Hackathons/HooHacks-12
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Merge branch 'main' of https://github.com/GamerBoss101/HooHacks-12

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This commit is contained in:
Surya Vemulapalli
2025-03-29 22:01:07 -04:00
parent 03652b7180 131c8c9e78
commit e8a9207da4
2 changed files with 404 additions and 1 deletions
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285
Backend/index.html
View File

@@ -1,4 +1,3 @@
/index.html
<!DOCTYPE html>
<html lang="en">
<head>
@@ -93,6 +92,16 @@
let mediaRecorder;
let audioChunks = [];
let isRecording = false;
let audioContext;
let streamProcessor;
let isStreaming = false;
let streamButton;
let isSpeaking = false;
let silenceTimer = null;
let energyWindow = [];
const ENERGY_WINDOW_SIZE = 10;
const CLIENT_SILENCE_THRESHOLD = 0.01;
const CLIENT_SILENCE_DURATION_MS = 1000; // 1 second
// DOM elements
const conversationEl = document.getElementById('conversation');
@@ -102,6 +111,271 @@
const recordAudioBtn = document.getElementById('recordAudio');
const clearContextBtn = document.getElementById('clearContext');
// Add streaming button to the input row
window.addEventListener('load', () => {
const inputRow = document.querySelector('.input-row:nth-child(2)');
streamButton = document.createElement('button');
streamButton.id = 'streamAudio';
streamButton.textContent = 'Start Streaming';
streamButton.addEventListener('click', toggleStreaming);
inputRow.appendChild(streamButton);
connectWebSocket();
setupRecording();
setupAudioContext();
});
// Setup audio context for streaming
function setupAudioContext() {
try {
audioContext = new (window.AudioContext || window.webkitAudioContext)();
console.log('Audio context setup completed');
} catch (err) {
console.error('Error setting up audio context:', err);
addSystemMessage(`Audio context error: ${err.message}`);
}
}
// Toggle audio streaming
async function toggleStreaming() {
if (isStreaming) {
stopStreaming();
} else {
startStreaming();
}
}
// Start audio streaming with silence detection
async function startStreaming() {
try {
const stream = await navigator.mediaDevices.getUserMedia({ audio: true });
const speaker = parseInt(speakerSelectEl.value);
isStreaming = true;
isSpeaking = false;
energyWindow = [];
streamButton.textContent = 'Speaking...';
streamButton.classList.add('recording');
// Create audio processor node
const source = audioContext.createMediaStreamSource(stream);
streamProcessor = audioContext.createScriptProcessor(4096, 1, 1);
// Process and send audio data
streamProcessor.onaudioprocess = function(e) {
const audioData = e.inputBuffer.getChannelData(0);
// Calculate energy (volume) for silence detection
const energy = calculateAudioEnergy(audioData);
updateEnergyWindow(energy);
// Check if currently silent
const avgEnergy = calculateAverageEnergy();
const isSilent = avgEnergy < CLIENT_SILENCE_THRESHOLD;
// Handle silence/speech transitions for visual feedback
handleSpeechState(isSilent);
// Continue processing audio regardless of silence state
const downsampled = downsampleBuffer(audioData, audioContext.sampleRate, 24000);
sendAudioChunk(downsampled, speaker);
};
// Connect the nodes
source.connect(streamProcessor);
streamProcessor.connect(audioContext.destination);
addSystemMessage('Audio streaming started - speak naturally and pause when finished');
} catch (err) {
console.error('Error starting audio stream:', err);
addSystemMessage(`Streaming error: ${err.message}`);
isStreaming = false;
streamButton.textContent = 'Start Streaming';
streamButton.classList.remove('recording');
}
}
// Calculate audio energy (volume)
function calculateAudioEnergy(buffer) {
let sum = 0;
for (let i = 0; i < buffer.length; i++) {
sum += Math.abs(buffer[i]);
}
return sum / buffer.length;
}
// Update the sliding energy window
function updateEnergyWindow(energy) {
energyWindow.push(energy);
if (energyWindow.length > ENERGY_WINDOW_SIZE) {
energyWindow.shift();
}
}
// Calculate average energy from the window
function calculateAverageEnergy() {
if (energyWindow.length === 0) return 0;
return energyWindow.reduce((sum, val) => sum + val, 0) / energyWindow.length;
}
// Handle speech state changes and visual feedback
function handleSpeechState(isSilent) {
if (isSpeaking && isSilent) {
// Transition from speaking to silence
if (!silenceTimer) {
silenceTimer = setTimeout(() => {
// Silence persisted long enough
streamButton.textContent = 'Processing...';
