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import asyncio
import base64
import json
from pathlib import Path
import os
import numpy as np
import openai
from dotenv import load_dotenv
from fastapi import FastAPI, Request
from fastapi.responses import HTMLResponse, StreamingResponse
from fastrtc import (
AdditionalOutputs,
AsyncStreamHandler,
Stream,
get_twilio_turn_credentials,
wait_for_item,
)
from gradio.utils import get_space
from openai.types.beta.realtime import ResponseAudioTranscriptDoneEvent
import httpx
from typing import Optional, List, Dict
import gradio as gr
load_dotenv()
SAMPLE_RATE = 24000
# Supported languages for OpenAI Realtime API
SUPPORTED_LANGUAGES = {
"ko": "한국어 (Korean)",
"en": "English",
"es": "Español (Spanish)",
"fr": "Français (French)",
"de": "Deutsch (German)",
"it": "Italiano (Italian)",
"pt": "Português (Portuguese)",
"ru": "Русский (Russian)",
"ja": "日本語 (Japanese)",
"zh": "中文 (Chinese)",
"ar": "العربية (Arabic)",
"hi": "हिन्दी (Hindi)",
"nl": "Nederlands (Dutch)",
"pl": "Polski (Polish)",
"tr": "Türkçe (Turkish)",
"vi": "Tiếng Việt (Vietnamese)",
"th": "ไทย (Thai)",
"id": "Bahasa Indonesia",
"sv": "Svenska (Swedish)",
"da": "Dansk (Danish)",
"no": "Norsk (Norwegian)",
"fi": "Suomi (Finnish)",
"he": "עברית (Hebrew)",
"uk": "Українська (Ukrainian)",
"cs": "Čeština (Czech)",
"el": "Ελληνικά (Greek)",
"ro": "Română (Romanian)",
"hu": "Magyar (Hungarian)",
"ms": "Bahasa Melayu (Malay)"
}
# HTML content embedded as a string
HTML_CONTENT = """<!DOCTYPE html>
<html lang="ko">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Mouth of 'MOUSE'</title>
<style>
:root {
--primary-color: #6f42c1;
--secondary-color: #563d7c;
--dark-bg: #121212;
--card-bg: #1e1e1e;
--text-color: #f8f9fa;
--border-color: #333;
--hover-color: #8a5cf6;
}
body {
font-family: "SF Pro Display", -apple-system, BlinkMacSystemFont, sans-serif;
background-color: var(--dark-bg);
color: var(--text-color);
margin: 0;
padding: 0;
height: 100vh;
display: flex;
flex-direction: column;
overflow: hidden;
}
.container {
max-width: 1400px;
margin: 0 auto;
padding: 20px;
flex-grow: 1;
display: flex;
flex-direction: column;
width: 100%;
height: 100vh;
box-sizing: border-box;
overflow: hidden;
}
.header {
text-align: center;
padding: 15px 0;
border-bottom: 1px solid var(--border-color);
margin-bottom: 20px;
flex-shrink: 0;
background-color: var(--card-bg);
}
.main-content {
display: flex;
gap: 20px;
flex-grow: 1;
min-height: 0;
overflow: hidden;
}
.sidebar {
width: 350px;
flex-shrink: 0;
display: flex;
flex-direction: column;
gap: 20px;
overflow-y: auto;
max-height: calc(100vh - 120px);
}
.chat-section {
flex-grow: 1;
display: flex;
flex-direction: column;
min-width: 0;
}
.logo {
display: flex;
align-items: center;
justify-content: center;
gap: 10px;
}
.logo h1 {
margin: 0;
background: linear-gradient(135deg, var(--primary-color), #a78bfa);
-webkit-background-clip: text;
background-clip: text;
color: transparent;
font-size: 32px;
letter-spacing: 1px;
}
/* Settings section */
.settings-section {
background-color: var(--card-bg);
border-radius: 12px;
padding: 20px;
border: 1px solid var(--border-color);
overflow-y: auto;
flex-grow: 1;
}
.settings-grid {
display: flex;
flex-direction: column;
gap: 15px;
margin-bottom: 15px;
}
.interpretation-section {
display: flex;
flex-direction: column;
gap: 15px;
padding: 15px;
background-color: var(--dark-bg);
border-radius: 8px;
margin-top: 15px;
}
.interpretation-info {
font-size: 13px;
color: #999;
margin-top: 5px;
}
.setting-item {
display: flex;
align-items: center;
justify-content: space-between;
gap: 10px;
}
.setting-label {
font-size: 14px;
color: #aaa;
min-width: 60px;
}
/* Toggle switch */
.toggle-switch {
position: relative;
width: 50px;
height: 26px;
background-color: #ccc;
border-radius: 13px;
cursor: pointer;
transition: background-color 0.3s;
}
.toggle-switch.active {
background-color: var(--primary-color);
}
.toggle-slider {
position: absolute;
top: 3px;
left: 3px;
width: 20px;
height: 20px;
background-color: white;
border-radius: 50%;
transition: transform 0.3s;
}
.toggle-switch.active .toggle-slider {
transform: translateX(24px);
}
/* Select dropdown */
select {
background-color: var(--card-bg);
color: var(--text-color);
border: 1px solid var(--border-color);
padding: 8px 12px;
border-radius: 6px;
font-size: 14px;
cursor: pointer;
min-width: 120px;
max-width: 200px;
}
select:focus {
outline: none;
border-color: var(--primary-color);
}
/* Text inputs */
.text-input-section {
margin-top: 15px;
}
input[type="text"], textarea {
width: 100%;
background-color: var(--dark-bg);
color: var(--text-color);
border: 1px solid var(--border-color);
padding: 10px;
border-radius: 6px;
font-size: 14px;
box-sizing: border-box;
margin-top: 5px;
}
input[type="text"]:focus, textarea:focus {
outline: none;
border-color: var(--primary-color);
}
textarea {
resize: vertical;
min-height: 80px;
}
.chat-container {
border-radius: 12px;
background-color: var(--card-bg);
box-shadow: 0 8px 32px rgba(0, 0, 0, 0.2);
padding: 20px;
flex-grow: 1;
display: flex;
flex-direction: column;
border: 1px solid var(--border-color);
overflow: hidden;
min-height: 0;
height: 100%;
}
.chat-messages {
flex-grow: 1;
overflow-y: auto;
padding: 15px;
scrollbar-width: thin;
scrollbar-color: var(--primary-color) var(--card-bg);
min-height: 0;
max-height: calc(100vh - 250px);
}
.chat-messages::-webkit-scrollbar {
width: 6px;
}
.chat-messages::-webkit-scrollbar-thumb {
background-color: var(--primary-color);
border-radius: 6px;
}
.message {
margin-bottom: 15px;
padding: 12px 16px;
border-radius: 8px;
font-size: 15px;
line-height: 1.5;
position: relative;
max-width: 85%;
animation: fade-in 0.3s ease-out;
word-wrap: break-word;
}
@keyframes fade-in {
from {
opacity: 0;
transform: translateY(10px);
}
to {
opacity: 1;
transform: translateY(0);
}
}
