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ChatInterface

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Interface

TabbedInterface

ChatInterface

gradio.ChatInterface(fn, type="messages", ···)

Description

ChatInterface is Gradio's high-level abstraction for creating chatbot UIs, and allows you to create a web-based demo around a chatbot model in a few lines of code. Only one parameter is required: fn, which takes a function that governs the response of the chatbot based on the user input and chat history. Additional parameters can be used to control the appearance and behavior of the demo.

Example Usage

Basic Example: A chatbot that echoes back the users’s message

import gradio as gr

def echo(message, history):
    return message

demo = gr.ChatInterface(fn=echo, type="messages", examples=["hello", "hola", "merhaba"], title="Echo Bot")
demo.launch()

Custom Chatbot: A gr.ChatInterface with a custom gr.Chatbot that includes a placeholder as well as upvote/downvote buttons. The upvote/downvote buttons are automatically added when a .like() event is attached to a gr.Chatbot. In order to attach event listeners to your custom chatbot, wrap the gr.Chatbot as well as the gr.ChatInterface inside of a gr.Blocks like this:

import gradio as gr

def yes(message, history):
    return "yes"

def vote(data: gr.LikeData):
    if data.liked:
        print("You upvoted this response: " + data.value["value"])
    else:
        print("You downvoted this response: " + data.value["value"])

with gr.Blocks() as demo:
    chatbot = gr.Chatbot(placeholder="<strong>Your Personal Yes-Man</strong><br>Ask Me Anything")
    chatbot.like(vote, None, None)
    gr.ChatInterface(fn=yes, type="messages", chatbot=chatbot)
    
demo.launch()

Initialization

fn: Callable

the function to wrap the chat interface around. In the default case (assuming `type` is set to "messages"), the function should accept two parameters: a `str` input message and `list` of openai-style dictionary {"role": "user" | "assistant", "content": `str` | {"path": `str`} | `gr.Component`} representing the chat history, and return/yield a `str` (if a simple message) or `dict` (for a complete openai-style message) response.

multimodal: bool

default = False

if True, the chat interface will use a `gr.MultimodalTextbox` component for the input, which allows for the uploading of multimedia files. If False, the chat interface will use a gr.Textbox component for the input. If this is True, the first argument of `fn` should accept not a `str` message but a `dict` message with keys "text" and "files"

type: Literal['messages', 'tuples'] | None

default = None

The format of the messages passed into the chat history parameter of `fn`. If "messages", passes the history as a list of dictionaries with openai-style "role" and "content" keys. The "content" key's value should be one of the following - (1) strings in valid Markdown (2) a dictionary with a "path" key and value corresponding to the file to display or (3) an instance of a Gradio component: at the moment gr.Image, gr.Plot, gr.Video, gr.Gallery, gr.Audio, and gr.HTML are supported. The "role" key should be one of 'user' or 'assistant'. Any other roles will not be displayed in the output. If this parameter is 'tuples' (deprecated), passes the chat history as 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.

chatbot: Chatbot | None

default = None

an instance of the gr.Chatbot component to use for the chat interface, if you would like to customize the chatbot properties. If not provided, a default gr.Chatbot component will be created.

textbox: Textbox | MultimodalTextbox | None

default = None

an instance of the gr.Textbox or gr.MultimodalTextbox component to use for the chat interface, if you would like to customize the textbox properties. If not provided, a default gr.Textbox or gr.MultimodalTextbox component will be created.

additional_inputs: str | Component | list[str | Component] | None

default = None

an instance or list of instances of gradio components (or their string shortcuts) to use as additional inputs to the chatbot. If the components are not already rendered in a surrounding Blocks, then the components will be displayed under the chatbot, in an accordion. The values of these components will be passed into `fn` as arguments in order after the chat history.

additional_inputs_accordion: str | Accordion | None

default = None

if a string is provided, this is the label of the `gr.Accordion` to use to contain additional inputs. A `gr.Accordion` object can be provided as well to configure other properties of the container holding the additional inputs. Defaults to a `gr.Accordion(label="Additional Inputs", open=False)`. This parameter is only used if `additional_inputs` is provided.

additional_outputs: Component | list[Component] | None

default = None

an instance or list of instances of gradio components to use as additional outputs from the chat function. These must be components that are already defined in the same Blocks scope. If provided, the chat function should return additional values for these components. See demo/chatinterface_artifacts.

examples: list[str] | list[MultimodalValue] | list[list] | None

default = None

sample inputs for the function; if provided, appear within the chatbot and can be clicked to populate the chatbot input. Should be a list of strings representing text-only examples, or a list of dictionaries (with keys `text` and `files`) representing multimodal examples. If `additional_inputs` are provided, the examples must be a list of lists, where the first element of each inner list is the string or dictionary example message and the remaining elements are the example values for the additional inputs -- in this case, the examples will appear under the chatbot.

example_labels: list[str] | None

default = None

labels for the examples, to be displayed instead of the examples themselves. If provided, should be a list of strings with the same length as the examples list. Only applies when examples are displayed within the chatbot (i.e. when `additional_inputs` is not provided).

example_icons: list[str] | None

default = None

icons for the examples, to be displayed above the examples. If provided, should be a list of string URLs or local paths with the same length as the examples list. Only applies when examples are displayed within the chatbot (i.e. when `additional_inputs` is not provided).

run_examples_on_click: bool

default = True

if True, clicking on an example will run the example through the chatbot fn and the response will be displayed in the chatbot. If False, clicking on an example will only populate the chatbot input with the example message. Has no effect if `cache_examples` is True

cache_examples: bool | None

default = None

if True, caches examples in the server for fast runtime in examples. The default option in HuggingFace Spaces is True. The default option elsewhere is False.

cache_mode: Literal['eager', 'lazy'] | None

default = None

if "eager", all examples are cached at app launch. If "lazy", examples are cached for all users after the first use by any user of the app. If None, will use the GRADIO_CACHE_MODE environment variable if defined, or default to "eager".

title: str | None

default = None

a title for the interface; if provided, appears above chatbot 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 chatbot and beneath the title in regular font. Accepts Markdown and HTML content.

