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First, we'll build the UI without handling these events and build from there. We'll use the Hugging Face InferenceClient in order to get started without setting up any API keys. This is what the first draft of our application looks like: ```python from huggingface_hub import InferenceClient import gradio as gr clie...
The UI
https://gradio.app/guides/chatbot-specific-events
Chatbots - Chatbot Specific Events Guide
Our undo event will populate the textbox with the previous user message and also remove all subsequent assistant responses. In order to know the index of the last user message, we can pass `gr.UndoData` to our event handler function like so: ```python def handle_undo(history, undo_data: gr.UndoData): return histo...
The Undo Event
https://gradio.app/guides/chatbot-specific-events
Chatbots - Chatbot Specific Events Guide
The retry event will work similarly. We'll use `gr.RetryData` to get the index of the previous user message and remove all the subsequent messages from the history. Then we'll use the `respond` function to generate a new response. We could also get the previous prompt via the `value` property of `gr.RetryData`. ```pyt...
The Retry Event
https://gradio.app/guides/chatbot-specific-events
Chatbots - Chatbot Specific Events Guide
By now you should hopefully be seeing the pattern! To let users like a message, we'll add a `.like` event to our chatbot. We'll pass it a function that accepts a `gr.LikeData` object. In this case, we'll just print the message that was either liked or disliked. ```python def handle_like(data: gr.LikeData): if data...
The Like Event
https://gradio.app/guides/chatbot-specific-events
Chatbots - Chatbot Specific Events Guide
Same idea with the edit listener! with `gr.Chatbot(editable=True)`, you can capture user edits. The `gr.EditData` object tells us the index of the message edited and the new text of the mssage. Below, we use this object to edit the history, and delete any subsequent messages. ```python def handle_edit(history, edit_d...
The Edit Event
https://gradio.app/guides/chatbot-specific-events
Chatbots - Chatbot Specific Events Guide
As a bonus, we'll also cover the `.clear()` event, which is triggered when the user clicks the clear icon to clear all messages. As a developer, you can attach additional events that should happen when this icon is clicked, e.g. to handle clearing of additional chatbot state: ```python from uuid import uuid4 import gr...
The Clear Event
https://gradio.app/guides/chatbot-specific-events
Chatbots - Chatbot Specific Events Guide
That's it! You now know how you can implement the retry, undo, like, and clear events for the Chatbot.
Conclusion
https://gradio.app/guides/chatbot-specific-events
Chatbots - Chatbot Specific Events Guide
The chat widget appears as a small button in the corner of your website. When clicked, it opens a chat interface that communicates with your Gradio app via the JavaScript Client API. Users can ask questions and receive responses directly within the widget.
How does it work?
https://gradio.app/guides/creating-a-website-widget-from-a-gradio-chatbot
Chatbots - Creating A Website Widget From A Gradio Chatbot Guide
* A running Gradio app (local or on Hugging Face Spaces). In this example, we'll use the [Gradio Playground Space](https://huggingface.co/spaces/abidlabs/gradio-playground-bot), which helps generate code for Gradio apps based on natural language descriptions. 1. Create and Style the Chat Widget First, add this HTML a...
Prerequisites
https://gradio.app/guides/creating-a-website-widget-from-a-gradio-chatbot
Chatbots - Creating A Website Widget From A Gradio Chatbot Guide
solid eee; display: flex; } chat-input { flex-grow: 1; padding: 8px; border: 1px solid ddd; border-radius: 4px; margin-right: 8px; } .message { margin: 8px 0; padding: 8px; border-radius: 4px; } .user-message { background: e9ecef; margin-left: 20px; } .bot-message { ...
Prerequisites
https://gradio.app/guides/creating-a-website-widget-from-a-gradio-chatbot
Chatbots - Creating A Website Widget From A Gradio Chatbot Guide
client.predict("/chat", { message: {"text": userMessage, "files": []} }); const message = result.data[0]; console.log(result.data[0]); const botMessage = result.data[0].join('\n'); appendMessage(botMessage, 'bot'); ...
