mirror of
https://github.com/HumanAIGC-Engineering/gradio-webrtc.git
synced 2026-02-05 18:09:23 +08:00
218 lines
6.3 KiB
Python
218 lines
6.3 KiB
Python
import asyncio
|
|
import base64
|
|
import json
|
|
import os
|
|
import secrets
|
|
from pathlib import Path
|
|
|
|
import gradio as gr
|
|
import numpy as np
|
|
from dotenv import load_dotenv
|
|
from fastapi import FastAPI, Request
|
|
from fastapi.responses import HTMLResponse
|
|
from fastrtc import (
|
|
AdditionalOutputs,
|
|
AsyncStreamHandler,
|
|
Stream,
|
|
get_cloudflare_turn_credentials_async,
|
|
wait_for_item,
|
|
)
|
|
from websockets.asyncio.client import connect
|
|
|
|
load_dotenv()
|
|
|
|
cur_dir = Path(__file__).parent
|
|
|
|
API_KEY = os.getenv("MODELSCOPE_API_KEY", "")
|
|
API_URL = "wss://dashscope.aliyuncs.com/api-ws/v1/realtime?model=qwen-omni-turbo-realtime-2025-03-26"
|
|
VOICES = ["Chelsie", "Serena", "Ethan", "Cherry"]
|
|
headers = {"Authorization": "Bearer " + API_KEY}
|
|
|
|
|
|
class QwenOmniHandler(AsyncStreamHandler):
|
|
def __init__(
|
|
self,
|
|
) -> None:
|
|
super().__init__(
|
|
expected_layout="mono",
|
|
output_sample_rate=24_000,
|
|
input_sample_rate=16_000,
|
|
)
|
|
self.connection = None
|
|
self.output_queue = asyncio.Queue()
|
|
|
|
def copy(self):
|
|
return QwenOmniHandler()
|
|
|
|
@staticmethod
|
|
def msg_id() -> str:
|
|
return f"event_{secrets.token_hex(10)}"
|
|
|
|
async def start_up(
|
|
self,
|
|
):
|
|
"""Connect to realtime API. Run forever in separate thread to keep connection open."""
|
|
voice_id = "Serena"
|
|
print("voice_id", voice_id)
|
|
async with connect(
|
|
API_URL,
|
|
additional_headers=headers,
|
|
) as conn:
|
|
self.client = conn
|
|
await conn.send(
|
|
json.dumps(
|
|
{
|
|
"event_id": self.msg_id(),
|
|
"type": "session.update",
|
|
"session": {
|
|
"modalities": [
|
|
"text",
|
|
"audio",
|
|
],
|
|
"voice": voice_id,
|
|
"input_audio_format": "pcm16",
|
|
},
|
|
}
|
|
)
|
|
)
|
|
self.connection = conn
|
|
try:
|
|
async for data in self.connection:
|
|
event = json.loads(data)
|
|
print("event", event["type"])
|
|
if "type" not in event:
|
|
continue
|
|
# Handle interruptions
|
|
if event["type"] == "input_audio_buffer.speech_started":
|
|
self.clear_queue()
|
|
if event["type"] == "response.audio.delta":
|
|
print("putting output")
|
|
await self.output_queue.put(
|
|
(
|
|
self.output_sample_rate,
|
|
np.frombuffer(
|
|
base64.b64decode(event["delta"]), dtype=np.int16
|
|
).reshape(1, -1),
|
|
),
|
|
)
|
|
except Exception as e:
|
|
print("error", e)
|
|
|
|
async def receive(self, frame: tuple[int, np.ndarray]) -> None:
|
|
if not self.connection:
|
|
return
|
|
_, array = frame
|
|
array = array.squeeze()
|
|
audio_message = base64.b64encode(array.tobytes()).decode("utf-8")
|
|
try:
|
|
await self.connection.send(
|
|
json.dumps(
|
|
{
|
|
"event_id": self.msg_id(),
|
|
"type": "input_audio_buffer.append",
|
|
"audio": audio_message,
|
|
}
|
|
)
|
|
)
|
|
except Exception as e:
|
|
print("error", e)
|
|
|
|
async def emit(self) -> tuple[int, np.ndarray] | AdditionalOutputs | None:
|
|
return await wait_for_item(self.output_queue)
|
|
|
|
async def shutdown(self) -> None:
|
|
if self.connection:
|
|
await self.connection.close()
|
|
self.connection = None
|
|
|
|
|
|
voice = gr.Dropdown(choices=VOICES, value=VOICES[0], type="value", label="Voice")
|
|
stream = Stream(
|
|
QwenOmniHandler(),
|
|
mode="send-receive",
|
|
modality="audio",
|
|
additional_inputs=[voice],
|
|
additional_outputs=None,
|
|
rtc_configuration=get_cloudflare_turn_credentials_async,
|
|
concurrency_limit=20,
|
|
time_limit=180,
|
|
)
|
|
|
|
app = FastAPI()
|
|
|
|
|
|
@app.post("/telephone/incoming")
|
|
async def handle_incoming_call(request: Request):
|
|
"""
|
|
Handle incoming telephone calls (e.g., via Twilio).
|
|
|
|
Generates TwiML instructions to connect the incoming call to the
|
|
WebSocket handler (`/telephone/handler`) for audio streaming.
|
|
|
|
Args:
|
|
request: The FastAPI Request object for the incoming call webhook.
|
|
|
|
Returns:
|
|
An HTMLResponse containing the TwiML instructions as XML.
|
|
"""
|
|
from twilio.twiml.voice_response import Connect, VoiceResponse
|
|
|
|
if len(stream.connections) > (stream.concurrency_limit or 20):
|
|
response = VoiceResponse()
|
|
response.say("Qwen is busy please try again later!")
|
|
return HTMLResponse(content=str(response), media_type="application/xml")
|
|
|
|
response = VoiceResponse()
|
|
response.say("Connecting to Qwen")
|
|
connect = Connect()
|
|
print("request.url.hostname", request.url.hostname)
|
|
connect.stream(url=f"wss://{request.url.hostname}/telephone/handler")
|
|
response.append(connect)
|
|
response.say("The call has been disconnected.")
|
|
return HTMLResponse(content=str(response), media_type="application/xml")
|
|
|
|
|
|
stream.mount(app)
|
|
|
|
|
|
@app.get("/")
|
|
async def _():
|
|
html_content = """
|
|
<!DOCTYPE html>
|
|
<html>
|
|
<head>
|
|
<title>Qwen Phone Chat</title>
|
|
<style>
|
|
body {
|
|
font-family: Arial, sans-serif;
|
|
max-width: 800px;
|
|
margin: 0 auto;
|
|
padding: 20px;
|
|
line-height: 1.6;
|
|
}
|
|
pre {
|
|
background-color: #f5f5f5;
|
|
padding: 15px;
|
|
border-radius: 5px;
|
|
overflow-x: auto;
|
|
}
|
|
h1 {
|
|
color: #333;
|
|
}
|
|
</style>
|
|
</head>
|
|
<body>
|
|
<h1>Qwen Phone Chat</h1>
|
|
<p>Call +1 (877) 853-7936</p>
|
|
</body>
|
|
</html>
|
|
"""
|
|
return HTMLResponse(content=html_content)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
# stream.fastphone(host="0.0.0.0", port=7860)
|
|
import uvicorn
|
|
|
|
uvicorn.run(app, host="0.0.0.0", port=7860)
|