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| import asyncio | |
| import base64 | |
| import json | |
| from pathlib import Path | |
| import os | |
| import numpy as np | |
| import openai | |
| from dotenv import load_dotenv | |
| from fastapi import FastAPI, Request | |
| from fastapi.responses import HTMLResponse, StreamingResponse | |
| from fastrtc import ( | |
| AdditionalOutputs, | |
| AsyncStreamHandler, | |
| Stream, | |
| get_twilio_turn_credentials, | |
| wait_for_item, | |
| ) | |
| from gradio.utils import get_space | |
| from openai.types.beta.realtime import ResponseAudioTranscriptDoneEvent | |
| import httpx | |
| from typing import Optional, List, Dict | |
| import gradio as gr | |
| import io | |
| from scipy import signal | |
| import wave | |
| load_dotenv() | |
| SAMPLE_RATE = 24000 | |
| # Supported languages for OpenAI Realtime API | |
| SUPPORTED_LANGUAGES = { | |
| "ko": "한국어 (Korean)", | |
| "en": "English", | |
| "es": "Español (Spanish)", | |
| "fr": "Français (French)", | |
| "de": "Deutsch (German)", | |
| "it": "Italiano (Italian)", | |
| "pt": "Português (Portuguese)", | |
| "ru": "Русский (Russian)", | |
| "ja": "日本語 (Japanese)", | |
| "zh": "中文 (Chinese)", | |
| "ar": "العربية (Arabic)", | |
| "hi": "हिन्दी (Hindi)", | |
| "nl": "Nederlands (Dutch)", | |
| "pl": "Polski (Polish)", | |
| "tr": "Türkçe (Turkish)", | |
| "vi": "Tiếng Việt (Vietnamese)", | |
| "th": "ไทย (Thai)", | |
| "id": "Bahasa Indonesia", | |
| "sv": "Svenska (Swedish)", | |
| "da": "Dansk (Danish)", | |
| "no": "Norsk (Norwegian)", | |
| "fi": "Suomi (Finnish)", | |
| "he": "עברית (Hebrew)", | |
| "uk": "Українська (Ukrainian)", | |
| "cs": "Čeština (Czech)", | |
| "el": "Ελληνικά (Greek)", | |
| "ro": "Română (Romanian)", | |
| "hu": "Magyar (Hungarian)", | |
| "ms": "Bahasa Melayu (Malay)" | |
| } | |
| # HTML content embedded as a string | |
| HTML_CONTENT = """<!DOCTYPE html> | |
| <html lang="ko"> | |
| <head> | |
| <meta charset="UTF-8"> | |
| <meta name="viewport" content="width=device-width, initial-scale=1.0"> | |
| <title>Mouth of 'MOUSE'</title> | |
| <style> | |
| :root { | |
| --primary-color: #6f42c1; | |
| --secondary-color: #563d7c; | |
| --dark-bg: #121212; | |
| --card-bg: #1e1e1e; | |
| --text-color: #f8f9fa; | |
| --border-color: #333; | |
| --hover-color: #8a5cf6; | |
| } | |
| body { | |
| font-family: "SF Pro Display", -apple-system, BlinkMacSystemFont, sans-serif; | |
| background-color: var(--dark-bg); | |
| color: var(--text-color); | |
| margin: 0; | |
| padding: 0; | |
| height: 100vh; | |
| display: flex; | |
| flex-direction: column; | |
| overflow: hidden; | |
| } | |
| .container { | |
| max-width: 1400px; | |
| margin: 0 auto; | |
| padding: 20px; | |
| flex-grow: 1; | |
| display: flex; | |
| flex-direction: column; | |
| width: 100%; | |
| height: 100vh; | |
| box-sizing: border-box; | |
| overflow: hidden; | |
| } | |
| .header { | |
| text-align: center; | |
| padding: 15px 0; | |
| border-bottom: 1px solid var(--border-color); | |
| margin-bottom: 20px; | |
| flex-shrink: 0; | |
| background-color: var(--card-bg); | |
| } | |
| .main-content { | |
| display: flex; | |
| gap: 20px; | |
| flex-grow: 1; | |
| min-height: 0; | |
| overflow: hidden; | |
| } | |
| .sidebar { | |
| width: 350px; | |
| flex-shrink: 0; | |
| display: flex; | |
| flex-direction: column; | |
| gap: 20px; | |
| overflow-y: auto; | |
| max-height: calc(100vh - 120px); | |
| } | |
| .chat-section { | |
| flex-grow: 1; | |
| display: flex; | |
| flex-direction: column; | |
| min-width: 0; | |
| } | |
| .logo { | |
| display: flex; | |
| align-items: center; | |
| justify-content: center; | |
| gap: 10px; | |
| } | |
| .logo h1 { | |
| margin: 0; | |
| background: linear-gradient(135deg, var(--primary-color), #a78bfa); | |
| -webkit-background-clip: text; | |
| background-clip: text; | |
| color: transparent; | |
| font-size: 32px; | |
| letter-spacing: 1px; | |
| } | |
| /* Settings section */ | |
| .settings-section { | |
| background-color: var(--card-bg); | |
| border-radius: 12px; | |
| padding: 20px; | |
| border: 1px solid var(--border-color); | |
| overflow-y: auto; | |
| flex-grow: 1; | |
| } | |
| .settings-grid { | |
| display: flex; | |
| flex-direction: column; | |
| gap: 15px; | |
| margin-bottom: 15px; | |
| } | |
| .interpretation-section { | |
| display: flex; | |
| flex-direction: column; | |
| gap: 15px; | |
| padding: 15px; | |
| background-color: var(--dark-bg); | |
| border-radius: 8px; | |
| margin-top: 15px; | |
| } | |
| .interpretation-info { | |
| font-size: 13px; | |
| color: #999; | |
| margin-top: 5px; | |
| } | |
| .setting-item { | |
| display: flex; | |
| align-items: center; | |
| justify-content: space-between; | |
| gap: 10px; | |
| } | |
| .setting-label { | |
| font-size: 14px; | |
| color: #aaa; | |
| min-width: 60px; | |
| } | |
| /* Toggle switch */ | |
| .toggle-switch { | |
| position: relative; | |
| width: 50px; | |
| height: 26px; | |
| background-color: #ccc; | |
| border-radius: 13px; | |
| cursor: pointer; | |
| transition: background-color 0.3s; | |
| } | |
| .toggle-switch.active { | |
| background-color: var(--primary-color); | |
| } | |
| .toggle-slider { | |
| position: absolute; | |
| top: 3px; | |
| left: 3px; | |
| width: 20px; | |
| height: 20px; | |
| background-color: white; | |
| border-radius: 50%; | |
| transition: transform 0.3s; | |
| } | |
| .toggle-switch.active .toggle-slider { | |
| transform: translateX(24px); | |
| } | |
| /* Select dropdown */ | |
| select { | |
| background-color: var(--card-bg); | |
| color: var(--text-color); | |
| border: 1px solid var(--border-color); | |
| padding: 8px 12px; | |
| border-radius: 6px; | |
| font-size: 14px; | |
| cursor: pointer; | |
| min-width: 120px; | |
| max-width: 200px; | |
| } | |
| select:focus { | |
| outline: none; | |
| border-color: var(--primary-color); | |
| } | |
| /* Text inputs */ | |
| .text-input-section { | |
| margin-top: 15px; | |
| } | |
| input[type="text"], textarea { | |
| width: 100%; | |
| background-color: var(--dark-bg); | |
| color: var(--text-color); | |
| border: 1px solid var(--border-color); | |
| padding: 10px; | |
| border-radius: 6px; | |
| font-size: 14px; | |
| box-sizing: border-box; | |
| margin-top: 5px; | |
| } | |
| input[type="text"]:focus, textarea:focus { | |
| outline: none; | |
| border-color: var(--primary-color); | |
| } | |
| textarea { | |
| resize: vertical; | |
| min-height: 80px; | |
| } | |
| .chat-container { | |
| border-radius: 12px; | |
