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We'll stream the user's audio from their microphone to the server and determine if the user has stopped speaking on each new chunk of audio. Here's our `process_audio` function: ```python import numpy as np from utils import determine_pause def process_audio(audio: tuple, state: AppState): if state.stream is Non...
Processing User Audio
https://gradio.app/guides/conversational-chatbot
Streaming - Conversational Chatbot Guide
After processing the user's audio, we need to generate and stream the chatbot's response. Here's our `response` function: ```python import io import tempfile from pydub import AudioSegment def response(state: AppState): if not state.pause_detected and not state.started_talking: return None, AppState() ...
Generating the Response
https://gradio.app/guides/conversational-chatbot
Streaming - Conversational Chatbot Guide
Now let's put it all together using Gradio's Blocks API: ```python import gradio as gr def start_recording_user(state: AppState): if not state.stopped: return gr.Audio(recording=True) with gr.Blocks() as demo: with gr.Row(): with gr.Column(): input_audio = gr.Audio( ...
Building the Gradio App
https://gradio.app/guides/conversational-chatbot
Streaming - Conversational Chatbot Guide
This guide demonstrates how to build a conversational chatbot application using Gradio and the mini omni model. You can adapt this framework to create various audio-based chatbot demos. To see the full application in action, visit the Hugging Face Spaces demo: https://huggingface.co/spaces/gradio/omni-mini Feel free t...
Conclusion
https://gradio.app/guides/conversational-chatbot
Streaming - Conversational Chatbot Guide
Start by installing all the dependencies. Add the following lines to a `requirements.txt` file and run `pip install -r requirements.txt`: ```bash opencv-python fastrtc onnxruntime-gpu ``` We'll use the ONNX runtime to speed up YOLOv10 inference. This guide assumes you have access to a GPU. If you don't, change `onnxr...
Setting up
https://gradio.app/guides/object-detection-from-webcam-with-webrtc
Streaming - Object Detection From Webcam With Webrtc Guide
We'll download the YOLOv10 model from the Hugging Face hub and instantiate a custom inference class to use this model. The implementation of the inference class isn't covered in this guide, but you can find the source code [here](https://huggingface.co/spaces/freddyaboulton/webrtc-yolov10n/blob/main/inference.pyL9) i...
The Inference Function
https://gradio.app/guides/object-detection-from-webcam-with-webrtc
Streaming - Object Detection From Webcam With Webrtc Guide
The Gradio demo is straightforward, but we'll implement a few specific features: 1. Use the `WebRTC` custom component to ensure input and output are sent to/from the server with WebRTC. 2. The [WebRTC](https://github.com/freddyaboulton/gradio-webrtc) component will serve as both an input and output component. 3. Util...
The Gradio Demo
https://gradio.app/guides/object-detection-from-webcam-with-webrtc
Streaming - Object Detection From Webcam With Webrtc Guide
Our app is hosted on Hugging Face Spaces [here](https://huggingface.co/spaces/freddyaboulton/webrtc-yolov10n). You can use this app as a starting point to build real-time image applications with Gradio. Don't hesitate to open issues in the space or in the [FastRTC GitHub repo](https://github.com/gradio-app/fastrtc) i...
Conclusion
https://gradio.app/guides/object-detection-from-webcam-with-webrtc
Streaming - Object Detection From Webcam With Webrtc Guide
Modern voice applications should feel natural and responsive, moving beyond the traditional "click-to-record" pattern. By combining Groq's fast inference capabilities with automatic speech detection, we can create a more intuitive interaction model where users can simply start talking whenever they want to engage with ...
Introduction
https://gradio.app/guides/automatic-voice-detection
Streaming - Automatic Voice Detection Guide
Many voice apps currently work by the user clicking record, speaking, then stopping the recording. While this can be a powerful demo, the most natural mode of interaction with voice requires the app to dynamically detect when the user is speaking, so they can talk back and forth without having to continually click a re...
Background
https://gradio.app/guides/automatic-voice-detection
Streaming - Automatic Voice Detection Guide
- **Gradio**: Provides the web interface and audio handling capabilities - **@ricky0123/vad-web**: Handles voice activity detection - **Groq**: Powers fast LLM inference for natural conversations - **Whisper**: Transcribes speech to text Setting Up the Environment First, let’s install and import our essential librari...
Key Components
https://gradio.app/guides/automatic-voice-detection
Streaming - Automatic Voice Detection Guide
e’ll create a function to transcribe the user’s audio input into text using Whisper, a powerful transcription model hosted on Groq. This transcription will also help us determine whether there’s meaningful speech in the input. Here’s how: ```python def transcribe_audio(client, file_name): if file_name is None: ...
