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import gradio as gr
import asyncio
from websockets import connect, Data, ClientConnection
from dotenv import load_dotenv
import json
import os
import threading
import numpy as np
import base64
import soundfile as sf
import io
from pydub import AudioSegment
import time
import uuid
class LogColors:
OK = '\033[94m'
SUCCESS = '\033[92m'
WARNING = '\033[93m'
ERROR = '\033[91m'
ENDC = '\033[0m'
load_dotenv()
OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY")
if not OPENAI_API_KEY:
raise ValueError("OPENAI_API_KEY environment variable must be set")
WEBSOCKET_URI = "wss://api.openai.com/v1/realtime?intent=transcription"
WEBSOCKET_HEADERS = {
"Authorization": "Bearer " + OPENAI_API_KEY,
"OpenAI-Beta": "realtime=v1"
}
transcription = ""
css = """
"""
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
async def connect(self):
try:
self.websocket = await connect(self.uri, additional_headers=self.headers)
print(f"{LogColors.SUCCESS}Connected to OpenAI WebSocket{LogColors.ENDC}\n")
# Send session settings to OpenAI
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"{LogColors.ERROR}WebSocket Connection Error: {e}{LogColors.ENDC}")
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):
global transcription
message_object = json.loads(message)
if message_object["type"] != "error":
print(f"{LogColors.OK}Received message: {LogColors.ENDC} {message}")
if message_object["type"] == "conversation.item.input_audio_transcription.delta":
delta = message_object["delta"]
transcription += delta
elif message_object["type"] == "conversation.item.input_audio_transcription.completed":
transcription += ' ' if len(transcription) and transcription[-1] != ' ' else ''
else:
print(f"{LogColors.ERROR}Error: {message}{LogColors.ENDC}")
async def send_audio_chunks(self):
while True:
audio_data = await self.queue.get()
sample_rate, audio_array = audio_data
if self.websocket:
# Convert to mono if stereo
if audio_array.ndim > 1:
audio_array = audio_array.mean(axis=1)
# Convert to float32 and normalize
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
# Convert to 16-bit PCM
audio_array_int16 = (audio_array * 32767).astype(np.int16)
audio_buffer = io.BytesIO()
sf.write(audio_buffer, audio_array_int16, sample_rate, format='WAV', subtype='PCM_16')
audio_buffer.seek(0)
audio_segment = AudioSegment.from_file(audio_buffer, format="wav")
resampled_audio = audio_segment.set_frame_rate(24000)
output_buffer = io.BytesIO()
resampled_audio.export(output_buffer, format="wav")
output_buffer.seek(0)
base64_audio = base64.b64encode(output_buffer.read()).decode("utf-8")
await self.websocket.send(json.dumps({"type": "input_audio_buffer.append", "audio": base64_audio}))
print(f"{LogColors.OK}Sent audio chunk{LogColors.ENDC}")
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)
else:
print(f"{LogColors.WARNING}Queue is full, dropping audio chunk{LogColors.ENDC}")
async def close(self):
if self.websocket:
await self.websocket.close()
connections.pop(self.client_id)
print(f"{LogColors.WARNING}WebSocket connection closed{LogColors.ENDC}")
def send_audio_chunk(new_chunk: gr.Audio, client_id: str):
if client_id not in connections:
return "Connection is being established, please try again in a few seconds."
sr, y = new_chunk
connections[client_id].enqueue_audio_chunk(sr, y)
return transcription
def create_new_websocket_connection():
client_id = str(uuid.uuid4())
connections[client_id] = WebSocketClient(WEBSOCKET_URI, WEBSOCKET_HEADERS, client_id)
threading.Thread(target=connections[client_id].run, daemon=True).start()
return client_id
if __name__ == "__main__":
with gr.Blocks(css=css, theme=gr.themes.Soft()) as demo:
gr.Markdown(f"# Realtime transcription demo")
with gr.Row():
with gr.Column():
output_textbox = gr.Textbox(label="Transcription", value="", lines=7, interactive=False, autoscroll=True)
with gr.Row():
with gr.Column(scale=5):
audio_input = gr.Audio(streaming=True, format="wav")
with gr.Column():
clear_button = gr.Button("Clear")
client_id = gr.State()
state = gr.State()
clear_button.click(lambda: None, outputs=[state]).then(lambda: "", outputs=[output_textbox])
audio_input.stream(send_audio_chunk, [audio_input, client_id], [output_textbox], stream_every=0.5, concurrency_limit=None)
demo.load(create_new_websocket_connection, outputs=[client_id])
demo.launch()