EllieKini/Herta
Audio-to-Audio • Updated
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The main Client class for the Python client. This class is used to connect
to a remote Gradio app and call its API endpoints.
| Description | https://gradio.app/docs/python-client/client | Python Client - Client Docs |
from gradio_client import Client
client = Client("abidlabs/whisper-large-v2") connecting to a Hugging Face Space
client.predict("test.mp4", api_name="/predict")
>> What a nice recording! returns the result of the remote API call
client = Client("https://bec81a83-5b5c-471e.gradio.live") conne... | Example usage | https://gradio.app/docs/python-client/client | Python Client - Client Docs |
Parameters ▼
src: str
either the name of the Hugging Face Space to load, (e.g. "abidlabs/whisper-
large-v2") or the full URL (including "http" or "https") of the hosted Gradio
app to load (e.g. "http://mydomain.com/app" or
"https://bec81a83-5b5c-471e.gradio.live/").
token: str | None
d... | Initialization | https://gradio.app/docs/python-client/client | Python Client - Client Docs |
n the remote machine instead.
ssl_verify: bool
default `= True`
if False, skips certificate validation which allows the client to connect to
Gradio apps that are using self-signed certificates.
analytics_enabled: bool
default `= True`
Whether to allow basic telemetry. If None, will u... | Initialization | https://gradio.app/docs/python-client/client | Python Client - Client Docs |
Description
Event listeners allow you to respond to user interactions with the UI
components you've defined in a Gradio Blocks app. When a user interacts with
an element, such as changing a slider value or uploading an image, a function
is called.
Supported Event Listeners
The Client component supports the following... | Event Listeners | https://gradio.app/docs/python-client/client | Python Client - Client Docs |
eters. For hardware upgrades (beyond the basic
CPU tier), you may be required to provide billing information on Hugging Face:
<https://huggingface.co/settings/billing> <br>
Event Parameters
Parameters ▼
args: <class 'inspect._empty'>
The positional arguments to pass to the remote API endpoint. The or... | Event Listeners | https://gradio.app/docs/python-client/client | Python Client - Client Docs |
**Stream From a Gradio app in 5 lines**
Use the `submit` method to get a job you can iterate over.
In python:
from gradio_client import Client
client = Client("gradio/llm_stream")
for result in client.submit("What's the best UI framework in Python?"):
print(result)
... | Ergonomic API 💆 | https://gradio.app/docs/python-client/version-1-release | Python Client - Version 1 Release Docs |
Anything you can do in the UI, you can do with the client:
* 🔐Authentication
* 🛑 Job Cancelling
* ℹ️ Access Queue Position and API
* 📕 View the API information
Here's an example showing how to display the queue position of a pending job:
from gradio_client import Client
client = ... | Transparent Design 🪟 | https://gradio.app/docs/python-client/version-1-release | Python Client - Version 1 Release Docs |
The client can run from pretty much any python and javascript environment
(node, deno, the browser, Service Workers).
Here's an example using the client from a Flask server using gevent:
from gevent import monkey
monkey.patch_all()
from gradio_client import Client
from flask import Fla... | Portable Design ⛺️ | https://gradio.app/docs/python-client/version-1-release | Python Client - Version 1 Release Docs |
Changes
**Python**
* The `serialize` argument of the `Client` class was removed and has no effect.
* The `upload_files` argument of the `Client` was removed.
* All filepaths must be wrapped in the `handle_file` method. For example, `caption = client.predict(handle_file('./dog.jpg'))`.
* The `output_dir` a... | v1.0 Migration Guide and Breaking | https://gradio.app/docs/python-client/version-1-release | Python Client - Version 1 Release Docs |
A Job is a wrapper over the Future class that represents a prediction call
that has been submitted by the Gradio client. This class is not meant to be
instantiated directly, but rather is created by the Client.submit() method.
