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import asyncio
from websockets import connect, Data, ClientConnection
import json
import numpy as np
import base64
import soundfile as sf
import io
from pydub import AudioSegment
import os
# Load OpenAI API key
from dotenv import load_dotenv
load_dotenv()
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
if not OPENAI_API_KEY:
raise ValueError("OPENAI_API_KEY must be set in environment")
WEBSOCKET_URI = "wss://api.openai.com/v1/realtime?intent=transcription"
WEBSOCKET_HEADERS = {
"Authorization": f"Bearer {OPENAI_API_KEY}",
"OpenAI-Beta": "realtime=v1"
}
# Shared client registry
connections = {}
class WebSocketClient:
def __init__(self, uri: str, headers: dict, client_id: str):
self.uri = uri
self.headers = headers
self.websocket: ClientConnection = None
self.queue = asyncio.Queue(maxsize=10)
self.loop = None
self.client_id = client_id
self.transcript = ""
async def connect(self):
try:
self.websocket = await connect(self.uri, additional_headers=self.headers)
print(f"✅ Connected to OpenAI WebSocket")
# Send transcription session settings
with open("openai_transcription_settings.json", "r") as f:
settings = f.read()
await self.websocket.send(settings)
await asyncio.gather(self.receive_messages(), self.send_audio_chunks())
except Exception as e:
print(f"❌ WebSocket Error: {e}")
def run(self):
self.loop = asyncio.new_event_loop()
asyncio.set_event_loop(self.loop)
self.loop.run_until_complete(self.connect())
def process_websocket_message(self, message: Data):
try:
message_object = json.loads(message)
if message_object["type"] == "conversation.item.input_audio_transcription.delta":
delta = message_object["delta"]
self.transcript += delta
elif message_object["type"] == "conversation.item.input_audio_transcription.completed":
self.transcript += ' ' if self.transcript and self.transcript[-1] != ' ' else ''
except Exception as e:
print(f"⚠️ Error processing message: {e}")
async def send_audio_chunks(self):
while True:
sample_rate, audio_array = await self.queue.get()
if self.websocket:
if audio_array.ndim > 1:
audio_array = audio_array.mean(axis=1)
audio_array = audio_array.astype(np.float32)
audio_array /= np.max(np.abs(audio_array)) if np.max(np.abs(audio_array)) > 0 else 1.0
int_audio = (audio_array * 32767).astype(np.int16)
buffer = io.BytesIO()
sf.write(buffer, int_audio, sample_rate, format="WAV", subtype="PCM_16")
buffer.seek(0)
audio_segment = AudioSegment.from_file(buffer, format="wav")
resampled = audio_segment.set_frame_rate(24000)
out_buf = io.BytesIO()
resampled.export(out_buf, format="wav")
out_buf.seek(0)
b64_audio = base64.b64encode(out_buf.read()).decode("utf-8")
await self.websocket.send(json.dumps({
"type": "input_audio_buffer.append",
"audio": b64_audio
}))
async def receive_messages(self):
async for message in self.websocket:
self.process_websocket_message(message)
def enqueue_audio_chunk(self, sample_rate: int, chunk_array: np.ndarray):
if not self.queue.full():
asyncio.run_coroutine_threadsafe(self.queue.put((sample_rate, chunk_array)), self.loop)
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