Update README.md

README.md

@@ -50,278 +50,3 @@ pip install fastrtc[vad, tts]
 ## Docs
 
 [https://fastrtc.org](https://fastrtc.org)
-
-## Examples
-See the [Cookbook](https://fastrtc.org/pr-preview/pr-60/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 an 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(detection),
-    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
-```