.message.user {
background: linear-gradient(135deg, #2c3e50, #34495e);
margin-left: auto;
border-bottom-right-radius: 2px;
}
.message.assistant {
background: linear-gradient(135deg, var(--secondary-color), var(--primary-color));
margin-right: auto;
border-bottom-left-radius: 2px;
}
.message.search-result {
background: linear-gradient(135deg, #1a5a3e, #2e7d32);
font-size: 14px;
padding: 10px;
margin-bottom: 10px;
}
.controls {
text-align: center;
margin-top: auto;
display: flex;
justify-content: center;
gap: 10px;
flex-shrink: 0;
padding-top: 20px;
}
/* Responsive design */
@media (max-width: 1024px) {
.sidebar {
width: 300px;
}
}
@media (max-width: 768px) {
.main-content {
flex-direction: column;
}
.sidebar {
width: 100%;
margin-bottom: 20px;
}
.chat-section {
height: 400px;
}
}
button {
background: linear-gradient(135deg, var(--primary-color), var(--secondary-color));
color: white;
border: none;
padding: 14px 28px;
font-family: inherit;
font-size: 16px;
cursor: pointer;
transition: all 0.3s;
text-transform: uppercase;
letter-spacing: 1px;
border-radius: 50px;
display: flex;
align-items: center;
justify-content: center;
gap: 10px;
box-shadow: 0 4px 10px rgba(111, 66, 193, 0.3);
}
button:hover {
transform: translateY(-2px);
box-shadow: 0 6px 15px rgba(111, 66, 193, 0.5);
background: linear-gradient(135deg, var(--hover-color), var(--primary-color));
}
button:active {
transform: translateY(1px);
}
#send-button {
background: linear-gradient(135deg, #2ecc71, #27ae60);
padding: 10px 20px;
font-size: 14px;
flex-shrink: 0;
}
#send-button:hover {
background: linear-gradient(135deg, #27ae60, #229954);
}
#audio-output {
display: none;
}
.icon-with-spinner {
display: flex;
align-items: center;
justify-content: center;
gap: 12px;
min-width: 180px;
}
.spinner {
width: 20px;
height: 20px;
border: 2px solid #ffffff;
border-top-color: transparent;
border-radius: 50%;
animation: spin 1s linear infinite;
flex-shrink: 0;
}
@keyframes spin {
to {
transform: rotate(360deg);
}
}
.audio-visualizer {
display: flex;
align-items: center;
justify-content: center;
gap: 5px;
min-width: 80px;
height: 25px;
}
.visualizer-bar {
width: 4px;
height: 100%;
background-color: rgba(255, 255, 255, 0.7);
border-radius: 2px;
transform-origin: bottom;
transform: scaleY(0.1);
transition: transform 0.1s ease;
}
.toast {
position: fixed;
top: 20px;
left: 50%;
transform: translateX(-50%);
padding: 16px 24px;
border-radius: 8px;
font-size: 14px;
z-index: 1000;
display: none;
box-shadow: 0 4px 12px rgba(0, 0, 0, 0.3);
}
.toast.error {
background-color: #f44336;
color: white;
}
.toast.warning {
background-color: #ff9800;
color: white;
}
.status-indicator {
display: inline-flex;
align-items: center;
margin-top: 10px;
font-size: 14px;
color: #aaa;
}
.status-dot {
width: 8px;
height: 8px;
border-radius: 50%;
margin-right: 8px;
}
.status-dot.connected {
background-color: #4caf50;
}
.status-dot.disconnected {
background-color: #f44336;
}
.status-dot.connecting {
background-color: #ff9800;
animation: pulse 1.5s infinite;
}
@keyframes pulse {
0% {
opacity: 0.6;
}
50% {
opacity: 1;
}
100% {
opacity: 0.6;
}
}
.mouse-logo {
position: relative;
width: 40px;
height: 40px;
}
.mouse-ears {
position: absolute;
width: 15px;
height: 15px;
background-color: var(--primary-color);
border-radius: 50%;
}
.mouse-ear-left {
top: 0;
left: 5px;
}
.mouse-ear-right {
top: 0;
right: 5px;
}
.mouse-face {
position: absolute;
top: 10px;
left: 5px;
width: 30px;
height: 30px;
background-color: var(--secondary-color);
border-radius: 50%;
}
.language-info {
font-size: 12px;
color: #888;
margin-left: 5px;
}
</style>
</head>
<body>
<div id="error-toast" class="toast"></div>
<div class="container">
<div class="header">
<div class="logo">
<div class="mouse-logo">
<div class="mouse-ears mouse-ear-left"></div>
<div class="mouse-ears mouse-ear-right"></div>
<div class="mouse-face"></div>
</div>
<h1>MOUSE 음성 챗</h1>
</div>
<div class="status-indicator">
<div id="status-dot" class="status-dot disconnected"></div>
<span id="status-text">연결 대기 중</span>
</div>
</div>
<div class="main-content">
<div class="sidebar">
<div class="settings-section">
<h3 style="margin: 0 0 15px 0; color: var(--primary-color);">설정</h3>
<div class="settings-grid">
<div class="setting-item">
<span class="setting-label">웹 검색</span>
<div id="search-toggle" class="toggle-switch">
<div class="toggle-slider"></div>
</div>
</div>
<div class="setting-item">
<span class="setting-label">자동 번역</span>
<select id="language-select">
<option value="">비활성화</option>
<option value="ko">한국어 (Korean)</option>
<option value="en">English</option>
<option value="es">Español (Spanish)</option>
<option value="fr">Français (French)</option>
<option value="de">Deutsch (German)</option>
<option value="it">Italiano (Italian)</option>
<option value="pt">Português (Portuguese)</option>
<option value="ru">Русский (Russian)</option>
<option value="ja">日本語 (Japanese)</option>
<option value="zh">中文 (Chinese)</option>
<option value="ar">العربية (Arabic)</option>
<option value="hi">हिन्दी (Hindi)</option>
<option value="nl">Nederlands (Dutch)</option>
<option value="pl">Polski (Polish)</option>
<option value="tr">Türkçe (Turkish)</option>
<option value="vi">Tiếng Việt (Vietnamese)</option>
<option value="th">ไทย (Thai)</option>
<option value="id">Bahasa Indonesia</option>
<option value="sv">Svenska (Swedish)</option>
<option value="da">Dansk (Danish)</option>
<option value="no">Norsk (Norwegian)</option>
<option value="fi">Suomi (Finnish)</option>
<option value="he">עברית (Hebrew)</option>
<option value="uk">Українська (Ukrainian)</option>
<option value="cs">Čeština (Czech)</option>
<option value="el">Ελληνικά (Greek)</option>
<option value="ro">Română (Romanian)</option>
<option value="hu">Magyar (Hungarian)</option>
<option value="ms">Bahasa Melayu (Malay)</option>
</select>
</div>
</div>