A Job object includes methods to get the status of the prediction call, as
well to get the ... | Description | https://gradio.app/docs/python-client/job | Python Client - Job Docs |
Parameters ▼
future: Future
The future object that represents the prediction call, created by the
Client.submit() method
communicator: Communicator | None
default `= None`
The communicator object that is used to communicate between the client and the
background thread running the job
... | Initialization | https://gradio.app/docs/python-client/job | Python Client - Job Docs |
Description
Event listeners allow you to respond to user interactions with the UI
components you've defined in a Gradio Blocks app. When a user interacts with
an element, such as changing a slider value or uploading an image, a function
is called.
Supported Event Listeners
The Job component supports the following ev... | Event Listeners | https://gradio.app/docs/python-client/job | Python Client - Job Docs |
ZeroGPU
ZeroGPU spaces are rate-limited to ensure that a single user does not hog all
of the available GPUs. The limit is controlled by a special token that the
Hugging Face Hub infrastructure adds to all incoming requests to Spaces. This
token is a request header called `X-IP-Token` and its value changes depending
on... | Explaining Rate Limits for | https://gradio.app/docs/python-client/using-zero-gpu-spaces | Python Client - Using Zero Gpu Spaces Docs |
Token
In the following hypothetical example, when a user presses enter in the
textbox, the `generate()` function is called, which calls a second function,
`text_to_image()`. Because the Gradio Client is being instantiated indirectly,
in `text_to_image()`, we will need to extract their token from the `X-IP-
Token` head... | Avoiding Rate Limits by Manually Passing an IP | https://gradio.app/docs/python-client/using-zero-gpu-spaces | Python Client - Using Zero Gpu Spaces Docs |
If you already have a recent version of `gradio`, then the `gradio_client` is
included as a dependency. But note that this documentation reflects the latest
version of the `gradio_client`, so upgrade if you’re not sure!
The lightweight `gradio_client` package can be installed from pip (or pip3)
and is tested to work w... | Installation | https://gradio.app/docs/python-client/introduction | Python Client - Introduction Docs |
Spaces
Start by connecting instantiating a `Client` object and connecting it to a
Gradio app that is running on Hugging Face Spaces.
from gradio_client import Client
client = Client("abidlabs/en2fr") a Space that translates from English to French
You can also connect to private Spaces by pass... | Connecting to a Gradio App on Hugging Face | https://gradio.app/docs/python-client/introduction | Python Client - Introduction Docs |
use
While you can use any public Space as an API, you may get rate limited by
Hugging Face if you make too many requests. For unlimited usage of a Space,
simply duplicate the Space to create a private Space, and then use it to make
as many requests as you’d like!
The `gradio_client` includes a class method: `Client.d... | Duplicating a Space for private | https://gradio.app/docs/python-client/introduction | Python Client - Introduction Docs |
app
If your app is running somewhere else, just provide the full URL instead,
including the “http://” or “https://“. Here’s an example of making predictions
to a Gradio app that is running on a share URL:
from gradio_client import Client
client = Client("https://bec81a83-5b5c-471e.gradio.live")... | Connecting a general Gradio | https://gradio.app/docs/python-client/introduction | Python Client - Introduction Docs |
Once you have connected to a Gradio app, you can view the APIs that are
available to you by calling the `Client.view_api()` method. For the Whisper
Space, we see the following:
Client.predict() Usage Info
---------------------------
Named API endpoints: 1
- predict(audio, api_name="/pre... | Inspecting the API endpoints | https://gradio.app/docs/python-client/introduction | Python Client - Introduction Docs |
As an alternative to running the `.view_api()` method, you can click on the
“Use via API” link in the footer of the Gradio app, which shows us the same
information, along with example usage.
The View API pag... | The “View API” Page | https://gradio.app/docs/python-client/introduction | Python Client - Introduction Docs |
The simplest way to make a prediction is simply to call the `.predict()`
function with the appropriate arguments:
from gradio_client import Client
client = Client("abidlabs/en2fr", api_name='/predict')
client.predict("Hello")
>> Bonjour
If there are multiple parameters, then you sh... | Making a prediction | https://gradio.app/docs/python-client/introduction | Python Client - Introduction Docs |
to the Gradio server and ensures that the file is
preprocessed correctly:
from gradio_client import Client, file
client = Client("abidlabs/whisper")
client.predict(
audio=file("https://audio-samples.github.io/samples/mp3/blizzard_unconditional/sample-0.mp3")
)
>> "My th... | Making a prediction | https://gradio.app/docs/python-client/introduction | Python Client - Introduction Docs |
Oe should note that `.predict()` is a _blocking_ operation as it waits for the
operation to complete before returning the prediction.
