Introducing Gradio 5.0

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  1. Routes
  2. Request

New to Gradio? Start here: Getting Started

See the Release History

To install Gradio from main, run the following command:

pip install https://gradio-builds.s3.amazonaws.com/9285dd9eb842ee05bd8a0fd4f0f9143788096bbc/gradio-5.9.1-py3-none-any.whl

*Note: Setting share=True in launch() will not work.

Request

gradio.Request(ยทยทยท)

Description

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_hash, and path_params. If auth is enabled, the username attribute can be used to get the logged in user. In some environments, the dict-like attributes (e.g. requests.headers, requests.query_params) of this class are automatically converted to to dictionaries, so we recommend converting them to dictionaries before accessing attributes for consistent behavior in different environments.

Example Usage

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_hash)
    return text
io = gr.Interface(echo, "textbox", "textbox").launch()

Initialization

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 unique for each page load.

Demos

import gradio as gr

def predict(text, request: gr.Request):
    headers = request.headers
    host = request.client.host
    user_agent = request.headers["user-agent"]
    return {
        "ip": host,
        "user_agent": user_agent,
        "headers": headers,
    }

gr.Interface(predict, "text", "json").launch()