<div class="interpretation-section">
<div class="setting-item">
<span class="setting-label">자동 통역</span>
<div id="interpretation-toggle" class="toggle-switch">
<div class="toggle-slider"></div>
</div>
</div>
<div class="setting-item" id="interpretation-language-container" style="display: none;">
<span class="setting-label">통역 언어</span>
<select id="interpretation-language-select">
<option value="">언어 선택</option>
<option value="ko">한국어 (Korean)</option>
<option value="en">English</option>
<option value="es">Español (Spanish)</option>
<option value="fr">Français (French)</option>
<option value="de">Deutsch (German)</option>
<option value="it">Italiano (Italian)</option>
<option value="pt">Português (Portuguese)</option>
<option value="ru">Русский (Russian)</option>
<option value="ja">日本語 (Japanese)</option>
<option value="zh">中文 (Chinese)</option>
<option value="ar">العربية (Arabic)</option>
<option value="hi">हिन्दी (Hindi)</option>
<option value="nl">Nederlands (Dutch)</option>
<option value="pl">Polski (Polish)</option>
<option value="tr">Türkçe (Turkish)</option>
<option value="vi">Tiếng Việt (Vietnamese)</option>
<option value="th">ไทย (Thai)</option>
<option value="id">Bahasa Indonesia</option>
<option value="sv">Svenska (Swedish)</option>
<option value="da">Dansk (Danish)</option>
<option value="no">Norsk (Norwegian)</option>
<option value="fi">Suomi (Finnish)</option>
<option value="he">עברית (Hebrew)</option>
<option value="uk">Українська (Ukrainian)</option>
<option value="cs">Čeština (Czech)</option>
<option value="el">Ελληνικά (Greek)</option>
<option value="ro">Română (Romanian)</option>
<option value="hu">Magyar (Hungarian)</option>
<option value="ms">Bahasa Melayu (Malay)</option>
</select>
</div>
</div>
<div class="interpretation-info" id="interpretation-info" style="display: none;">
통역 모드: 입력한 음성이 선택한 언어로 자동 통역됩니다.
</div>
<div class="text-input-section">
<label for="system-prompt" class="setting-label">시스템 프롬프트:</label>
<textarea id="system-prompt" placeholder="AI 어시스턴트의 성격, 역할, 행동 방식을 정의하세요...">You are a helpful assistant. Respond in a friendly and professional manner.</textarea>
</div>
</div>
<div class="controls">
<button id="start-button">대화 시작</button>
</div>
</div>
<div class="chat-section">
<div class="chat-container">
<h3 style="margin: 0 0 15px 0; color: var(--primary-color);">대화</h3>
<div class="chat-messages" id="chat-messages"></div>
<div class="text-input-section" style="margin-top: 10px;">
<div style="display: flex; gap: 10px;">
<input type="text" id="text-input" placeholder="텍스트 메시지를 입력하세요..." style="flex-grow: 1;" />
<button id="send-button" style="display: none;">전송</button>
</div>
</div>
</div>
</div>
</div>
</div>
<audio id="audio-output"></audio>
<script>
let peerConnection;
let webrtc_id;
let webSearchEnabled = false;
let selectedLanguage = "";
let interpretationMode = false;
let interpretationLanguage = "";
let systemPrompt = "You are a helpful assistant. Respond in a friendly and professional manner.";
const audioOutput = document.getElementById('audio-output');
const startButton = document.getElementById('start-button');
const sendButton = document.getElementById('send-button');
const chatMessages = document.getElementById('chat-messages');
const statusDot = document.getElementById('status-dot');
const statusText = document.getElementById('status-text');
const searchToggle = document.getElementById('search-toggle');
const languageSelect = document.getElementById('language-select');
const interpretationToggle = document.getElementById('interpretation-toggle');
const interpretationLanguageSelect = document.getElementById('interpretation-language-select');
const interpretationLanguageContainer = document.getElementById('interpretation-language-container');
const interpretationInfo = document.getElementById('interpretation-info');
const systemPromptInput = document.getElementById('system-prompt');
const textInput = document.getElementById('text-input');
let audioLevel = 0;
let animationFrame;
let audioContext, analyser, audioSource;
let dataChannel = null;
let isVoiceActive = false;
// Web search toggle functionality
searchToggle.addEventListener('click', () => {
webSearchEnabled = !webSearchEnabled;
searchToggle.classList.toggle('active', webSearchEnabled);
console.log('Web search enabled:', webSearchEnabled);
});
// Language selection
languageSelect.addEventListener('change', () => {
selectedLanguage = languageSelect.value;
console.log('Selected language:', selectedLanguage);
});
// Interpretation mode toggle
interpretationToggle.addEventListener('click', () => {
if (!interpretationMode) {
// Turning ON interpretation mode
interpretationLanguageContainer.style.display = 'flex';
interpretationInfo.style.display = 'block';
// Show language selector first
showError('통역 언어를 선택해주세요.');
interpretationToggle.classList.remove('active');
// Don't actually enable interpretation mode until language is selected
return;
} else {
// Turning OFF interpretation mode
interpretationMode = false;
interpretationToggle.classList.remove('active');
interpretationLanguageContainer.style.display = 'none';
interpretationInfo.style.display = 'none';
interpretationLanguage = '';
interpretationLanguageSelect.value = '';
// Re-enable other features
languageSelect.disabled = false;
searchToggle.style.opacity = '1';
searchToggle.style.pointerEvents = 'auto';
textInput.disabled = false;
textInput.placeholder = '텍스트 메시지를 입력하세요...';
sendButton.style.display = 'block';
console.log('Interpretation mode disabled');
}
console.log('Interpretation mode:', interpretationMode);
});
// Interpretation language selection
interpretationLanguageSelect.addEventListener('change', () => {
interpretationLanguage = interpretationLanguageSelect.value;
console.log('Interpretation language:', interpretationLanguage);
if (interpretationLanguage && !interpretationMode) {