In many cases, you may be better off letting the job run in the background
until you need the results of the prediction. You can do this by creating a
`Job` instance using the `.submit(... | Running jobs asynchronously | https://gradio.app/docs/python-client/introduction | Python Client - Introduction Docs |
Alternatively, one can add one or more callbacks to perform actions after the
job has completed running, like this:
from gradio_client import Client
def print_result(x):
print("The translated result is: {x}")
client = Client(space="abidlabs/en2fr")
job = client.submit("... | Adding callbacks | https://gradio.app/docs/python-client/introduction | Python Client - Introduction Docs |
The `Job` object also allows you to get the status of the running job by
calling the `.status()` method. This returns a `StatusUpdate` object with the
following attributes: `code` (the status code, one of a set of defined strings
representing the status. See the `utils.Status` class), `rank` (the current
position of th... | Status | https://gradio.app/docs/python-client/introduction | Python Client - Introduction Docs |
The `Job` class also has a `.cancel()` instance method that cancels jobs that
have been queued but not started. For example, if you run:
client = Client("abidlabs/whisper")
job1 = client.submit(file("audio_sample1.wav"))
job2 = client.submit(file("audio_sample2.wav"))
job1.cancel() will retu... | Cancelling Jobs | https://gradio.app/docs/python-client/introduction | Python Client - Introduction Docs |
Some Gradio API endpoints do not return a single value, rather they return a
series of values. You can get the series of values that have been returned at
any time from such a generator endpoint by running `job.outputs()`:
from gradio_client import Client
client = Client(src="gradio/count_genera... | Generator Endpoints | https://gradio.app/docs/python-client/introduction | Python Client - Introduction Docs |
Gradio demos can include [session state](https://www.gradio.app/guides/state-
in-blocks), which provides a way for demos to persist information from user
interactions within a page session.
For example, consider the following demo, which maintains a list of words that
a user has submitted in a `gr.State` component. Wh... | Demos with Session State | https://gradio.app/docs/python-client/introduction | Python Client - Introduction Docs |
`gradio-rs` is a Gradio Client in Rust built by
[@JacobLinCool](https://github.com/JacobLinCool). You can find the repo
[here](https://github.com/JacobLinCool/gradio-rs), and more in depth API
documentation [here](https://docs.rs/gradio/latest/gradio/).
| Introduction | https://gradio.app/docs/third-party-clients/rust-client | Third Party Clients - Rust Client Docs |
Here is an example of using BS-RoFormer model to separate vocals and
background music from an audio file.
use gradio::{PredictionInput, Client, ClientOptions};
[tokio::main]
async fn main() {
if std::env::args().len() < 2 {
println!("Please provide an audio file path as a... | Usage | https://gradio.app/docs/third-party-clients/rust-client | Third Party Clients - Rust Client Docs |
cargo install gradio
gr --help
Take [stabilityai/stable-
diffusion-3-medium](https://huggingface.co/spaces/stabilityai/stable-
diffusion-3-medium) HF Space as an example:
> gr list stabilityai/stable-diffusion-3-medium
API Spec for stabilityai/stable-diffusion-3-medium:
/infer
... | Command Line Interface | https://gradio.app/docs/third-party-clients/rust-client | Third Party Clients - Rust Client Docs |
Gradio applications support programmatic requests from many environments:
* The [Python Client](/docs/python-client): `gradio-client` allows you to make requests from Python environments.
* The [JavaScript Client](/docs/js-client): `@gradio/client` allows you to make requests in TypeScript from the browser or serv... | Gradio Clients | https://gradio.app/docs/third-party-clients/introduction | Third Party Clients - Introduction Docs |
We also encourage the development and use of third party clients built by
the community:
* [Rust Client](/docs/third-party-clients/rust-client): `gradio-rs` built by [@JacobLinCool](https://github.com/JacobLinCool) allows you to make requests in Rust.
