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seawolf2357 commited on 9 days ago

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1 Parent(s): bef1173

Create app.py

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app.py +2182 -0

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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
+import aiosqlite
+from langdetect import detect, LangDetectException
+from datetime import datetime
+import uuid
+load_dotenv()
+SAMPLE_RATE = 24000
+# Use Persistent Storage path for Hugging Face Space
+# In HF Spaces, persistent storage is at /data
+if os.path.exists("/data"):
+    PERSISTENT_DIR = "/data"
+else:
+    PERSISTENT_DIR = "./data"
+os.makedirs(PERSISTENT_DIR, exist_ok=True)
+DB_PATH = os.path.join(PERSISTENT_DIR, "personal_assistant.db")
+print(f"Using persistent directory: {PERSISTENT_DIR}")
+print(f"Database path: {DB_PATH}")
+# 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>Personal AI Assistant</title>
+    <style>
+        :root {
+            --primary-color: #6f42c1;
+            --secondary-color: #563d7c;
+            --dark-bg: #121212;
+            --card-bg: #1e1e1e;
+            --text-color: #f8f9fa;
+            --border-color: #333;
+            --hover-color: #8a5cf6;
+            --memory-color: #4a9eff;
+        }
+        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;
+        }
+        .settings-grid {
+            display: flex;
+            flex-direction: column;
+            gap: 15px;
+            margin-bottom: 15px;
+        }
+        .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);
+        }
+        /* Memory section */
+        .memory-section {
+            background-color: var(--card-bg);
+            border-radius: 12px;
+            padding: 20px;
+            border: 1px solid var(--border-color);
+            max-height: 300px;
+            overflow-y: auto;
+        }
+        .memory-item {
+            padding: 10px;
+            margin-bottom: 10px;
+            background: linear-gradient(135deg, rgba(74, 158, 255, 0.1), rgba(111, 66, 193, 0.1));
+            border-radius: 6px;
+            border-left: 3px solid var(--memory-color);
+        }
+        .memory-category {
+            font-size: 12px;
+            color: var(--memory-color);
+            font-weight: bold;
+            text-transform: uppercase;
+            margin-bottom: 5px;
+        }
+        .memory-content {
+            font-size: 14px;
+            color: var(--text-color);
+        }
+        /* History section */
+        .history-section {
+            background-color: var(--card-bg);
+            border-radius: 12px;
+            padding: 20px;
+            border: 1px solid var(--border-color);
+            max-height: 200px;
+            overflow-y: auto;
+        }
+        .history-item {
+            padding: 10px;
+            margin-bottom: 10px;
+            background-color: var(--dark-bg);
+            border-radius: 6px;
+            cursor: pointer;
+            transition: background-color 0.2s;
+        }
+        .history-item:hover {
+            background-color: var(--hover-color);
+        }
+        .history-date {
+            font-size: 12px;
+            color: #888;
+        }
+        .history-preview {
+            font-size: 14px;
+            margin-top: 5px;
+            overflow: hidden;
+            text-overflow: ellipsis;
+            white-space: nowrap;
+        }
+        /* 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.memory-update {
+            background: linear-gradient(135deg, rgba(74, 158, 255, 0.2), rgba(111, 66, 193, 0.2));
+            font-size: 13px;
+            padding: 8px 12px;
+            margin-bottom: 10px;
+            border-left: 3px solid var(--memory-color);
+        }
+        .language-info {
+            font-size: 12px;
+            color: #888;
+            margin-left: 5px;
+        }
+        .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);
+        }
+        #end-session-button {
+            background: linear-gradient(135deg, #4a9eff, #3a7ed8);
+            padding: 8px 16px;
+            font-size: 13px;
+        }
+        #end-session-button:hover {
+            background: linear-gradient(135deg, #3a7ed8, #2a5eb8);
+        }
+        #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;
+        }
+        .toast.success {
+            background-color: #4caf50;
+            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;
+            }
+        }
+        .user-avatar {
+            width: 40px;
+            height: 40px;
+            background: linear-gradient(135deg, var(--primary-color), var(--secondary-color));
+            border-radius: 50%;
+            display: flex;
+            align-items: center;
+            justify-content: center;
+            font-size: 20px;
+            font-weight: bold;
+            color: white;
+        }
+    </style>
+</head>
+<body>
+    <div id="error-toast" class="toast"></div>
+    <div class="container">
+        <div class="header">
+            <div class="logo">
+                <div class="user-avatar" id="user-avatar">👤</div>
+                <h1>Personal AI Assistant</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>
+                    <div class="text-input-section">
+                        <label for="user-name" class="setting-label">사용자 이름:</label>
+                        <input type="text" id="user-name" placeholder="이름을 입력하세요..." />
+                    </div>
+                </div>
+                <div class="memory-section">
+                    <h3 style="margin: 0 0 15px 0; color: var(--memory-color);">기억된 정보</h3>
+                    <div id="memory-list"></div>
+                </div>
+                <div class="history-section">
+                    <h3 style="margin: 0 0 15px 0; color: var(--primary-color);">대화 기록</h3>
+                    <div id="history-list"></div>
+                </div>
+                <div class="controls">
+                    <button id="start-button">대화 시작</button>
+                    <button id="end-session-button" style="display: none;">기억 업데이트</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 currentSessionId = null;
