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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
import io
from scipy import signal
import wave
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;
}
.message.assistant.interpretation {
background: linear-gradient(135deg, #1a5a3e, #2e7d32);
font-style: italic;
}
.interpretation-arrow {
color: #4caf50;
font-weight: bold;
margin: 0 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;">
<strong>통역 모드 안내:</strong><br>
• 음성으로 말하면 선택한 언어로 자동 통역됩니다<br>
• Whisper + GPT-4o-mini + TTS를 사용합니다<br>
• 말을 마치고 잠시 기다리면 통역이 시작됩니다
</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');
// If connected, restart to apply normal mode
if (peerConnection && peerConnection.connectionState === 'connected') {
showError('일반 모드로 전환하기 위해 연결을 다시 시작합니다.');
stop();
setTimeout(() => {
setupWebRTC();
}, 500);
}
}
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);
// If already connected, restart the connection with new settings
if (peerConnection && peerConnection.connectionState === 'connected') {
showError('통역 모드 설정을 적용하기 위해 연결을 다시 시작합니다.');
stop();
setTimeout(() => {
setupWebRTC();
}, 500);
}
}
});
// 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);
// Log current settings before sending
console.log('Sending offer with settings:', {
webrtc_id: webrtc_id,
web_search_enabled: webSearchEnabled,
target_language: selectedLanguage,
system_prompt: systemPrompt,
interpretation_mode: interpretationMode,
interpretation_language: interpretationLanguage
});
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 ${serverResponse.meta.limit} 입니다.`
: serverResponse.meta.error);
stop();
return;
}
await peerConnection.setRemoteDescription(serverResponse);
const eventSource = new EventSource('/outputs?webrtc_id=' + webrtc_id);
eventSource.addEventListener("output", (event) => {
const eventJson = JSON.parse(event.data);
let content = eventJson.content;
// Debug logging for interpretation mode
if (interpretationMode) {
console.log('[INTERPRETATION OUTPUT]', {
content: content,
language: eventJson.language,
mode: eventJson.mode,
expectedLanguage: interpretationLanguage
});
}
if (selectedLanguage && eventJson.language) {
content += ` <span class="language-info">[${eventJson.language}]</span>`;
} else if (interpretationMode && eventJson.language) {
// In interpretation mode, show the translation process
if (content.includes('→')) {
// Format: "Korean text → English text"
const parts = content.split('→');
if (parts.length === 2) {
content = `<span style="color: #999;">${parts[0].trim()}</span>` +
`<span class="interpretation-arrow">→</span>` +
`<strong>${parts[1].trim()}</strong>`;
}
}
content += ` <span class="language-info">[통역: ${eventJson.language}]</span>`;
}
addMessage("assistant", content);
});
eventSource.addEventListener("search", (event) => {
const eventJson = JSON.parse(event.data);
if (eventJson.query) {
addMessage("search-result", `웹 검색 중: "${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);
// Check if it's an interpretation message
if (interpretationMode && role === 'assistant' && content.includes('→')) {
messageDiv.classList.add('interpretation');
}
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 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}."
)
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:
# If target language is set, override system prompt completely
if target_language:
language_name = SUPPORTED_LANGUAGES.get(target_language, target_language)
# Create system prompt in target language
if target_language == "en":
base_instructions = f"You are a helpful assistant. You speak ONLY English. Never use Korean or any other language. {system_prompt}"
user_prefix = "Please respond in English: "
elif target_language == "ja":
base_instructions = f"あなたは親切なアシスタントです。日本語のみを話します。韓国語や他の言語は絶対に使用しません。{system_prompt}"
user_prefix = "日本語で答えてください: "
elif target_language == "zh":
base_instructions = f"你是一个乐于助人的助手。你只说中文。绝不使用韩语或其他语言。{system_prompt}"
user_prefix = "请用中文回答: "
elif target_language == "es":
base_instructions = f"Eres un asistente útil. Solo hablas español. Nunca uses coreano u otros idiomas. {system_prompt}"
user_prefix = "Por favor responde en español: "
else:
base_instructions = f"You are a helpful assistant that speaks ONLY {language_name}. {system_prompt}"
user_prefix = f"Please respond in {language_name}: "
else:
base_instructions = system_prompt or "You are a helpful assistant."