| background-color: var(--card-bg); | |
| box-shadow: 0 8px 32px rgba(0, 0, 0, 0.2); | |
| padding: 20px; | |
| flex-grow: 1; | |
| display: flex; | |
| flex-direction: column; | |
| border: 1px solid var(--border-color); | |
| overflow: hidden; | |
| min-height: 0; | |
| height: 100%; | |
| } | |
| .chat-messages { | |
| flex-grow: 1; | |
| overflow-y: auto; | |
| padding: 15px; | |
| scrollbar-width: thin; | |
| scrollbar-color: var(--primary-color) var(--card-bg); | |
| min-height: 0; | |
| max-height: calc(100vh - 250px); | |
| } | |
| .chat-messages::-webkit-scrollbar { | |
| width: 6px; | |
| } | |
| .chat-messages::-webkit-scrollbar-thumb { | |
| background-color: var(--primary-color); | |
| border-radius: 6px; | |
| } | |
| .message { | |
| margin-bottom: 15px; | |
| padding: 12px 16px; | |
| border-radius: 8px; | |
| font-size: 15px; | |
| line-height: 1.5; | |
| position: relative; | |
| max-width: 85%; | |
| animation: fade-in 0.3s ease-out; | |
| word-wrap: break-word; | |
| } | |
| @keyframes fade-in { | |
| from { | |
| opacity: 0; | |
| transform: translateY(10px); | |
| } | |
| to { | |
| opacity: 1; | |
| transform: translateY(0); | |
| } | |
| } | |
| .message.user { | |
| background: linear-gradient(135deg, #2c3e50, #34495e); | |
| margin-left: auto; | |
| border-bottom-right-radius: 2px; | |
| } | |
| .message.assistant { | |
| background: linear-gradient(135deg, var(--secondary-color), var(--primary-color)); | |
| margin-right: auto; | |
| border-bottom-left-radius: 2px; | |
| } | |
| .message.search-result { | |
| background: linear-gradient(135deg, #1a5a3e, #2e7d32); | |
| font-size: 14px; | |
| padding: 10px; | |
| margin-bottom: 10px; | |
| } | |
| .message.assistant.interpretation { | |
| background: linear-gradient(135deg, #1a5a3e, #2e7d32); | |
| font-style: italic; | |
| } | |
| .interpretation-arrow { | |
| color: #4caf50; | |
| font-weight: bold; | |
| margin: 0 10px; | |
| } | |
| .controls { | |
| text-align: center; | |
| margin-top: auto; | |
| display: flex; | |
| justify-content: center; | |
| gap: 10px; | |
| flex-shrink: 0; | |
| padding-top: 20px; | |
| } | |
| /* Responsive design */ | |
| @media (max-width: 1024px) { | |
| .sidebar { | |
| width: 300px; | |
| } | |
| } | |
| @media (max-width: 768px) { | |
| .main-content { | |
| flex-direction: column; | |
| } | |
| .sidebar { | |
| width: 100%; | |
| margin-bottom: 20px; | |
| } | |
| .chat-section { | |
| height: 400px; | |
| } | |
| } | |
| button { | |
| background: linear-gradient(135deg, var(--primary-color), var(--secondary-color)); | |
| color: white; | |
| border: none; | |
| padding: 14px 28px; | |
| font-family: inherit; | |
| font-size: 16px; | |
| cursor: pointer; | |
| transition: all 0.3s; | |
| text-transform: uppercase; | |
| letter-spacing: 1px; | |
| border-radius: 50px; | |
| display: flex; | |
| align-items: center; | |
| justify-content: center; | |
| gap: 10px; | |
| box-shadow: 0 4px 10px rgba(111, 66, 193, 0.3); | |
| } | |
| button:hover { | |
| transform: translateY(-2px); | |
| box-shadow: 0 6px 15px rgba(111, 66, 193, 0.5); | |
| background: linear-gradient(135deg, var(--hover-color), var(--primary-color)); | |
| } | |
| button:active { | |
| transform: translateY(1px); | |
| } | |
| #send-button { | |
| background: linear-gradient(135deg, #2ecc71, #27ae60); | |
| padding: 10px 20px; | |
| font-size: 14px; | |
| flex-shrink: 0; | |
| } | |
| #send-button:hover { | |
| background: linear-gradient(135deg, #27ae60, #229954); | |
| } | |
| #audio-output { | |
| display: none; | |
| } | |
| .icon-with-spinner { | |
| display: flex; | |
| align-items: center; | |
| justify-content: center; | |
| gap: 12px; | |
| min-width: 180px; | |
| } | |
| .spinner { | |
| width: 20px; | |
| height: 20px; | |
| border: 2px solid #ffffff; | |
| border-top-color: transparent; | |
| border-radius: 50%; | |
| animation: spin 1s linear infinite; | |
| flex-shrink: 0; | |
| } | |
| @keyframes spin { | |
| to { | |
| transform: rotate(360deg); | |
| } | |
| } | |
| .audio-visualizer { | |
| display: flex; | |
| align-items: center; | |
| justify-content: center; | |
| gap: 5px; | |
| min-width: 80px; | |
| height: 25px; | |
| } | |
| .visualizer-bar { | |
| width: 4px; | |
| height: 100%; | |
| background-color: rgba(255, 255, 255, 0.7); | |
| border-radius: 2px; | |
| transform-origin: bottom; | |
| transform: scaleY(0.1); | |
| transition: transform 0.1s ease; | |
| } | |
| .toast { | |
| position: fixed; | |
| top: 20px; | |
| left: 50%; | |
| transform: translateX(-50%); | |
| padding: 16px 24px; | |
| border-radius: 8px; | |
| font-size: 14px; | |
| z-index: 1000; | |
| display: none; | |
| box-shadow: 0 4px 12px rgba(0, 0, 0, 0.3); | |
| } | |
| .toast.error { | |
| background-color: #f44336; | |
| color: white; | |
| } | |
| .toast.warning { | |
| background-color: #ff9800; | |
| color: white; | |
| } | |
| .status-indicator { | |
| display: inline-flex; | |
| align-items: center; | |
| margin-top: 10px; | |
| font-size: 14px; | |
| color: #aaa; | |
| } | |
| .status-dot { | |
| width: 8px; | |
| height: 8px; | |
| border-radius: 50%; | |
| margin-right: 8px; | |
| } | |
| .status-dot.connected { | |
| background-color: #4caf50; | |
| } | |
| .status-dot.disconnected { | |
| background-color: #f44336; | |
| } | |
| .status-dot.connecting { | |
| background-color: #ff9800; | |
| animation: pulse 1.5s infinite; | |
| } | |
| @keyframes pulse { | |
| 0% { | |
| opacity: 0.6; | |
| } | |
| 50% { | |
| opacity: 1; | |
| } | |
| 100% { | |
| opacity: 0.6; | |
| } | |
| } | |
| .mouse-logo { | |
| position: relative; | |
| width: 40px; | |
| height: 40px; | |
| } | |
| .mouse-ears { | |
| position: absolute; | |
| width: 15px; | |
| height: 15px; | |
| background-color: var(--primary-color); | |
| border-radius: 50%; | |
| } | |
| .mouse-ear-left { | |
| top: 0; | |
| left: 5px; | |
| } | |
| .mouse-ear-right { | |
| top: 0; | |
| right: 5px; | |
| } | |
| .mouse-face { | |
| position: absolute; | |
| top: 10px; | |
| left: 5px; | |
| width: 30px; | |
| height: 30px; | |
| background-color: var(--secondary-color); | |
| border-radius: 50%; | |
| } | |
| .language-info { | |
| font-size: 12px; | |
| color: #888; | |
| margin-left: 5px; | |
| } | |
| </style> | |
| </head> | |
| <body> | |
| <div id="error-toast" class="toast"></div> | |
| <div class="container"> | |
| <div class="header"> | |
| <div class="logo"> | |
| <div class="mouse-logo"> | |
| <div class="mouse-ears mouse-ear-left"></div> | |
| <div class="mouse-ears mouse-ear-right"></div> | |
