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seawolf2357 commited on 5 days ago

Commit

73eebb3

verified ·

1 Parent(s): 1283bb7

Update app-backup4.py

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app-backup4.py +599 -152

app-backup4.py CHANGED Viewed

@@ -31,7 +31,18 @@ import uuid
 load_dotenv()
 SAMPLE_RATE = 24000
-DB_PATH = "chat_history.db"
 # HTML content embedded as a string
 HTML_CONTENT = """<!DOCTYPE html>
@@ -40,7 +51,7 @@ HTML_CONTENT = """<!DOCTYPE html>
 <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;
@@ -50,6 +61,7 @@ HTML_CONTENT = """<!DOCTYPE html>
             --text-color: #f8f9fa;
             --border-color: #333;
             --hover-color: #8a5cf6;
         }
         body {
             font-family: "SF Pro Display", -apple-system, BlinkMacSystemFont, sans-serif;
@@ -126,7 +138,6 @@ HTML_CONTENT = """<!DOCTYPE html>
             padding: 20px;
             border: 1px solid var(--border-color);
             overflow-y: auto;
-            flex-grow: 1;
         }
         .settings-grid {
             display: flex;
@@ -171,14 +182,40 @@ HTML_CONTENT = """<!DOCTYPE html>
         .toggle-switch.active .toggle-slider {
             transform: translateX(24px);
         }
         /* History section */
         .history-section {
             background-color: var(--card-bg);
             border-radius: 12px;
             padding: 20px;
             border: 1px solid var(--border-color);
-            margin-top: 20px;
-            max-height: 300px;
             overflow-y: auto;
         }
         .history-item {
@@ -292,6 +329,13 @@ HTML_CONTENT = """<!DOCTYPE html>
             padding: 10px;
             margin-bottom: 10px;
         }
         .language-info {
             font-size: 12px;
             color: #888;
@@ -359,6 +403,14 @@ HTML_CONTENT = """<!DOCTYPE html>
         #send-button:hover {
             background: linear-gradient(135deg, #27ae60, #229954);
         }
         #audio-output {
             display: none;
         }
@@ -420,6 +472,10 @@ HTML_CONTENT = """<!DOCTYPE html>
             background-color: #ff9800;
             color: white;
         }
         .status-indicator {
             display: inline-flex;
             align-items: center;
@@ -454,34 +510,17 @@ HTML_CONTENT = """<!DOCTYPE html>
                 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%;
         }
     </style>
 </head>
@@ -491,12 +530,8 @@ HTML_CONTENT = """<!DOCTYPE html>
     <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>
@@ -517,11 +552,16 @@ HTML_CONTENT = """<!DOCTYPE html>
                         </div>
                     </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="history-section">
                     <h3 style="margin: 0 0 15px 0; color: var(--primary-color);">대화 기록</h3>
                     <div id="history-list"></div>
@@ -529,6 +569,7 @@ HTML_CONTENT = """<!DOCTYPE html>
                 <div class="controls">
                     <button id="start-button">대화 시작</button>
                 </div>
             </div>
@@ -552,24 +593,44 @@ HTML_CONTENT = """<!DOCTYPE html>
         let peerConnection;
         let webrtc_id;
         let webSearchEnabled = false;
-        let systemPrompt = "You are a helpful assistant. Respond in a friendly and professional manner.";
         let currentSessionId = null;
         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 systemPromptInput = document.getElementById('system-prompt');
         const textInput = document.getElementById('text-input');
         const historyList = document.getElementById('history-list');
         let audioLevel = 0;
         let animationFrame;
         let audioContext, analyser, audioSource;
         let dataChannel = null;
         let isVoiceActive = false;
         // Start new session
         async function startNewSession() {
             const response = await fetch('/session/new', { method: 'POST' });
@@ -577,6 +638,62 @@ HTML_CONTENT = """<!DOCTYPE html>
             currentSessionId = data.session_id;
             console.log('New session started:', currentSessionId);
             loadHistory();
         }
         // Load conversation history
@@ -623,11 +740,6 @@ HTML_CONTENT = """<!DOCTYPE html>
             console.log('Web search enabled:', webSearchEnabled);
         });
-        // 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) {
@@ -637,11 +749,19 @@ HTML_CONTENT = """<!DOCTYPE html>
         });
         sendButton.addEventListener('click', sendTextMessage);
         async function sendTextMessage() {
             const message = textInput.value.trim();
             if (!message) return;
             // Add user message to chat
             addMessage('user', message);
             textInput.value = '';
@@ -662,8 +782,9 @@ HTML_CONTENT = """<!DOCTYPE html>
                     body: JSON.stringify({
                         message: message,
                         web_search_enabled: webSearchEnabled,
-                        system_prompt: systemPrompt,
-                        session_id: currentSessionId
                     })