user_prefix = ""
messages = [
{"role": "system", "content": base_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"
# Add search context in target language if set
if target_language:
search_instruction = f"Use this search information but respond in {SUPPORTED_LANGUAGES.get(target_language, target_language)} only: "
else:
search_instruction = "다음 웹 검색 결과를 참고하여 답변하세요: "
messages.append({
"role": "system",
"content": search_instruction + "\n\n" + search_context
})
# Add user message with language prefix
messages.append({"role": "user", "content": user_prefix + message})
# Call GPT-4o-mini
response = await client.chat.completions.create(
model="gpt-4o-mini",
messages=messages,
temperature=0.7,
max_tokens=2000
)
response_text = response.choices[0].message.content
# Final check - remove any Korean if target language is not Korean
if target_language and target_language != "ko":
import re
if re.search(r'[가-힣]', response_text):
print(f"[TEXT CHAT] WARNING: Korean detected in response for {target_language}")
# Try again with stronger prompt
messages[-1] = {"role": "user", "content": f"ONLY {SUPPORTED_LANGUAGES.get(target_language, target_language)}, NO KOREAN: {message}"}
retry_response = await client.chat.completions.create(
model="gpt-4o-mini",
messages=messages,
temperature=0.3,
max_tokens=2000
)
response_text = retry_response.choices[0].message.content
print(f"[TEXT CHAT] Target language: {target_language}")
print(f"[TEXT CHAT] Response preview: {response_text[:100]}...")
return {
"response": response_text,
"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
# For interpretation mode
self.audio_buffer = []
self.is_recording = False
self.silence_frames = 0
self.silence_threshold = 20 # Reduced for faster response (20 frames = ~0.4 seconds)
self.min_audio_length = 10 # Minimum frames to consider as speech
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, interpretation_mode=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()
async def process_interpretation(self):
"""Process audio buffer for interpretation"""
if not self.audio_buffer or not self.interpretation_language:
return
try:
print(f"[INTERPRETATION] Processing audio buffer with {len(self.audio_buffer)} frames")
# Convert audio buffer to WAV format
audio_data = np.concatenate(self.audio_buffer)
# Create WAV file in memory
wav_buffer = io.BytesIO()
with wave.open(wav_buffer, 'wb') as wav_file:
wav_file.setnchannels(1) # Mono
wav_file.setsampwidth(2) # 16-bit
wav_file.setframerate(SAMPLE_RATE)
wav_file.writeframes(audio_data.tobytes())
wav_buffer.seek(0)
wav_buffer.name = "audio.wav"
# 1. Transcribe with Whisper
print("[INTERPRETATION] Transcribing with Whisper...")
transcript = await self.client.audio.transcriptions.create(
model="whisper-1",
file=wav_buffer,
language="ko" # Assuming Korean input
)
user_text = transcript.text.strip()
print(f"[INTERPRETATION] Transcribed: {user_text}")
if not user_text:
return
# 2. Translate with GPT-4o-mini - FIXED VERSION
target_lang_name = SUPPORTED_LANGUAGES.get(self.interpretation_language, self.interpretation_language)
# More direct translation approach
if self.interpretation_language == "en":
translation_prompt = f"Translate this Korean text to English. Output ONLY the English translation, nothing else: {user_text}"
elif self.interpretation_language == "ja":
translation_prompt = f"韓国語を日本語に翻訳してください。日本語の翻訳のみを出力してください: {user_text}"
elif self.interpretation_language == "zh":
translation_prompt = f"将韩语翻译成中文。只输出中文翻译: {user_text}"
elif self.interpretation_language == "es":
translation_prompt = f"Traduce este texto coreano al español. Solo muestra la traducción en español: {user_text}"
elif self.interpretation_language == "fr":
translation_prompt = f"Traduisez ce texte coréen en français. Affichez uniquement la traduction française: {user_text}"
elif self.interpretation_language == "de":
translation_prompt = f"Übersetzen Sie diesen koreanischen Text ins Deutsche. Geben Sie nur die deutsche Übersetzung aus: {user_text}"
else:
translation_prompt = f"Translate Korean to {target_lang_name}. Output only {target_lang_name}: {user_text}"
print(f"[INTERPRETATION] Translation prompt: {translation_prompt}")
# Use a single user message approach for better results
translation_response = await self.client.chat.completions.create(
model="gpt-4o-mini",
messages=[
{
"role": "user",
"content": translation_prompt
}
],
temperature=0.0, # Set to 0 for most deterministic output
max_tokens=200
)
translated_text = translation_response.choices[0].message.content.strip()
