base on The python library for real-time communication <div style='text-align: center; margin-bottom: 1rem; display: flex; justify-content: center; align-items: center;'> <h1 style='color: white; margin: 0;'>FastRTC</h1> <img src='https://huggingface.co/datasets/freddyaboulton/bucket/resolve/main/fastrtc_logo_small.png' alt="FastRTC Logo" style="margin-right: 10px;"> </div> <div style="display: flex; flex-direction: row; justify-content: center"> <img style="display: block; padding-right: 5px; height: 20px;" alt="Static Badge" src="https://img.shields.io/pypi/v/fastrtc"> <a href="https://github.com/gradio-app/fastrtc" target="_blank"><img alt="Static Badge" src="https://img.shields.io/badge/github-white?logo=github&logoColor=black"></a> </div> <h3 style='text-align: center'> The Real-Time Communication Library for Python. </h3> Turn any python function into a real-time audio and video stream over WebRTC or WebSockets. ## Installation ```bash pip install fastrtc ``` to use built-in pause detection (see [ReplyOnPause](https://fastrtc.org/userguide/audio/#reply-on-pause)), and text to speech (see [Text To Speech](https://fastrtc.org/userguide/audio/#text-to-speech)), install the `vad` and `tts` extras: ```bash pip install "fastrtc[vad, tts]" ``` ## Key Features - 🗣️ Automatic Voice Detection and Turn Taking built-in, only worry about the logic for responding to the user. - 💻 Automatic UI - Use the `.ui.launch()` method to launch the webRTC-enabled built-in Gradio UI. - 🔌 Automatic WebRTC Support - Use the `.mount(app)` method to mount the stream on a FastAPI app and get a webRTC endpoint for your own frontend! - ⚡️ Websocket Support - Use the `.mount(app)` method to mount the stream on a FastAPI app and get a websocket endpoint for your own frontend! - 📞 Automatic Telephone Support - Use the `fastphone()` method of the stream to launch the application and get a free temporary phone number! - 🤖 Completely customizable backend - A `Stream` can easily be mounted on a FastAPI app so you can easily extend it to fit your production application. See the [Talk To Claude](https://huggingface.co/spaces/fastrtc/talk-to-claude) demo for an example of how to serve a custom JS frontend. ## Docs [https://fastrtc.org](https://fastrtc.org) ## Examples See the [Cookbook](https://fastrtc.org/cookbook/) for examples of how to use the library. <table> <tr> <td width="50%"> <h3>🗣️👀 Gemini Audio Video Chat</h3> <p>Stream BOTH your webcam video and audio feeds to Google Gemini. You can also upload images to augment your conversation!</p> <video width="100%" src="https://github.com/user-attachments/assets/9636dc97-4fee-46bb-abb8-b92e69c08c71" controls></video> <p> <a href="https://huggingface.co/spaces/freddyaboulton/gemini-audio-video-chat">Demo</a> | <a href="https://huggingface.co/spaces/freddyaboulton/gemini-audio-video-chat/blob/main/app.py">Code</a> </p> </td> <td width="50%"> <h3>🗣️ Google Gemini Real Time Voice API</h3> <p>Talk to Gemini in real time using Google's voice API.</p> <video width="100%" src="https://github.com/user-attachments/assets/ea6d18cb-8589-422b-9bba-56332d9f61de" controls></video> <p> <a href="https://huggingface.co/spaces/fastrtc/talk-to-gemini">Demo</a> | <a href="https://huggingface.co/spaces/fastrtc/talk-to-gemini/blob/main/app.py">Code</a> </p> </td> </tr> <tr> <td width="50%"> <h3>🗣️ OpenAI Real Time Voice API</h3> <p>Talk to ChatGPT in real time using OpenAI's voice API.