* [Powershell Client](https://github.com/rrg92/powershai): `pow... | Community Clients | https://gradio.app/docs/third-party-clients/introduction | Third Party Clients - Introduction Docs |
Load a chat interface from an OpenAI API chat compatible endpoint.
| Description | https://gradio.app/docs/gradio/load_chat | Gradio - Load_Chat Docs |
import gradio as gr
demo = gr.load_chat("http://localhost:11434/v1", model="deepseek-r1")
demo.launch()
| Example Usage | https://gradio.app/docs/gradio/load_chat | Gradio - Load_Chat Docs |
Parameters ▼
base_url: str
The base URL of the endpoint, e.g. "http://localhost:11434/v1/"
model: str
The name of the model you are loading, e.g. "llama3.2"
token: str | None
default `= None`
The API token or a placeholder string if you are using a local model, e.g.
"... | Initialization | https://gradio.app/docs/gradio/load_chat | Gradio - Load_Chat Docs |
Set the static paths to be served by the gradio app.
Static files are are served directly from the file system instead of being
copied. They are served to users with The Content-Disposition HTTP header set
to "inline" when sending these files to users. This indicates that the file
should be displayed directly in the ... | Description | https://gradio.app/docs/gradio/set_static_paths | Gradio - Set_Static_Paths Docs |
import gradio as gr
Paths can be a list of strings or pathlib.Path objects
corresponding to filenames or directories.
gr.set_static_paths(paths=["test/test_files/"])
The example files and the default value of the input
will not be copied to the gradio cache and will be served directly.
... | Example Usage | https://gradio.app/docs/gradio/set_static_paths | Gradio - Set_Static_Paths Docs |
Parameters ▼
paths: str | pathlib.Path | list[str | pathlib.Path]
filepath or list of filepaths or directory names to be served by the gradio
app. If it is a directory name, ALL files located within that directory will
be considered static and not moved to the gradio cache. This also means that
ALL fil... | Initialization | https://gradio.app/docs/gradio/set_static_paths | Gradio - Set_Static_Paths Docs |
A Gradio request object that can be used to access the request headers,
cookies, query parameters and other information about the request from within
the prediction function. The class is a thin wrapper around the
fastapi.Request class. Attributes of this class include: `headers`, `client`,
`query_params`, `session_has... | Description | https://gradio.app/docs/gradio/request | Gradio - Request Docs |
import gradio as gr
def echo(text, request: gr.Request):
if request:
print("Request headers dictionary:", request.headers)
print("IP address:", request.client.host)
print("Query parameters:", dict(request.query_params))
print("Session hash:", request.session_h... | Example Usage | https://gradio.app/docs/gradio/request | Gradio - Request Docs |
Parameters ▼
request: fastapi.Request | None
default `= None`
A fastapi.Request
username: str | None
default `= None`
The username of the logged in user (if auth is enabled)
session_hash: str | None
default `= None`
The session hash of the current session. It is uni... | Initialization | https://gradio.app/docs/gradio/request | Gradio - Request Docs |
request_ip_headers
| Demos | https://gradio.app/docs/gradio/request | Gradio - Request Docs |
Creates a file explorer component that allows users to browse files on the
machine hosting the Gradio app. As an input component, it also allows users to
select files to be used as input to a function, while as an output component,
it displays selected files.
| Description | https://gradio.app/docs/gradio/fileexplorer | Gradio - Fileexplorer Docs |
**Using FileExplorer as an input component.**
How FileExplorer will pass its value to your function:
Type: `list[str] | str | None`
Passes the selected file or directory as a `str` path (relative to `root`) or
`list[str}` depending on `file_count`
Example Code
import gradio as gr
... | Behavior | https://gradio.app/docs/gradio/fileexplorer | Gradio - Fileexplorer Docs |
Parameters ▼
glob: str
default `= "**/*"`
The glob-style pattern used to select which files to display, e.g. "*" to
match all files, "*.png" to match all .png files, "**/*.txt" to match any .txt
file in any subdirectory, etc. The default value matches all files and folders
recursively. See the Python ... | Initialization | https://gradio.app/docs/gradio/fileexplorer | Gradio - Fileexplorer Docs |
onent. If None and
used in a `gr.Interface`, the label will be the name of the parameter this
component is assigned to.