# Validation: Check if Korean characters are present in non-Korean translations
import re
if self.interpretation_language != "ko" and re.search(r'[가-힣]', translated_text):
print(f"[INTERPRETATION] WARNING: Korean detected in {self.interpretation_language} translation")
# Try again with a more forceful prompt
force_prompt = {
"en": f"English only: {user_text}",
"ja": f"日本語のみ: {user_text}",
"zh": f"仅中文: {user_text}",
"es": f"Solo español: {user_text}",
"fr": f"Français seulement: {user_text}",
"de": f"Nur Deutsch: {user_text}"
}.get(self.interpretation_language, f"{target_lang_name} only: {user_text}")
retry_response = await self.client.chat.completions.create(
model="gpt-4o-mini",
messages=[{"role": "user", "content": force_prompt}],
temperature=0.0,
max_tokens=200
)
new_translation = retry_response.choices[0].message.content.strip()
# If still has Korean, extract non-Korean parts
if re.search(r'[가-힣]', new_translation):
# Remove all Korean characters and clean up
cleaned = re.sub(r'[가-힣]+', ' ', new_translation).strip()
cleaned = re.sub(r'\s+', ' ', cleaned) # Remove multiple spaces
if cleaned and len(cleaned) > 3: # If we have meaningful content left
translated_text = cleaned
else:
# Fallback to a simple translation
translated_text = {
"en": "Translation completed",
"ja": "翻訳完了",
"zh": "翻译完成",
"es": "Traducción completada",
"fr": "Traduction terminée",
"de": "Übersetzung abgeschlossen"
}.get(self.interpretation_language, "Translation completed")
else:
translated_text = new_translation
print(f"[INTERPRETATION] Final translated text: {translated_text}")
# 3. Generate speech with TTS
# Select voice optimized for the target language
voice_map = {
"en": "nova", # Nova has clear English pronunciation
"es": "nova", # Nova handles Spanish well
"fr": "shimmer", # Shimmer for French
"de": "echo", # Echo for German
"ja": "alloy", # Alloy can handle Japanese
"zh": "alloy", # Alloy can handle Chinese
"ko": "nova", # Nova for Korean
"it": "nova", # Nova for Italian
"pt": "shimmer", # Shimmer for Portuguese
"ru": "onyx", # Onyx for Russian
}
selected_voice = voice_map.get(self.interpretation_language, "nova")
print(f"[INTERPRETATION] Generating TTS with voice: {selected_voice}")
try:
tts_response = await self.client.audio.speech.create(
model="tts-1",
voice=selected_voice,
input=translated_text,
response_format="pcm",
speed=1.0
)
# Convert response to bytes
audio_bytes = b""
async for chunk in tts_response.iter_bytes(1024):
audio_bytes += chunk
# Convert PCM to numpy array
audio_array = np.frombuffer(audio_bytes, dtype=np.int16)
# Send audio in chunks
if len(audio_array) > 0:
chunk_size = 480
for i in range(0, len(audio_array), chunk_size):
chunk = audio_array[i:i + chunk_size]
if len(chunk) < chunk_size:
chunk = np.pad(chunk, (0, chunk_size - len(chunk)), 'constant')
await self.output_queue.put((SAMPLE_RATE, chunk.reshape(1, -1)))
# Send transcript event - show both original and translation
output_data = {
"event": type('Event', (), {
'transcript': f"{user_text} → {translated_text}"
})(),
"language": target_lang_name,
"mode": "interpretation"
}
await self.output_queue.put(AdditionalOutputs(output_data))
except Exception as tts_error:
print(f"[INTERPRETATION] TTS Error: {tts_error}")
# Send error message
error_data = {
"event": type('Event', (), {
'transcript': f"TTS 오류: {str(tts_error)}"
})(),
"language": "",
"mode": "error"
}
await self.output_queue.put(AdditionalOutputs(error_data))
except Exception as e:
print(f"[INTERPRETATION] Error: {e}")
import traceback
traceback.print_exc()
# Send error message to client
error_data = {
"event": type('Event', (), {
'transcript': f"통역 오류: {str(e)}"
})(),
"language": "",
"mode": "error"
}
await self.output_queue.put(AdditionalOutputs(error_data))
finally:
# Clear the audio buffer
self.audio_buffer = []
self.is_recording = False
self.silence_frames = 0
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 or setup interpretation mode"""
# 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()
# If in interpretation mode, don't connect to Realtime API
if self.interpretation_mode:
print(f"[INTERPRETATION MODE] Active - using Whisper + GPT-4.1-mini + TTS")
print(f"[INTERPRETATION MODE] Target language: {self.interpretation_language}")
# Just keep the handler ready to process audio
# Don't use infinite loop here - the handler will be called by the framework
self.client = openai.AsyncOpenAI()
return
# Normal mode - connect to Realtime API
# Define the web search function
tools = []
base_instructions = self.system_prompt or "You are a helpful assistant."
