# Using the ElevenLabs API for text to speech streaming?
**URL:**
**Author:**  [@ethantan](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Fu%2Fethantan)%5C
**Post date:** [March 8, 2023, 2:10pm UTC](/static-proxy?url=https%3A%2F%2Fdiscuss.huggingface.co%2Ft%2Fusing-the-elevenlabs-api-for-text-to-speech-streaming%2F33346%2F1 "2023-03-08T14:10:16Z")
Hello how can I use the ElevenLabs API for realtime text-to-speech streaming output with Gradio please?
[https://api.elevenlabs.io/docs#/text-to-speech/Text\_to\_speech\_v1\_text\_to\_speech\_\_voice\_id\_\_stream\_post](https://api.elevenlabs.io/docs#/text-to-speech/Text_to_speech_v1_text_to_speech __voice_id__ stream_post)
Many thanks
---
Hi @ethantan !
This gradio demo uses a different streaming api but I imagine you can adept it to your use case.
> **[Gradio Demo Streaming - a Hugging Face Space by ysharma](https://huggingface.co/spaces/ysharma/Gradio-demo-streaming)**
>
> Discover amazing ML apps made by the community
Cc @ysharma
---
```auto
import gradio as gr
import librosa
import pyaudio
import numpy as np
import requests
import tempfile
import os
import io
from io import BytesIO
import base64
from faster_whisper import WhisperModel
model_size = "large-v2"
# Run on GPU with FP16
model = WhisperModel(model_size, device="cuda", compute_type="float16")
def main():
with gr.Blocks(theme=gr.themes.Soft(primary_hue='orange',
secondary_hue='orange', neutral_hue='stone')) as app:
def text_to_speech(text):
url = f"https://api.elevenlabs.io/v1/text-to-speech/YOUR_VOICE"
headers = {
"accept": "audio/mpeg",
"xi-api-key": "API_KEY",
"Content-Type": "application/json",
}
data = {"text": text}
response = requests.post(url, headers = headers, json=data)
if response.status_code == 200:
print(response.status_code)
return response.content
else:
print(f"Error: {response.status_code}")
return None
def on_click_play_audio_button(text):
#text = response2
print(text)
audio_content = text_to_speech(text)
if audio_content is not None:
# with open("output_audio.mp3", "wb") as audio_file:
# audio_file.write(audio_content)
audio_bytes = BytesIO(audio_content)
audio_bytes.seek(0)
audio_base_64 = base64.b64encode(audio_bytes.read()).decode("utf-8")
audio_player = f''
return audio_player
with gr.Row():
with gr.Column(scale=3):
query = gr.Textbox(label='Query', lines=1, placeholder="Ask a question to the dataset...")
gr.Textbox.style(query, show_copy_button=True)
with gr.Column(scale=.1, min_width=200):
audio = gr.Audio(source="microphone", type="filepath", label="Audio")
def get_audio(audio):
if audio != None:
segments, _ = model.transcribe(audio)
text = []
for segment in segments:
text.append(segment.text)
text = ' '.join(text)
return text
else:
return None
html = gr.HTML()
audio.change(get_audio, audio, query).then(on_click_play_audio_button, inputs=[query], outputs=[html])
app.launch(share=True, width=1600, height=800)
if __name__ == " __main__":
main()
```
This code generates text from your speech and convert it back to an ElevenLab audio.
You can modify it slightly so that it works with chatbot conversations!
Change the url link and API and it should work once you install all dependencies!