+        let userName = localStorage.getItem('userName') || '';
+        let userMemories = {};
+        const audioOutput = document.getElementById('audio-output');
+        const startButton = document.getElementById('start-button');
+        const endSessionButton = document.getElementById('end-session-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 textInput = document.getElementById('text-input');
+        const historyList = document.getElementById('history-list');
+        const memoryList = document.getElementById('memory-list');
+        const userNameInput = document.getElementById('user-name');
+        const userAvatar = document.getElementById('user-avatar');
+        let audioLevel = 0;
+        let animationFrame;
+        let audioContext, analyser, audioSource;
+        let dataChannel = null;
+        let isVoiceActive = false;
+        // Initialize user name
+        userNameInput.value = userName;
+        if (userName) {
+            userAvatar.textContent = userName.charAt(0).toUpperCase();
+        }
+        userNameInput.addEventListener('input', () => {
+            userName = userNameInput.value;
+            localStorage.setItem('userName', userName);
+            if (userName) {
+                userAvatar.textContent = userName.charAt(0).toUpperCase();
+            } else {
+                userAvatar.textContent = '👤';
+            }
+        });
+        // Start new session
+        async function startNewSession() {
+            const response = await fetch('/session/new', { method: 'POST' });
+            const data = await response.json();
+            currentSessionId = data.session_id;
+            console.log('New session started:', currentSessionId);
+            loadHistory();
+            loadMemories();
+        }
+        // Load memories
+        async function loadMemories() {
+            try {
+                const response = await fetch('/memory/all');
+                const memories = await response.json();
+                userMemories = {};
+                memoryList.innerHTML = '';
+                memories.forEach(memory => {
+                    if (!userMemories[memory.category]) {
+                        userMemories[memory.category] = [];
+                    }
+                    userMemories[memory.category].push(memory.content);
+                    const item = document.createElement('div');
+                    item.className = 'memory-item';
+                    item.innerHTML = `
+                        <div class="memory-category">${memory.category}</div>
+                        <div class="memory-content">${memory.content}</div>
+                    `;
+                    memoryList.appendChild(item);
+                });
+                console.log('Loaded memories:', userMemories);
+            } catch (error) {
+                console.error('Failed to load memories:', error);
+            }
+        }
+        // End session and update memories
+        async function endSession() {
+            if (!currentSessionId) return;
+            try {
+                addMessage('memory-update', '대화 내용을 분석하여 기억을 업데이트하고 있습니다...');
+                const response = await fetch('/session/end', {
+                    method: 'POST',
+                    headers: { 'Content-Type': 'application/json' },
+                    body: JSON.stringify({ session_id: currentSessionId })
+                });
+                const result = await response.json();
+                if (result.status === 'ok') {
+                    showToast('기억이 성공적으로 업데이트되었습니다.', 'success');
+                    loadMemories();
+                    startNewSession();
+                }
+            } catch (error) {
+                console.error('Failed to end session:', error);
+                showError('기억 업데이트 중 오류가 발생했습니다.');
+            }
+        }
+        // Load conversation history
+        async function loadHistory() {
+            try {
+                const response = await fetch('/history/recent');
+                const conversations = await response.json();
+                historyList.innerHTML = '';
+                conversations.forEach(conv => {
+                    const item = document.createElement('div');
+                    item.className = 'history-item';
+                    item.innerHTML = `
+                        <div class="history-date">${new Date(conv.created_at).toLocaleString()}</div>
+                        <div class="history-preview">${conv.summary || '대화 시작'}</div>
+                    `;
+                    item.onclick = () => loadConversation(conv.id);
+                    historyList.appendChild(item);
+                });
+            } catch (error) {
+                console.error('Failed to load history:', error);
+            }
+        }
+        // Load specific conversation
+        async function loadConversation(sessionId) {
+            try {
+                const response = await fetch(`/history/${sessionId}`);
+                const messages = await response.json();
+                chatMessages.innerHTML = '';
+                messages.forEach(msg => {
+                    addMessage(msg.role, msg.content, false);
+                });
+            } catch (error) {
+                console.error('Failed to load conversation:', error);
+            }
+        }
+        // Web search toggle functionality
+        searchToggle.addEventListener('click', () => {
+            webSearchEnabled = !webSearchEnabled;
+            searchToggle.classList.toggle('active', webSearchEnabled);
+            console.log('Web search enabled:', webSearchEnabled);
+        });
+        // Text input handling
+        textInput.addEventListener('keypress', (e) => {
+            if (e.key === 'Enter' && !e.shiftKey) {
+                e.preventDefault();
+                sendTextMessage();
+            }
+        });
+        sendButton.addEventListener('click', sendTextMessage);
+        endSessionButton.addEventListener('click', endSession);
+        async function sendTextMessage() {
+            const message = textInput.value.trim();
+            if (!message) return;
+            // Check for stop words
+            const stopWords = ["중단", "그만", "스톱", "stop", "닥쳐", "멈춰", "중지"];