| <div class="mouse-face"></div> | |
| </div> | |
| <h1>MOUSE 음성 챗</h1> | |
| </div> | |
| <div class="status-indicator"> | |
| <div id="status-dot" class="status-dot disconnected"></div> | |
| <span id="status-text">연결 대기 중</span> | |
| </div> | |
| </div> | |
| <div class="main-content"> | |
| <div class="sidebar"> | |
| <div class="settings-section"> | |
| <h3 style="margin: 0 0 15px 0; color: var(--primary-color);">설정</h3> | |
| <div class="settings-grid"> | |
| <div class="setting-item"> | |
| <span class="setting-label">웹 검색</span> | |
| <div id="search-toggle" class="toggle-switch"> | |
| <div class="toggle-slider"></div> | |
| </div> | |
| </div> | |
| <div class="setting-item"> | |
| <span class="setting-label">자동 번역</span> | |
| <select id="language-select"> | |
| <option value="">비활성화</option> | |
| <option value="ko">한국어 (Korean)</option> | |
| <option value="en">English</option> | |
| <option value="es">Español (Spanish)</option> | |
| <option value="fr">Français (French)</option> | |
| <option value="de">Deutsch (German)</option> | |
| <option value="it">Italiano (Italian)</option> | |
| <option value="pt">Português (Portuguese)</option> | |
| <option value="ru">Русский (Russian)</option> | |
| <option value="ja">日本語 (Japanese)</option> | |
| <option value="zh">中文 (Chinese)</option> | |
| <option value="ar">العربية (Arabic)</option> | |
| <option value="hi">हिन्दी (Hindi)</option> | |
| <option value="nl">Nederlands (Dutch)</option> | |
| <option value="pl">Polski (Polish)</option> | |
| <option value="tr">Türkçe (Turkish)</option> | |
| <option value="vi">Tiếng Việt (Vietnamese)</option> | |
| <option value="th">ไทย (Thai)</option> | |
| <option value="id">Bahasa Indonesia</option> | |
| <option value="sv">Svenska (Swedish)</option> | |
| <option value="da">Dansk (Danish)</option> | |
| <option value="no">Norsk (Norwegian)</option> | |
| <option value="fi">Suomi (Finnish)</option> | |
| <option value="he">עברית (Hebrew)</option> | |
| <option value="uk">Українська (Ukrainian)</option> | |
| <option value="cs">Čeština (Czech)</option> | |
| <option value="el">Ελληνικά (Greek)</option> | |
| <option value="ro">Română (Romanian)</option> | |
| <option value="hu">Magyar (Hungarian)</option> | |
| <option value="ms">Bahasa Melayu (Malay)</option> | |
| </select> | |
| </div> | |
| </div> | |
| <div class="interpretation-section"> | |
| <div class="setting-item"> | |
| <span class="setting-label">자동 통역</span> | |
| <div id="interpretation-toggle" class="toggle-switch"> | |
| <div class="toggle-slider"></div> | |
| </div> | |
| </div> | |
| <div class="setting-item" id="interpretation-language-container" style="display: none;"> | |
| <span class="setting-label">통역 언어</span> | |
| <select id="interpretation-language-select"> | |
| <option value="">언어 선택</option> | |
| <option value="ko">한국어 (Korean)</option> | |
| <option value="en">English</option> | |
| <option value="es">Español (Spanish)</option> | |
| <option value="fr">Français (French)</option> | |
| <option value="de">Deutsch (German)</option> | |
| <option value="it">Italiano (Italian)</option> | |
| <option value="pt">Português (Portuguese)</option> | |
| <option value="ru">Русский (Russian)</option> | |
| <option value="ja">日本語 (Japanese)</option> | |
| <option value="zh">中文 (Chinese)</option> | |
| <option value="ar">العربية (Arabic)</option> | |
| <option value="hi">हिन्दी (Hindi)</option> | |
| <option value="nl">Nederlands (Dutch)</option> | |
| <option value="pl">Polski (Polish)</option> | |
| <option value="tr">Türkçe (Turkish)</option> | |
| <option value="vi">Tiếng Việt (Vietnamese)</option> | |
| <option value="th">ไทย (Thai)</option> | |
| <option value="id">Bahasa Indonesia</option> | |
| <option value="sv">Svenska (Swedish)</option> | |
| <option value="da">Dansk (Danish)</option> | |
| <option value="no">Norsk (Norwegian)</option> | |
| <option value="fi">Suomi (Finnish)</option> | |
| <option value="he">עברית (Hebrew)</option> | |
| <option value="uk">Українська (Ukrainian)</option> | |
| <option value="cs">Čeština (Czech)</option> | |
| <option value="el">Ελληνικά (Greek)</option> | |
| <option value="ro">Română (Romanian)</option> | |
| <option value="hu">Magyar (Hungarian)</option> | |
| <option value="ms">Bahasa Melayu (Malay)</option> | |
| </select> | |
| </div> | |
| </div> | |
| <div class="interpretation-info" id="interpretation-info" style="display: none;"> | |
| <strong>통역 모드 안내:</strong><br> | |
| • 음성으로 말하면 선택한 언어로 자동 통역됩니다<br> | |
| • Whisper + GPT-4o-mini + TTS를 사용합니다<br> | |
| • 말을 마치고 잠시 기다리면 통역이 시작됩니다 | |
| </div> | |
| <div class="text-input-section"> | |
| <label for="system-prompt" class="setting-label">시스템 프롬프트:</label> | |
| <textarea id="system-prompt" placeholder="AI 어시스턴트의 성격, 역할, 행동 방식을 정의하세요...">You are a helpful assistant. Respond in a friendly and professional manner.</textarea> | |
| </div> | |
| </div> | |
| <div class="controls"> | |
| <button id="start-button">대화 시작</button> | |
| </div> | |
| </div> | |
| <div class="chat-section"> | |
| <div class="chat-container"> | |
| <h3 style="margin: 0 0 15px 0; color: var(--primary-color);">대화</h3> | |
| <div class="chat-messages" id="chat-messages"></div> | |
| <div class="text-input-section" style="margin-top: 10px;"> | |
| <div style="display: flex; gap: 10px;"> | |
| <input type="text" id="text-input" placeholder="텍스트 메시지를 입력하세요..." style="flex-grow: 1;" /> | |
| <button id="send-button" style="display: none;">전송</button> | |
| </div> | |
| </div> | |
| </div> | |
| </div> | |
| </div> | |
| </div> | |
| <audio id="audio-output"></audio> | |
| <script> | |
| let peerConnection; | |
| let webrtc_id; | |
| let webSearchEnabled = false; | |
| let selectedLanguage = ""; | |
| let interpretationMode = false; | |
| let interpretationLanguage = ""; | |
| let systemPrompt = "You are a helpful assistant. Respond in a friendly and professional manner."; | |
| const audioOutput = document.getElementById('audio-output'); | |
| const startButton = document.getElementById('start-button'); | |
| const sendButton = document.getElementById('send-button'); | |
| const chatMessages = document.getElementById('chat-messages'); | |
| const statusDot = document.getElementById('status-dot'); | |
| const statusText = document.getElementById('status-text'); | |
| const searchToggle = document.getElementById('search-toggle'); | |
| const languageSelect = document.getElementById('language-select'); | |
| const interpretationToggle = document.getElementById('interpretation-toggle'); | |
