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(>=0.5.2,<0.6.0)" + "sounddevice (>=0.5.2,<0.6.0)", + "soundfile (>=0.13.1,<0.14.0)", + "azure-cognitiveservices-speech (>=1.44.0,<2.0.0)" ] diff --git a/src/mic_rtc_streaming/backend/backend.py b/src/mic_rtc_streaming/backend/backend.py new file mode 100644 index 0000000..ea47f5d --- /dev/null +++ b/src/mic_rtc_streaming/backend/backend.py @@ -0,0 +1,85 @@ +# backend/main.py +import asyncio, logging, uuid + +from typing import List, Set + +from fastapi import FastAPI, WebSocket +from fastapi.middleware.cors import CORSMiddleware +from pydantic import BaseModel +from aiortc import RTCPeerConnection, RTCSessionDescription, MediaStreamTrack + +# Global: desired packetization time in ms for Opus (change here to affect both backend and frontend) +PTIME = 40 + +app = FastAPI() + +# Allow CORS for frontend on localhost +app.add_middleware( + CORSMiddleware, + allow_origins=["*"], # You can restrict this to ["http://localhost:8501"] if you want + allow_credentials=True, + allow_methods=["*"], + allow_headers=["*"], +) + +pcs: Set[RTCPeerConnection] = set() # keep refs so they don’t GC early + +class Offer(BaseModel): + sdp: str + type: str + +@app.post("/offer") +async def offer(offer: Offer): + logging.info("/offer endpoint called") + + pc = RTCPeerConnection() # No STUN needed for localhost + pcs.add(pc) + id_ = uuid.uuid4().hex[:8] + logging.info(f"{id_}: new PeerConnection") + + @pc.on("track") + async def on_track(track: MediaStreamTrack): + logging.info(f"{id_}: track {track.kind} received") + try: + first = True + while True: + pkt = await track.recv() # RTP audio frame (already decrypted) + pkt_bytes = bytes(pkt.planes[0]) + if first: + logging.info( + f"{id_}: frame sample_rate={pkt.sample_rate}, channels={pkt.layout.channels}, format={pkt.format.name}" + ) + logging.info(f"{id_}: received audio frame of len {len(pkt_bytes)} bytes") #received audio frame of len 23040 bytes + first = False + # TODO: write to file, pipe to ASR, etc. + except Exception as e: + logging.error(f"{id_}: Exception in on_track: {e}") + + # --- SDP negotiation --- + logging.info(f"{id_}: setting remote description") + await pc.setRemoteDescription(RTCSessionDescription(**offer.dict())) + + logging.info(f"{id_}: creating answer") + answer = await pc.createAnswer() + sdp = answer.sdp + # Insert a=ptime using the global PTIME variable + ptime_line = f"a=ptime:{PTIME}" + if "a=sendrecv" in sdp: + sdp = sdp.replace("a=sendrecv", f"a=sendrecv\n{ptime_line}") + else: + sdp += f"\n{ptime_line}" + new_answer = RTCSessionDescription(sdp=sdp, type=answer.type) + await pc.setLocalDescription(new_answer) + logging.info(f"{id_}: sending answer with {ptime_line}") + return {"sdp": pc.localDescription.sdp, + "type": pc.localDescription.type} + +@app.on_event("shutdown") +async def cleanup(): + coros = [pc.close() for pc in pcs] + await asyncio.gather(*coros) + +if __name__ == "__main__": + import uvicorn + logging.basicConfig(level=logging.INFO) + uvicorn.run("backend:app", host="0.0.0.0", port=8000) diff --git a/src/mic_rtc_streaming/frontend/frontend.py b/src/mic_rtc_streaming/frontend/frontend.py new file mode 100644 index 0000000..216b811 --- /dev/null +++ b/src/mic_rtc_streaming/frontend/frontend.py @@ -0,0 +1,75 @@ +# frontend/app.py +import streamlit as st +import requests + +# Global: desired packetization time in ms for Opus (should match backend) +PTIME = 40 +BACKEND_URL = "http://localhost:8000" + +def main(): + + st.title("🎙️ WebRTC mic → backend demo") + st.markdown("Click start and speak; watch your backend logs to see incoming RTP.") + + component = f""" + + + """ + st.components.v1.html(component, height=80) + +# if __name__ == "__main__": +# import sys +# import os +# from pathlib import Path + +# # Prevent infinite relaunch loop if already running inside Streamlit +# if os.environ.get("STREAMLIT_SERVER_RUNNING") == "1": +# # Already running in Streamlit, do nothing special +# pass +# else: +# venv_bin = Path(__file__).resolve().parent.parent.parent.parent / ".venv/bin" +# streamlit_bin = venv_bin / "streamlit" +# if streamlit_bin.exists(): +# cmd = f"{streamlit_bin} run {sys.argv[0]}" + +# Ensure Streamlit runs the UI code +main() + +# else: +# cmd = f"streamlit run {sys.argv[0]}" +# os.execvp("/bin/bash", ["/bin/bash", "-c", f"source {venv_bin}/activate && {cmd}"]) + diff --git a/src/mic_rtc_streaming/run.sh b/src/mic_rtc_streaming/run.sh new file mode 100644 index 0000000..93e9af4 --- /dev/null +++ b/src/mic_rtc_streaming/run.sh @@ -0,0 +1,26 @@ +#!