+            if (stopWords.some(word => message.toLowerCase().includes(word))) {
+                addMessage('assistant', '대화를 중단합니다.');
+                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,
+                        session_id: currentSessionId,
+                        user_name: userName,
+                        memories: userMemories
+                    })
+                });
+                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 (data.detected_language) {
+                        content += ` <span class="language-info">[${data.detected_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';
+                sendButton.style.display = 'block';
+                endSessionButton.style.display = 'block';
+                isVoiceActive = true;
+            } else if (state === 'connecting') {
+                statusText.textContent = '연결 중...';
+                sendButton.style.display = 'none';
+                endSessionButton.style.display = 'none';
+            } else {
+                statusText.textContent = '연결 대기 중';
+                sendButton.style.display = 'block';
+                endSessionButton.style.display = 'block';
+                isVoiceActive = false;
+            }
+        }
+        function showToast(message, type = 'info') {
+            const toast = document.getElementById('error-toast');
+            toast.textContent = message;
+            toast.className = `toast ${type}`;
+            toast.style.display = 'block';
+            setTimeout(() => {
+                toast.style.display = 'none';
+            }, 5000);
+        }
+        function showError(message) {
+            showToast(message, 'error');
+        }
+        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();
+        }
+        async function setupWebRTC() {
+            const config = __RTC_CONFIGURATION__;
+            peerConnection = new RTCPeerConnection(config);
+            const timeoutId = setTimeout(() => {
+                showToast("연결이 평소보다 오래 걸리고 있습니다. VPN을 사용 중이신가요?", 'warning');
+            }, 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,
+                        session_id: currentSessionId,
+                        user_name: userName,
+                        memories: userMemories
+                    })
+                });
+                const serverResponse = await response.json();
+                if (serverResponse.status === 'failed') {
+                    showError(serverResponse.meta.error === 'concurrency_limit_reached'
+                        ? `너무 많은 연결입니다. 최대 한도는 ${serverResponse.meta.limit} 입니다.`
+                        : serverResponse.meta.error);
+                    stop();
+                    return;
+                }
+                await peerConnection.setRemoteDescription(serverResponse);
+                const eventSource = new EventSource('/outputs?webrtc_id=' + webrtc_id);
+                eventSource.addEventListener("output", (event) => {
+                    const eventJson = JSON.parse(event.data);
+                    let content = eventJson.content;
+                    if (eventJson.detected_language) {
+                        content += ` <span class="language-info">[${eventJson.detected_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, save = true) {
+            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;
+            // Save message to database if save flag is true
+            if (save && currentSessionId && role !== 'memory-update' && role !== 'search-result') {
+                fetch('/message/save', {
+                    method: 'POST',
+                    headers: { 'Content-Type': 'application/json' },
+                    body: JSON.stringify({
+                        session_id: currentSessionId,
+                        role: role,
+                        content: content
+                    })
+                }).catch(error => console.error('Failed to save message:', error));
+            }
+        }
+        function stop() {
+            console.log('[STOP] Stopping connection...');
+            // Cancel animation frame first
+            if (animationFrame) {
+                cancelAnimationFrame(animationFrame);
+                animationFrame = null;
+            }
+            // Close audio context
+            if (audioContext) {
+                audioContext.close();
+                audioContext = null;
+                analyser = null;
+                audioSource = null;
+            }
+            // Close data channel
+            if (dataChannel) {
+                dataChannel.close();
+                dataChannel = null;
+            }
+            // Close peer connection
+            if (peerConnection) {
+                console.log('[STOP] Current connection state:', peerConnection.connectionState);
+                // Stop all transceivers
+                if (peerConnection.getTransceivers) {
+                    peerConnection.getTransceivers().forEach(transceiver => {
+                        if (transceiver.stop) {
+                            transceiver.stop();
+                        }
+                    });
+                }
+                // Stop all senders
+                if (peerConnection.getSenders) {
+                    peerConnection.getSenders().forEach(sender => {
+                        if (sender.track) {
+                            sender.track.stop();
+                        }
+                    });
+                }
+                // Stop all receivers
+                if (peerConnection.getReceivers) {
+                    peerConnection.getReceivers().forEach(receiver => {
+                        if (receiver.track) {
+                            receiver.track.stop();
+                        }
+                    });
+                }
+                // Close the connection
+                peerConnection.close();
+                // Clear the reference
+                peerConnection = null;
+                console.log('[STOP] Connection closed');
+            }
+            // Reset audio level
+            audioLevel = 0;
+            isVoiceActive = false;
+            // Update UI
+            updateButtonState();
+            // Clear any existing webrtc_id