Key Components
https://gradio.app/guides/automatic-voice-detection
Streaming - Automatic Voice Detection Guide
ext.strip() return None ``` We also need to interpret the audio data response. The process_whisper_response function takes the resulting completion from Whisper and checks if the audio was just background noise or had actual speaking that was transcribed. It uses a threshold of 0.7 to interpret the no_speech_...
Key Components
https://gradio.app/guides/automatic-voice-detection
Streaming - Automatic Voice Detection Guide
ly detect when someone starts or stops speaking. Here’s how to implement it using ONNX in JavaScript: ```javascript async function main() { const script1 = document.createElement("script"); script1.src = "https://cdn.jsdelivr.net/npm/onnxruntime-web@1.14.0/dist/ort.js"; document.head.appendChild(script1) const...
Key Components
https://gradio.app/guides/automatic-voice-detection
Streaming - Automatic Voice Detection Guide
", streaming=False, waveform_options=gr.WaveformOptions(waveform_color="B83A4B"), ) with gr.Row(): chatbot = gr.Chatbot(label="Conversation") state = gr.State(value=AppState()) demo.launch(theme=theme, js=js) ``` In this code block, we’re using Gradio’s `Blocks` API to c...
Key Components
https://gradio.app/guides/automatic-voice-detection
Streaming - Automatic Voice Detection Guide
1. When you open the app, the VAD system automatically initializes and starts listening for speech 2. As soon as you start talking, it triggers the recording automatically 3. When you stop speaking, the recording ends and: - The audio is transcribed using Whisper - The transcribed text is sent to the LLM - The...
Summary
https://gradio.app/guides/automatic-voice-detection
Streaming - Automatic Voice Detection Guide
First, we'll install the following requirements in our system: ``` opencv-python torch transformers>=4.43.0 spaces ``` Then, we'll download the model from the Hugging Face Hub: ```python from transformers import RTDetrForObjectDetection, RTDetrImageProcessor image_processor = RTDetrImageProcessor.from_pretrained("P...
Setting up the Model
https://gradio.app/guides/object-detection-from-video
Streaming - Object Detection From Video Guide
Our inference function will accept a video and a desired confidence threshold. Object detection models identify many objects and assign a confidence score to each object. The lower the confidence, the higher the chance of a false positive. So we will let our users set the confidence threshold. Our function will iterat...
The Inference Function
https://gradio.app/guides/object-detection-from-video
Streaming - Object Detection From Video Guide
frame = cv2.resize( frame, (0,0), fx=0.5, fy=0.5) frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) if n_frames % SUBSAMPLE == 0: batch.append(frame) if len(batch) == 2 * desired_fps: inputs = image_processor(images=batch, return_tensors="pt").to("cuda") w...
The Inference Function
https://gradio.app/guides/object-detection-from-video
Streaming - Object Detection From Video Guide
dth, height))` line. The `video_codec` is how we specify the type of video file. Only "mp4" and "ts" files are supported for video sreaming at the moment. 2. **The Inference Loop** For each frame in the video, we will resize it to be half the size. OpenCV reads files in `BGR` format, so will convert to the expected ...
The Inference Function
https://gradio.app/guides/object-detection-from-video
Streaming - Object Detection From Video Guide
The UI code is pretty similar to other kinds of Gradio apps. We'll use a standard two-column layout so that users can see the input and output videos side by side. In order for streaming to work, we have to set `streaming=True` in the output video. Setting the video to autoplay is not necessary but it's a better expe...
The Gradio Demo
https://gradio.app/guides/object-detection-from-video
Streaming - Object Detection From Video Guide
You can check out our demo hosted on Hugging Face Spaces [here](https://huggingface.co/spaces/gradio/rt-detr-object-detection). It is also embedded on this page below $demo_rt-detr-object-detection
Conclusion
https://gradio.app/guides/object-detection-from-video
Streaming - Object Detection From Video Guide
Automatic speech recognition (ASR), the conversion of spoken speech to text, is a very important and thriving area of machine learning. ASR algorithms run on practically every smartphone, and are becoming increasingly embedded in professional workflows, such as digital assistants for nurses and doctors. Because ASR alg...
Introduction
https://gradio.app/guides/real-time-speech-recognition
Streaming - Real Time Speech Recognition Guide
First, you will need to have an ASR model that you have either trained yourself or you will need to download a pretrained model. In this tutorial, we will start by using a pretrained ASR model from the model, `whisper`. Here is the code to load `whisper` from Hugging Face `transformers`. ```python from transformers i...