// Now actually enable interpretation mode
interpretationMode = true;
interpretationToggle.classList.add('active');
// Disable other features
languageSelect.value = '';
selectedLanguage = '';
languageSelect.disabled = true;
searchToggle.classList.remove('active');
webSearchEnabled = false;
searchToggle.style.opacity = '0.5';
searchToggle.style.pointerEvents = 'none';
textInput.disabled = true;
textInput.placeholder = '통역 모드에서는 텍스트 입력이 지원되지 않습니다';
sendButton.style.display = 'none';
console.log('Interpretation mode enabled with language:', interpretationLanguage);
}
});
// System prompt update
systemPromptInput.addEventListener('input', () => {
systemPrompt = systemPromptInput.value || "You are a helpful assistant. Respond in a friendly and professional manner.";
});
// Text input handling
textInput.addEventListener('keypress', (e) => {
if (e.key === 'Enter' && !e.shiftKey) {
e.preventDefault();
sendTextMessage();
}
});
sendButton.addEventListener('click', sendTextMessage);
async function sendTextMessage() {
const message = textInput.value.trim();
if (!message) return;
// Don't allow text messages in interpretation mode
if (interpretationMode) {
showError('통역 모드에서는 텍스트 입력이 지원되지 않습니다.');
return;
}
// Add user message to chat
addMessage('user', message);
textInput.value = '';
// Show sending indicator
const typingIndicator = document.createElement('div');
typingIndicator.classList.add('message', 'assistant');
typingIndicator.textContent = '입력 중...';
typingIndicator.id = 'typing-indicator';
chatMessages.appendChild(typingIndicator);
chatMessages.scrollTop = chatMessages.scrollHeight;
try {
// Send to text chat endpoint
const response = await fetch('/chat/text', {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({
message: message,
web_search_enabled: webSearchEnabled,
target_language: selectedLanguage,
system_prompt: systemPrompt
})
});
const data = await response.json();
// Remove typing indicator
const indicator = document.getElementById('typing-indicator');
if (indicator) indicator.remove();
if (data.error) {
showError(data.error);
} else {
// Add assistant response
let content = data.response;
if (selectedLanguage && data.language) {
content += ` <span class="language-info">[${data.language}]</span>`;
}
addMessage('assistant', content);
}
} catch (error) {
console.error('Error sending text message:', error);
const indicator = document.getElementById('typing-indicator');
if (indicator) indicator.remove();
showError('메시지 전송 중 오류가 발생했습니다.');
}
}
function updateStatus(state) {
statusDot.className = 'status-dot ' + state;
if (state === 'connected') {
statusText.textContent = '연결됨';
if (!interpretationMode) {
sendButton.style.display = 'block';
}
isVoiceActive = true;
} else if (state === 'connecting') {
statusText.textContent = '연결 중...';
sendButton.style.display = 'none';
} else {
statusText.textContent = '연결 대기 중';
if (!interpretationMode) {
sendButton.style.display = 'block'; // Show send button even when disconnected for text chat
}
isVoiceActive = false;
}
}
function updateButtonState() {
const button = document.getElementById('start-button');
if (peerConnection && (peerConnection.connectionState === 'connecting' || peerConnection.connectionState === 'new')) {
button.innerHTML = `
<div class="icon-with-spinner">
<div class="spinner"></div>
<span>연결 중...</span>
</div>
`;
updateStatus('connecting');
} else if (peerConnection && peerConnection.connectionState === 'connected') {
button.innerHTML = `
<div class="icon-with-spinner">
<div class="audio-visualizer" id="audio-visualizer">
<div class="visualizer-bar"></div>
<div class="visualizer-bar"></div>
<div class="visualizer-bar"></div>
<div class="visualizer-bar"></div>
<div class="visualizer-bar"></div>
</div>
<span>대화 종료</span>
</div>
`;
updateStatus('connected');
} else {
button.innerHTML = '대화 시작';
updateStatus('disconnected');
}
}
function setupAudioVisualization(stream) {
audioContext = new (window.AudioContext || window.webkitAudioContext)();
analyser = audioContext.createAnalyser();
audioSource = audioContext.createMediaStreamSource(stream);
audioSource.connect(analyser);
analyser.fftSize = 256;
const bufferLength = analyser.frequencyBinCount;
const dataArray = new Uint8Array(bufferLength);
const visualizerBars = document.querySelectorAll('.visualizer-bar');
const barCount = visualizerBars.length;
function updateAudioLevel() {
analyser.getByteFrequencyData(dataArray);
for (let i = 0; i < barCount; i++) {
const start = Math.floor(i * (bufferLength / barCount));
const end = Math.floor((i + 1) * (bufferLength / barCount));
let sum = 0;
for (let j = start; j < end; j++) {
sum += dataArray[j];
}
const average = sum / (end - start) / 255;
const scaleY = 0.1 + average * 0.9;
visualizerBars[i].style.transform = `scaleY(${scaleY})`;
}
animationFrame = requestAnimationFrame(updateAudioLevel);
}
updateAudioLevel();
}
function showError(message) {
const toast = document.getElementById('error-toast');
toast.textContent = message;
toast.className = 'toast error';
toast.style.display = 'block';
setTimeout(() => {
toast.style.display = 'none';
}, 5000);
}
async function setupWebRTC() {
const config = __RTC_CONFIGURATION__;
peerConnection = new RTCPeerConnection(config);
const timeoutId = setTimeout(() => {
const toast = document.getElementById('error-toast');
toast.textContent = "연결이 평소보다 오래 걸리고 있습니다. VPN을 사용 중이신가요?";
toast.className = 'toast warning';
toast.style.display = 'block';
setTimeout(() => {
toast.style.display = 'none';
}, 5000);
}, 5000);
try {
const stream = await navigator.mediaDevices.getUserMedia({
audio: true
});
setupAudioVisualization(stream);
stream.getTracks().forEach(track => {
peerConnection.addTrack(track, stream);
});
peerConnection.addEventListener('track', (evt) => {
if (audioOutput.srcObject !== evt.streams[0]) {
audioOutput.srcObject = evt.streams[0];