+            if (webrtc_id) {
+                console.log('[STOP] Clearing webrtc_id:', webrtc_id);
+                webrtc_id = null;
+            }
+        }
+        startButton.addEventListener('click', () => {
+            console.log('clicked');
+            console.log(peerConnection, peerConnection?.connectionState);
+            if (!peerConnection || peerConnection.connectionState !== 'connected') {
+                setupWebRTC();
+            } else {
+                console.log('stopping');
+                stop();
+            }
+        });
+        // Initialize on page load
+        window.addEventListener('DOMContentLoaded', () => {
+            sendButton.style.display = 'block';
+            endSessionButton.style.display = 'block';
+            startNewSession();
+            loadHistory();
+            loadMemories();
+        });
+    </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 []
+# Database helper class
+class PersonalAssistantDB:
+    """Database manager for personal assistant"""
+    @staticmethod
+    async def init():
+        """Initialize database tables"""
+        async with aiosqlite.connect(DB_PATH) as db:
+            # Conversations table
+            await db.execute("""
+                CREATE TABLE IF NOT EXISTS conversations (
+                    id TEXT PRIMARY KEY,
+                    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
+                    updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
+                    summary TEXT
+                )
+            """)
+            # Messages table
+            await db.execute("""
+                CREATE TABLE IF NOT EXISTS messages (
+                    id INTEGER PRIMARY KEY AUTOINCREMENT,
+                    session_id TEXT NOT NULL,
+                    role TEXT NOT NULL,
+                    content TEXT NOT NULL,
+                    detected_language TEXT,
+                    timestamp TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
+                    FOREIGN KEY (session_id) REFERENCES conversations(id)
+                )
+            """)
+            # User memories table - stores personal information
+            await db.execute("""
+                CREATE TABLE IF NOT EXISTS user_memories (
+                    id INTEGER PRIMARY KEY AUTOINCREMENT,
+                    category TEXT NOT NULL,
+                    content TEXT NOT NULL,
+                    confidence REAL DEFAULT 1.0,
+                    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
+                    updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
+                    source_session_id TEXT,
+                    FOREIGN KEY (source_session_id) REFERENCES conversations(id)
+                )
+            """)
+            # Create indexes for better performance
+            await db.execute("CREATE INDEX IF NOT EXISTS idx_memories_category ON user_memories(category)")
+            await db.execute("CREATE INDEX IF NOT EXISTS idx_messages_session ON messages(session_id)")
+            await db.commit()
+    @staticmethod
+    async def create_session(session_id: str):
+        """Create a new conversation session"""
+        async with aiosqlite.connect(DB_PATH) as db:
+            await db.execute(
+                "INSERT INTO conversations (id) VALUES (?)",
+                (session_id,)
+            )
+            await db.commit()
+    @staticmethod
+    async def save_message(session_id: str, role: str, content: str):
+        """Save a message to the database"""
+        # Check for None or empty content
+        if not content:
+            print(f"[SAVE_MESSAGE] Empty content for {role} message, skipping")
+            return
+        # Detect language
+        detected_language = None
+        try:
+            if content and len(content) > 10:
+                detected_language = detect(content)
+        except (LangDetectException, Exception) as e:
+            print(f"Language detection error: {e}")
+        async with aiosqlite.connect(DB_PATH) as db:
+            await db.execute(
+                """INSERT INTO messages (session_id, role, content, detected_language)
+                   VALUES (?, ?, ?, ?)""",
+                (session_id, role, content, detected_language)
+            )
+            # Update conversation's updated_at timestamp
+            await db.execute(
+                "UPDATE conversations SET updated_at = CURRENT_TIMESTAMP WHERE id = ?",
+                (session_id,)
+            )
+            # Update conversation summary (use first user message as summary)
+            if role == "user":
+                cursor = await db.execute(
+                    "SELECT summary FROM conversations WHERE id = ?",
+                    (session_id,)
+                )
+                row = await cursor.fetchone()
+                if row and not row[0]:
+                    summary = content[:100] + "..." if len(content) > 100 else content
+                    await db.execute(
+                        "UPDATE conversations SET summary = ? WHERE id = ?",
+                        (summary, session_id)
+                    )
+            await db.commit()
+    @staticmethod
+    async def get_recent_conversations(limit: int = 10):
+        """Get recent conversations"""
+        async with aiosqlite.connect(DB_PATH) as db:
+            cursor = await db.execute(
+                """SELECT id, created_at, summary
+                   FROM conversations
+                   ORDER BY updated_at DESC
+                   LIMIT ?""",
+                (limit,)
+            )
+            rows = await cursor.fetchall()
+            return [
+                {
+                    "id": row[0],
+                    "created_at": row[1],
+                    "summary": row[2] or "새 대화"
+                }
+                for row in rows
+            ]
+    @staticmethod
+    async def get_conversation_messages(session_id: str):
+        """Get all messages for a conversation"""
+        async with aiosqlite.connect(DB_PATH) as db:
+            cursor = await db.execute(
+                """SELECT role, content, detected_language, timestamp
+                   FROM messages
+                   WHERE session_id = ?