1. Set up the Transformers ASR Model
https://gradio.app/guides/real-time-speech-recognition
Streaming - Real Time Speech Recognition Guide
We will start by creating a _full-context_ ASR demo, in which the user speaks the full audio before using the ASR model to run inference. This is very easy with Gradio -- we simply create a function around the `pipeline` object above. We will use `gradio`'s built in `Audio` component, configured to take input from the...
2. Create a Full-Context ASR Demo with Transformers
https://gradio.app/guides/real-time-speech-recognition
Streaming - Real Time Speech Recognition Guide
To make this a *streaming* demo, we need to make these changes: 1. Set `streaming=True` in the `Audio` component 2. Set `live=True` in the `Interface` 3. Add a `state` to the interface to store the recorded audio of a user Tip: You can also set `time_limit` and `stream_every` parameters in the interface. The `time_li...
3. Create a Streaming ASR Demo with Transformers
https://gradio.app/guides/real-time-speech-recognition
Streaming - Real Time Speech Recognition Guide
**Prerequisite**: Gradio requires [Python 3.10 or higher](https://www.python.org/downloads/). We recommend installing Gradio using `pip`, which is included by default in Python. Run this in your terminal or command prompt: ```bash pip install --upgrade gradio ``` Tip: It is best to install Gradio in a virtual envi...
Installation
https://gradio.app/guides/quickstart
Getting Started - Quickstart Guide
You can run Gradio in your favorite code editor, Jupyter notebook, Google Colab, or anywhere else you write Python. Let's write your first Gradio app: $code_hello_world_4 Tip: We shorten the imported name from <code>gradio</code> to <code>gr</code>. This is a widely adopted convention for better readability of code...
Building Your First Demo
https://gradio.app/guides/quickstart
Getting Started - Quickstart Guide
turn one or more outputs. The `Interface` class has three core arguments: - `fn`: the function to wrap a user interface (UI) around - `inputs`: the Gradio component(s) to use for the input. The number of components should match the number of arguments in your function. - `outputs`: the Gradio component(s) to use for...
Building Your First Demo
https://gradio.app/guides/quickstart
Getting Started - Quickstart Guide
What good is a beautiful demo if you can't share it? Gradio lets you easily share a machine learning demo without having to worry about the hassle of hosting on a web server. Simply set `share=True` in `launch()`, and a publicly accessible URL will be created for your demo. Let's revisit our example demo, but change t...
Sharing Your Demo
https://gradio.app/guides/quickstart
Getting Started - Quickstart Guide
So far, we've been discussing the `Interface` class, which is a high-level class that lets you build demos quickly with Gradio. But what else does Gradio include? Custom Demos with `gr.Blocks` Gradio offers a low-level approach for designing web apps with more customizable layouts and data flows with the `gr.Blocks` ...
An Overview of Gradio
https://gradio.app/guides/quickstart
Getting Started - Quickstart Guide
.app/guides/getting-started-with-the-python-client) (`gradio_client`): query any Gradio app programmatically in Python. * [Gradio JavaScript Client](https://www.gradio.app/guides/getting-started-with-the-js-client) (`@gradio/client`): query any Gradio app programmatically in JavaScript. * [Hugging Face Spaces](https://...
An Overview of Gradio
https://gradio.app/guides/quickstart
Getting Started - Quickstart Guide
Keep learning about Gradio sequentially using the Gradio Guides, which include explanations as well as example code and embedded interactive demos. Next up: [let's dive deeper into the Interface class](https://www.gradio.app/guides/the-interface-class). Or, if you already know the basics and are looking for something ...
What's Next?
https://gradio.app/guides/quickstart
Getting Started - Quickstart Guide
Global state in Gradio apps is very simple: any variable created outside of a function is shared globally between all users. This makes managing global state very simple and without the need for external services. For example, in this application, the `visitor_count` variable is shared between all users ```py import ...
Global State
https://gradio.app/guides/state-in-blocks
Building With Blocks - State In Blocks Guide
Gradio supports session state, where data persists across multiple submits within a page session. To reiterate, session data is _not_ shared between different users of your model, and does _not_ persist if a user refreshes the page to reload the Gradio app. To store data in a session state, you need to do three things:...
Session State
https://gradio.app/guides/state-in-blocks
Building With Blocks - State In Blocks Guide
riggered if the **hash** of the value changes. So if you define a custom class and create a `gr.State` variable that is an instance of that class, make sure that the the class includes a sensible `__hash__` implementation. The value of a session State variable is cleared when the user refreshes the page. The value is...
Session State
https://gradio.app/guides/state-in-blocks
Building With Blocks - State In Blocks Guide
return "Error: Session not initialized" with gr.Blocks() as demo: output = gr.Textbox(label="Status") counter = gr.Number(label="Counter Value") increment_btn = gr.Button("Increment Counter") increment_btn.click(increment_counter, inputs=None, outputs=counter) Initialize instance when page ...