Prerequisites
https://gradio.app/guides/creating-a-website-widget-from-a-gradio-chatbot
Chatbots - Creating A Website Widget From A Gradio Chatbot Guide
%20Recording%202024-12-19%20at%203.32.46%E2%80%AFPM.gif) If you build a website widget from a Gradio app, feel free to share it on X and tag [the Gradio account](https://x.com/Gradio), and we are happy to help you amplify!
Prerequisites
https://gradio.app/guides/creating-a-website-widget-from-a-gradio-chatbot
Chatbots - Creating A Website Widget From A Gradio Chatbot Guide
The Slack bot will listen to messages mentioning it in channels. When it receives a message (which can include text as well as files), it will send it to your Gradio app via Gradio's built-in API. Your bot will reply with the response it receives from the API. Because Gradio's API is very flexible, you can create Sla...
How does it work?
https://gradio.app/guides/creating-a-slack-bot-from-a-gradio-app
Chatbots - Creating A Slack Bot From A Gradio App Guide
* Install the latest version of `gradio` and the `slack-bolt` library: ```bash pip install --upgrade gradio slack-bolt~=1.0 ``` * Have a running Gradio app. This app can be running locally or on Hugging Face Spaces. In this example, we will be using the [Gradio Playground Space](https://huggingface.co/spaces/abidlabs...
Prerequisites
https://gradio.app/guides/creating-a-slack-bot-from-a-gradio-app
Chatbots - Creating A Slack Bot From A Gradio App Guide
eHandler SLACK_BOT_TOKEN = PASTE YOUR SLACK BOT TOKEN HERE SLACK_APP_TOKEN = PASTE YOUR SLACK APP TOKEN HERE app = App(token=SLACK_BOT_TOKEN) @app.event("app_mention") def handle_app_mention_events(body, say): user_id = body["event"]["user"] say(f"Hi <@{user_id}>! You mentioned me and said: {body['event']['t...
Prerequisites
https://gradio.app/guides/creating-a-slack-bot-from-a-gradio-app
Chatbots - Creating A Slack Bot From A Gradio App Guide
= body["authorizations"][0]["user_id"] clean_message = text.replace(f"<@{bot_user_id}>", "").strip() Handle images if present files = [] if "files" in body["event"]: for file in body["event"]["files"]: if file["filetype"] in ["png", "jpg", "jpeg", "gif", "webp"]: ...
Prerequisites
https://gradio.app/guides/creating-a-slack-bot-from-a-gradio-app
Chatbots - Creating A Slack Bot From A Gradio App Guide
/main/gradio-guides/Screen%20Recording%202024-12-19%20at%203.30.00%E2%80%AFPM.gif) If you build a Slack bot from a Gradio app, feel free to share it on X and tag [the Gradio account](https://x.com/Gradio), and we are happy to help you amplify!
Prerequisites
https://gradio.app/guides/creating-a-slack-bot-from-a-gradio-app
Chatbots - Creating A Slack Bot From A Gradio App Guide
The Discord bot will listen to messages mentioning it in channels. When it receives a message (which can include text as well as files), it will send it to your Gradio app via Gradio's built-in API. Your bot will reply with the response it receives from the API. Because Gradio's API is very flexible, you can create D...
How does it work?
https://gradio.app/guides/creating-a-discord-bot-from-a-gradio-app
Chatbots - Creating A Discord Bot From A Gradio App Guide
* Install the latest version of `gradio` and the `discord.py` libraries: ``` pip install --upgrade gradio discord.py~=2.0 ``` * Have a running Gradio app. This app can be running locally or on Hugging Face Spaces. In this example, we will be using the [Gradio Playground Space](https://huggingface.co/spaces/abidlabs/g...