| const interpretationLanguageSelect = document.getElementById('interpretation-language-select'); | |
| const interpretationLanguageContainer = document.getElementById('interpretation-language-container'); | |
| const interpretationInfo = document.getElementById('interpretation-info'); | |
| const systemPromptInput = document.getElementById('system-prompt'); | |
| const textInput = document.getElementById('text-input'); | |
| let audioLevel = 0; | |
| let animationFrame; | |
| let audioContext, analyser, audioSource; | |
| let dataChannel = null; | |
| let isVoiceActive = false; | |
| // Web search toggle functionality | |
| searchToggle.addEventListener('click', () => { | |
| webSearchEnabled = !webSearchEnabled; | |
| searchToggle.classList.toggle('active', webSearchEnabled); | |
| console.log('Web search enabled:', webSearchEnabled); | |
| }); | |
| // Language selection | |
| languageSelect.addEventListener('change', () => { | |
| selectedLanguage = languageSelect.value; | |
| console.log('Selected language:', selectedLanguage); | |
| }); | |
| // Interpretation mode toggle | |
| interpretationToggle.addEventListener('click', () => { | |
| if (!interpretationMode) { | |
| // Turning ON interpretation mode | |
| interpretationLanguageContainer.style.display = 'flex'; | |
| interpretationInfo.style.display = 'block'; | |
| // Show language selector first | |
| showError('통역 언어를 선택해주세요.'); | |
| interpretationToggle.classList.remove('active'); | |
| // Don't actually enable interpretation mode until language is selected | |
| return; | |
| } else { | |
| // Turning OFF interpretation mode | |
| interpretationMode = false; | |
| interpretationToggle.classList.remove('active'); | |
| interpretationLanguageContainer.style.display = 'none'; | |
| interpretationInfo.style.display = 'none'; | |
| interpretationLanguage = ''; | |
| interpretationLanguageSelect.value = ''; | |
| // Re-enable other features | |
| languageSelect.disabled = false; | |
| searchToggle.style.opacity = '1'; | |
| searchToggle.style.pointerEvents = 'auto'; | |
| textInput.disabled = false; | |
| textInput.placeholder = '텍스트 메시지를 입력하세요...'; | |
| sendButton.style.display = 'block'; | |
| console.log('Interpretation mode disabled'); | |
| // If connected, restart to apply normal mode | |
| if (peerConnection && peerConnection.connectionState === 'connected') { | |
| showError('일반 모드로 전환하기 위해 연결을 다시 시작합니다.'); | |
| stop(); | |
| setTimeout(() => { | |
| setupWebRTC(); | |
| }, 500); | |
| } | |
| } | |
| console.log('Interpretation mode:', interpretationMode); | |
| }); | |
| // Interpretation language selection | |
| interpretationLanguageSelect.addEventListener('change', () => { | |
| interpretationLanguage = interpretationLanguageSelect.value; | |
| console.log('Interpretation language:', interpretationLanguage); | |
| if (interpretationLanguage && !interpretationMode) { | |
| // Now actually enable interpretation mode | |
| interpretationMode = true; | |
| interpretationToggle.classList.add('active'); | |
| // Disable other features | |
| languageSelect.value = ''; | |
| selectedLanguage = ''; | |
| languageSelect.disabled = true; | |
| searchToggle.classList.remove('active'); | |
| webSearchEnabled = false; | |
| searchToggle.style.opacity = '0.5'; | |
| searchToggle.style.pointerEvents = 'none'; | |
| textInput.disabled = true; | |
| textInput.placeholder = '통역 모드에서는 텍스트 입력이 지원되지 않습니다'; | |
| sendButton.style.display = 'none'; | |
| console.log('Interpretation mode enabled with language:', interpretationLanguage); | |
| // If already connected, restart the connection with new settings | |
| if (peerConnection && peerConnection.connectionState === 'connected') { | |
| showError('통역 모드 설정을 적용하기 위해 연결을 다시 시작합니다.'); | |
| stop(); | |
| setTimeout(() => { | |
| setupWebRTC(); | |
| }, 500); | |
| } | |
| } | |
| }); | |
| // System prompt update | |
| systemPromptInput.addEventListener('input', () => { | |
| systemPrompt = systemPromptInput.value || "You are a helpful assistant. Respond in a friendly and professional manner."; | |
| }); | |
| // Text input handling | |
| textInput.addEventListener('keypress', (e) => { | |
| if (e.key === 'Enter' && !e.shiftKey) { | |
| e.preventDefault(); | |
| sendTextMessage(); | |
| } | |
| }); | |
| sendButton.addEventListener('click', sendTextMessage); | |
| async function sendTextMessage() { | |
| const message = textInput.value.trim(); | |
| if (!message) return; | |
| // Don't allow text messages in interpretation mode | |
| if (interpretationMode) { | |
| showError('통역 모드에서는 텍스트 입력이 지원되지 않습니다.'); | |
| return; | |
| } | |
| // Add user message to chat | |
| addMessage('user', message); | |
| textInput.value = ''; | |
| // Show sending indicator | |
| const typingIndicator = document.createElement('div'); | |
| typingIndicator.classList.add('message', 'assistant'); | |
| typingIndicator.textContent = '입력 중...'; | |
| typingIndicator.id = 'typing-indicator'; | |
| chatMessages.appendChild(typingIndicator); | |
| chatMessages.scrollTop = chatMessages.scrollHeight; | |
| try { | |
| // Send to text chat endpoint | |
| const response = await fetch('/chat/text', { | |
| method: 'POST', | |
| headers: { 'Content-Type': 'application/json' }, | |
| body: JSON.stringify({ | |
| message: message, | |
| web_search_enabled: webSearchEnabled, | |
| target_language: selectedLanguage, | |
| system_prompt: systemPrompt | |
| }) | |
| }); | |
| const data = await response.json(); | |
| // Remove typing indicator | |
| const indicator = document.getElementById('typing-indicator'); | |
| if (indicator) indicator.remove(); | |
| if (data.error) { | |
| showError(data.error); | |
| } else { | |
| // Add assistant response | |
| let content = data.response; | |
| if (selectedLanguage && data.language) { | |
| content += ` <span class="language-info">[${data.language}]</span>`; | |
| } | |
| addMessage('assistant', content); | |
| } | |
| } catch (error) { | |
| console.error('Error sending text message:', error); | |
| const indicator = document.getElementById('typing-indicator'); | |
| if (indicator) indicator.remove(); | |
| showError('메시지 전송 중 오류가 발생했습니다.'); | |
| } | |
| } | |
| function updateStatus(state) { | |
| statusDot.className = 'status-dot ' + state; | |
| if (state === 'connected') { | |
| statusText.textContent = '연결됨'; | |
| if (!interpretationMode) { | |
| sendButton.style.display = 'block'; | |
| } | |
| isVoiceActive = true; | |
| } else if (state === 'connecting') { | |
| statusText.textContent = '연결 중...'; | |
| sendButton.style.display = 'none'; | |
| } else { | |