Session State
https://gradio.app/guides/state-in-blocks
Building With Blocks - State In Blocks Guide
Gradio also supports browser state, where data persists in the browser's localStorage even after the page is refreshed or closed. This is useful for storing user preferences, settings, API keys, or other data that should persist across sessions. To use local state: 1. Create a `gr.BrowserState` object. You can optiona...
Browser State
https://gradio.app/guides/state-in-blocks
Building With Blocks - State In Blocks Guide
Elements within a `with gr.Row` clause will all be displayed horizontally. For example, to display two Buttons side by side: ```python with gr.Blocks() as demo: with gr.Row(): btn1 = gr.Button("Button 1") btn2 = gr.Button("Button 2") ``` You can set every element in a Row to have the same height. ...
Rows
https://gradio.app/guides/controlling-layout
Building With Blocks - Controlling Layout Guide
Components within a Column will be placed vertically atop each other. Since the vertical layout is the default layout for Blocks apps anyway, to be useful, Columns are usually nested within Rows. For example: $code_rows_and_columns $demo_rows_and_columns See how the first column has two Textboxes arranged vertically....
Columns and Nesting
https://gradio.app/guides/controlling-layout
Building With Blocks - Controlling Layout Guide
Some components support setting height and width. These parameters accept either a number (interpreted as pixels) or a string. Using a string allows the direct application of any CSS unit to the encapsulating Block element. Below is an example illustrating the use of viewport width (vw): ```python import gradio as gr...
Dimensions
https://gradio.app/guides/controlling-layout
Building With Blocks - Controlling Layout Guide
You can also create Tabs using the `with gr.Tab('tab_name'):` clause. Any component created inside of a `with gr.Tab('tab_name'):` context appears in that tab. Consecutive Tab clauses are grouped together so that a single tab can be selected at one time, and only the components within that Tab's context are shown. For...
Tabs and Accordions
https://gradio.app/guides/controlling-layout
Building With Blocks - Controlling Layout Guide
The sidebar is a collapsible panel that renders child components on the left side of the screen and can be expanded or collapsed. For example: $code_blocks_sidebar Learn more about [Sidebar](https://gradio.app/docs/gradio/sidebar) in the docs.
Sidebar
https://gradio.app/guides/controlling-layout
Building With Blocks - Controlling Layout Guide
In order to provide a guided set of ordered steps, a controlled workflow, you can use the `Walkthrough` component with accompanying `Step` components. The `Walkthrough` component has a visual style and user experience tailored for this usecase. Authoring this component is very similar to `Tab`, except it is the app d...
Multi-step walkthroughs
https://gradio.app/guides/controlling-layout
Building With Blocks - Controlling Layout Guide
Both Components and Layout elements have a `visible` argument that can set initially and also updated. Setting `gr.Column(visible=...)` on a Column can be used to show or hide a set of Components. $code_blocks_form $demo_blocks_form
Visibility
https://gradio.app/guides/controlling-layout
Building With Blocks - Controlling Layout Guide
In some cases, you might want to define components before you actually render them in your UI. For instance, you might want to show an examples section using `gr.Examples` above the corresponding `gr.Textbox` input. Since `gr.Examples` requires as a parameter the input component object, you will need to first define th...
Defining and Rendering Components Separately
https://gradio.app/guides/controlling-layout
Building With Blocks - Controlling Layout Guide
Take a look at the demo below. $code_hello_blocks $demo_hello_blocks - First, note the `with gr.Blocks() as demo:` clause. The Blocks app code will be contained within this clause. - Next come the Components. These are the same Components used in `Interface`. However, instead of being passed to some constructor, Comp...
Blocks Structure
https://gradio.app/guides/blocks-and-event-listeners
Building With Blocks - Blocks And Event Listeners Guide
In the example above, you'll notice that you are able to edit Textbox `name`, but not Textbox `output`. This is because any Component that acts as an input to an event listener is made interactive. However, since Textbox `output` acts only as an output, Gradio determines that it should not be made interactive. You can ...
Event Listeners and Interactivity
https://gradio.app/guides/blocks-and-event-listeners
Building With Blocks - Blocks And Event Listeners Guide
Take a look at the demo below: $code_blocks_hello $demo_blocks_hello Instead of being triggered by a click, the `welcome` function is triggered by typing in the Textbox `inp`. This is due to the `change()` event listener. Different Components support different event listeners. For example, the `Video` Component suppo...