streamButton.style.backgroundColor = '#FFA500'; // Orange
addSystemMessage('Detected pause in speech, processing response...');
}, CLIENT_SILENCE_DURATION_MS);
}
} else if (!isSpeaking && !isSilent) {
// Transition from silence to speaking
isSpeaking = true;
streamButton.textContent = 'Speaking...';
streamButton.style.backgroundColor = '#f44336'; // Red
// Clear any pending silence timer
if (silenceTimer) {
clearTimeout(silenceTimer);
silenceTimer = null;
}
} else if (isSpeaking && !isSilent) {
// Still speaking, reset any silence timer
if (silenceTimer) {
clearTimeout(silenceTimer);
silenceTimer = null;
}
}
// Update speaking state
if (!isSilent) {
isSpeaking = true;
}
}
// Send audio chunk to server
function sendAudioChunk(audioData, speaker) {
const wavData = createWavBlob(audioData, 24000);
const reader = new FileReader();
reader.onloadend = function() {
const base64data = reader.result;
// Send to server
ws.send(JSON.stringify({
action: 'stream_audio',
speaker: speaker,
audio: base64data
}));
};
reader.readAsDataURL(wavData);
}
// Stop audio streaming
function stopStreaming() {
if (streamProcessor) {
streamProcessor.disconnect();
streamProcessor = null;
}
// Clear any pending silence timer
if (silenceTimer) {
clearTimeout(silenceTimer);
silenceTimer = null;
}
isStreaming = false;
isSpeaking = false;
energyWindow = [];
streamButton.textContent = 'Start Streaming';
streamButton.classList.remove('recording');
streamButton.style.backgroundColor = ''; // Reset to default
addSystemMessage('Audio streaming stopped');
// Send stop streaming signal to server
ws.send(JSON.stringify({
action: 'stop_streaming',
speaker: parseInt(speakerSelectEl.value)
}));
}
// Downsample audio buffer to target sample rate
function downsampleBuffer(buffer, sampleRate, targetSampleRate) {
if (targetSampleRate === sampleRate) {
return buffer;
}
const sampleRateRatio = sampleRate / targetSampleRate;
const newLength = Math.round(buffer.length / sampleRateRatio);
const result = new Float32Array(newLength);
let offsetResult = 0;
let offsetBuffer = 0;
while (offsetResult < result.length) {
const nextOffsetBuffer = Math.round((offsetResult + 1) * sampleRateRatio);
let accum = 0, count = 0;
for (let i = offsetBuffer; i < nextOffsetBuffer && i < buffer.length; i++) {
accum += buffer[i];
count++;
}
result[offsetResult] = accum / count;
offsetResult++;
offsetBuffer = nextOffsetBuffer;
}
return result;
}
// Create WAV blob from Float32Array
function createWavBlob(samples, sampleRate) {
const buffer = new ArrayBuffer(44 + samples.length * 2);
const view = new DataView(buffer);
// RIFF chunk descriptor
writeString(view, 0, 'RIFF');
view.setUint32(4, 36 + samples.length * 2, true);
writeString(view, 8, 'WAVE');
// fmt sub-chunk
writeString(view, 12, 'fmt ');
view.setUint32(16, 16, true);
view.setUint16(20, 1, true); // PCM format
view.setUint16(22, 1, true); // Mono channel
view.setUint32(24, sampleRate, true);
view.setUint32(28, sampleRate * 2, true);
view.setUint16(32, 2, true);
view.setUint16(34, 16, true);
// data sub-chunk
writeString(view, 36, 'data');
view.setUint32(40, samples.length * 2, true);
// Write the PCM samples
const volume = 0.5;
for (let i = 0; i < samples.length; i++) {
const sample = Math.max(-1, Math.min(1, samples[i]));
view.setInt16(44 + i * 2, sample < 0 ? sample * 0x8000 : sample * 0x7FFF, true);
}
return new Blob([buffer], { type: 'audio/wav' });
}
function writeString(view, offset, string) {
for (let i = 0; i < string.length; i++) {
view.setUint8(offset + i, string.charCodeAt(i));
}
}
// Connect to WebSocket
function connectWebSocket() {
const wsProtocol = window.location.protocol === 'https:' ? 'wss:' : 'ws:';
@@ -125,10 +399,19 @@
// Add message to conversation
addAIMessage(response.audio);
// Reset the streaming button if we're still in streaming mode
if (isStreaming) {
streamButton.textContent = 'Speaking...';
streamButton.style.backgroundColor = '#f44336'; // Back to red
isSpeaking = false; // Reset speaking state
}
} else if (response.type === 'error') {
addSystemMessage(`Error: ${response.message}`);
} else if (response.type === 'context_updated') {
addSystemMessage(response.message);
} else if (response.type === 'streaming_status') {
addSystemMessage(`Streaming ${response.status}`);
}
};

120
Backend/server.py
View File

@@ -12,6 +12,8 @@ from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel
from generator import load_csm_1b, Segment
import uvicorn