Prerequisites
https://gradio.app/guides/creating-a-discord-bot-from-a-gradio-app
Chatbots - Creating A Discord Bot From A Gradio App Guide
CORD BOT TOKEN HERE client = discord.Client() @client.event async def on_ready(): print(f'{client.user} has connected to Discord!') client.run(TOKEN) ``` Now, run this file: `python bot.py`, which should run and print a message like: ```text We have logged in as GradioPlaygroundBot1451 ``` If that is working,...
Prerequisites
https://gradio.app/guides/creating-a-discord-bot-from-a-gradio-app
Chatbots - Creating A Discord Bot From A Gradio App Guide
.filename.lower().endswith(ext) for ext in ['png', 'jpg', 'jpeg', 'gif', 'webp']): image_path = download_image(attachment) files.append(handle_file(image_path)) break Stream the responses to the channel for response in gradio_client.su...
Prerequisites
https://gradio.app/guides/creating-a-discord-bot-from-a-gradio-app
Chatbots - Creating A Discord Bot From A Gradio App Guide
c example - you can extend it to handle more types of files, add error handling, or integrate with different Gradio apps. ![](https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/gradio-guides/Screen%20Recording%202024-12-18%20at%204.26.55%E2%80%AFPM.gif) If you build a Discord bot from a Gra...
Prerequisites
https://gradio.app/guides/creating-a-discord-bot-from-a-gradio-app
Chatbots - Creating A Discord Bot From A Gradio App Guide
**Important Note**: if you are getting started, we recommend using the `gr.ChatInterface` to create chatbots -- its a high-level abstraction that makes it possible to create beautiful chatbot applications fast, often with a single line of code. [Read more about it here](/guides/creating-a-chatbot-fast). This tutorial ...
Introduction
https://gradio.app/guides/creating-a-custom-chatbot-with-blocks
Chatbots - Creating A Custom Chatbot With Blocks Guide
Let's start with recreating the simple demo above. As you may have noticed, our bot simply randomly responds "How are you?", "Today is a great day", or "I'm very hungry" to any input. Here's the code to create this with Gradio: $code_chatbot_simple There are three Gradio components here: - A `Chatbot`, whose value s...
A Simple Chatbot Demo
https://gradio.app/guides/creating-a-custom-chatbot-with-blocks
Chatbots - Creating A Custom Chatbot With Blocks Guide
There are several ways we can improve the user experience of the chatbot above. First, we can stream responses so the user doesn't have to wait as long for a message to be generated. Second, we can have the user message appear immediately in the chat history, while the chatbot's response is being generated. Here's the ...
Add Streaming to your Chatbot
https://gradio.app/guides/creating-a-custom-chatbot-with-blocks
Chatbots - Creating A Custom Chatbot With Blocks Guide
The `gr.Chatbot` component supports a subset of markdown including bold, italics, and code. For example, we could write a function that responds to a user's message, with a bold **That's cool!**, like this: ```py def bot(history): response = {"role": "assistant", "content": "**That's cool!**"} history.append(r...
Adding Markdown, Images, Audio, or Videos
https://gradio.app/guides/creating-a-custom-chatbot-with-blocks
Chatbots - Creating A Custom Chatbot With Blocks Guide
ggingface.co/spaces/gradio/chatbot_streaming): A streaming chatbot demo built with `gr.Chatbot` and Blocks. - [gradio/chatbot_examples](https://huggingface.co/spaces/gradio/chatbot_examples): A chatbot that presents new visitors with a list of multimodal examples they can use to start the conversation.
Adding Markdown, Images, Audio, or Videos
https://gradio.app/guides/creating-a-custom-chatbot-with-blocks
Chatbots - Creating A Custom Chatbot With Blocks Guide
Just like the classic Magic 8 Ball, a user should ask it a question orally and then wait for a response. Under the hood, we'll use Whisper to transcribe the audio and then use an LLM to generate a magic-8-ball-style answer. Finally, we'll use Parler TTS to read the response aloud.