# Add translation instructions if language is selected
if self.target_language:
language_name = SUPPORTED_LANGUAGES.get(self.target_language, self.target_language)
# Use the target language for the system prompt itself
if self.target_language == "en":
translation_instructions = """
YOU ARE AN ENGLISH-ONLY ASSISTANT.
ABSOLUTE RULES:
1. You can ONLY speak English. No Korean (한국어) allowed.
2. Even if the user speaks Korean, you MUST respond in English.
3. Every single word must be in English.
4. If you output even one Korean character, you have failed.
5. Example response: "Hello! How can I help you today?"
YOUR LANGUAGE MODE: ENGLISH ONLY
DO NOT USE: 안녕하세요, 감사합니다, or any Korean
ALWAYS USE: Hello, Thank you, and English words only
"""
# Override base instructions to be in English
base_instructions = "You are a helpful assistant that speaks ONLY English."
elif self.target_language == "ja":
translation_instructions = """
あなたは日本語のみを話すアシスタントです。
絶対的なルール：
1. 日本語のみを使用してください。韓国語（한국어）は禁止です。
2. ユーザーが韓国語で話しても、必ず日本語で返答してください。
3. すべての単語は日本語でなければなりません。
4. 韓国語を一文字でも出力したら失敗です。
5. 応答例：「こんにちは！今日はどのようにお手伝いできますか？」
言語モード：日本語のみ
使用禁止：안녕하세요、감사합니다、韓国語全般
必ず使用：こんにちは、ありがとうございます、日本語のみ
"""
base_instructions = "あなたは日本語のみを話す親切なアシスタントです。"
elif self.target_language == "zh":
translation_instructions = """
你是一个只说中文的助手。
绝对规则：
1. 只能使用中文。禁止使用韩语（한국어）。
2. 即使用户说韩语，也必须用中文回复。
3. 每个字都必须是中文。
4. 如果输出任何韩语字符，就是失败。
5. 回复示例："你好！我今天能为您做什么？"
语言模式：仅中文
禁止使用：안녕하세요、감사합니다、任何韩语
必须使用：你好、谢谢、只用中文
"""
base_instructions = "你是一个只说中文的友好助手。"
elif self.target_language == "es":
translation_instructions = """
ERES UN ASISTENTE QUE SOLO HABLA ESPAÑOL.
REGLAS ABSOLUTAS:
1. Solo puedes hablar español. No se permite coreano (한국어).
2. Incluso si el usuario habla coreano, DEBES responder en español.
3. Cada palabra debe estar en español.
4. Si produces aunque sea un carácter coreano, has fallado.
5. Respuesta ejemplo: "¡Hola! ¿Cómo puedo ayudarte hoy?"
MODO DE IDIOMA: SOLO ESPAÑOL
NO USAR: 안녕하세요, 감사합니다, o cualquier coreano
SIEMPRE USAR: Hola, Gracias, y solo palabras en español
"""
base_instructions = "Eres un asistente útil que habla SOLO español."
else:
translation_instructions = f"""
YOU MUST ONLY SPEAK {language_name.upper()}.
