diff --git a/fern/docs.yml b/fern/docs.yml
index 196de1eb..30d4ed17 100644
--- a/fern/docs.yml
+++ b/fern/docs.yml
@@ -76,6 +76,8 @@ navigation:
                     path: docs/pages/cookbooks/legacy/text-to-speech/streaming.mdx
                   - page: WebSockets
                     path: docs/pages/cookbooks/legacy/text-to-speech/websockets.mdx
+                  - page: WebRTC
+                    path: docs/pages/cookbooks/legacy/text-to-speech/webrtc.mdx
                   - page: Request stitching
                     path: docs/pages/cookbooks/legacy/text-to-speech/request-stitching.mdx
                   - page: Pronunciation dictionaries
diff --git a/fern/docs/pages/cookbooks/legacy/text-to-speech/webrtc.mdx b/fern/docs/pages/cookbooks/legacy/text-to-speech/webrtc.mdx
new file mode 100644
index 00000000..df0507f1
--- /dev/null
+++ b/fern/docs/pages/cookbooks/legacy/text-to-speech/webrtc.mdx
@@ -0,0 +1,125 @@
+---
+title: Real-time audio streaming with WebRTC
+subtitle: Learn how to convert text to speech via a WebRTC connection.
+---
+
+## Introduction
+
+WebRTC is a technology that enables real-time communication between web browsers and servers. It allows for low-latency, high-quality audio and video communication, and is supported by most modern browsers.
+
+In this guide, we'll build a simple WebRTC application entirely in Python.
+Our application will continuously listen for incoming audio from a microphone and then repeat the audio back to the user in a different voice.
+We'll use the `fastrtc` library to handle the WebRTC connection and the `elevenlabs` library to handle the speech-to-text and text-to-speech conversion.
+
+This is a preview of what we'll build:
+
+<video
+  controls
+  className="w-full"
+  src="https://github.com/user-attachments/assets/149bcda7-7381-4a15-bc63-e7c244e61f75"
+></video>
+
+## Setup
+
+Install the required packages to manage environmental variables and handle the WebRTC connection:
+
+```bash
+pip install python-dotenv
+pip install fastrtc[vad]
+pip install elevenlabs
+```
+
+Next, create a `.env` file in your project directory and add your API key:
+
+```bash .env
+ELEVENLABS_API_KEY=your_elevenlabs_api_key_here
+```
+
+Create a new file named `webrtc-streaming.py` for our code.
+
+## Initialize the client
+
+First, let's initialize the ElevenLabs client with the API key from the `.env` file:
+
+```python
+import os
+from dotenv import load_dotenv
+from elevenlabs import ElevenLabs
+
+load_dotenv()
+
+elevenlabs_client = ElevenLabs(api_key=os.getenv("ELEVENLABS_API_KEY"))
+```
+
+## Define the Echo function
+
+The `echo` function will take as input the user's audio and the desired voice ID.
+It will then convert the incoming audio to text and then to speech with the ElevenLabs client.
+
+```python
+import numpy as np
+from numpy.typing import NDArray
+from fastrtc import audio_to_bytes
+
+def echo(audio: tuple[int, NDArray[np.int16]], voice_id: str):
+    transcription = elevenlabs_client.speech_to_text.convert(
+        file=audio_to_bytes(audio),
+        model_id="scribe_v1",
+        tag_audio_events=True,
+        language_code="eng",
+    )
+    for chunk in elevenlabs_client.text_to_speech.convert_as_stream(
+        text=transcription.text,  # type: ignore
+        voice_id=voice_id,
+        model_id="eleven_multilingual_v2",
+        output_format="pcm_24000",
+    ):
+        audio_array = np.frombuffer(chunk, dtype=np.int16).reshape(1, -1)
+        yield (24000, audio_array)
+```
+
+## Define the FastRTC Application
+
+Now we'll create a FastRTC `Stream` object to turn our echo function into a WebRTC stream. We'll wrap the `echo` function with `ReplyOnPause` to handle turn-taking and voice activity detection. We'll also add a dropdown to let users select different voices:
+
+```python
+import gradio as gr
+from fastrtc import ReplyOnPause, Stream
+
+stream = Stream(
+    ReplyOnPause(echo),
+    modality="audio",
+    mode="send-receive",
+    additional_inputs=[
+        gr.Dropdown(
+            value="Xb7hH8MSUJpSbSDYk0k2",
+            choices=[
+                ("Alice", "Xb7hH8MSUJpSbSDYk0k2"),
+                ("Aria", "9BWtsMINqrJLrRacOk9x"),
+                ("Bill", "pqHfZKP75CvOlQylNhV4"),
+                ("Brian", "nPczCjzI2devNBz1zQrb"),
+            ]
+        )
+    ],
+    ui_args={
+        "title": "Echo Audio with ElevenLabs",
+        "subtitle": "Choose a voice and speak naturally. The model will echo it back in a different voice.",
+    },
+)
+
+stream.ui.launch()
+```
+
+## Run the application
+
+```bash
+python webrtc-streaming.py
+```
+
+You can see the full code [here](https://gist.github.com/freddyaboulton/2a50928337b177205264112531d7552c)
+
+## Conclusion
+
+You've now implemented a WebRTC streaming application in just 50 lines of Python! This example demonstrates how to create a real-time audio processing pipeline that leverages ElevenLabs' speech-to-text and text-to-speech capabilities.
+
+For more information on customizing your WebRTC application, check out the [fastrtc documentation](https://fastrtc.org).