audioOutput.play();
}
});
// Create data channel for text messages
dataChannel = peerConnection.createDataChannel('text');
dataChannel.onopen = () => {
console.log('Data channel opened');
};
dataChannel.onmessage = (event) => {
const eventJson = JSON.parse(event.data);
if (eventJson.type === "error") {
showError(eventJson.message);
}
};
const offer = await peerConnection.createOffer();
await peerConnection.setLocalDescription(offer);
await new Promise((resolve) => {
if (peerConnection.iceGatheringState === "complete") {
resolve();
} else {
const checkState = () => {
if (peerConnection.iceGatheringState === "complete") {
peerConnection.removeEventListener("icegatheringstatechange", checkState);
resolve();
}
};
peerConnection.addEventListener("icegatheringstatechange", checkState);
}
});
peerConnection.addEventListener('connectionstatechange', () => {
console.log('connectionstatechange', peerConnection.connectionState);
if (peerConnection.connectionState === 'connected') {
clearTimeout(timeoutId);
const toast = document.getElementById('error-toast');
toast.style.display = 'none';
}
updateButtonState();
});
webrtc_id = Math.random().toString(36).substring(7);
const response = await fetch('/webrtc/offer', {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({
sdp: peerConnection.localDescription.sdp,
type: peerConnection.localDescription.type,
webrtc_id: webrtc_id,
web_search_enabled: webSearchEnabled,
target_language: selectedLanguage,
system_prompt: systemPrompt,
interpretation_mode: interpretationMode,
interpretation_language: interpretationLanguage
})
});
const serverResponse = await response.json();
if (serverResponse.status === 'failed') {
showError(serverResponse.meta.error === 'concurrency_limit_reached'
? `너무 많은 연결입니다. 최대 한도는 ${serverResponse.meta.limit} 입니다.`
: serverResponse.meta.error);
stop();
return;
}
await peerConnection.setRemoteDescription(serverResponse);
const eventSource = new EventSource('/outputs?webrtc_id=' + webrtc_id);
eventSource.addEventListener("output", (event) => {
const eventJson = JSON.parse(event.data);
let content = eventJson.content;
if (selectedLanguage && eventJson.language) {
content += ` <span class="language-info">[${eventJson.language}]</span>`;
}
addMessage("assistant", content);
});
eventSource.addEventListener("search", (event) => {
const eventJson = JSON.parse(event.data);
if (eventJson.query) {
addMessage("search-result", `웹 검색 중: "${eventJson.query}"`);
}
});
} catch (err) {
clearTimeout(timeoutId);
console.error('Error setting up WebRTC:', err);
showError('연결을 설정하지 못했습니다. 다시 시도해 주세요.');
stop();
}
}
function addMessage(role, content) {
const messageDiv = document.createElement('div');
messageDiv.classList.add('message', role);
if (content.includes('<span')) {
messageDiv.innerHTML = content;
} else {
messageDiv.textContent = content;
}
chatMessages.appendChild(messageDiv);
chatMessages.scrollTop = chatMessages.scrollHeight;
}
function stop() {
if (animationFrame) {
cancelAnimationFrame(animationFrame);
}
if (audioContext) {
audioContext.close();
audioContext = null;
analyser = null;
audioSource = null;
}
if (peerConnection) {
if (peerConnection.getTransceivers) {
peerConnection.getTransceivers().forEach(transceiver => {
if (transceiver.stop) {
transceiver.stop();
}
});
}
if (peerConnection.getSenders) {
peerConnection.getSenders().forEach(sender => {
if (sender.track && sender.track.stop) sender.track.stop();
});
}
console.log('closing');
peerConnection.close();
}
dataChannel = null;
updateButtonState();
audioLevel = 0;
}
startButton.addEventListener('click', () => {
console.log('clicked');
console.log(peerConnection, peerConnection?.connectionState);
if (!peerConnection || peerConnection.connectionState !== 'connected') {
setupWebRTC();
} else {
console.log('stopping');
stop();
}
});
// Initialize send button visibility on page load
window.addEventListener('DOMContentLoaded', () => {
sendButton.style.display = 'block';
});
</script>
</body>
</html>"""
class BraveSearchClient:
"""Brave Search API client"""
def __init__(self, api_key: str):
self.api_key = api_key
self.base_url = "https://api.search.brave.com/res/v1/web/search"
async def search(self, query: str, count: int = 10) -> List[Dict]:
"""Perform a web search using Brave Search API"""
if not self.api_key:
return []
headers = {
"Accept": "application/json",
"X-Subscription-Token": self.api_key
}
params = {
"q": query,
"count": count,
"lang": "ko"
}
async with httpx.AsyncClient() as client:
try:
response = await client.get(self.base_url, headers=headers, params=params)
response.raise_for_status()
data = response.json()
results = []
if "web" in data and "results" in data["web"]:
for result in data["web"]["results"][:count]:
results.append({
"title": result.get("title", ""),
"url": result.get("url", ""),
"description": result.get("description", "")
})
return results
except Exception as e:
print(f"Brave Search error: {e}")
return []
# Initialize search client globally
brave_api_key = os.getenv("BSEARCH_API")
search_client = BraveSearchClient(brave_api_key) if brave_api_key else None
print(f"Search client initialized: {search_client is not None}, API key present: {bool(brave_api_key)}")
# Store connection settings
connection_settings = {}
# Initialize OpenAI client for text chat
client = openai.AsyncOpenAI()
def update_chatbot(chatbot: list[dict], response: ResponseAudioTranscriptDoneEvent):
chatbot.append({"role": "assistant", "content": response.transcript})
return chatbot
def get_translation_instructions(target_language: str) -> str:
"""Get instructions for translation based on target language"""
if not target_language:
return ""
language_name = SUPPORTED_LANGUAGES.get(target_language, target_language)
return (
f"\n\nIMPORTANT: You must respond in {language_name} ({target_language}). "
f"Translate all your responses to {language_name}."