| statusText.textContent = '연결 대기 중'; | |
| if (!interpretationMode) { | |
| sendButton.style.display = 'block'; // Show send button even when disconnected for text chat | |
| } | |
| isVoiceActive = false; | |
| } | |
| } | |
| function updateButtonState() { | |
| const button = document.getElementById('start-button'); | |
| if (peerConnection && (peerConnection.connectionState === 'connecting' || peerConnection.connectionState === 'new')) { | |
| button.innerHTML = ` | |
| <div class="icon-with-spinner"> | |
| <div class="spinner"></div> | |
| <span>연결 중...</span> | |
| </div> | |
| `; | |
| updateStatus('connecting'); | |
| } else if (peerConnection && peerConnection.connectionState === 'connected') { | |
| button.innerHTML = ` | |
| <div class="icon-with-spinner"> | |
| <div class="audio-visualizer" id="audio-visualizer"> | |
| <div class="visualizer-bar"></div> | |
| <div class="visualizer-bar"></div> | |
| <div class="visualizer-bar"></div> | |
| <div class="visualizer-bar"></div> | |
| <div class="visualizer-bar"></div> | |
| </div> | |
| <span>대화 종료</span> | |
| </div> | |
| `; | |
| updateStatus('connected'); | |
| } else { | |
| button.innerHTML = '대화 시작'; | |
| updateStatus('disconnected'); | |
| } | |
| } | |
| function setupAudioVisualization(stream) { | |
| audioContext = new (window.AudioContext || window.webkitAudioContext)(); | |
| analyser = audioContext.createAnalyser(); | |
| audioSource = audioContext.createMediaStreamSource(stream); | |
| audioSource.connect(analyser); | |
| analyser.fftSize = 256; | |
| const bufferLength = analyser.frequencyBinCount; | |
| const dataArray = new Uint8Array(bufferLength); | |
| const visualizerBars = document.querySelectorAll('.visualizer-bar'); | |
| const barCount = visualizerBars.length; | |
| function updateAudioLevel() { | |
| analyser.getByteFrequencyData(dataArray); | |
| for (let i = 0; i < barCount; i++) { | |
| const start = Math.floor(i * (bufferLength / barCount)); | |
| const end = Math.floor((i + 1) * (bufferLength / barCount)); | |
| let sum = 0; | |
| for (let j = start; j < end; j++) { | |
| sum += dataArray[j]; | |
| } | |
| const average = sum / (end - start) / 255; | |
| const scaleY = 0.1 + average * 0.9; | |
| visualizerBars[i].style.transform = `scaleY(${scaleY})`; | |
| } | |
| animationFrame = requestAnimationFrame(updateAudioLevel); | |
| } | |
| updateAudioLevel(); | |
| } | |
| function showError(message) { | |
| const toast = document.getElementById('error-toast'); | |
| toast.textContent = message; | |
| toast.className = 'toast error'; | |
| toast.style.display = 'block'; | |
| setTimeout(() => { | |
| toast.style.display = 'none'; | |
| }, 5000); | |
| } | |
| async function setupWebRTC() { | |
| const config = __RTC_CONFIGURATION__; | |
| peerConnection = new RTCPeerConnection(config); | |
| const timeoutId = setTimeout(() => { | |
| const toast = document.getElementById('error-toast'); | |
| toast.textContent = "연결이 평소보다 오래 걸리고 있습니다. VPN을 사용 중이신가요?"; | |
| toast.className = 'toast warning'; | |
| toast.style.display = 'block'; | |
| setTimeout(() => { | |
| toast.style.display = 'none'; | |
| }, 5000); | |
| }, 5000); | |
| try { | |
| const stream = await navigator.mediaDevices.getUserMedia({ | |
| audio: true | |
| }); | |
| setupAudioVisualization(stream); | |
| stream.getTracks().forEach(track => { | |
| peerConnection.addTrack(track, stream); | |
| }); | |
| peerConnection.addEventListener('track', (evt) => { | |
| if (audioOutput.srcObject !== evt.streams[0]) { | |
| audioOutput.srcObject = evt.streams[0]; | |
| audioOutput.play(); | |
| } | |
| }); | |
| // Create data channel for text messages | |
| dataChannel = peerConnection.createDataChannel('text'); | |
| dataChannel.onopen = () => { | |
| console.log('Data channel opened'); | |
| }; | |
| dataChannel.onmessage = (event) => { | |
| const eventJson = JSON.parse(event.data); | |
| if (eventJson.type === "error") { | |
| showError(eventJson.message); | |
| } | |
| }; | |
| const offer = await peerConnection.createOffer(); | |
| await peerConnection.setLocalDescription(offer); | |
| await new Promise((resolve) => { | |
| if (peerConnection.iceGatheringState === "complete") { | |
| resolve(); | |
| } else { | |
| const checkState = () => { | |
| if (peerConnection.iceGatheringState === "complete") { | |
| peerConnection.removeEventListener("icegatheringstatechange", checkState); | |
| resolve(); | |
| } | |
| }; | |
| peerConnection.addEventListener("icegatheringstatechange", checkState); | |
| } | |
| }); | |
| peerConnection.addEventListener('connectionstatechange', () => { | |
| console.log('connectionstatechange', peerConnection.connectionState); | |
| if (peerConnection.connectionState === 'connected') { | |
| clearTimeout(timeoutId); | |
| const toast = document.getElementById('error-toast'); | |
| toast.style.display = 'none'; | |
| } | |
| updateButtonState(); | |
| }); | |
| webrtc_id = Math.random().toString(36).substring(7); | |
| // Log current settings before sending | |
| console.log('Sending offer with settings:', { | |
| webrtc_id: webrtc_id, | |
| web_search_enabled: webSearchEnabled, | |
| target_language: selectedLanguage, | |
| system_prompt: systemPrompt, | |
| interpretation_mode: interpretationMode, | |
| interpretation_language: interpretationLanguage | |
| }); | |
| const response = await fetch('/webrtc/offer', { | |
| method: 'POST', | |
| headers: { 'Content-Type': 'application/json' }, | |
| body: JSON.stringify({ | |
| sdp: peerConnection.localDescription.sdp, | |
| type: peerConnection.localDescription.type, | |
| webrtc_id: webrtc_id, | |
| web_search_enabled: webSearchEnabled, | |
| target_language: selectedLanguage, | |
| system_prompt: systemPrompt, | |
| interpretation_mode: interpretationMode, | |
| interpretation_language: interpretationLanguage | |
| }) | |
| }); | |
| const serverResponse = await response.json(); | |
| if (serverResponse.status === 'failed') { | |
| showError(serverResponse.meta.error === 'concurrency_limit_reached' | |
| ? `너무 많은 연결입니다. 최대 한도는 ${serverResponse.meta.limit} 입니다.` | |
| : serverResponse.meta.error); | |
| stop(); | |
| return; | |
| } | |
| await peerConnection.setRemoteDescription(serverResponse); | |
| const eventSource = new EventSource('/outputs?webrtc_id=' + webrtc_id); | |
| eventSource.addEventListener("output", (event) => { | |
| const eventJson = JSON.parse(event.data); | |
| let content = eventJson.content; | |
| // Debug logging for interpretation mode | |
| if (interpretationMode) { | |