every: Timer | float | None
default `= None`
Continously calls `value` to recalculate it if `value` is a function (has no
effect otherwise). Can provide a Timer whose tick resets `va... | Initialization | https://gradio.app/docs/gradio/fileexplorer | Gradio - Fileexplorer Docs |
min_height: int | str | None
default `= None`
interactive: bool | None
default `= None`
if True, will allow users to select file(s); if False, will only display
files. If not provided, this is inferred based on whether the component is
used as an input or output.
visib... | Initialization | https://gradio.app/docs/gradio/fileexplorer | Gradio - Fileexplorer Docs |
buttons: list[Button] | None
default `= None`
A list of gr.Button() instances to show in the top right corner of the
component. Custom buttons will appear in the toolbar with their configured
icon and/or label, and clicking them will trigger any .click() events
registered on the button.
| Initialization | https://gradio.app/docs/gradio/fileexplorer | Gradio - Fileexplorer Docs |
Shortcuts
gradio.FileExplorer
Interface String Shortcut `"fileexplorer"`
Initialization Uses default values
| Shortcuts | https://gradio.app/docs/gradio/fileexplorer | Gradio - Fileexplorer Docs |
Description
Event listeners allow you to respond to user interactions with the UI
components you've defined in a Gradio Blocks app. When a user interacts with
an element, such as changing a slider value or uploading an image, a function
is called.
Supported Event Listeners
The FileExplorer component supports the fol... | Event Listeners | https://gradio.app/docs/gradio/fileexplorer | Gradio - Fileexplorer Docs |
text] | 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 | BlockContext | list[Component | BlockContext] | Set[Component | BlockContext] | None
default `= None`
List of gradio.components to use as outp... | Event Listeners | https://gradio.app/docs/gradio/fileexplorer | Gradio - Fileexplorer Docs |
lt `= 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... | Event Listeners | https://gradio.app/docs/gradio/fileexplorer | Gradio - Fileexplorer Docs |
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 | Literal[True] | None
default `= ... | Event Listeners | https://gradio.app/docs/gradio/fileexplorer | Gradio - Fileexplorer Docs |
ique key for this event listener to be used in @gr.render(). If set, this
value identifies an event as identical across re-renders when the key is
identical.
validator: Callable | None
default `= None`
Optional validation function to run before the main function. If provided,
this function will be exe... | Event Listeners | https://gradio.app/docs/gradio/fileexplorer | Gradio - Fileexplorer Docs |
Creates a chatbot that displays user-submitted messages and responses.
Supports a subset of Markdown including bold, italics, code, tables. Also
supports audio/video/image files, which are displayed in the Chatbot, and
other kinds of files which are displayed as links. This component is usually
used as an output compon... | Description | https://gradio.app/docs/gradio/chatbot | Gradio - Chatbot Docs |
The Chatbot component accepts a list of messages, where each message is a
dictionary with `role` and `content` keys. This format is compatible with the
message format expected by most LLM APIs (OpenAI, Claude, HuggingChat, etc.),
making it easy to pipe model outputs directly into the component.
The `role` key should b... | Behavior | https://gradio.app/docs/gradio/chatbot | Gradio - Chatbot Docs |
Parameters ▼
value: list[MessageDict | Message] | Callable | None
default `= None`
Default list of messages to show in chatbot, where each message is of the
format {"role": "user", "content": "Help me."}. Role can be one of "user",
"assistant", or "system". Content should be either text, or media pass... | Initialization | https://gradio.app/docs/gradio/chatbot | Gradio - Chatbot Docs |
ide
as B. Should be an integer. scale applies in Rows, and to top-level Components
in Blocks where fill_height=True.