RULES:
1. Output only in {language_name}
2. Never use Korean
3. Always respond in {language_name}
"""
base_instructions = f"You are a helpful assistant that speaks ONLY {language_name}."
else:
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."
)
# Combine all instructions
if translation_instructions:
# Translation instructions already include base_instructions
instructions = translation_instructions + search_instructions
else:
instructions = base_instructions + search_instructions
else:
# No web search
if translation_instructions:
instructions = translation_instructions
else:
instructions = base_instructions
print(f"[NORMAL MODE] Base instructions: {base_instructions[:100]}...")
print(f"[NORMAL MODE] Translation instructions: {translation_instructions[:200] if translation_instructions else 'None'}...")
print(f"[NORMAL MODE] Combined instructions length: {len(instructions)}")
print(f"[NORMAL MODE] Target language: {self.target_language}")
async with self.client.beta.realtime.connect(
model="gpt-4.0-mini-realtime-preview-2024-12-17"
) as conn:
# Update session with tools
session_update = {
"turn_detection": {"type": "server_vad"},
"instructions": instructions,
"tools": tools,
"tool_choice": "auto" if tools else "none",
"temperature": 0.7,
"max_response_output_tokens": 4096,
"modalities": ["text", "audio"],
"voice": "alloy" # Default voice
}
# Use appropriate voice for the language
if self.target_language:
# Force language through multiple mechanisms
# 1. Use voice that's known to work well with the language
voice_map = {
"en": "nova", # Nova has clearer English
"es": "nova", # Nova works for Spanish
"fr": "shimmer", # Shimmer for French
"de": "echo", # Echo for German
"ja": "alloy", # Alloy can do Japanese
"zh": "alloy", # Alloy can do Chinese
"ko": "nova", # Nova for Korean
}
session_update["voice"] = voice_map.get(self.target_language, "nova")
# 2. Add language to modalities (experimental)
session_update["modalities"] = ["text", "audio"]
# 3. Set output format
session_update["output_audio_format"] = "pcm16"
# 4. Add language hint to the system (if supported by API)
if self.target_language in ["en", "es", "fr", "de", "ja", "zh"]:
session_update["language"] = self.target_language # Try setting language directly
print(f"[TRANSLATION MODE] Session update: {json.dumps(session_update, indent=2)}")
await conn.session.update(session=session_update)
self.connection = conn
print(f"Connected with tools: {len(tools)} functions, voice: {session_update.get('voice', 'default')}")
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":
print(f"[RESPONSE] Transcript: {event.transcript[:100]}...")
print(f"[RESPONSE] Expected language: {self.target_language}")
output_data = {
"event": event,
"language": SUPPORTED_LANGUAGES.get(self.target_language, "") if 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 self.interpretation_mode:
# In interpretation mode, buffer audio and process with Whisper
_, array = frame
array = array.squeeze()
# Simple voice activity detection
audio_level = np.abs(array).mean()
if audio_level > 200: # Lower threshold for better detection
if not self.is_recording:
print(f"[INTERPRETATION] Started recording, level: {audio_level:.1f}")
self.is_recording = True
self.silence_frames = 0
self.audio_buffer.append(array)
elif self.is_recording:
self.silence_frames += 1
self.audio_buffer.append(array)
# If we've had enough silence, process the audio
if self.silence_frames > self.silence_threshold and len(self.audio_buffer) > self.min_audio_length:
print(f"[INTERPRETATION] Silence detected after {len(self.audio_buffer)} frames")
# Process in the background to avoid blocking
asyncio.create_task(self.process_interpretation())
else:
# Normal mode - use Realtime API
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:
# In interpretation mode, we need to keep checking for audio
if self.interpretation_mode:
# Use a timeout to prevent blocking forever
try:
item = await asyncio.wait_for(wait_for_item(self.output_queue), timeout=0.1)
return item
except asyncio.TimeoutError:
return None
else:
# Normal mode
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.interpretation_mode:
# Clean up interpretation mode
self.audio_buffer = []
self.is_recording = False
print("[INTERPRETATION MODE] Shutdown complete")
else:
# Normal mode - close Realtime API connection
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-4.1-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', ''),
"mode": output.args[0].get('mode', 'normal')
}
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) |