+                   ORDER BY timestamp ASC""",
+                (session_id,)
+            )
+            rows = await cursor.fetchall()
+            return [
+                {
+                    "role": row[0],
+                    "content": row[1],
+                    "detected_language": row[2],
+                    "timestamp": row[3]
+                }
+                for row in rows
+            ]
+    @staticmethod
+    async def save_memory(category: str, content: str, session_id: str = None, confidence: float = 1.0):
+        """Save or update a user memory"""
+        async with aiosqlite.connect(DB_PATH) as db:
+            # Check if similar memory exists
+            cursor = await db.execute(
+                """SELECT id, content FROM user_memories
+                   WHERE category = ? AND content LIKE ?
+                   LIMIT 1""",
+                (category, f"%{content[:20]}%")
+            )
+            existing = await cursor.fetchone()
+            if existing:
+                # Update existing memory
+                await db.execute(
+                    """UPDATE user_memories
+                       SET content = ?, confidence = ?, updated_at = CURRENT_TIMESTAMP,
+                           source_session_id = ?
+                       WHERE id = ?""",
+                    (content, confidence, session_id, existing[0])
+                )
+            else:
+                # Insert new memory
+                await db.execute(
+                    """INSERT INTO user_memories (category, content, confidence, source_session_id)
+                       VALUES (?, ?, ?, ?)""",
+                    (category, content, confidence, session_id)
+                )
+            await db.commit()
+    @staticmethod
+    async def get_all_memories():
+        """Get all user memories"""
+        async with aiosqlite.connect(DB_PATH) as db:
+            cursor = await db.execute(
+                """SELECT category, content, confidence, updated_at
+                   FROM user_memories
+                   ORDER BY category, updated_at DESC"""
+            )
+            rows = await cursor.fetchall()
+            return [
+                {
+                    "category": row[0],
+                    "content": row[1],
+                    "confidence": row[2],
+                    "updated_at": row[3]
+                }
+                for row in rows
+            ]
+    @staticmethod
+    async def extract_and_save_memories(session_id: str):
+        """Extract memories from conversation and save them"""
+        # Get all messages from the session
+        messages = await PersonalAssistantDB.get_conversation_messages(session_id)
+        if not messages:
+            return
+        # Prepare conversation text for analysis
+        conversation_text = "\n".join([
+            f"{msg['role']}: {msg['content']}"
+            for msg in messages if msg.get('content')
+        ])
+        # Use GPT to extract memories
+        client = openai.AsyncOpenAI()
+        try:
+            response = await client.chat.completions.create(
+                model="gpt-4.1-mini",
+                messages=[
+                    {
+                        "role": "system",
+                        "content": """You are a memory extraction system. Extract personal information from conversations.
+Categories to extract:
+- personal_info: 이름, 나이, 성별, 직업, 거주지
+- preferences: 좋아하는 것, 싫어하는 것, 취향
+- important_dates: 생일, 기념일, 중요한 날짜
+- relationships: 가족, 친구, 동료 관계
+- hobbies: 취미, 관심사
+- health: 건강 상태, 알레르기, 의료 정보
+- goals: 목표, 계획, 꿈
+- routines: 일상, 습관, 루틴
+- work: 직장, 업무, 프로젝트
+- education: 학력, 전공, 학습
+Return as JSON array with format:
+[
+  {
+    "category": "category_name",
+    "content": "extracted information in Korean",
+    "confidence": 0.0-1.0
+  }
+]
+Only extract clear, factual information. Do not make assumptions."""