min_width: int
default `= 160`
minimum pixel width, will wrap if not sufficient screen space to satisfy this
value. If a certain scale value results in this Component being narrower tha... | Initialization | https://gradio.app/docs/gradio/chatbot | Gradio - Chatbot Docs |
parameters from this component's constructor. Inside a gr.render()
function, if a component is re-rendered with the same key, these (and only
these) parameters will be preserved in the UI (if they have been changed by
the user or an event listener) instead of re-rendered based on the values
provided during constructor.... | Initialization | https://gradio.app/docs/gradio/chatbot | Gradio - Chatbot Docs |
pen delimiter (str), "right": close
delimiter (str), "display": whether to display in newline (bool)} that will be
used to render LaTeX expressions. If not provided, `latex_delimiters` is set
to `[{ "left": "$$", "right": "$$", "display": True }]`, so only expressions
enclosed in $$ delimiters will be rendered as LaTeX... | Initialization | https://gradio.app/docs/gradio/chatbot | Gradio - Chatbot Docs |
rder). Pass
None for either the user or bot image to skip. Must be within the working
directory of the Gradio app or an external URL.
sanitize_html: bool
default `= True`
If False, will disable HTML sanitization for chatbot messages. This is not
recommended, as it can lead to security vulnerabilities.... | Initialization | https://gradio.app/docs/gradio/chatbot | Gradio - Chatbot Docs |
ered
vertically and horizontally in the Chatbot. Supports Markdown and HTML. If
None, no placeholder is displayed.
examples: list[ExampleMessage] | None
default `= None`
A list of example messages to display in the chatbot before any user/assistant
messages are shown. Each example should be a dictiona... | Initialization | https://gradio.app/docs/gradio/chatbot | Gradio - Chatbot Docs |
and displayed in a separate collapsible
message with metadata={"title": "Reasoning"}. For example, [("<thinking>",
"</thinking>")] will extract content between <thinking> and </thinking> tags.
Each thinking block will be displayed as a separate collapsible message before
the main response. If None (default), no automat... | Initialization | https://gradio.app/docs/gradio/chatbot | Gradio - Chatbot Docs |
Shortcuts
gradio.Chatbot
Interface String Shortcut `"chatbot"`
Initialization Uses default values
| Shortcuts | https://gradio.app/docs/gradio/chatbot | Gradio - Chatbot Docs |
**Displaying Thoughts/Tool Usage**
You can provide additional metadata regarding any tools used to generate the
response. This is useful for displaying the thought process of LLM agents. For
example,
def generate_response(history):
history.append(
ChatMessage(role="assistant",
... | Examples | https://gradio.app/docs/gradio/chatbot | Gradio - Chatbot Docs |
deo("https://github.com/gradio-app/gradio/raw/main/gradio/media_assets/videos/world.mp4")}
]
with gr.Blocks() as demo:
chatbot = gr.Chatbot()
button = gr.Button("Load audio and video")
button.click(load, None, chatbot)
demo.launch()
| Examples | https://gradio.app/docs/gradio/chatbot | Gradio - Chatbot Docs |
chatbot_simplechatbot_streamingchatbot_with_toolschatbot_core_components
| Demos | https://gradio.app/docs/gradio/chatbot | Gradio - Chatbot Docs |
Description
Event listeners allow you to respond to user interactions with the UI
components you've defined in a Gradio Blocks app. When a user interacts with
an element, such as changing a slider value or uploading an image, a function
is called.
Supported Event Listeners
The Chatbot component supports the followin... | Event Listeners | https://gradio.app/docs/gradio/chatbot | Gradio - Chatbot Docs |
s event has SelectData of type gradio.SelectData that carries
information, accessible through SelectData.index and SelectData.value. See
SelectData documentation on how to use this event data.