| console.log('[INTERPRETATION OUTPUT]', { | |
| content: content, | |
| language: eventJson.language, | |
| mode: eventJson.mode, | |
| expectedLanguage: interpretationLanguage | |
| }); | |
| } | |
| if (selectedLanguage && eventJson.language) { | |
| content += ` <span class="language-info">[${eventJson.language}]</span>`; | |
| } else if (interpretationMode && eventJson.language) { | |
| // In interpretation mode, show the translation process | |
| if (content.includes('→')) { | |
| // Format: "Korean text → English text" | |
| const parts = content.split('→'); | |
| if (parts.length === 2) { | |
| content = `<span style="color: #999;">${parts[0].trim()}</span>` + | |
| `<span class="interpretation-arrow">→</span>` + | |
| `<strong>${parts[1].trim()}</strong>`; | |
| } | |
| } | |
| content += ` <span class="language-info">[통역: ${eventJson.language}]</span>`; | |
| } | |
| addMessage("assistant", content); | |
| }); | |
| eventSource.addEventListener("search", (event) => { | |
| const eventJson = JSON.parse(event.data); | |
| if (eventJson.query) { | |
| addMessage("search-result", `웹 검색 중: "${eventJson.query}"`); | |
| } | |
| }); | |
| } catch (err) { | |
| clearTimeout(timeoutId); | |
| console.error('Error setting up WebRTC:', err); | |
| showError('연결을 설정하지 못했습니다. 다시 시도해 주세요.'); | |
| stop(); | |
| } | |
| } | |
| function addMessage(role, content) { | |
| const messageDiv = document.createElement('div'); | |
| messageDiv.classList.add('message', role); | |
| // Check if it's an interpretation message | |
| if (interpretationMode && role === 'assistant' && content.includes('→')) { | |
| messageDiv.classList.add('interpretation'); | |
| } | |
| if (content.includes('<span')) { | |
| messageDiv.innerHTML = content; | |
| } else { | |
| messageDiv.textContent = content; | |
| } | |
| chatMessages.appendChild(messageDiv); | |
| chatMessages.scrollTop = chatMessages.scrollHeight; | |
| } | |
| function stop() { | |
| if (animationFrame) { | |
| cancelAnimationFrame(animationFrame); | |
| } | |
| if (audioContext) { | |
| audioContext.close(); | |
| audioContext = null; | |
| analyser = null; | |
| audioSource = null; | |
| } | |
| if (peerConnection) { | |
| if (peerConnection.getTransceivers) { | |
| peerConnection.getTransceivers().forEach(transceiver => { | |
| if (transceiver.stop) { | |
| transceiver.stop(); | |
| } | |
| }); | |
| } | |
| if (peerConnection.getSenders) { | |
| peerConnection.getSenders().forEach(sender => { | |
| if (sender.track && sender.track.stop) sender.track.stop(); | |
| }); | |
| } | |
| console.log('closing'); | |
| peerConnection.close(); | |
| } | |
| dataChannel = null; | |
| updateButtonState(); | |
| audioLevel = 0; | |
| } | |
| startButton.addEventListener('click', () => { | |
| console.log('clicked'); | |
| console.log(peerConnection, peerConnection?.connectionState); | |
| if (!peerConnection || peerConnection.connectionState !== 'connected') { | |
| setupWebRTC(); | |
| } else { | |
| console.log('stopping'); | |
| stop(); | |
| } | |
| }); | |
| // Initialize send button visibility on page load | |
| window.addEventListener('DOMContentLoaded', () => { | |
| sendButton.style.display = 'block'; | |
| }); | |
| </script> | |
| </body> | |
| </html>""" | |
| class BraveSearchClient: | |
| """Brave Search API client""" | |
| def __init__(self, api_key: str): | |
| self.api_key = api_key | |
| self.base_url = "https://api.search.brave.com/res/v1/web/search" | |
| async def search(self, query: str, count: int = 10) -> List[Dict]: | |
| """Perform a web search using Brave Search API""" | |
| if not self.api_key: | |
| return [] | |
| headers = { | |
| "Accept": "application/json", | |
| "X-Subscription-Token": self.api_key | |
| } | |
| params = { | |
| "q": query, | |
| "count": count, | |
| "lang": "ko" | |
| } | |
| async with httpx.AsyncClient() as client: | |
| try: | |
| response = await client.get(self.base_url, headers=headers, params=params) | |
| response.raise_for_status() | |
| data = response.json() | |
| results = [] | |
| if "web" in data and "results" in data["web"]: | |
| for result in data["web"]["results"][:count]: | |
| results.append({ | |
| "title": result.get("title", ""), | |
| "url": result.get("url", ""), | |
| "description": result.get("description", "") | |
| }) | |
| return results | |
| except Exception as e: | |
| print(f"Brave Search error: {e}") | |
| return [] | |
| # Initialize search client globally | |
| brave_api_key = os.getenv("BSEARCH_API") | |
| search_client = BraveSearchClient(brave_api_key) if brave_api_key else None | |
| print(f"Search client initialized: {search_client is not None}, API key present: {bool(brave_api_key)}") | |
| # Store connection settings | |
| connection_settings = {} | |
| # Initialize OpenAI client for text chat | |
| client = openai.AsyncOpenAI() | |
| def get_translation_instructions(target_language: str) -> str: | |
| """Get instructions for translation based on target language""" | |
| if not target_language: | |
| return "" | |
| language_name = SUPPORTED_LANGUAGES.get(target_language, target_language) | |
| return ( | |
| f"\n\nIMPORTANT: You must respond in {language_name} ({target_language}). " | |
| f"Translate all your responses to {language_name}." | |
| ) | |
| def update_chatbot(chatbot: list[dict], response: ResponseAudioTranscriptDoneEvent): | |
| chatbot.append({"role": "assistant", "content": response.transcript}) | |
| return chatbot | |
| def get_translation_instructions(target_language: str) -> str: | |
| """Get instructions for translation based on target language""" | |
| if not target_language: | |
| return "" | |
| language_name = SUPPORTED_LANGUAGES.get(target_language, target_language) | |
| return ( | |
| f"\n\nIMPORTANT: You must respond in {language_name} ({target_language}). " | |
| f"Translate all your responses to {language_name}." | |
| ) | |
| async def process_text_chat(message: str, web_search_enabled: bool, target_language: str, | |
| system_prompt: str) -> Dict[str, str]: | |
| """Process text chat using GPT-4o-mini model""" | |
| try: | |
| # If target language is set, override system prompt completely | |
| if target_language: | |
| language_name = SUPPORTED_LANGUAGES.get(target_language, target_language) | |
| # Create system prompt in target language | |
| if target_language == "en": | |
| base_instructions = f"You are a helpful assistant. You speak ONLY English. Never use Korean or any other language. {system_prompt}" | |
| user_prefix = "Please respond in English: " | |
| elif target_language == "ja": | |