+                    },
+                    {
+                        "role": "user",
+                        "content": f"Extract memories from this conversation:\n\n{conversation_text}"
+                    }
+                ],
+                temperature=0.3,
+                max_tokens=2000
+            )
+            # Parse and save memories
+            memories_text = response.choices[0].message.content
+            # Extract JSON from response
+            import re
+            json_match = re.search(r'\[.*\]', memories_text, re.DOTALL)
+            if json_match:
+                memories = json.loads(json_match.group())
+                for memory in memories:
+                    if memory.get('content') and len(memory['content']) > 5:
+                        await PersonalAssistantDB.save_memory(
+                            category=memory.get('category', 'general'),
+                            content=memory['content'],
+                            session_id=session_id,
+                            confidence=memory.get('confidence', 0.8)
+                        )
+                print(f"Extracted and saved {len(memories)} memories from session {session_id}")
+        except Exception as e:
+            print(f"Error extracting memories: {e}")
+# 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 format_memories_for_prompt(memories: Dict[str, List[str]]) -> str:
+    """Format memories for inclusion in system prompt"""
+    if not memories:
+        return ""
+    memory_text = "\n\n=== 기억된 정보 ===\n"
+    for category, items in memories.items():
+        if items and isinstance(items, list):
+            memory_text += f"\n[{category}]\n"
+            for item in items:
+                if item:  # Check if item is not None or empty
+                    memory_text += f"- {item}\n"
+    return memory_text
+async def process_text_chat(message: str, web_search_enabled: bool, session_id: str,
+                          user_name: str = "", memories: Dict = None) -> Dict[str, str]:
+    """Process text chat using GPT-4o-mini model"""
+    try:
+        # Check for empty or None message
+        if not message:
+            return {"error": "메시지가 비어있습니다."}
+        # Check for stop words
+        stop_words = ["중단", "그만", "스톱", "stop", "닥쳐", "멈춰", "중지"]
+        if any(word in message.lower() for word in stop_words):
+            return {
+                "response": "대화를 중단합니다.",
+                "detected_language": "ko"
+            }
+        # Build system prompt with memories
+        base_prompt = f"""You are a personal AI assistant for {user_name if user_name else 'the user'}.
+You remember all previous conversations and personal information about the user.
+Be friendly, helpful, and personalized in your responses.
+Always use the information you remember to make conversations more personal and relevant.
+IMPORTANT: Give only ONE response. Do not repeat or give multiple answers."""
+        # Add memories to prompt
+        if memories:
+            memory_text = format_memories_for_prompt(memories)
+            base_prompt += memory_text
+        messages = [{"role": "system", "content": base_prompt}]
+        # Handle web search if enabled
+        if web_search_enabled and search_client and message:
+            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:
+                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": "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-4.1-mini",
+            messages=messages,
+            temperature=0.7,
+            max_tokens=2000
+        )
+        response_text = response.choices[0].message.content
+        # Detect language
+        detected_language = None
+        try:
+            if response_text and len(response_text) > 10:
+                detected_language = detect(response_text)
+        except:
+            pass
+        # Save messages to database
+        if session_id:
+            await PersonalAssistantDB.save_message(session_id, "user", message)
+            await PersonalAssistantDB.save_message(session_id, "assistant", response_text)
+        return {
+            "response": response_text,
+            "detected_language": detected_language
+        }
+    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, webrtc_id: str = None,
+                 session_id: str = None, user_name: str = "", memories: Dict = None) -> 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.session_id = session_id
+        self.user_name = user_name
+        self.memories = memories or {}
+        self.is_responding = False  # Track if already responding
+        self.should_stop = False  # Track if conversation should stop
+        print(f"[INIT] Handler created with web_search={web_search_enabled}, session_id={session_id}, user={user_name}")
+    def copy(self):
+        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]
+                print(f"[COPY] Copying settings from {recent_id}:")
+                return OpenAIHandler(
+                    web_search_enabled=settings.get('web_search_enabled', False),
+                    webrtc_id=recent_id,
+                    session_id=settings.get('session_id'),
+                    user_name=settings.get('user_name', ''),
+                    memories=settings.get('memories', {})
+                )
+        print(f"[COPY] No settings found, creating default handler")
+        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."
+        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 start_up(self):
+        """Connect to realtime API"""
+        if connection_settings and self.webrtc_id:
+            if self.webrtc_id in connection_settings:
+                settings = connection_settings[self.webrtc_id]
+                self.web_search_enabled = settings.get('web_search_enabled', False)
+                self.session_id = settings.get('session_id')
+                self.user_name = settings.get('user_name', '')
+                self.memories = settings.get('memories', {})
+                print(f"[START_UP] Updated settings from storage for {self.webrtc_id}")
+        self.client = openai.AsyncOpenAI()
+        print(f"[REALTIME API] Connecting...")
+        # Build system prompt with memories
+        base_instructions = f"""You are a personal AI assistant for {self.user_name if self.user_name else 'the user'}.
+You remember all previous conversations and personal information about the user.
+Be friendly, helpful, and personalized in your responses.
+Always use the information you remember to make conversations more personal and relevant.
+IMPORTANT: Give only ONE response per user input. Do not repeat yourself or give multiple answers."""
+        # Add memories to prompt
+        if self.memories:
+            memory_text = format_memories_for_prompt(self.memories)
+            base_instructions += memory_text
+        # Define the web search function
+        tools = []
+        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"]
+                    }
+                }
+            }]
+            search_instructions = (
+                "\n\nYou have web search capabilities. "
+                "Use web_search for current information like weather, news, prices, etc."
