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Chatbot

gradio.Chatbot(···)

Description

Displays a chatbot output showing both 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.

Behavior

As input: passes the messages in the Chatbot as a List[List[str | None | Tuple]], i.e. a list of lists. The inner list has 2 elements: the user message and the response message. See `Postprocessing` for the format of these messages.

As output: expects function to return a List[List[str | None | Tuple]], i.e. a list of lists. The inner list should have 2 elements: the user message and the response message. The individual messages can be (1) strings in valid Markdown, (2) tuples if sending files: (a filepath or URL to a file, [optional string alt text]) -- if the file is image/video/audio, it is displayed in the Chatbot, or (3) None, in which case the message is not displayed.

Initialization

Parameter Description
value

list[list[str | tuple[str] | tuple[str | Path, str] | None]] | Callable | None

default: None

Default value to show in chatbot. If callable, the function will be called whenever the app loads to set the initial value of the component.

color_map

dict[str, str] | None

default: None

label

str | None

default: None

component name in interface.

every

float | None

default: None

If `value` is a callable, run the function 'every' number of seconds while the client connection is open. Has no effect otherwise. Queue must be enabled. The event can be accessed (e.g. to cancel it) via this component's .load_event attribute.

show_label

bool

default: True

if True, will display label.

container

bool

default: True

If True, will place the component in a container - providing some extra padding around the border.

scale

int | None

default: None

relative width compared to adjacent Components in a Row. For example, if Component A has scale=2, and Component B has scale=1, A will be twice as wide as B. Should be an integer.

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 than min_width, the min_width parameter will be respected first.

visible

bool

default: True

If False, component will be hidden.

elem_id

str | None

default: None

An optional string that is assigned as the id of this component in the HTML DOM. Can be used for targeting CSS styles.

elem_classes

list[str] | str | None

default: None

An optional list of strings that are assigned as the classes of this component in the HTML DOM. Can be used for targeting CSS styles.

height

int | None

default: None

height of the component in pixels.

latex_delimiters

list[dict[str, str | bool]] | None

default: None

A list of dicts of the form {"left": open 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, and in a new line. Pass in an empty list to disable LaTeX rendering. For more information, see the [KaTeX documentation](https://katex.org/docs/autorender.html).

show_share_button

bool | None

default: None

If True, will show a share icon in the corner of the component that allows user to share outputs to Hugging Face Spaces Discussions. If False, icon does not appear. If set to None (default behavior), then the icon appears if this Gradio app is launched on Spaces, but not otherwise.

Shortcuts

Class Interface String Shortcut Initialization

gradio.Chatbot

"chatbot"

Uses default values

Demos

import gradio as gr
import random
import time

with gr.Blocks() as demo:
    chatbot = gr.Chatbot()
    msg = gr.Textbox()
    clear = gr.ClearButton([msg, chatbot])

    def respond(message, chat_history):
        bot_message = random.choice(["How are you?", "I love you", "I'm very hungry"])
        chat_history.append((message, bot_message))
        time.sleep(2)
        return "", chat_history

    msg.submit(respond, [msg, chatbot], [msg, chatbot])

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

Methods

change

gradio.Chatbot.change(fn, ···)

Description

This listener is triggered when the component's value changes either because of user input (e.g. a user types in a textbox) OR because of a function update (e.g. an image receives a value from the output of an event trigger). See `.input()` for a listener that is only triggered by user input. This method can be used when this component is in a Gradio Blocks.

Agruments

Parameter Description
fn

Callable | None

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

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 False, the endpoint will not be exposed in the api docs. If set to None, the endpoint will be exposed in the api docs as an unnamed endpoint, although this behavior will be changed in Gradio 4.0. If set to a string, the endpoint will be exposed in the api docs with the given name.

status_tracker

None

default: None

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. Queue must be enabled.

select

gradio.Chatbot.select(fn, ···)

Description

Event listener for when the user selects message from Chatbot. Uses event data gradio.SelectData to carry `value` referring to text of selected message, and `index` tuple to refer to [message, participant] index. See EventData documentation on how to use this event data.

Agruments

Parameter Description
fn

Callable | None

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

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 False, the endpoint will not be exposed in the api docs. If set to None, the endpoint will be exposed in the api docs as an unnamed endpoint, although this behavior will be changed in Gradio 4.0. If set to a string, the endpoint will be exposed in the api docs with the given name.

status_tracker

None

default: None

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. Queue must be enabled.