Chatbot.option_select(fn, ···)
This listener is triggered when the user clicks on an option from within the
Cha... | Event Listeners | https://gradio.app/docs/gradio/chatbot | Gradio - Chatbot Docs |
ckContext] | Set[Component | BlockContext] | 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
default `= None`
defines how the endpoint appears in the API docs. Can be a string or None. If
set to... | Event Listeners | https://gradio.app/docs/gradio/chatbot | Gradio - Chatbot Docs |
f 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 ... | Event Listeners | https://gradio.app/docs/gradio/chatbot | Gradio - Chatbot Docs |
d submission after the
pending event is complete.
js: str | Literal[True] | 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.
concurr... | Event Listeners | https://gradio.app/docs/gradio/chatbot | Gradio - Chatbot Docs |
= None`
Optional validation function to run before the main function. If provided,
this function will be executed first with queue=False, and only if it
completes successfully will the main function be called. The validator
receives the same inputs as the main function and should return a
`gr.validate()` for each inpu... | Event Listeners | https://gradio.app/docs/gradio/chatbot | Gradio - Chatbot Docs |
Helper Classes | https://gradio.app/docs/gradio/chatbot | Gradio - Chatbot Docs | |
gradio.ChatMessage(···)
Description
A dataclass that represents a message in the Chatbot component (with
type="messages"). The only required field is `content`. The value of
`gr.Chatbot` is a list of these dataclasses.
Parameters ▼
content: MessageContent | list[MessageContent]
The content of the me... | ChatMessage | https://gradio.app/docs/gradio/chatbot | Gradio - Chatbot Docs |
A typed dictionary to represent metadata for a message in the Chatbot
component. An instance of this dictionary is used for the `metadata` field in
a ChatMessage when the chat message should be displayed as a thought.
Keys ▼
title: str
The title of the 'thought' message. Only required field.
... | MetadataDict | https://gradio.app/docs/gradio/chatbot | Gradio - Chatbot Docs |
A typed dictionary to represent an option in a ChatMessage. A list of these
dictionaries is used for the `options` field in a ChatMessage.
Keys ▼
value: str
The value to return when the option is selected.
label: str
The text to display in the option, if different from the value.
[Ch... | OptionDict | https://gradio.app/docs/gradio/chatbot | Gradio - Chatbot Docs |
The gr.KeyUpData class is a subclass of gr.EventData that specifically
carries information about the `.key_up()` event. When gr.KeyUpData is added as
a type hint to an argument of an event listener method, a gr.KeyUpData object
will automatically be passed as the value of that argument. The attributes of
this object co... | Description | https://gradio.app/docs/gradio/keyupdata | Gradio - Keyupdata Docs |
import gradio as gr
def test(value, key_up_data: gr.KeyUpData):
return {
"component value": value,
"input value": key_up_data.input_value,
"key": key_up_data.key
}
with gr.Blocks() as demo:
d = gr.Dropdown(["abc", "def"], allow_custom_value=T... | Example Usage | https://gradio.app/docs/gradio/keyupdata | Gradio - Keyupdata Docs |
Parameters ▼
key: str
The key that was pressed.
input_value: str
The displayed value in the input textbox after the key was pressed. This may
be different than the `value` attribute of the component itself, as the
`value` attribute of some components (e.g. Dropdown) are not updated unt... | Attributes | https://gradio.app/docs/gradio/keyupdata | Gradio - Keyupdata Docs |
dropdown_key_up
| Demos | https://gradio.app/docs/gradio/keyupdata | Gradio - Keyupdata Docs |
The gr.CopyData class is a subclass of gr.EventData that specifically
carries information about the `.copy()` event. When gr.CopyData is added as a
type hint to an argument of an event listener method, a gr.CopyData object
will automatically be passed as the value of that argument. The attributes of
this object contain... | Description | https://gradio.app/docs/gradio/copydata | Gradio - Copydata Docs |
import gradio as gr
def on_copy(copy_data: gr.CopyData):
return f"Copied text: {copy_data.value}"
with gr.Blocks() as demo:
textbox = gr.Textbox("Hello World!")
copied = gr.Textbox()
textbox.copy(on_copy, None, copied)
demo.launch()
| Example Usage | https://gradio.app/docs/gradio/copydata | Gradio - Copydata Docs |
Parameters ▼
value: Any
The value that was copied.
| Attributes | https://gradio.app/docs/gradio/copydata | Gradio - Copydata Docs |
Creates an image component that can be used to upload images (as an input)
or display images (as an output).
| Description | https://gradio.app/docs/gradio/image | Gradio - Image Docs |
**Using Image as an input component.**
How Image will pass its value to your function:
Type: `np.ndarray | PIL.Image.Image | str | None`
Passes the uploaded image as a `numpy.array`, `PIL.Image` or `str` filepath
depending on `type`.