+            )
+            instructions = base_instructions + search_instructions
+        else:
+            instructions = base_instructions
+        async with self.client.beta.realtime.connect(
+            model="gpt-4o-mini-realtime-preview-2024-12-17"
+        ) as conn:
+            session_update = {
+                "turn_detection": {
+                    "type": "server_vad",
+                    "threshold": 0.5,
+                    "prefix_padding_ms": 300,
+                    "silence_duration_ms": 200
+                },
+                "instructions": instructions,
+                "tools": tools,
+                "tool_choice": "auto" if tools else "none",
+                "temperature": 0.7,
+                "max_response_output_tokens": 4096,
+                "modalities": ["text", "audio"],
+                "voice": "alloy"
+            }
+            try:
+                await conn.session.update(session=session_update)
+                self.connection = conn
+                print(f"Connected with tools: {len(tools)} functions")
+                print(f"Session update successful")
+            except Exception as e:
+                print(f"Error updating session: {e}")
+                raise
+            async for event in self.connection:
+                # Debug log for all events
+                if hasattr(event, 'type'):
+                    if event.type not in ["response.audio.delta", "response.audio.done"]:
+                        print(f"[EVENT] Type: {event.type}")
+                # Handle user input audio transcription
+                if event.type == "conversation.item.input_audio_transcription.completed":
+                    if hasattr(event, 'transcript') and event.transcript:
+                        user_text = event.transcript.lower()
+                        stop_words = ["중단", "그만", "스톱", "stop", "닥쳐", "멈춰", "중지"]
+                        if any(word in user_text for word in stop_words):
+                            print(f"[STOP DETECTED] User said: {event.transcript}")
+                            self.should_stop = True
+                            if self.connection:
+                                try:
+                                    await self.connection.response.cancel()
+                                except:
+                                    pass
+                            continue
+                        # Save user message to database
+                        if self.session_id:
+                            await PersonalAssistantDB.save_message(self.session_id, "user", event.transcript)
+                # Handle user transcription for stop detection (alternative event)
+                elif event.type == "conversation.item.created":
+                    if hasattr(event, 'item') and hasattr(event.item, 'role') and event.item.role == "user":
+                        if hasattr(event.item, 'content') and event.item.content:
+                            for content_item in event.item.content:
+                                if hasattr(content_item, 'transcript') and content_item.transcript:
+                                    user_text = content_item.transcript.lower()
+                                    stop_words = ["중단", "그만", "스톱", "stop", "닥쳐", "멈춰", "중지"]
+                                    if any(word in user_text for word in stop_words):
+                                        print(f"[STOP DETECTED] User said: {content_item.transcript}")
+                                        self.should_stop = True
+                                        if self.connection:
+                                            try:
+                                                await self.connection.response.cancel()
+                                            except:
+                                                pass
+                                        continue
+                                    # Save user message to database
+                                    if self.session_id:
+                                        await PersonalAssistantDB.save_message(self.session_id, "user", content_item.transcript)
+                elif event.type == "response.audio_transcript.done":
+                    # Prevent multiple responses
+                    if self.is_responding:
+                        print("[DUPLICATE RESPONSE] Skipping duplicate response")
+                        continue
+                    self.is_responding = True
+                    print(f"[RESPONSE] Transcript: {event.transcript[:100] if event.transcript else 'None'}...")
+                    # Detect language
+                    detected_language = None
+                    try:
+                        if event.transcript and len(event.transcript) > 10:
+                            detected_language = detect(event.transcript)
+                    except Exception as e:
+                        print(f"Language detection error: {e}")
+                    # Save to database
+                    if self.session_id and event.transcript:
+                        await PersonalAssistantDB.save_message(self.session_id, "assistant", event.transcript)
+                    output_data = {
+                        "event": event,
+                        "detected_language": detected_language
+                    }
+                    await self.output_queue.put(AdditionalOutputs(output_data))
+                elif event.type == "response.done":
+                    # Reset responding flag when response is complete
+                    self.is_responding = False
+                    self.should_stop = False
+                    print("[RESPONSE DONE] Response completed")
+                elif event.type == "response.audio.delta":
+                    # Check if we should stop
+                    if self.should_stop:
+                        continue
+                    if hasattr(event, 'delta'):
+                        await self.output_queue.put(
+                            (
+                                self.output_sample_rate,
+                                np.frombuffer(
+                                    base64.b64decode(event.delta), dtype=np.int16
+                                ).reshape(1, -1),
+                            ),
+                        )
+                # Handle errors
+                elif event.type == "error":