| base_instructions = f"あなたは親切なアシスタントです。日本語のみを話します。韓国語や他の言語は絶対に使用しません。{system_prompt}" | |
| user_prefix = "日本語で答えてください: " | |
| elif target_language == "zh": | |
| base_instructions = f"你是一个乐于助人的助手。你只说中文。绝不使用韩语或其他语言。{system_prompt}" | |
| user_prefix = "请用中文回答: " | |
| elif target_language == "es": | |
| base_instructions = f"Eres un asistente útil. Solo hablas español. Nunca uses coreano u otros idiomas. {system_prompt}" | |
| user_prefix = "Por favor responde en español: " | |
| else: | |
| base_instructions = f"You are a helpful assistant that speaks ONLY {language_name}. {system_prompt}" | |
| user_prefix = f"Please respond in {language_name}: " | |
| else: | |
| base_instructions = system_prompt or "You are a helpful assistant." | |
| user_prefix = "" | |
| messages = [ | |
| {"role": "system", "content": base_instructions} | |
| ] | |
| # Handle web search if enabled | |
| if web_search_enabled and search_client: | |
| # Check if the message requires web search | |
| search_keywords = ["날씨", "기온", "비", "눈", "뉴스", "소식", "현재", "최근", | |
| "오늘", "지금", "가격", "환율", "주가", "weather", "news", | |
| "current", "today", "price", "2024", "2025"] | |
| should_search = any(keyword in message.lower() for keyword in search_keywords) | |
| if should_search: | |
| # Perform web search | |
| search_results = await search_client.search(message) | |
| if search_results: | |
| search_context = "웹 검색 결과:\n\n" | |
| for i, result in enumerate(search_results[:5], 1): | |
| search_context += f"{i}. {result['title']}\n{result['description']}\n\n" | |
| # Add search context in target language if set | |
| if target_language: | |
| search_instruction = f"Use this search information but respond in {SUPPORTED_LANGUAGES.get(target_language, target_language)} only: " | |
| else: | |
| search_instruction = "다음 웹 검색 결과를 참고하여 답변하세요: " | |
| messages.append({ | |
| "role": "system", | |
| "content": search_instruction + "\n\n" + search_context | |
| }) | |
| # Add user message with language prefix | |
| messages.append({"role": "user", "content": user_prefix + message}) | |
| # Call GPT-4o-mini | |
| response = await client.chat.completions.create( | |
| model="gpt-4o-mini", | |
| messages=messages, | |
| temperature=0.7, | |
| max_tokens=2000 | |
| ) | |
| response_text = response.choices[0].message.content | |
| # Final check - remove any Korean if target language is not Korean | |
| if target_language and target_language != "ko": | |
| import re | |
| if re.search(r'[가-힣]', response_text): | |
| print(f"[TEXT CHAT] WARNING: Korean detected in response for {target_language}") | |
| # Try again with stronger prompt | |
| messages[-1] = {"role": "user", "content": f"ONLY {SUPPORTED_LANGUAGES.get(target_language, target_language)}, NO KOREAN: {message}"} | |
| retry_response = await client.chat.completions.create( | |
| model="gpt-4o-mini", | |
| messages=messages, | |
| temperature=0.3, | |
| max_tokens=2000 | |
| ) | |
| response_text = retry_response.choices[0].message.content | |
| print(f"[TEXT CHAT] Target language: {target_language}") | |
| print(f"[TEXT CHAT] Response preview: {response_text[:100]}...") | |
| return { | |
| "response": response_text, | |
| "language": SUPPORTED_LANGUAGES.get(target_language, "") if target_language else "" | |
| } | |
| except Exception as e: | |
| print(f"Error in text chat: {e}") | |
| return {"error": str(e)} | |
| class OpenAIHandler(AsyncStreamHandler): | |
| def __init__(self, web_search_enabled: bool = False, target_language: str = "", | |
| system_prompt: str = "", webrtc_id: str = None, | |
| interpretation_mode: bool = False, interpretation_language: str = "") -> None: | |
| super().__init__( | |
| expected_layout="mono", | |
| output_sample_rate=SAMPLE_RATE, | |
| output_frame_size=480, | |
| input_sample_rate=SAMPLE_RATE, | |
| ) | |
| self.connection = None | |
| self.output_queue = asyncio.Queue() | |
| self.search_client = search_client | |
| self.function_call_in_progress = False | |
| self.current_function_args = "" | |
| self.current_call_id = None | |
| self.webrtc_id = webrtc_id | |
| self.web_search_enabled = web_search_enabled | |
| self.target_language = target_language | |
| self.system_prompt = system_prompt | |
| self.interpretation_mode = interpretation_mode | |
| self.interpretation_language = interpretation_language | |
| # For interpretation mode | |
| self.audio_buffer = [] | |
| self.is_recording = False | |
| self.silence_frames = 0 | |
| self.silence_threshold = 20 # Reduced for faster response (20 frames = ~0.4 seconds) | |
| self.min_audio_length = 10 # Minimum frames to consider as speech | |
| print(f"Handler created with web_search_enabled={web_search_enabled}, " | |
| f"target_language={target_language}, webrtc_id={webrtc_id}, " | |
| f"interpretation_mode={interpretation_mode}, interpretation_language={interpretation_language}") | |
| def copy(self): | |
| # Get the most recent settings | |
| if connection_settings: | |
| # Get the most recent webrtc_id | |
| recent_ids = sorted(connection_settings.keys(), | |
| key=lambda k: connection_settings[k].get('timestamp', 0), | |
| reverse=True) | |
| if recent_ids: | |
| recent_id = recent_ids[0] | |
| settings = connection_settings[recent_id] | |
| return OpenAIHandler( | |
| web_search_enabled=settings.get('web_search_enabled', False), | |
| target_language=settings.get('target_language', ''), | |
| system_prompt=settings.get('system_prompt', ''), | |
| webrtc_id=recent_id, | |
| interpretation_mode=settings.get('interpretation_mode', False), | |
| interpretation_language=settings.get('interpretation_language', '') | |
| ) | |
| print(f"Handler.copy() called - creating new handler with default settings") | |
| return OpenAIHandler(web_search_enabled=False, interpretation_mode=False) | |
| async def search_web(self, query: str) -> str: | |
| """Perform web search and return formatted results""" | |
| if not self.search_client or not self.web_search_enabled: | |
| return "웹 검색이 비활성화되어 있습니다." | |
| print(f"Searching web for: {query}") | |
| results = await self.search_client.search(query) | |
| if not results: | |
| return f"'{query}'에 대한 검색 결과를 찾을 수 없습니다." | |
| # Format search results | |
| formatted_results = [] | |
| for i, result in enumerate(results, 1): | |
| formatted_results.append( | |
| f"{i}. {result['title']}\n" | |
| f" URL: {result['url']}\n" | |
| f" {result['description']}\n" | |
| ) | |
| return f"웹 검색 결과 '{query}':\n\n" + "\n".join(formatted_results) | |
| async def process_text_message(self, message: str): | |