Types of Event Listeners
https://gradio.app/guides/blocks-and-event-listeners
Building With Blocks - Blocks And Event Listeners Guide
A Blocks app is not limited to a single data flow the way Interfaces are. Take a look at the demo below: $code_reversible_flow $demo_reversible_flow Note that `num1` can act as input to `num2`, and also vice-versa! As your apps get more complex, you will have many data flows connecting various Components. Here's an ...
Multiple Data Flows
https://gradio.app/guides/blocks-and-event-listeners
Building With Blocks - Blocks And Event Listeners Guide
The event listeners you've seen so far have a single input component. If you'd like to have multiple input components pass data to the function, you have two options on how the function can accept input component values: 1. as a list of arguments, or 2. as a single dictionary of values, keyed by the component Let's s...
Function Input List vs Set
https://gradio.app/guides/blocks-and-event-listeners
Building With Blocks - Blocks And Event Listeners Guide
Similarly, you may return values for multiple output components either as: 1. a list of values, or 2. a dictionary keyed by the component Let's first see an example of (1), where we set the values of two output components by returning two values: ```python with gr.Blocks() as demo: food_box = gr.Number(value=10,...
Function Return List vs Dict
https://gradio.app/guides/blocks-and-event-listeners
Building With Blocks - Blocks And Event Listeners Guide
d_box` component. Dictionary returns are helpful when an event listener affects many components on return, or conditionally affects outputs and not others. Keep in mind that with dictionary returns, we still need to specify the possible outputs in the event listener.
Function Return List vs Dict
https://gradio.app/guides/blocks-and-event-listeners
Building With Blocks - Blocks And Event Listeners Guide
The return value of an event listener function is usually the updated value of the corresponding output Component. Sometimes we want to update the configuration of the Component as well, such as the visibility. In this case, we return a new Component, setting the properties we want to change. $code_blocks_essay_simple...
Updating Component Configurations
https://gradio.app/guides/blocks-and-event-listeners
Building With Blocks - Blocks And Event Listeners Guide
In some cases, you may want to leave a component's value unchanged. Gradio includes a special function, `gr.skip()`, which can be returned from your function. Returning this function will keep the output component (or components') values as is. Let us illustrate with an example: $code_skip $demo_skip Note the differe...
Not Changing a Component's Value
https://gradio.app/guides/blocks-and-event-listeners
Building With Blocks - Blocks And Event Listeners Guide
You can also run events consecutively by using the `then` method of an event listener. This will run an event after the previous event has finished running. This is useful for running events that update components in multiple steps. For example, in the chatbot example below, we first update the chatbot with the user m...
Running Events Consecutively
https://gradio.app/guides/blocks-and-event-listeners
Building With Blocks - Blocks And Event Listeners Guide
Often times, you may want to bind multiple triggers to the same function. For example, you may want to allow a user to click a submit button, or press enter to submit a form. You can do this using the `gr.on` method and passing a list of triggers to the `trigger`. $code_on_listener_basic $demo_on_listener_basic You c...
Binding Multiple Triggers to a Function
https://gradio.app/guides/blocks-and-event-listeners
Building With Blocks - Blocks And Event Listeners Guide
If you want to set a Component's value to always be a function of the value of other Components, you can use the following shorthand: ```python with gr.Blocks() as demo: num1 = gr.Number() num2 = gr.Number() product = gr.Number(lambda a, b: a * b, inputs=[num1, num2]) ``` This functionally the same as: ```pytho...
Binding a Component Value Directly to a Function of Other Components
https://gradio.app/guides/blocks-and-event-listeners
Building With Blocks - Blocks And Event Listeners Guide
In the example below, we will create a variable number of Textboxes. When the user edits the input Textbox, we create a Textbox for each letter in the input. Try it out below: $code_render_split_simple $demo_render_split_simple See how we can now create a variable number of Textboxes using our custom logic - in this ...
Dynamic Number of Components
https://gradio.app/guides/dynamic-apps-with-render-decorator
Building With Blocks - Dynamic Apps With Render Decorator Guide
If you're creating components, you probably want to attach event listeners to them as well. Let's take a look at an example that takes in a variable number of Textbox as input, and merges all the text into a single box. $code_render_merge_simple $demo_render_merge_simple Let's take a look at what's happening here: 1...
Dynamic Event Listeners
https://gradio.app/guides/dynamic-apps-with-render-decorator
Building With Blocks - Dynamic Apps With Render Decorator Guide
The `key=` argument is used to let Gradio know that the same component is being generated when your render function re-runs. This does two things: 1. The same element in the browser is re-used from the previous render for this Component. This gives browser performance gains - as there's no need to destroy and rebuild ...
Closer Look at `keys=` parameter
https://gradio.app/guides/dynamic-apps-with-render-decorator
Building With Blocks - Dynamic Apps With Render Decorator Guide
Let's look at two examples that use all the features above. First, try out the to-do list app below: $code_todo_list $demo_todo_list Note that almost the entire app is inside a single `gr.render` that reacts to the tasks `gr.State` variable. This variable is a nested list, which presents some complexity. If you desi...