                 });
@@ -696,16 +817,34 @@ HTML_CONTENT = """<!DOCTYPE html>
             if (state === 'connected') {
                 statusText.textContent = '연결됨';
                 sendButton.style.display = 'block';
                 isVoiceActive = true;
             } else if (state === 'connecting') {
                 statusText.textContent = '연결 중...';
                 sendButton.style.display = 'none';
             } else {
                 statusText.textContent = '연결 대기 중';
-                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')) {
@@ -735,6 +874,7 @@ HTML_CONTENT = """<!DOCTYPE html>
                 updateStatus('disconnected');
             }
         }
         function setupAudioVisualization(stream) {
             audioContext = new (window.AudioContext || window.webkitAudioContext)();
             analyser = audioContext.createAnalyser();
@@ -769,27 +909,14 @@ HTML_CONTENT = """<!DOCTYPE html>
             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
@@ -832,6 +959,7 @@ HTML_CONTENT = """<!DOCTYPE html>
                         peerConnection.addEventListener("icegatheringstatechange", checkState);
                     }
                 });
                 peerConnection.addEventListener('connectionstatechange', () => {
                     console.log('connectionstatechange', peerConnection.connectionState);
                     if (peerConnection.connectionState === 'connected') {
@@ -841,15 +969,8 @@ HTML_CONTENT = """<!DOCTYPE html>
                     }
                     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,
-                    system_prompt: systemPrompt,
-                    session_id: currentSessionId
-                });
                 const response = await fetch('/webrtc/offer', {
                     method: 'POST',
@@ -859,10 +980,12 @@ HTML_CONTENT = """<!DOCTYPE html>
                         type: peerConnection.localDescription.type,
                         webrtc_id: webrtc_id,
                         web_search_enabled: webSearchEnabled,
-                        system_prompt: systemPrompt,
-                        session_id: currentSessionId
                     })
                 });
                 const serverResponse = await response.json();
                 if (serverResponse.status === 'failed') {
                     showError(serverResponse.meta.error === 'concurrency_limit_reached'
@@ -871,6 +994,7 @@ HTML_CONTENT = """<!DOCTYPE html>
                     stop();
                     return;
                 }
                 await peerConnection.setRemoteDescription(serverResponse);
                 const eventSource = new EventSource('/outputs?webrtc_id=' + webrtc_id);
                 eventSource.addEventListener("output", (event) => {
@@ -895,6 +1019,7 @@ HTML_CONTENT = """<!DOCTYPE html>
                 stop();
             }
         }
         function addMessage(role, content, save = true) {
             const messageDiv = document.createElement('div');
             messageDiv.classList.add('message', role);
@@ -908,7 +1033,7 @@ HTML_CONTENT = """<!DOCTYPE html>
             chatMessages.scrollTop = chatMessages.scrollHeight;
             // Save message to database if save flag is true
-            if (save && currentSessionId) {
                 fetch('/message/save', {
                     method: 'POST',
                     headers: { 'Content-Type': 'application/json' },
@@ -997,6 +1122,7 @@ HTML_CONTENT = """<!DOCTYPE html>
                 webrtc_id = null;
             }
         }
         startButton.addEventListener('click', () => {
             console.log('clicked');
             console.log(peerConnection, peerConnection?.connectionState);
@@ -1011,8 +1137,10 @@ HTML_CONTENT = """<!DOCTYPE html>
         // Initialize on page load
         window.addEventListener('DOMContentLoaded', () => {
             sendButton.style.display = 'block';
             startNewSession();
             loadHistory();
         });
     </script>
 </body>
@@ -1062,13 +1190,14 @@ class BraveSearchClient:
 # Database helper class
-class ChatDatabase:
-    """Database manager for chat history"""
     @staticmethod
     async def init():
         """Initialize database tables"""
         async with aiosqlite.connect(DB_PATH) as db:
             await db.execute("""
                 CREATE TABLE IF NOT EXISTS conversations (
                     id TEXT PRIMARY KEY,
@@ -1078,6 +1207,7 @@ class ChatDatabase:
                 )
             """)
             await db.execute("""
                 CREATE TABLE IF NOT EXISTS messages (
                     id INTEGER PRIMARY KEY AUTOINCREMENT,
@@ -1090,6 +1220,24 @@ class ChatDatabase:
                 )
             """)
             await db.commit()
     @staticmethod
@@ -1105,13 +1253,18 @@ class ChatDatabase:
     @staticmethod
     async def save_message(session_id: str, role: str, content: str):
         """Save a message to the database"""
         # Detect language
         detected_language = None
         try:
-            if content and len(content) > 10:  # Only detect for substantial content