)
async def process_text_chat(message: str, web_search_enabled: bool, target_language: str,
system_prompt: str) -> Dict[str, str]:
"""Process text chat using GPT-4o-mini model"""
try:
# Prepare system message
base_instructions = system_prompt or "You are a helpful assistant."
translation_instructions = get_translation_instructions(target_language)
messages = [
{"role": "system", "content": base_instructions + translation_instructions}
]
# Handle web search if enabled
if web_search_enabled and search_client:
# Check if the message requires web search
search_keywords = ["날씨", "기온", "비", "눈", "뉴스", "소식", "현재", "최근",
"오늘", "지금", "가격", "환율", "주가", "weather", "news",
"current", "today", "price", "2024", "2025"]
should_search = any(keyword in message.lower() for keyword in search_keywords)
if should_search:
# Perform web search
search_results = await search_client.search(message)
if search_results:
search_context = "웹 검색 결과:\n\n"
for i, result in enumerate(search_results[:5], 1):
search_context += f"{i}. {result['title']}\n{result['description']}\n\n"
messages.append({
"role": "system",
"content": f"다음 웹 검색 결과를 참고하여 답변하세요:\n\n{search_context}"
})
messages.append({"role": "user", "content": message})
# Call GPT-4o-mini
response = await client.chat.completions.create(
model="gpt-4o-mini",
messages=messages,
temperature=0.7,
max_tokens=2000
)
return {
"response": response.choices[0].message.content,
"language": SUPPORTED_LANGUAGES.get(target_language, "") if target_language else ""
}
except Exception as e:
print(f"Error in text chat: {e}")
return {"error": str(e)}
class OpenAIHandler(AsyncStreamHandler):
def __init__(self, web_search_enabled: bool = False, target_language: str = "",
system_prompt: str = "", webrtc_id: str = None,
interpretation_mode: bool = False, interpretation_language: str = "") -> None:
super().__init__(
expected_layout="mono",
output_sample_rate=SAMPLE_RATE,
output_frame_size=480,
input_sample_rate=SAMPLE_RATE,
)
self.connection = None
self.output_queue = asyncio.Queue()
self.search_client = search_client
self.function_call_in_progress = False
self.current_function_args = ""
self.current_call_id = None
self.webrtc_id = webrtc_id
self.web_search_enabled = web_search_enabled
self.target_language = target_language
self.system_prompt = system_prompt
self.interpretation_mode = interpretation_mode
self.interpretation_language = interpretation_language
print(f"Handler created with web_search_enabled={web_search_enabled}, "
f"target_language={target_language}, webrtc_id={webrtc_id}, "
f"interpretation_mode={interpretation_mode}, interpretation_language={interpretation_language}")
def copy(self):
# Get the most recent settings
if connection_settings:
# Get the most recent webrtc_id
recent_ids = sorted(connection_settings.keys(),
key=lambda k: connection_settings[k].get('timestamp', 0),
reverse=True)
if recent_ids:
recent_id = recent_ids[0]
settings = connection_settings[recent_id]
return OpenAIHandler(
web_search_enabled=settings.get('web_search_enabled', False),
target_language=settings.get('target_language', ''),
system_prompt=settings.get('system_prompt', ''),
webrtc_id=recent_id,
interpretation_mode=settings.get('interpretation_mode', False),
interpretation_language=settings.get('interpretation_language', '')
)
print(f"Handler.copy() called - creating new handler with default settings")
return OpenAIHandler(web_search_enabled=False)
async def search_web(self, query: str) -> str:
"""Perform web search and return formatted results"""
if not self.search_client or not self.web_search_enabled:
return "웹 검색이 비활성화되어 있습니다."
print(f"Searching web for: {query}")
results = await self.search_client.search(query)
if not results:
return f"'{query}'에 대한 검색 결과를 찾을 수 없습니다."
# Format search results
formatted_results = []
for i, result in enumerate(results, 1):
formatted_results.append(
f"{i}. {result['title']}\n"
f" URL: {result['url']}\n"
f" {result['description']}\n"
)
return f"웹 검색 결과 '{query}':\n\n" + "\n".join(formatted_results)
async def process_text_message(self, message: str):
"""Process text message from user"""
if self.connection:
await self.connection.conversation.item.create(
item={
"type": "message",
"role": "user",
"content": [{"type": "input_text", "text": message}]
}
)
await self.connection.response.create()
def get_interpretation_instructions(self):
"""Get instructions for interpretation mode"""
if not self.interpretation_mode or not self.interpretation_language:
return ""
target_language_name = SUPPORTED_LANGUAGES.get(self.interpretation_language, self.interpretation_language)
target_code = self.interpretation_language
# Language-specific examples
examples = {
"en": "Hello, the weather is nice today",
"es": "Hola, el clima está agradable hoy",
"fr": "Bonjour, il fait beau aujourd'hui",
"de": "Hallo, das Wetter ist heute schön",
"ja": "こんにちは、今日はいい天気ですね",
"zh": "你好，今天天气很好"
}
example_translation = examples.get(target_code, "Hello, the weather is nice today")
return (
f"INTERPRETATION MODE - CRITICAL RULES:\n\n"
f"1. You are ONLY a translator to {target_language_name} (language code: {target_code}).\n"
f"2. NEVER respond in any other language.\n"
f"3. NEVER generate conversation or additional content.\n"
f"4. ONLY translate what the user says.\n"
f"5. STOP immediately after translating.\n\n"
f"Example:\n"
f"If user says: '안녕하세요, 오늘 날씨가 좋네요'\n"
f"You MUST respond ONLY: '{example_translation}'\n\n"
f"DO NOT say anything else. DO NOT continue talking.\n"
f"Your output language MUST be {target_language_name} ONLY."