Putting it Together
https://gradio.app/guides/dynamic-apps-with-render-decorator
Building With Blocks - Dynamic Apps With Render Decorator Guide
Gradio themes are the easiest way to customize the look and feel of your app. You can choose from a variety of themes, or create your own. To do so, pass the `theme=` kwarg to the `launch()` method of the `Blocks` constructor. For example: ```python with gr.Blocks() as demo: ... your code here demo.launch(theme=gr...
Adding custom CSS to your demo
https://gradio.app/guides/custom-CSS-and-JS
Building With Blocks - Custom Css And Js Guide
You can `elem_id` to add an HTML element `id` to any component, and `elem_classes` to add a class or list of classes. This will allow you to select elements more easily with CSS. This approach is also more likely to be stable across Gradio versions as built-in class names or ids may change (however, as mentioned in the...
The `elem_id` and `elem_classes` Arguments
https://gradio.app/guides/custom-CSS-and-JS
Building With Blocks - Custom Css And Js Guide
There are 3 ways to add javascript code to your Gradio demo: 1. You can add JavaScript code as a string to the `js` parameter of the `Blocks` or `Interface` initializer. This will run the JavaScript code when the demo is first loaded. Below is an example of adding custom js to show an animated welcome message when th...
Adding custom JavaScript to your demo
https://gradio.app/guides/custom-CSS-and-JS
Building With Blocks - Custom Css And Js Guide
n open-source web application showcasing various features and capabilities."> <!-- Facebook Meta Tags --> <meta property="og:url" content="https://example.com"> <meta property="og:type" content="website"> <meta property="og:title" content="Sample App"> <meta property="og:description" content="An open-source web applic...
Adding custom JavaScript to your demo
https://gradio.app/guides/custom-CSS-and-JS
Building With Blocks - Custom Css And Js Guide
"input": case "textarea": break; default: if (e.key.toLowerCase() == "s" && e.shiftKey) { document.getElementById("my_btn").click(); } } } document.addEventListener('keypress', shortcuts, false); </script> """ with gr.Blocks() as demo: action_button = gr.Butt...
Adding custom JavaScript to your demo
https://gradio.app/guides/custom-CSS-and-JS
Building With Blocks - Custom Css And Js Guide
The `gr.HTML` component can also be used to create custom input components by triggering events. You will provide `js_on_load`, javascript code that runs when the component loads. The code has access to the `trigger` function to trigger events that Gradio can listen to, and the object `props` which has access to all th...
Triggering Events and Custom Input Components
https://gradio.app/guides/custom-HTML-components
Building With Blocks - Custom Html Components Guide
ce when the component is first rendered. If your component creates new elements dynamically that need event listeners, attach the event listener to a parent element that exists when the component loads, and check for the target. For example: ```js element.addEventListener('click', (e) => if (e.target && e.target.m...
Triggering Events and Custom Input Components
https://gradio.app/guides/custom-HTML-components
Building With Blocks - Custom Html Components Guide
The `watch` function, available inside `js_on_load`, lets you run a callback whenever specific props change when the component is an output to a Python event listener. Read current values directly from `props` inside the callback. ```js // Watch a single prop watch('value', () => { console.log('value is now:', pro...
Watching Props with `watch`
https://gradio.app/guides/custom-HTML-components
Building With Blocks - Custom Html Components Guide
The `head` parameter lets you load external JavaScript or CSS libraries directly on the component. The `head` content is injected and loaded **before** `js_on_load` runs, so your code can immediately use the library. ```python gr.HTML( value=[30, 70, 45, 90, 60], html_template="<canvas id='chart'></canvas>", ...
Loading Third-Party Scripts with `head`
https://gradio.app/guides/custom-HTML-components
Building With Blocks - Custom Html Components Guide
You can call Python functions directly from your `js_on_load` code using the `server_functions` parameter. Pass a list of Python functions to `server_functions`, and they become available as async methods on a `server` object inside `js_on_load`. $code_html_server_functions $demo_html_server_functions
Server Functions
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Building With Blocks - Custom Html Components Guide
If you are reusing the same HTML component in multiple places, you can create a custom component class by subclassing `gr.HTML` and setting default values for the templates and other arguments. Here's an example of creating a reusable StarRating component. $code_star_rating_component $demo_star_rating_component Note:...
Component Classes
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Building With Blocks - Custom Html Components Guide
The `gr.HTML` component can also be used as a container for other Gradio components using the `@children` placeholder. This allows you to create custom layouts with HTML/CSS. The `@children` must be at the top-level of the `html_template`. Since children cannot be nested inside the template, target the parent element...