                 detected_language = detect(content)
-        except LangDetectException:
-            pass
         async with aiosqlite.connect(DB_PATH) as db:
             await db.execute(
@@ -1133,7 +1286,7 @@ class ChatDatabase:
                     (session_id,)
                 )
                 row = await cursor.fetchone()
-                if row and not row[0]:  # If no summary exists
                     summary = content[:100] + "..." if len(content) > 100 else content
                     await db.execute(
                         "UPDATE conversations SET summary = ? WHERE id = ?",
@@ -1184,6 +1337,139 @@ class ChatDatabase:
                 }
                 for row in rows
             ]
 # Initialize search client globally
@@ -1203,16 +1489,54 @@ def update_chatbot(chatbot: list[dict], response: ResponseAudioTranscriptDoneEve
     return chatbot
-async def process_text_chat(message: str, web_search_enabled: bool, system_prompt: str, session_id: str) -> Dict[str, str]:
     """Process text chat using GPT-4o-mini model"""
     try:
-        messages = [
-            {"role": "system", "content": system_prompt or "You are a helpful assistant."}
-        ]
         # 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"]
@@ -1220,7 +1544,6 @@ async def process_text_chat(message: str, web_search_enabled: bool, system_promp
             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"
@@ -1254,8 +1577,8 @@ async def process_text_chat(message: str, web_search_enabled: bool, system_promp
         # Save messages to database
         if session_id:
-            await ChatDatabase.save_message(session_id, "user", message)
-            await ChatDatabase.save_message(session_id, "assistant", response_text)
         return {
             "response": response_text,
@@ -1268,8 +1591,8 @@ async def process_text_chat(message: str, web_search_enabled: bool, system_promp
 class OpenAIHandler(AsyncStreamHandler):
-    def __init__(self, web_search_enabled: bool = False, system_prompt: str = "",
-                 webrtc_id: str = None, session_id: str = None) -> None:
         super().__init__(
             expected_layout="mono",
             output_sample_rate=SAMPLE_RATE,
@@ -1284,15 +1607,16 @@ class OpenAIHandler(AsyncStreamHandler):
         self.current_call_id = None
         self.webrtc_id = webrtc_id
         self.web_search_enabled = web_search_enabled
-        self.system_prompt = system_prompt
         self.session_id = session_id
-        print(f"[INIT] Handler created with web_search={web_search_enabled}, session_id={session_id}")
     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)
@@ -1300,14 +1624,14 @@ class OpenAIHandler(AsyncStreamHandler):
                 recent_id = recent_ids[0]
                 settings = connection_settings[recent_id]
-                # Log the settings being copied
                 print(f"[COPY] Copying settings from {recent_id}:")
                 return OpenAIHandler(
                     web_search_enabled=settings.get('web_search_enabled', False),
-                    system_prompt=settings.get('system_prompt', ''),
                     webrtc_id=recent_id,
-                    session_id=settings.get('session_id')
                 )
         print(f"[COPY] No settings found, creating default handler")
@@ -1323,7 +1647,6 @@ class OpenAIHandler(AsyncStreamHandler):
         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(
@@ -1348,25 +1671,34 @@ class OpenAIHandler(AsyncStreamHandler):
     async def start_up(self):
         """Connect to realtime API"""
-        # First check if we have the most recent settings
         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.system_prompt = settings.get('system_prompt', '')
                 self.session_id = settings.get('session_id')
                 print(f"[START_UP] Updated settings from storage for {self.webrtc_id}")
         self.client = openai.AsyncOpenAI()
-        # Connect to Realtime API
         print(f"[REALTIME API] Connecting...")
         # Define the web search function
         tools = []
-        base_instructions = self.system_prompt or "You are a helpful assistant."
         if self.web_search_enabled and self.search_client:
             tools = [{
                 "type": "function",
@@ -1385,20 +1717,10 @@ class OpenAIHandler(AsyncStreamHandler):
                     }
                 }
             }]
-            print("Web search function added to tools")
             search_instructions = (
                 "\n\nYou have web search capabilities. "
-                "IMPORTANT: You MUST use the web_search function for ANY of these topics:\n"
-                "- Weather (날씨, 기온, 비, 눈)\n"
-                "- News (뉴스, 소식)\n"
-                "- Current events (현재, 최근, 오늘, 지금)\n"
-                "- Prices (가격, 환율, 주가)\n"
-                "- Sports scores or results\n"
-                "- Any question about 2024 or 2025\n"
-                "- Any time-sensitive information\n\n"
-                "When in doubt, USE web_search. It's better to search and provide accurate information "