)
def get_translation_instructions(self):
"""Get instructions for translation based on target language"""
if not self.target_language or self.interpretation_mode:
return ""
language_name = SUPPORTED_LANGUAGES.get(self.target_language, self.target_language)
return (
f"\n\nIMPORTANT: You must respond in {language_name} ({self.target_language}). "
f"Translate all your responses to {language_name}. "
f"This includes both spoken and written responses."
)
async def start_up(self):
"""Connect to realtime API with function calling enabled"""
# First check if we have the most recent settings
if connection_settings:
recent_ids = sorted(connection_settings.keys(),
key=lambda k: connection_settings[k].get('timestamp', 0),
reverse=True)
if recent_ids:
recent_id = recent_ids[0]
settings = connection_settings[recent_id]
self.web_search_enabled = settings.get('web_search_enabled', False)
self.target_language = settings.get('target_language', '')
self.system_prompt = settings.get('system_prompt', '')
self.interpretation_mode = settings.get('interpretation_mode', False)
self.interpretation_language = settings.get('interpretation_language', '')
self.webrtc_id = recent_id
print(f"start_up: Updated settings from storage - webrtc_id={self.webrtc_id}, "
f"web_search_enabled={self.web_search_enabled}, target_language={self.target_language}, "
f"interpretation_mode={self.interpretation_mode}")
print(f"Handler interpretation settings: mode={self.interpretation_mode}, language={self.interpretation_language}")
print(f"Starting up handler with web_search_enabled={self.web_search_enabled}, "
f"target_language={self.target_language}, interpretation_mode={self.interpretation_mode}, "
f"interpretation_language={self.interpretation_language}")
self.client = openai.AsyncOpenAI()
# Define the web search function
tools = []
base_instructions = self.system_prompt or "You are a helpful assistant."
# Check if in interpretation mode
if self.interpretation_mode:
# In interpretation mode, override all instructions
base_instructions = (
f"You are a professional interpreter. Your ONLY task is to translate what the user says "
f"into {SUPPORTED_LANGUAGES.get(self.interpretation_language, self.interpretation_language)}. "
f"Do not add any commentary, do not continue the conversation, do not generate new content. "
f"Simply translate what was said and stop."
)
interpretation_instructions = self.get_interpretation_instructions()
instructions = base_instructions + "\n\n" + interpretation_instructions
# No tools in interpretation mode
tools = []
print(f"Interpretation mode active - target language: {self.interpretation_language}")
else:
# Normal mode - add translation instructions if language is selected
translation_instructions = self.get_translation_instructions()
if self.web_search_enabled and self.search_client:
tools = [{
"type": "function",
"function": {
"name": "web_search",
"description": "Search the web for current information. Use this for weather, news, prices, current events, or any time-sensitive topics.",
"parameters": {
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "The search query"
}
},
"required": ["query"]
}
}
}]
print("Web search function added to tools")
search_instructions = (
"\n\nYou have web search capabilities. "
"IMPORTANT: You MUST use the web_search function for ANY of these topics:\n"
"- Weather (날씨, 기온, 비, 눈)\n"
"- News (뉴스, 소식)\n"
"- Current events (현재, 최근, 오늘, 지금)\n"
"- Prices (가격, 환율, 주가)\n"
"- Sports scores or results\n"
"- Any question about 2024 or 2025\n"
"- Any time-sensitive information\n\n"
"When in doubt, USE web_search. It's better to search and provide accurate information "
"than to guess or use outdated information."
)
instructions = base_instructions + search_instructions + translation_instructions
else:
instructions = base_instructions + translation_instructions
async with self.client.beta.realtime.connect(
model="gpt-4o-mini-realtime-preview-2024-12-17"
) as conn:
# Update session with tools
session_update = {
"turn_detection": {
"type": "server_vad",
"threshold": 0.5,
"prefix_padding_ms": 300,
"silence_duration_ms": 500 if self.interpretation_mode else 700
},
"instructions": instructions,
"tools": tools,
"tool_choice": "auto" if tools else "none"
}
# Add voice setting based on interpretation or translation language
voice_language = self.interpretation_language if self.interpretation_mode else self.target_language
if voice_language:
# Use only alloy voice to avoid language confusion
# The model will handle the language based on instructions
session_update["voice"] = "alloy"
# For interpretation mode, explicitly set the output language
if self.interpretation_mode:
session_update["output_audio_format"] = "pcm16"
print(f"Voice set to: alloy for language: {voice_language}")
# For interpretation mode, ensure proper language settings
if self.interpretation_mode and self.interpretation_language:
session_update["modalities"] = ["text", "audio"]
session_update["temperature"] = 0.3 # Lower temperature for more accurate translation
session_update["max_response_output_tokens"] = 500 # Limit output to prevent long generations
print(f"Interpretation session config: voice={session_update.get('voice')}, lang={self.interpretation_language}")
await conn.session.update(session=session_update)
self.connection = conn
print(f"Connected with tools: {len(tools)} functions, voice: {session_update.get('voice', 'default')}, "
f"interpretation_mode: {self.interpretation_mode}, language: {self.interpretation_language if self.interpretation_mode else self.target_language}")
async for event in self.connection:
# Debug logging for function calls
if event.type.startswith("response.function_call"):
print(f"Function event: {event.type}")
if event.type == "response.audio_transcript.done":
output_data = {
"event": event,
"language": SUPPORTED_LANGUAGES.get(
self.interpretation_language if self.interpretation_mode else self.target_language,
""
) if (self.interpretation_language or self.target_language) else ""
}
await self.output_queue.put(AdditionalOutputs(output_data))
elif event.type == "response.audio.delta":
await self.output_queue.put(
(
self.output_sample_rate,
np.frombuffer(
base64.b64decode(event.delta), dtype=np.int16
).reshape(1, -1),
),
)
# Handle function calls (only in non-interpretation mode)
elif event.type == "response.function_call_arguments.start" and not self.interpretation_mode:
print(f"Function call started")
self.function_call_in_progress = True
