALYTICS_ENABLED environment variable or default to True.
`mode` str default: "blocks"	A human-friendly name for the kind of Blocks or Interface being created. Used internally for analytics.
`title` str default: "Gradio"	The tab title to display when this is opened in a browser window.
`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.
`js` str \| None default: None	Custom js or path to js file to run when demo is first loaded. This javascript will be included in the demo webpage.
`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.
`fill_height` bool default: False	Whether to vertically expand top-level child components to the height of the window. If True, expansion occurs when the scale value of the child components >= 1.
`delete_cache` tuple[int, int] \| None default: None	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.

Demos

import gradio as gr

def welcome(name):
    return f"Welcome to Gradio, {name}!"

with gr.Blocks() as demo:
    gr.Markdown(
    """
    # Hello World!
    Start typing below to see the output.
    """)
    inp = gr.Textbox(placeholder="What is your name?")
    out = gr.Textbox()
    inp.change(welcome, inp, out)

if __name__ == "__main__":
    demo.launch()

import numpy as np
import gradio as gr


def flip_text(x):
    return x[::-1]


def flip_image(x):
    return np.fliplr(x)


with gr.Blocks() as demo:
    gr.Markdown("Flip text or image files using this demo.")
    with gr.Tab("Flip Text"):
        text_input = gr.Textbox()
        text_output = gr.Textbox()
        text_button = gr.Button("Flip")
    with gr.Tab("Flip Image"):
        with gr.Row():
            image_input = gr.Image()
            image_output = gr.Image()
        image_button = gr.Button("Flip")

    with gr.Accordion("Open for More!", open=False):
        gr.Markdown("Look at me...")
        temp_slider = gr.Slider(minimum=0.0, maximum=1.0, value=0.1, step=0.1, interactive=True, label="Slide me")
        temp_slider.change(lambda x:x, [temp_slider])

    text_button.click(flip_text, inputs=text_input, outputs=text_output)
    image_button.click(flip_image, inputs=image_input, outputs=image_output)

if __name__ == "__main__":
    demo.launch()

from transformers import pipeline

import gradio as gr

asr = pipeline("automatic-speech-recognition", "facebook/wav2vec2-base-960h")
classifier = pipeline("text-classification")


def speech_to_text(speech):
    text = asr(speech)["text"]
    return text


def text_to_sentiment(text):
    return classifier(text)[0]["label"]


demo = gr.Blocks()

with demo:
    audio_file = gr.Audio(type="filepath")
    text = gr.Textbox()
    label = gr.Label()

    b1 = gr.Button("Recognize Speech")
    b2 = gr.Button("Classify Sentiment")

    b1.click(speech_to_text, inputs=audio_file, outputs=text)
    b2.click(text_to_sentiment, inputs=text, outputs=label)

if __name__ == "__main__":
    demo.launch()

import gradio as gr

from transformers import pipeline

english_translator = gr.load(name="spaces/gradio/english_translator")
english_generator = pipeline("text-generation", model="distilgpt2")


def generate_text(text):
    english_text = english_generator(text)[0]["generated_text"]
    german_text = english_translator(english_text)
    return english_text, german_text


with gr.Blocks() as demo:
    with gr.Row():
        with gr.Column():
            seed = gr.Text(label="Input Phrase")
        with gr.Column():
            english = gr.Text(label="Generated English Text")
            german = gr.Text(label="Generated German Text")
    btn = gr.Button("Generate")
    btn.click(generate_text, inputs=[seed], outputs=[english, german])
    gr.Examples(["My name is Clara and I am"], inputs=[seed])

if __name__ == "__main__":
    demo.launch()

Methods

launch

gradio.Blocks.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]
with gr.Blocks() as demo:
    button = gr.Button(value="Reverse")
    button.click(reverse, gr.Textbox(), gr.Textbox())
demo.launch(share=True, auth=("username", "password"))

Agruments

Parameter	Description
`inline` bool \| None default: None	whether to display in the interface inline in an iframe. Defaults to True in python notebooks; False otherwise.
`inbrowser` bool default: False	whether to automatically launch the interface in a new tab on the default browser.
`share` bool \| None default: None	whether to create a publicly shareable link for the interface. 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.
`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 interface. 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	If True, the interface will block the main thread while the server is running.
`show_error` bool default: False	If True, any errors in the interface 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 interface (used if inline=True)
`width` int \| str default: "100%"	The width in pixels of the iframe element containing the interface (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 (in addition to the directory containing the gradio python file). 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.

queue

gradio.Blocks.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

with gr.Blocks() as demo:
    button = gr.Button(label="Generate Image")
    button.click(fn=image_generator, inputs=gr.Textbox(), outputs=gr.Image())
demo.queue(max_size=10)
demo.launch()

Agruments

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.

integrate

gradio.Blocks.integrate(···)

Description

A catch-all method for integrating with other libraries. This method should be run after launch()

Agruments

Parameter Description

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

comet_ml

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

load

gradio.Blocks.load(block, ···)

Description

This listener is triggered when the Blocks initially loads in the browser.

Agruments

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` Component \| 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 \| None default: None	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 to use this event. If fn is None, show_api will automatically be set to False.

Guides

Blocks And Event Listeners

Controlling Layout

State In Blocks

Custom CSS And JS

Using Blocks Like Functions

← TabbedInterface

Row →

Blocks

Description
Example Usage
Initialization
Demos
Methods
launch
queue
integrate
load
Guides