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import streamlit as st |
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import requests |
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import asyncio |
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import aiohttp |
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from aiortc import MediaStreamTrack, RTCPeerConnection, RTCSessionDescription |
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from aiortc.contrib.media import MediaBlackhole, MediaRecorder |
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import av |
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import base64 |
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import json |
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API_URL = "https://api-inference.huggingface.co/models/openai/whisper-large-v3-turbo" |
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headers = {"Authorization": f"Bearer {st.secrets['hf_token']}"} |
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class AudioTranscriber: |
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def __init__(self): |
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self.buffer = [] |
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self.text = "" |
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async def transcribe(self, audio_data): |
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async with aiohttp.ClientSession() as session: |
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async with session.post(API_URL, headers=headers, data=audio_data) as response: |
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result = await response.json() |
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if 'text' in result: |
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self.text += result['text'] + " " |
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st.text_area("Transcription", self.text, height=200) |
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class AudioTrack(MediaStreamTrack): |
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kind = "audio" |
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def __init__(self, track, transcriber): |
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super().__init__() |
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self.track = track |
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self.transcriber = transcriber |
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async def recv(self): |
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frame = await self.track.recv() |
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if len(self.transcriber.buffer) < 5: |
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self.transcriber.buffer.append(frame.to_ndarray()) |
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else: |
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audio_data = b''.join([av.AudioFrame.from_ndarray(buf).to_bytes() for buf in self.transcriber.buffer]) |
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asyncio.create_task(self.transcriber.transcribe(audio_data)) |
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self.transcriber.buffer = [] |
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return frame |
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async def process_offer(offer, transcriber): |
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pc = RTCPeerConnection() |
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pc.addTransceiver("audio", direction="recvonly") |
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@pc.on("track") |
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def on_track(track): |
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if track.kind == "audio": |
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pc.addTrack(AudioTrack(track, transcriber)) |
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await pc.setRemoteDescription(RTCSessionDescription(sdp=offer["sdp"], type=offer["type"])) |
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answer = await pc.createAnswer() |
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await pc.setLocalDescription(answer) |
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return {"sdp": pc.localDescription.sdp, "type": pc.localDescription.type} |
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st.title("Real-time Speech Recognition with Whisper") |
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webrtc_ctx = st.config.get_option("server.enableXsrfProtection") |
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if webrtc_ctx: |
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st.warning("To use this app, you need to disable XSRF protection. Set server.enableXsrfProtection=false in your Streamlit config.") |
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else: |
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offer = st.text_input("Paste the offer SDP here") |
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if offer: |
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transcriber = AudioTranscriber() |
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answer = asyncio.run(process_offer(json.loads(offer), transcriber)) |
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st.text_area("Answer SDP", json.dumps(answer)) |
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st.write("Speak into your microphone. The transcription will appear below.") |
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st.markdown("---") |
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st.write("Note: This app uses the Whisper API from Hugging Face for real-time speech recognition.") |