The Overview
https://gradio.app/guides/streaming-ai-generated-audio
Streaming - Streaming Ai Generated Audio Guide
First let's define the UI and put placeholders for all the python logic. ```python import gradio as gr with gr.Blocks() as block: gr.HTML( f""" <h1 style='text-align: center;'> Magic 8 Ball 🎱 </h1> <h3 style='text-align: center;'> Ask a question and receive wisdom </h3> <p style='...
The UI
https://gradio.app/guides/streaming-ai-generated-audio
Streaming - Streaming Ai Generated Audio Guide
GPU](https://huggingface.co/zero-gpu-explorers) which has time-based quotas. Since generating the response can be done with Hugging Face's Inference API, we shouldn't include that code in our GPU function as it will needlessly use our GPU quota.
The UI
https://gradio.app/guides/streaming-ai-generated-audio
Streaming - Streaming Ai Generated Audio Guide
As mentioned above, we'll use [Hugging Face's Inference API](https://huggingface.co/docs/huggingface_hub/guides/inference) to transcribe the audio and generate a response from an LLM. After instantiating the client, I use the `automatic_speech_recognition` method (this automatically uses Whisper running on Hugging Face...
The Logic
https://gradio.app/guides/streaming-ai-generated-audio
Streaming - Streaming Ai Generated Audio Guide
for you but are you ready for the dog?'")}, {"role": "user", "content": f"Magic 8 Ball please answer this question - {question}"}] response = client.chat_completion(messages, max_tokens=64, seed=random.randint(1, 5000), model="mistralai/Mistral-7B-Instruct...
The Logic
https://gradio.app/guides/streaming-ai-generated-audio
Streaming - Streaming Ai Generated Audio Guide
sage=True ).to(device) tokenizer = AutoTokenizer.from_pretrained(repo_id) feature_extractor = AutoFeatureExtractor.from_pretrained(repo_id) sampling_rate = model.audio_encoder.config.sampling_rate frame_rate = model.audio_encoder.config.frame_rate @spaces.GPU def read_response(answer): play_steps_in_s = 2.0 ...
The Logic
https://gradio.app/guides/streaming-ai-generated-audio
Streaming - Streaming Ai Generated Audio Guide
You can see our final application [here](https://huggingface.co/spaces/gradio/magic-8-ball)!
Conclusion
https://gradio.app/guides/streaming-ai-generated-audio
Streaming - Streaming Ai Generated Audio 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
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
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
The next generation of AI user interfaces is moving towards audio-native experiences. Users will be able to speak to chatbots and receive spoken responses in return. Several models have been built under this paradigm, including GPT-4o and [mini omni](https://github.com/gpt-omni/mini-omni). In this guide, we'll walk yo...
Introduction
https://gradio.app/guides/conversational-chatbot
Streaming - Conversational Chatbot Guide
Our application will enable the following user experience: 1. Users click a button to start recording their message 2. The app detects when the user has finished speaking and stops recording 3. The user's audio is passed to the omni model, which streams back a response 4. After omni mini finishes speaking, the user's ...
Application Overview
https://gradio.app/guides/conversational-chatbot
Streaming - Conversational Chatbot Guide
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
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
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 tells Gradio that a component being created in a render function corresponds to the same logical component as in the previous render. This allows Gradio to reuse the existing browser element instead of destroying and recreating it on every render. It also preserves the user's entered value across r...
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
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
https://gradio.app/guides/custom-HTML-components
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
https://gradio.app/guides/custom-HTML-components
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
https://gradio.app/guides/custom-HTML-components
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`
https://gradio.app/guides/custom-HTML-components
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
https://gradio.app/guides/custom-HTML-components
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
https://gradio.app/guides/custom-HTML-components
Building With Blocks - Custom Html Components 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
Use `inputs_kwargs` when a component value should be passed to an event function by parameter name instead of by position. This is especially useful when calling an existing function with keyword-only parameters: the function can be connected directly without writing a wrapper just to rearrange its arguments. $code_ke...
Passing Inputs by Parameter Name
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