/bin/bash + +# Kill any orphaned backend/frontend processes from previous runs +pkill -f "uvicorn backend.backend:app" 2>/dev/null +pkill -f "streamlit run frontend/frontend.py" 2>/dev/null + +# Start backend +uvicorn backend.backend:app --host 0.0.0.0 --port 8000 & +BACKEND_PID=$! + +# Start frontend +streamlit run frontend/frontend.py & +FRONTEND_PID=$! + +# Trap exit signals to kill both processes +cleanup() { + echo "Stopping frontend (PID $FRONTEND_PID)..." + kill $FRONTEND_PID 2>/dev/null + echo "Stopping backend (PID $BACKEND_PID)..." + kill $BACKEND_PID 2>/dev/null + exit 0 +} +trap cleanup SIGINT SIGTERM EXIT + +# Wait for both to finish +wait diff --git a/network_audio_streaming/audio_sink.py b/src/network_audio_streaming/audio_sink.py similarity index 100% rename from network_audio_streaming/audio_sink.py rename to src/network_audio_streaming/audio_sink.py diff --git a/network_audio_streaming/audio_source.py b/src/network_audio_streaming/audio_source.py similarity index 100% rename from network_audio_streaming/audio_source.py rename to src/network_audio_streaming/audio_source.py diff --git a/src/realtime_translator/README.md b/src/realtime_translator/README.md new file mode 100644 index 0000000..8229a03 --- /dev/null +++ b/src/realtime_translator/README.md @@ -0,0 +1,30 @@ +# Real-Time Translator + +This package provides real-time speech translation using OpenAI Whisper, GPT-4o mini, and a neutral TTS voice. + +## Features +- Audio input (microphone or file) +- Transcription (Whisper) +- Translation (GPT-4o mini) +- Speech synthesis (OpenAI TTS, neutral voice) + +## Usage +``` +from realtime_translator.translator import RealTimeTranslator + +translator = RealTimeTranslator(openai_api_key="sk-...", source_lang="de", target_lang="en") +translator.process("input.wav", "output.wav") +``` + +## Requirements +- openai +- sounddevice +- soundfile + +## Install +``` +pip install -r requirements.txt +``` + +## Note +You need an OpenAI API key with access to Whisper, GPT-4o, and TTS endpoints. diff --git a/src/realtime_translator/__init__.py b/src/realtime_translator/__init__.py new file mode 100644 index 0000000..ac0e309 --- /dev/null +++ b/src/realtime_translator/__init__.py @@ -0,0 +1,3 @@ +# Real-time Translator Package + +# This package provides real-time speech translation using OpenAI Whisper, GPT-4o mini, and TTS. diff --git a/src/realtime_translator/speech_translation.py b/src/realtime_translator/speech_translation.py new file mode 100644 index 0000000..b8a3f8e --- /dev/null +++ b/src/realtime_translator/speech_translation.py @@ -0,0 +1,39 @@ +# pip install azure-cognitiveservices-speech +# see https://learn.microsoft.com/en-us/azure/ai-services/speech-service/speech-translation + +import os +import azure.cognitiveservices.speech as speechsdk + +ENDPOINT = "" +SPEECH_KEY = "" + +def recognize_from_microphone(): + # This example requires environment variables named "SPEECH_KEY" and "ENDPOINT" + # Replace with your own subscription key and endpoint, the endpoint is like : "https://YourServiceRegion.api.cognitive.microsoft.com" + speech_translation_config = speechsdk.translation.SpeechTranslationConfig(subscription=SPEECH_KEY, endpoint=ENDPOINT) + speech_translation_config.speech_recognition_language="en-US" + + to_language ="it" + speech_translation_config.add_target_language(to_language) + + audio_config = speechsdk.audio.AudioConfig(use_default_microphone=True) + translation_recognizer = speechsdk.translation.TranslationRecognizer(translation_config=speech_translation_config, audio_config=audio_config) + + print("Speak into your microphone.") + translation_recognition_result = translation_recognizer.recognize_once_async().get() + + if translation_recognition_result.reason == speechsdk.ResultReason.TranslatedSpeech: + print("Recognized: {}".format(translation_recognition_result.text)) + print("""Translated into '{}': {}""".format( + to_language, + translation_recognition_result.translations[to_language])) + elif translation_recognition_result.reason == speechsdk.ResultReason.NoMatch: + print("No speech could be recognized: {}".format(translation_recognition_result.no_match_details)) + elif translation_recognition_result.reason == speechsdk.ResultReason.Canceled: + cancellation_details = translation_recognition_result.cancellation_details + print("Speech Recognition canceled: {}".format(cancellation_details.reason)) + if cancellation_details.reason == speechsdk.CancellationReason.Error: + print("Error details: {}".format(cancellation_details.error_details)) + print("Did you set the speech resource key and endpoint values?") + +recognize_from_microphone() \ No newline at end of file