</p> <video width="100%" src="https://github.com/user-attachments/assets/178bdadc-f17b-461a-8d26-e915c632ff80" controls></video> <p> <a href="https://huggingface.co/spaces/fastrtc/talk-to-openai">Demo</a> | <a href="https://huggingface.co/spaces/fastrtc/talk-to-openai/blob/main/app.py">Code</a> </p> </td> <td width="50%"> <h3>🤖 Hello Computer</h3> <p>Say computer before asking your question!</p> <video width="100%" src="https://github.com/user-attachments/assets/afb2a3ef-c1ab-4cfb-872d-578f895a10d5" controls></video> <p> <a href="https://huggingface.co/spaces/fastrtc/hello-computer">Demo</a> | <a href="https://huggingface.co/spaces/fastrtc/hello-computer/blob/main/app.py">Code</a> </p> </td> </tr> <tr> <td width="50%"> <h3>🤖 Llama Code Editor</h3> <p>Create and edit HTML pages with just your voice! Powered by SambaNova systems.</p> <video width="100%" src="https://github.com/user-attachments/assets/98523cf3-dac8-4127-9649-d91a997e3ef5" controls></video> <p> <a href="https://huggingface.co/spaces/fastrtc/llama-code-editor">Demo</a> | <a href="https://huggingface.co/spaces/fastrtc/llama-code-editor/blob/main/app.py">Code</a> </p> </td> <td width="50%"> <h3>🗣️ Talk to Claude</h3> <p>Use the Anthropic and Play.Ht APIs to have an audio conversation with Claude.</p> <video width="100%" src="https://github.com/user-attachments/assets/fb6ef07f-3ccd-444a-997b-9bc9bdc035d3" controls></video> <p> <a href="https://huggingface.co/spaces/fastrtc/talk-to-claude">Demo</a> | <a href="https://huggingface.co/spaces/fastrtc/talk-to-claude/blob/main/app.py">Code</a> </p> </td> </tr> <tr> <td width="50%"> <h3>🎵 Whisper Transcription</h3> <p>Have whisper transcribe your speech in real time!</p> <video width="100%" src="https://github.com/user-attachments/assets/87603053-acdc-4c8a-810f-f618c49caafb" controls></video> <p> <a href="https://huggingface.co/spaces/fastrtc/whisper-realtime">Demo</a> | <a href="https://huggingface.co/spaces/fastrtc/whisper-realtime/blob/main/app.py">Code</a> </p> </td> <td width="50%"> <h3>📷 Yolov10 Object Detection</h3> <p>Run the Yolov10 model on a user webcam stream in real time!</p> <video width="100%" src="https://github.com/user-attachments/assets/f82feb74-a071-4e81-9110-a01989447ceb" controls></video> <p> <a href="https://huggingface.co/spaces/fastrtc/object-detection">Demo</a> | <a href="https://huggingface.co/spaces/fastrtc/object-detection/blob/main/app.py">Code</a> </p> </td> </tr> <tr> <td width="50%"> <h3>🗣️ Kyutai Moshi</h3> <p>Kyutai's moshi is a novel speech-to-speech model for modeling human conversations.</p> <video width="100%" src="https://github.com/user-attachments/assets/becc7a13-9e89-4a19-9df2-5fb1467a0137" controls></video> <p> <a href="https://huggingface.co/spaces/freddyaboulton/talk-to-moshi">Demo</a> | <a href="https://huggingface.co/spaces/freddyaboulton/talk-to-moshi/blob/main/app.py">Code</a> </p> </td> <td width="50%"> <h3>🗣️ Hello Llama: Stop Word Detection</h3> <p>A code editor built with Llama 3.3 70b that is triggered by the phrase "Hello Llama". Build a Siri-like coding assistant in 100 lines of code!