-                "than to guess or use outdated information."
             )
             instructions = base_instructions + search_instructions
@@ -1408,9 +1730,13 @@ class OpenAIHandler(AsyncStreamHandler):
         async with self.client.beta.realtime.connect(
             model="gpt-4o-mini-realtime-preview-2024-12-17"
         ) as conn:
-            # Update session with tools
             session_update = {
-                "turn_detection": {"type": "server_vad"},
                 "instructions": instructions,
                 "tools": tools,
                 "tool_choice": "auto" if tools else "none",
@@ -1420,29 +1746,84 @@ class OpenAIHandler(AsyncStreamHandler):
                 "voice": "alloy"
             }
-            await conn.session.update(session=session_update)
-            self.connection = conn
-            print(f"Connected with tools: {len(tools)} functions")
             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]}...")
                     # Detect language
                     detected_language = None
                     try:
                         if event.transcript and len(event.transcript) > 10:
                             detected_language = detect(event.transcript)
-                    except:
-                        pass
                     # Save to database
-                    if self.session_id:
-                        await ChatDatabase.save_message(self.session_id, "assistant", event.transcript)
                     output_data = {
                         "event": event,
@@ -1450,15 +1831,31 @@ class OpenAIHandler(AsyncStreamHandler):
                     }
                     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
                 elif event.type == "response.function_call_arguments.start":
@@ -1511,7 +1908,15 @@ class OpenAIHandler(AsyncStreamHandler):
             print(f"[RECEIVE] No connection, skipping")
             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)
@@ -1521,7 +1926,6 @@ class OpenAIHandler(AsyncStreamHandler):
     async def emit(self) -> tuple[int, np.ndarray] | AdditionalOutputs | None:
         item = await wait_for_item(self.output_queue)
-        # Check if it's a dict with text message
         if isinstance(item, dict) and item.get('type') == 'text_message':
             await self.process_text_message(item['content'])
             return None
@@ -1545,7 +1949,7 @@ 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],
@@ -1564,8 +1968,26 @@ stream.mount(app)
 # Initialize database on startup
 @app.on_event("startup")
 async def startup_event():
-    await ChatDatabase.init()
-    print("Database initialized")
 # Intercept offer to capture settings
 @app.post("/webrtc/offer", include_in_schema=False)
@@ -1575,24 +1997,26 @@ async def custom_offer(request: Request):
     webrtc_id = body.get("webrtc_id")
     web_search_enabled = body.get("web_search_enabled", False)
-    system_prompt = body.get("system_prompt", "")
     session_id = body.get("session_id")
     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}")
     # Store settings with timestamp
     if webrtc_id:
         connection_settings[webrtc_id] = {
             'web_search_enabled': web_search_enabled,
-            'system_prompt': system_prompt,
             'session_id': session_id,
             'timestamp': asyncio.get_event_loop().time()
         }
-        print(f"[OFFER] Stored settings for {webrtc_id}:")
-        print(f"[OFFER] {connection_settings[webrtc_id]}")
     # Remove our custom route temporarily
     custom_route = None
@@ -1618,10 +2042,25 @@ async def custom_offer(request: Request):
 async def create_new_session():
     """Create a new chat session"""
     session_id = str(uuid.uuid4())
-    await ChatDatabase.create_session(session_id)
     return {"session_id": session_id}
 @app.post("/message/save")
 async def save_message(request: Request):
     """Save a message to the database"""
@@ -1633,24 +2072,31 @@ async def save_message(request: Request):
     if not all([session_id, role, content]):
         return {"error": "Missing required fields"}
-    await ChatDatabase.save_message(session_id, role, content)
     return {"status": "ok"}
 @app.get("/history/recent")
 async def get_recent_history():
     """Get recent conversation history"""
-    conversations = await ChatDatabase.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 ChatDatabase.get_conversation_messages(session_id)
     return messages
 @app.post("/chat/text")
 async def chat_text(request: Request):
     """Handle text chat messages using GPT-4o-mini"""
@@ -1658,14 +2104,15 @@ async def chat_text(request: Request):
         body = await request.json()
         message = body.get("message", "")
         web_search_enabled = body.get("web_search_enabled", False)
-        system_prompt = body.get("system_prompt", "")
         session_id = body.get("session_id")
         if not message:
             return {"error": "메시지가 비어있습니다."}
         # Process text chat
-        result = await process_text_chat(message, web_search_enabled, system_prompt, session_id)
         return result