Embedding Components in HTML
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Building With Blocks - Custom Html Components Guide
Once you've built a custom HTML component, you can share it with the community by pushing it to the [HTML Components Gallery](https://www.gradio.app/custom-components/html-gallery). The gallery lets anyone browse, interact with, and copy the Python code for community-contributed components. Call `push_to_hub` on any `...
Sharing Components with `push_to_hub`
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Building With Blocks - Custom Html Components Guide
Keep in mind that using `gr.HTML` to create custom components involves injecting raw HTML and JavaScript into your Gradio app. Be cautious about using untrusted user input into `html_template` and `js_on_load`, as this could lead to cross-site scripting (XSS) vulnerabilities. You should also expect that any Python ev...
Security Considerations
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Building With Blocks - Custom Html Components Guide
- Browse the [HTML Components Gallery](https://www.gradio.app/custom-components/html-gallery) to see what the community has built and copy components into your own apps. - Check out more examples in [this directory](https://github.com/gradio-app/gradio/tree/main/gradio/components/custom_html_components). - Share your o...
Next Steps
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Building With Blocks - Custom Html Components Guide
Let's start by using `llama-index` on top of `openai` to build a RAG chatbot on any text or PDF files that you can demo and share in less than 30 lines of code. You'll need to have an OpenAI key for this example (keep reading for the free, open-source equivalent!) $code_llm_llamaindex
Llama Index
https://gradio.app/guides/chatinterface-examples
Chatbots - Chatinterface Examples Guide
Here's an example using `langchain` on top of `openai` to build a general-purpose chatbot. As before, you'll need to have an OpenAI key for this example. $code_llm_langchain Tip: For quick prototyping, the community-maintained <a href='https://github.com/AK391/langchain-gradio'>langchain-gradio repo</a> makes it eve...
LangChain
https://gradio.app/guides/chatinterface-examples
Chatbots - Chatinterface Examples Guide
Of course, we could also use the `openai` library directy. Here a similar example to the LangChain , but this time with streaming as well: Tip: For quick prototyping, the <a href='https://github.com/gradio-app/openai-gradio'>openai-gradio library</a> makes it even easier to build chatbots on top of OpenAI models.
OpenAI
https://gradio.app/guides/chatinterface-examples
Chatbots - Chatinterface Examples Guide
Of course, in many cases you want to run a chatbot locally. Here's the equivalent example using the SmolLM2-135M-Instruct model using the Hugging Face `transformers` library. $code_llm_hf_transformers
Hugging Face `transformers`
https://gradio.app/guides/chatinterface-examples
Chatbots - Chatinterface Examples Guide
The SambaNova Cloud API provides access to full-precision open-source models, such as the Llama family. Here's an example of how to build a Gradio app around the SambaNova API $code_llm_sambanova Tip: For quick prototyping, the <a href='https://github.com/gradio-app/sambanova-gradio'>sambanova-gradio library</a> mak...
SambaNova
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Chatbots - Chatinterface Examples Guide
The Hyperbolic AI API provides access to many open-source models, such as the Llama family. Here's an example of how to build a Gradio app around the Hyperbolic $code_llm_hyperbolic Tip: For quick prototyping, the <a href='https://github.com/HyperbolicLabs/hyperbolic-gradio'>hyperbolic-gradio library</a> makes it ev...
Hyperbolic
https://gradio.app/guides/chatinterface-examples
Chatbots - Chatinterface Examples Guide
Anthropic's Claude model can also be used via API. Here's a simple 20 questions-style game built on top of the Anthropic API: $code_llm_claude
Anthropic's Claude
https://gradio.app/guides/chatinterface-examples
Chatbots - Chatinterface Examples Guide
Chatbots are a popular application of large language models (LLMs). Using Gradio, you can easily build a chat application and share that with your users, or try it yourself using an intuitive UI. This tutorial uses `gr.ChatInterface()`, which is a high-level abstraction that allows you to create your chatbot UI fast, ...
Introduction
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Chatbots - Creating A Chatbot Fast Guide
If you have a chat server serving an OpenAI-API compatible endpoint (such as Ollama), you can spin up a ChatInterface in a single line of Python. First, also run `pip install openai`. Then, with your own URL, model, and optional token: ```python import gradio as gr gr.load_chat("http://localhost:11434/v1/", model="ll...
Note for OpenAI-API compatible endpoints
https://gradio.app/guides/creating-a-chatbot-fast
Chatbots - Creating A Chatbot Fast Guide
To create a chat application with `gr.ChatInterface()`, the first thing you should do is define your **chat function**. In the simplest case, your chat function should accept two arguments: `message` and `history` (the arguments can be named anything, but must be in this order). - `message`: a `str` representing the u...