self.current_function_args = ""
self.current_call_id = getattr(event, 'call_id', None)
elif event.type == "response.function_call_arguments.delta" and not self.interpretation_mode:
if self.function_call_in_progress:
self.current_function_args += event.delta
elif event.type == "response.function_call_arguments.done" and not self.interpretation_mode:
if self.function_call_in_progress:
print(f"Function call done, args: {self.current_function_args}")
try:
args = json.loads(self.current_function_args)
query = args.get("query", "")
# Emit search event to client
await self.output_queue.put(AdditionalOutputs({
"type": "search",
"query": query
}))
# Perform the search
search_results = await self.search_web(query)
print(f"Search results length: {len(search_results)}")
# Send function result back to the model
if self.connection and self.current_call_id:
await self.connection.conversation.item.create(
item={
"type": "function_call_output",
"call_id": self.current_call_id,
"output": search_results
}
)
await self.connection.response.create()
except Exception as e:
print(f"Function call error: {e}")
finally:
self.function_call_in_progress = False
self.current_function_args = ""
self.current_call_id = None
async def receive(self, frame: tuple[int, np.ndarray]) -> None:
if not self.connection:
return
try:
_, array = frame
array = array.squeeze()
audio_message = base64.b64encode(array.tobytes()).decode("utf-8")
await self.connection.input_audio_buffer.append(audio=audio_message)
except Exception as e:
print(f"Error in receive: {e}")
# Connection might be closed, ignore the error
async def emit(self) -> tuple[int, np.ndarray] | AdditionalOutputs | None:
item = await wait_for_item(self.output_queue)
# Check if it's a dict with text message
if isinstance(item, dict) and item.get('type') == 'text_message':
await self.process_text_message(item['content'])
return None
return item
async def shutdown(self) -> None:
if self.connection:
await self.connection.close()
self.connection = None
# Create initial handler instance
handler = OpenAIHandler(web_search_enabled=False, interpretation_mode=False)
# Create components
chatbot = gr.Chatbot(type="messages")
# Create stream with handler instance
stream = Stream(
handler, # Pass instance, not factory
mode="send-receive",
modality="audio",
additional_inputs=[chatbot],
additional_outputs=[chatbot],
additional_outputs_handler=update_chatbot,
rtc_configuration=get_twilio_turn_credentials() if get_space() else None,
concurrency_limit=5 if get_space() else None,
time_limit=300 if get_space() else None,
)
app = FastAPI()
# Mount stream
stream.mount(app)
# Intercept offer to capture settings
@app.post("/webrtc/offer", include_in_schema=False)
async def custom_offer(request: Request):
"""Intercept offer to capture settings"""
body = await request.json()
webrtc_id = body.get("webrtc_id")
web_search_enabled = body.get("web_search_enabled", False)
target_language = body.get("target_language", "")
system_prompt = body.get("system_prompt", "")
interpretation_mode = body.get("interpretation_mode", False)
interpretation_language = body.get("interpretation_language", "")
print(f"Custom offer - webrtc_id: {webrtc_id}, web_search_enabled: {web_search_enabled}, "
f"target_language: {target_language}, interpretation_mode: {interpretation_mode}, "
f"interpretation_language: {interpretation_language}")
# Store settings with timestamp
if webrtc_id:
connection_settings[webrtc_id] = {
'web_search_enabled': web_search_enabled,
'target_language': target_language,
'system_prompt': system_prompt,
'interpretation_mode': interpretation_mode,
'interpretation_language': interpretation_language,
'timestamp': asyncio.get_event_loop().time()
}
# Remove our custom route temporarily
custom_route = None
for i, route in enumerate(app.routes):
if hasattr(route, 'path') and route.path == "/webrtc/offer" and route.endpoint == custom_offer:
custom_route = app.routes.pop(i)
break
# Forward to stream's offer handler
response = await stream.offer(body)
# Re-add our custom route
if custom_route:
app.routes.insert(0, custom_route)
return response
@app.post("/chat/text")
async def chat_text(request: Request):
"""Handle text chat messages using GPT-4o-mini"""
try:
body = await request.json()
message = body.get("message", "")
web_search_enabled = body.get("web_search_enabled", False)
target_language = body.get("target_language", "")
system_prompt = body.get("system_prompt", "")
if not message:
return {"error": "메시지가 비어있습니다."}
# Process text chat
result = await process_text_chat(message, web_search_enabled, target_language, system_prompt)
return result
except Exception as e:
print(f"Error in chat_text endpoint: {e}")
return {"error": "채팅 처리 중 오류가 발생했습니다."}
@app.post("/text_message/{webrtc_id}")
async def receive_text_message(webrtc_id: str, request: Request):
"""Receive text message from client"""
body = await request.json()
message = body.get("content", "")
# Find the handler for this connection
if webrtc_id in stream.handlers:
handler = stream.handlers[webrtc_id]
# Queue the text message for processing
await handler.output_queue.put({
'type': 'text_message',
'content': message
})
return {"status": "ok"}
@app.get("/outputs")
async def outputs(webrtc_id: str):
"""Stream outputs including search events"""
async def output_stream():
async for output in stream.output_stream(webrtc_id):
if hasattr(output, 'args') and output.args:
# Check if it's a search event
if isinstance(output.args[0], dict) and output.args[0].get('type') == 'search':
yield f"event: search\ndata: {json.dumps(output.args[0])}\n\n"
# Regular transcript event with language info
elif isinstance(output.args[0], dict) and 'event' in output.args[0]:
event = output.args[0]['event']
if hasattr(event, 'transcript'):
data = {
"role": "assistant",
"content": event.transcript,
"language": output.args[0].get('language', '')
}
yield f"event: output\ndata: {json.dumps(data)}\n\n"
return StreamingResponse(output_stream(), media_type="text/event-stream")
@app.get("/")
async def index():
"""Serve the HTML page"""
rtc_config = get_twilio_turn_credentials() if get_space() else None
html_content = HTML_CONTENT.replace("__RTC_CONFIGURATION__", json.dumps(rtc_config))
return HTMLResponse(content=html_content)
if __name__ == "__main__":
import uvicorn
mode = os.getenv("MODE")
if mode == "UI":
stream.ui.launch(server_port=7860)
elif mode == "PHONE":
stream.fastphone(host="0.0.0.0", port=7860)
else:
uvicorn.run(app, host="0.0.0.0", port=7860) |