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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) | |