Example Code
import gradio as gr
def pred... | Behavior | https://gradio.app/docs/gradio/image | Gradio - Image Docs |
Parameters ▼
value: str | PIL.Image.Image | np.ndarray | Callable | None
default `= None`
A `PIL.Image`, `numpy.array`, `pathlib.Path`, or `str` filepath or URL for the
default value that Image component is going to take. If a function is
provided, the function will be called each time the app loads t... | Initialization | https://gradio.app/docs/gradio/image | Gradio - Image Docs |
erred
from the image file type (e.g. "RGBA" for a .png image, "RGB" in most other
cases).
sources: list[Literal['upload', 'webcam', 'clipboard']] | Literal['upload', 'webcam', 'clipboard'] | None
default `= None`
List of sources for the image. "upload" creates a box where user can drop an
image file, ... | Initialization | https://gradio.app/docs/gradio/image | Gradio - Image Docs |
calculate `value` if `value` is a
function (has no effect otherwise). `value` is recalculated any time the
inputs change.
show_label: bool | None
default `= None`
if True, will display label.
buttons: list[Literal['download', 'share', 'fullscreen'] | Button] | None
default `= None`
... | Initialization | https://gradio.app/docs/gradio/image | Gradio - Image Docs |
ovided, this is inferred based on whether the
component is used as an input or output.
visible: bool | Literal['hidden']
default `= True`
If False, component will be hidden. If "hidden", component will be visually
hidden and not take up space in the layout but still exist in the DOM
st... | Initialization | https://gradio.app/docs/gradio/image | Gradio - Image Docs |
s
provided during constructor.
webcam_options: WebcamOptions | None
default `= None`
placeholder: str | None
default `= None`
Custom text for the upload area. Overrides default upload messages when
provided. Accepts new lines and `` to designate a heading.
watermark: W... | Initialization | https://gradio.app/docs/gradio/image | Gradio - Image Docs |
Shortcuts
gradio.Image
Interface String Shortcut `"image"`
Initialization Uses default values
| Shortcuts | https://gradio.app/docs/gradio/image | Gradio - Image Docs |
The `type` parameter controls the format of the data passed to your Python
function. Choosing the right type avoids unnecessary conversions in your code:
`type`| Your function receives| Shape / Format| Best for
---|---|---|---
`"numpy"` (default)| `numpy.ndarray`| `(height, width, 3)`, dtype `uint8`,
values 0–255|... | Understanding Image Types | https://gradio.app/docs/gradio/image | Gradio - Image Docs |
The `gr.Image` component can process or display any image format that is
[supported by the PIL
library](https://pillow.readthedocs.io/en/stable/handbook/image-file-
formats.html), including animated GIFs. In addition, it also supports the SVG
image format.
When the `gr.Image` component is used as an input component, t... | `GIF` and `SVG` Image Formats | https://gradio.app/docs/gradio/image | Gradio - Image Docs |
sepia_filterfake_diffusion
| Demos | https://gradio.app/docs/gradio/image | Gradio - Image Docs |
Description
Event listeners allow you to respond to user interactions with the UI
components you've defined in a Gradio Blocks app. When a user interacts with
an element, such as changing a slider value or uploading an image, a function
is called.
Supported Event Listeners
The Image component supports the following ... | Event Listeners | https://gradio.app/docs/gradio/image | Gradio - Image Docs |
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 | BlockContext | list[Component | BlockContext] | Set[Component | BlockContext] | None
default `= None`
List o... | Event Listeners | https://gradio.app/docs/gradio/image | Gradio - Image Docs |
animation at all
show_progress_on: Component | list[Component] | None
default `= None`
Component or list of components to show the progress animation on. If None,
will show the progress animation on all of the output components.
queue: bool
default `= True`
If True, will place the r... | Event Listeners | https://gradio.app/docs/gradio/image | Gradio - Image Docs |
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