 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>
 <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;
             --text-color: #f8f9fa;
             --border-color: #333;
             --hover-color: #8a5cf6;
+            --memory-color: #4a9eff;
         }
         body {
             font-family: "SF Pro Display", -apple-system, BlinkMacSystemFont, sans-serif;
             padding: 20px;
             border: 1px solid var(--border-color);
             overflow-y: auto;
         }
         .settings-grid {
             display: flex;
         .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;
         }
+        .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;
         #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;
         }
             background-color: #ff9800;
             color: white;
         }
+        .toast.success {
+            background-color: #4caf50;
+            color: white;
+        }
         .status-indicator {
             display: inline-flex;
             align-items: center;
                 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>
     <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>
                         </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 class="controls">
                     <button id="start-button">대화 시작</button>
+                    <button id="end-session-button" style="display: none;">기억 업데이트</button>
                 </div>
             </div>
         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' });
             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
             console.log('Web search enabled:', webSearchEnabled);
         });
         // Text input handling
         textInput.addEventListener('keypress', (e) => {
             if (e.key === 'Enter' && !e.shiftKey) {
         });
         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 = '';
                     body: JSON.stringify({
                         message: message,
                         web_search_enabled: webSearchEnabled,
+                        session_id: currentSessionId,
+                        user_name: userName,
+                        memories: userMemories
                     })
                 });
             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')) {
                 updateStatus('disconnected');
             }
         }
         function setupAudioVisualization(stream) {
             audioContext = new (window.AudioContext || window.webkitAudioContext)();
             analyser = audioContext.createAnalyser();
             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
                         peerConnection.addEventListener("icegatheringstatechange", checkState);
                     }
                 });
                 peerConnection.addEventListener('connectionstatechange', () => {
                     console.log('connectionstatechange', peerConnection.connectionState);
                     if (peerConnection.connectionState === 'connected') {
                     }
                     updateButtonState();
                 });
+                webrtc_id = Math.random().toString(36).substring(7);
                 const response = await fetch('/webrtc/offer', {
                     method: 'POST',
                         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'
                     stop();
                     return;
                 }
                 await peerConnection.setRemoteDescription(serverResponse);
                 const eventSource = new EventSource('/outputs?webrtc_id=' + webrtc_id);
                 eventSource.addEventListener("output", (event) => {
                 stop();
             }
         }
         function addMessage(role, content, save = true) {
             const messageDiv = document.createElement('div');
             messageDiv.classList.add('message', role);
             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' },
                 webrtc_id = null;
             }
         }
         startButton.addEventListener('click', () => {
             console.log('clicked');
             console.log(peerConnection, peerConnection?.connectionState);
         // Initialize on page load
         window.addEventListener('DOMContentLoaded', () => {
             sendButton.style.display = 'block';
+            endSessionButton.style.display = 'block';
             startNewSession();
             loadHistory();
+            loadMemories();
         });
     </script>
 </body>
 # 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,
                 )
             """)
+            # Messages table
             await db.execute("""
                 CREATE TABLE IF NOT EXISTS messages (
                     id INTEGER PRIMARY KEY AUTOINCREMENT,
                 )
             """)
+            # 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
     @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(
                     (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 = ?",
                 }
                 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
     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"
         # 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,
 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,
         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)
                 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")
         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(
     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",
                     }
                 }
             }]
             search_instructions = (
                 "\n\nYou have web search capabilities. "
+                "Use web_search for current information like weather, news, prices, etc."
             )
             instructions = base_instructions + search_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",
                 "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,
                     }
                     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"[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)
     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
 # Create stream with handler instance
 stream = Stream(
+    handler,
     mode="send-receive",
     modality="audio",
     additional_inputs=[chatbot],
 # 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)
     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
 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"""
     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"""
         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