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 code string. This css will be included in the demo webpage.

css_paths: str | Path | list[str | Path] | None

default = None

Custom css as a pathlib.Path to a css file or a list of such paths. This css files will be read, concatenated, and included in the demo webpage. If the `css` parameter is also set, the css from `css` will be included first.

js: str | None

default = None

Custom js as a code string. 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 code to insert into the head of the demo webpage. This can be used to add custom meta tags, multiple scripts, stylesheets, etc. to the page.

head_paths: str | Path | list[str | Path] | None

default = None

Custom html code as a pathlib.Path to a html file or a list of such paths. This html files will be read, concatenated, and included in the head of the demo webpage. If the `head` parameter is also set, the html from `head` will be included first.

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.

autofocus: bool

default = True

if True, autofocuses to the textbox when the page loads.

autoscroll: bool

default = True

If True, will automatically scroll to the bottom of the chatbot when a new message appears, unless the user scrolls up. If False, will not scroll to the bottom of the chatbot automatically.

submit_btn: str | bool | None

default = True

If True, will show a submit button with a submit icon within the textbox. If a string, will use that string as the submit button text in place of the icon. If False, will not show a submit button.

stop_btn: str | bool | None

default = True

If True, will show a button with a stop icon during generator executions, to stop generating. If a string, will use that string as the submit button text in place of the stop icon. If False, will not show a stop button.

concurrency_limit: int | None | Literal['default']

default = "default"

if set, this is the maximum number of chatbot submissions that can be running simultaneously. Can be set to None to mean no limit (any number of chatbot submissions can be running simultaneously). Set to "default" to use the default concurrency limit (defined by the `default_concurrency_limit` parameter in `.queue()`, which is 1 by default).

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.

show_progress: Literal['full', 'minimal', 'hidden']

default = "minimal"

how to show the progress animation while event is running: "full" shows a spinner which covers the output component area as well as a runtime display in the upper right corner, "minimal" only shows the runtime display, "hidden" shows no progress animation at all

fill_height: bool

default = True

if True, the chat interface will expand to the height of window.

fill_width: bool

default = False

Whether to horizontally expand to fill container fully. If False, centers and constrains app to a maximum width.

api_name: str | Literal[False]

default = "chat"

the name of the API endpoint to use for the chat interface. Defaults to "chat". Set to False to disable the API endpoint.

Demos

import random import gradio as gr def random_response(message, history): return random.choice(["Yes", "No"]) demo = gr.ChatInterface(random_response, type="messages", autofocus=False) if __name__ == "__main__": demo.launch()

import random
import gradio as gr

def random_response(message, history):
    return random.choice(["Yes", "No"])

demo = gr.ChatInterface(random_response, type="messages", autofocus=False)

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

import time import gradio as gr def slow_echo(message, history): for i in range(len(message)): time.sleep(0.05) yield "You typed: " + message[: i + 1] demo = gr.ChatInterface(slow_echo, type="messages") if __name__ == "__main__": demo.launch()

import time
import gradio as gr

def slow_echo(message, history):
    for i in range(len(message)):
        time.sleep(0.05)
        yield "You typed: " + message[: i + 1]

demo = gr.ChatInterface(slow_echo, type="messages")

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

import gradio as gr python_code = """ def fib(n): if n <= 0: return 0 elif n == 1: return 1 else: return fib(n-1) + fib(n-2) """ js_code = """ function fib(n) { if (n <= 0) return 0; if (n === 1) return 1; return fib(n - 1) + fib(n - 2); } """ def chat(message, history): if "python" in message.lower(): return "Type Python or JavaScript to see the code.", gr.Code(language="python", value=python_code) elif "javascript" in message.lower(): return "Type Python or JavaScript to see the code.", gr.Code(language="javascript", value=js_code) else: return "Please ask about Python or JavaScript.", None with gr.Blocks() as demo: code = gr.Code(render=False) with gr.Row(): with gr.Column(): gr.Markdown("<center><h1>Write Python or JavaScript</h1></center>") gr.ChatInterface( chat, examples=["Python", "JavaScript"], additional_outputs=[code], type="messages" ) with gr.Column(): gr.Markdown("<center><h1>Code Artifacts</h1></center>") code.render() demo.launch()

import gradio as gr

python_code = """
def fib(n):
    if n <= 0:
        return 0
    elif n == 1:
        return 1
    else:
        return fib(n-1) + fib(n-2)
"""

js_code = """
function fib(n) {
    if (n <= 0) return 0;
    if (n === 1) return 1;
    return fib(n - 1) + fib(n - 2);
}
"""

def chat(message, history):
    if "python" in message.lower():
        return "Type Python or JavaScript to see the code.", gr.Code(language="python", value=python_code)
    elif "javascript" in message.lower():
        return "Type Python or JavaScript to see the code.", gr.Code(language="javascript", value=js_code)
    else:
        return "Please ask about Python or JavaScript.", None

with gr.Blocks() as demo:
    code = gr.Code(render=False)
    with gr.Row():
        with gr.Column():
            gr.Markdown("Write Python or JavaScript")
            gr.ChatInterface(
                chat,
                examples=["Python", "JavaScript"],
                additional_outputs=[code],
                type="messages"
            )
        with gr.Column():
            gr.Markdown("Code Artifacts")
            code.render()

demo.launch()

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