import time
from collections import deque
# Select device
if torch.cuda.is_available():
@@ -48,6 +50,9 @@ class ConnectionManager:
manager = ConnectionManager()
# Silence detection parameters
SILENCE_THRESHOLD = 0.01 # Adjust based on your audio normalization
SILENCE_DURATION_SEC = 1.0 # How long silence must persist to be considered "stopped talking"
# Helper function to convert audio data
async def decode_audio_data(audio_data: str) -> torch.Tensor:
@@ -92,6 +97,13 @@ async def encode_audio_data(audio_tensor: torch.Tensor) -> str:
async def websocket_endpoint(websocket: WebSocket):
await manager.connect(websocket)
context_segments = [] # Store conversation context
streaming_buffer = [] # Buffer for streaming audio chunks
is_streaming = False
# Variables for silence detection
last_active_time = time.time()
is_silence = False
energy_window = deque(maxlen=10) # For tracking recent audio energy
try:
while True:
@@ -161,6 +173,114 @@ async def websocket_endpoint(websocket: WebSocket):
"message": "Context cleared"
})
elif action == "stream_audio":
try:
speaker_id = request.get("speaker", 0)
audio_data = request.get("audio", "")
# Convert received audio to tensor
audio_chunk = await decode_audio_data(audio_data)
# Start streaming mode if not already started
if not is_streaming:
is_streaming = True
streaming_buffer = []
energy_window.clear()
is_silence = False
last_active_time = time.time()
await websocket.send_json({
"type": "streaming_status",
"status": "started"
})
# Calculate audio energy for silence detection
chunk_energy = torch.mean(torch.abs(audio_chunk)).item()
energy_window.append(chunk_energy)
avg_energy = sum(energy_window) / len(energy_window)
# Check if audio is silent
current_silence = avg_energy < SILENCE_THRESHOLD
# Track silence transition
if not is_silence and current_silence:
# Transition to silence
is_silence = True
last_active_time = time.time()
elif is_silence and not current_silence:
# User started talking again
is_silence = False
# Add chunk to buffer regardless of silence state
streaming_buffer.append(audio_chunk)
# Check if silence has persisted long enough to consider "stopped talking"
silence_elapsed = time.time() - last_active_time
if is_silence and silence_elapsed >= SILENCE_DURATION_SEC and len(streaming_buffer) > 0:
# User has stopped talking - process the collected audio
full_audio = torch.cat(streaming_buffer, dim=0)
# Process with speech-to-text (you would need to implement this)
# For now, just use a placeholder text
text = f"User audio from speaker {speaker_id}"
print(f"Detected end of speech, processing {len(streaming_buffer)} chunks")
# Add to conversation context
context_segments.append(Segment(text=text, speaker=speaker_id, audio=full_audio))
# Generate response
response_text = "This is a response to what you just said"
audio_tensor = generator.generate(
text=response_text,
speaker=1 if speaker_id == 0 else 0, # Use opposite speaker
context=context_segments,
max_audio_length_ms=10_000,
)
# Convert audio to base64 and send back to client
audio_base64 = await encode_audio_data(audio_tensor)
await websocket.send_json({
"type": "audio_response",
"audio": audio_base64
})
# Clear buffer and reset silence detection
streaming_buffer = []
energy_window.clear()
is_silence = False
last_active_time = time.time()
# If buffer gets too large without silence, process it anyway
# This prevents memory issues with very long streams
elif len(streaming_buffer) >= 30: # ~6 seconds of audio at 5 chunks/sec
print("Buffer limit reached, processing audio")
full_audio = torch.cat(streaming_buffer, dim=0)
text = f"Continued speech from speaker {speaker_id}"
context_segments.append(Segment(text=text, speaker=speaker_id, audio=full_audio))
streaming_buffer = []
except Exception as e:
print(f"Error processing streaming audio: {str(e)}")
await websocket.send_json({
"type": "error",
"message": f"Error processing streaming audio: {str(e)}"
})
elif action == "stop_streaming":
is_streaming = False
if streaming_buffer:
# Process any remaining audio in the buffer
full_audio = torch.cat(streaming_buffer, dim=0)
text = f"Final streaming audio from speaker {request.get('speaker', 0)}"
context_segments.append(Segment(text=text, speaker=request.get("speaker", 0), audio=full_audio))
streaming_buffer = []
await websocket.send_json({
"type": "streaming_status",
"status": "stopped"
})
except WebSocketDisconnect:
manager.disconnect(websocket)
print("Client disconnected")