+                    print(f"[ERROR] {event}")
+                    self.is_responding = False
+                # Handle function calls
+                elif event.type == "response.function_call_arguments.start":
+                    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":
+                    if self.function_call_in_progress:
+                        self.current_function_args += event.delta
+                elif event.type == "response.function_call_arguments.done":
+                    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:
+            print(f"[RECEIVE] No connection, skipping")
+            return
+        try:
+            if frame is None or len(frame) < 2:
+                print(f"[RECEIVE] Invalid frame")
+                return
+            _, array = frame
+            if array is None:
+                print(f"[RECEIVE] Null array")
+                return
+            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}")
+    async def emit(self) -> tuple[int, np.ndarray] | AdditionalOutputs | None:
+        item = await wait_for_item(self.output_queue)
+        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:
+        print(f"[SHUTDOWN] Called")
+        if self.connection:
+            await self.connection.close()
+            self.connection = None
+            print("[REALTIME API] Connection closed")
+# Create initial handler instance
+handler = OpenAIHandler(web_search_enabled=False)
+# Create components
+chatbot = gr.Chatbot(type="messages")
+# Create stream with handler instance
+stream = Stream(
+    handler,
+    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)
+# Initialize database on startup
+@app.on_event("startup")
+async def startup_event():
+    try:
+        await PersonalAssistantDB.init()
+        print(f"Database initialized at: {DB_PATH}")
+        print(f"Persistent directory: {PERSISTENT_DIR}")
+        print(f"DB file exists: {os.path.exists(DB_PATH)}")
+        # Check if we're in Hugging Face Space
+        if os.path.exists("/data"):
+            print("Running in Hugging Face Space with persistent storage")
+            # List files in persistent directory
+            try:
+                files = os.listdir(PERSISTENT_DIR)
+                print(f"Files in persistent directory: {files}")
+            except Exception as e:
+                print(f"Error listing files: {e}")
+    except Exception as e:
+        print(f"Error during startup: {e}")
+        # Try to create directory if it doesn't exist
+        os.makedirs(PERSISTENT_DIR, exist_ok=True)
+        await PersonalAssistantDB.init()
+# 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)
+    session_id = body.get("session_id")
+    user_name = body.get("user_name", "")
+    memories = body.get("memories", {})
+    print(f"[OFFER] Received offer with webrtc_id: {webrtc_id}")
+    print(f"[OFFER] web_search_enabled: {web_search_enabled}")
+    print(f"[OFFER] session_id: {session_id}")
+    print(f"[OFFER] user_name: {user_name}")
+    # Store settings with timestamp
+    if webrtc_id:
+        connection_settings[webrtc_id] = {
+            'web_search_enabled': web_search_enabled,
+            'session_id': session_id,
+            'user_name': user_name,
+            'memories': memories,
+            'timestamp': asyncio.get_event_loop().time()
+        }
+        print(f"[OFFER] Stored settings for {webrtc_id}")
+    # 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
+    print(f"[OFFER] Forwarding to stream.offer()")
+    response = await stream.offer(body)
+    # Re-add our custom route
+    if custom_route:
+        app.routes.insert(0, custom_route)
+    print(f"[OFFER] Response status: {response.get('status', 'unknown') if isinstance(response, dict) else 'OK'}")
+    return response
+@app.post("/session/new")
+async def create_new_session():
+    """Create a new chat session"""
+    session_id = str(uuid.uuid4())
+    await PersonalAssistantDB.create_session(session_id)
+    return {"session_id": session_id}
+@app.post("/session/end")
+async def end_session(request: Request):
+    """End session and extract memories"""
+    body = await request.json()
+    session_id = body.get("session_id")
+    if not session_id:
+        return {"error": "session_id required"}
+    # Extract and save memories from the conversation
+    await PersonalAssistantDB.extract_and_save_memories(session_id)
+    return {"status": "ok"}
+@app.post("/message/save")
+async def save_message(request: Request):
+    """Save a message to the database"""
+    body = await request.json()
+    session_id = body.get("session_id")
+    role = body.get("role")
+    content = body.get("content")
+    if not all([session_id, role, content]):
+        return {"error": "Missing required fields"}
+    await PersonalAssistantDB.save_message(session_id, role, content)
+    return {"status": "ok"}
+@app.get("/history/recent")
+async def get_recent_history():
+    """Get recent conversation history"""
+    conversations = await PersonalAssistantDB.get_recent_conversations()
+    return conversations
+@app.get("/history/{session_id}")
+async def get_conversation(session_id: str):
+    """Get messages for a specific conversation"""
+    messages = await PersonalAssistantDB.get_conversation_messages(session_id)
+    return messages
+@app.get("/memory/all")
+async def get_all_memories():
+    """Get all user memories"""
+    memories = await PersonalAssistantDB.get_all_memories()
+    return memories
+@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)
+        session_id = body.get("session_id")
+        user_name = body.get("user_name", "")
+        memories = body.get("memories", {})
+        if not message:
+            return {"error": "메시지가 비어있습니다."}
+        # Process text chat
+        result = await process_text_chat(message, web_search_enabled, session_id, user_name, memories)
+        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_data = output.args[0]
+                    if 'event' in event_data and hasattr(event_data['event'], 'transcript'):
+                        data = {
+                            "role": "assistant",
+                            "content": event_data['event'].transcript,
+                            "detected_language": event_data.get('detected_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)