Defining a chat function
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Chatbots - Creating A Chatbot Fast Guide
t take user input or the previous history into account! Here's another simple example showing how to incorporate a user's input as well as the history. ```python import gradio as gr def alternatingly_agree(message, history): if len([h for h in history if h['role'] == "assistant"]) % 2 == 0: return f"Yes, ...
Defining a chat function
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Chatbots - Creating A Chatbot Fast Guide
In your chat function, you can use `yield` to generate a sequence of partial responses, each replacing the previous ones. This way, you'll end up with a streaming chatbot. It's that simple! ```python import time import gradio as gr def slow_echo(message, history): for i in range(len(message)): time.sleep(...
Streaming chatbots
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Chatbots - Creating A Chatbot Fast Guide
If you're familiar with Gradio's `gr.Interface` class, the `gr.ChatInterface` includes many of the same arguments that you can use to customize the look and feel of your Chatbot. For example, you can: - add a title and description above your chatbot using `title` and `description` arguments. - add a theme or custom cs...
Customizing the Chat UI
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Chatbots - Creating A Chatbot Fast Guide
le of how we to apply the parameters we've discussed in this section: ```python import gradio as gr def yes_man(message, history): if message.endswith("?"): return "Yes" else: return "Ask me anything!" gr.ChatInterface( yes_man, chatbot=gr.Chatbot(height=300), textbox=gr.Textbox(p...
Customizing the Chat UI
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Chatbots - Creating A Chatbot Fast Guide
You may want to add multimodal capabilities to your chat interface. For example, you may want users to be able to upload images or files to your chatbot and ask questions about them. You can make your chatbot "multimodal" by passing in a single parameter (`multimodal=True`) to the `gr.ChatInterface` class. When `multi...
Multimodal Chat Interface
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Chatbots - Creating A Chatbot Fast Guide
ox` to the `textbox` parameter. You can customize the `MultimodalTextbox` further by passing in the `sources` parameter, which is a list of sources to enable. Here's an example that illustrates how to set up and customize and multimodal chat interface: ```python import gradio as gr def count_images(message, history...
Multimodal Chat Interface
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Chatbots - Creating A Chatbot Fast Guide
You may want to add additional inputs to your chat function and expose them to your users through the chat UI. For example, you could add a textbox for a system prompt, or a slider that sets the number of tokens in the chatbot's response. The `gr.ChatInterface` class supports an `additional_inputs` parameter which can ...
Additional Inputs
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Chatbots - Creating A Chatbot Fast Guide
s to the `examples` parameter, where each inner list represents one sample, and each inner list should be `1 + len(additional_inputs)` long. The first element in the inner list should be the example value for the chat message, and each subsequent element should be an example value for one of the additional inputs, in o...
Additional Inputs
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Chatbots - Creating A Chatbot Fast Guide
In the same way that you can accept additional inputs into your chat function, you can also return additional outputs. Simply pass in a list of components to the `additional_outputs` parameter in `gr.ChatInterface` and return additional values for each component from your chat function. Here's an example that extracts ...
Additional Outputs
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Chatbots - Creating A Chatbot Fast Guide
We mentioned earlier that in the simplest case, your chat function should return a `str` response, which will be rendered as Markdown in the chatbot. However, you can also return more complex responses as we discuss below: **Returning files or Gradio components** Currently, the following Gradio components can be dis...
Returning Complex Responses
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Chatbots - Creating A Chatbot Fast Guide
ma of the `gr.ChatMessage` data class as well as two internal typed dictionaries: ```py MessageContent = Union[str, FileDataDict, FileData, Component] @dataclass class ChatMessage: content: MessageContent | list[MessageContent] metadata: MetadataDict = None options: list[OptionDict] = None class Metada...
Returning Complex Responses
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Chatbots - Creating A Chatbot Fast Guide
corresponding to the `options` key should be a list of dictionaries, each with a `value` (a string that is the value that should be sent to the chat function when this response is clicked) and an optional `label` (if provided, is the text displayed as the preset response instead of the `value`). This example illustr...
Returning Complex Responses
https://gradio.app/guides/creating-a-chatbot-fast
Chatbots - Creating A Chatbot Fast Guide
You may wish to modify the value of the chatbot with your own events, other than those prebuilt in the `gr.ChatInterface`. For example, you could create a dropdown that prefills the chat history with certain conversations or add a separate button to clear the conversation history. The `gr.ChatInterface` supports these ...
Modifying the Chatbot Value Directly
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Chatbots - Creating A Chatbot Fast Guide