</p> <video width="100%" src="https://github.com/user-attachments/assets/3e10cb15-ff1b-4b17-b141-ff0ad852e613" controls></video> <p> <a href="https://huggingface.co/spaces/freddyaboulton/hey-llama-code-editor">Demo</a> | <a href="https://huggingface.co/spaces/freddyaboulton/hey-llama-code-editor/blob/main/app.py">Code</a> </p> </td> </tr> </table> ## Usage This is a shortened version of the official [usage guide](https://freddyaboulton.github.io/gradio-webrtc/user-guide/). - `.ui.launch()`: Launch a built-in UI for easily testing and sharing your stream. Built with [Gradio](https://www.gradio.app/). - `.fastphone()`: Get a free temporary phone number to call into your stream. Hugging Face token required. - `.mount(app)`: Mount the stream on a [FastAPI](https://fastapi.tiangolo.com/) app. Perfect for integrating with your already existing production system. ## Quickstart ### Echo Audio ```python from fastrtc import Stream, ReplyOnPause import numpy as np def echo(audio: tuple[int, np.ndarray]): # The function will be passed the audio until the user pauses # Implement any iterator that yields audio # See "LLM Voice Chat" for a more complete example yield audio stream = Stream( handler=ReplyOnPause(echo), modality="audio", mode="send-receive", ) ``` ### LLM Voice Chat ```py from fastrtc import ( ReplyOnPause, AdditionalOutputs, Stream, audio_to_bytes, aggregate_bytes_to_16bit ) import gradio as gr from groq import Groq import anthropic from elevenlabs import ElevenLabs groq_client = Groq() claude_client = anthropic.Anthropic() tts_client = ElevenLabs() # See "Talk to Claude" in Cookbook for an example of how to keep # track of the chat history. def response( audio: tuple[int, np.ndarray], ): prompt = groq_client.audio.transcriptions.create( file=("audio-file.mp3", audio_to_bytes(audio)), model="whisper-large-v3-turbo", response_format="verbose_json", ).text response = claude_client.messages.create( model="claude-3-5-haiku-20241022", max_tokens=512, messages=[{"role": "user", "content": prompt}], ) response_text = " ".join( block.text for block in response.content if getattr(block, "type", None) == "text" ) iterator = tts_client.text_to_speech.convert_as_stream( text=response_text, voice_id="JBFqnCBsd6RMkjVDRZzb", model_id="eleven_multilingual_v2", output_format="pcm_24000" ) for chunk in aggregate_bytes_to_16bit(iterator): audio_array = np.frombuffer(chunk, dtype=np.int16).reshape(1, -1) yield (24000, audio_array) stream = Stream( modality="audio", mode="send-receive", handler=ReplyOnPause(response), ) ``` ### Webcam Stream ```python from fastrtc import Stream import numpy as np def flip_vertically(image): return np.flip(image, axis=0) stream = Stream( handler=flip_vertically, modality="video", mode="send-receive", ) ``` ### Object Detection ```python from fastrtc import Stream import gradio as gr import cv2 from huggingface_hub import hf_hub_download from .inference import YOLOv10 model_file = hf_hub_download( repo_id="onnx-community/yolov10n", filename="onnx/model.onnx" ) # git clone https://huggingface.co/spaces/fastrtc/object-detection # for YOLOv10 implementation model = YOLOv10(model_file) def detection(image, conf_threshold=0.3): image = cv2.resize(image, (model.input_width, model.input_height)) new_image = model.detect_objects(image, conf_threshold) return cv2.resize(new_image, (500, 500)) stream = Stream( handler=detection, modality="video", mode="send-receive", additional_inputs=[ gr.Slider(minimum=0, maximum=1, step=0.01, value=0.3) ] ) ``` ## Running the Stream Run: ### Gradio ```py stream.ui.launch() ``` ### Telephone (Audio Only) ```py stream.fastphone() ``` ### FastAPI ```py app = FastAPI() stream.mount(app) # Optional: Add routes @app.get("/") async def _(): return HTMLResponse(content=open("index.html").read()) # uvicorn app:app --host 0.0.0.0 --port 8000 ``` ", Assign "at most 3 tags" to the expected json: {"id":"13039","tags":[]} "only from the tags list I provide: []" returns me the "expected json"