| """Process text message from user""" | |
| if self.connection: | |
| await self.connection.conversation.item.create( | |
| item={ | |
| "type": "message", | |
| "role": "user", | |
| "content": [{"type": "input_text", "text": message}] | |
| } | |
| ) | |
| await self.connection.response.create() | |
| async def process_interpretation(self): | |
| """Process audio buffer for interpretation""" | |
| if not self.audio_buffer or not self.interpretation_language: | |
| return | |
| try: | |
| print(f"[INTERPRETATION] Processing audio buffer with {len(self.audio_buffer)} frames") | |
| # Convert audio buffer to WAV format | |
| audio_data = np.concatenate(self.audio_buffer) | |
| # Create WAV file in memory | |
| wav_buffer = io.BytesIO() | |
| with wave.open(wav_buffer, 'wb') as wav_file: | |
| wav_file.setnchannels(1) # Mono | |
| wav_file.setsampwidth(2) # 16-bit | |
| wav_file.setframerate(SAMPLE_RATE) | |
| wav_file.writeframes(audio_data.tobytes()) | |
| wav_buffer.seek(0) | |
| wav_buffer.name = "audio.wav" | |
| # 1. Transcribe with Whisper | |
| print("[INTERPRETATION] Transcribing with Whisper...") | |
| transcript = await self.client.audio.transcriptions.create( | |
| model="whisper-1", | |
| file=wav_buffer, | |
| language="ko" # Assuming Korean input | |
| ) | |
| user_text = transcript.text.strip() | |
| print(f"[INTERPRETATION] Transcribed: {user_text}") | |
| if not user_text: | |
| return | |
| # 2. Translate with GPT-4o-mini | |
| target_lang_name = SUPPORTED_LANGUAGES.get(self.interpretation_language, self.interpretation_language) | |
| # Create very explicit translation examples | |
| translation_examples = { | |
| "en": { | |
| "안녕하세요": "Hello", | |
| "감사합니다": "Thank you", | |
| "오늘 날씨가 좋네요": "The weather is nice today" | |
| }, | |
| "ja": { | |
| "안녕하세요": "こんにちは", | |
| "감사합니다": "ありがとうございます", | |
| "오늘 날씨가 좋네요": "今日はいい天気ですね" | |
| }, | |
| "zh": { | |
| "안녕하세요": "你好", | |
| "감사합니다": "谢谢", | |
| "오늘 날씨가 좋네요": "今天天气很好" | |
| }, | |
| "es": { | |
| "안녕하세요": "Hola", | |
| "감사합니다": "Gracias", | |
| "오늘 날씨가 좋네요": "El clima está agradable hoy" | |
| } | |
| } | |
| examples = translation_examples.get(self.interpretation_language, translation_examples["en"]) | |
| examples_text = "\n".join([f'"{k}" → "{v}"' for k, v in examples.items()]) | |
| # Ultra-specific prompt | |
| system_prompt = f"""You are a Korean to {target_lang_name} translator. | |
| STRICT RULES: | |
| 1. Output ONLY the {target_lang_name} translation | |
| 2. Do NOT output Korean | |
| 3. Do NOT add explanations | |
| 4. Do NOT answer questions | |
| 5. Just translate | |
| Examples: | |
| {examples_text} | |
| Now translate the Korean text to {target_lang_name}. Output ONLY the translation in {target_lang_name}:""" | |
| print(f"[INTERPRETATION] Translating to {target_lang_name}...") | |
| print(f"[INTERPRETATION] System prompt: {system_prompt}") | |
| translation_response = await self.client.chat.completions.create( | |
| model="gpt-4o-mini", | |
| messages=[ | |
| { | |
| "role": "system", | |
| "content": system_prompt | |
| }, | |
| { | |
| "role": "user", | |
| "content": f"Translate this Korean to {target_lang_name}: {user_text}" | |
| } | |
| ], | |
| temperature=0.1, # Very low temperature | |
| max_tokens=200 | |
| ) | |
| translated_text = translation_response.choices[0].message.content.strip() | |
| # Remove any Korean characters if they accidentally appear | |
| import re | |
| if re.search(r'[가-힣]', translated_text): | |
| print(f"[INTERPRETATION] WARNING: Korean characters detected in translation: {translated_text}") | |
| # Try to extract only non-Korean parts | |
| translated_text = re.sub(r'[가-힣\s]+', ' ', translated_text).strip() | |
| print(f"[INTERPRETATION] Translated: {translated_text}") | |
| # 3. Generate speech with TTS | |
| print(f"[INTERPRETATION] Generating speech for text: {translated_text}") | |
| # Select appropriate voice and ensure it speaks the target language | |
| voice_map = { | |
| "en": "alloy", # Alloy is native English speaker | |
| "es": "nova", # Nova handles Spanish well | |
| "fr": "shimmer", # Shimmer handles French well | |
| "de": "echo", # Echo handles German well | |
| "ja": "nova", # Nova can handle Japanese | |
| "zh": "nova", # Nova can handle Chinese | |
| "ko": "nova", # Nova can handle Korean | |
| } | |
| selected_voice = voice_map.get(self.interpretation_language, "nova") | |
| print(f"[INTERPRETATION] Using voice: {selected_voice} for language: {self.interpretation_language}") | |
| # For some languages, we might need to add pronunciation hints | |
| if self.interpretation_language == "en" and re.search(r'[가-힣]', translated_text): | |
| print("[INTERPRETATION] ERROR: Korean characters in English translation!") | |
| translated_text = "Translation error occurred" | |
| try: | |
| tts_response = await self.client.audio.speech.create( | |
| model="tts-1", | |
| voice=selected_voice, | |
| input=translated_text, | |
| response_format="pcm", # PCM format for direct playback | |
| speed=1.0 | |
| ) | |
| except Exception as tts_error: | |
| print(f"[INTERPRETATION] TTS Error: {tts_error}") | |
| # If TTS fails, try with a different voice | |
| tts_response = await self.client.audio.speech.create( | |
| model="tts-1", | |
| voice="alloy", # Fallback to alloy | |
| input=translated_text, | |
| response_format="pcm", | |
| speed=1.0 | |
| ) | |
| # Convert response to bytes | |
| audio_bytes = b"" | |
| async for chunk in tts_response.iter_bytes(1024): | |
| audio_bytes += chunk | |
| # Convert PCM to numpy array (TTS outputs at 24kHz) | |
| audio_array = np.frombuffer(audio_bytes, dtype=np.int16) | |
| # Send audio in chunks | |
| if len(audio_array) > 0: | |
| # Split audio into chunks and send | |
| chunk_size = 480 # Match our frame size | |
| for i in range(0, len(audio_array), chunk_size): | |
| chunk = audio_array[i:i + chunk_size] | |
| if len(chunk) < chunk_size: | |
| # Pad the last chunk if necessary | |
| chunk = np.pad(chunk, (0, chunk_size - len(chunk)), 'constant') | |
| await self.output_queue.put((SAMPLE_RATE, chunk.reshape(1, -1))) | |
| # Send transcript event | |
| output_data = { | |
| "event": type('Event', (), { | |
| 'transcript': f"{user_text} → {translated_text}" | |
| })(), | |
| "language": target_lang_name, | |
| "mode": "interpretation" | |
| } | |
| await self.output_queue.put(AdditionalOutputs(output_data)) | |
| except Exception as e: | |
| print(f"[INTERPRETATION] Error: {e}") | |
| import traceback | |
| traceback.print_exc() | |
| # Send error message to client | |
| error_data = { | |
| "event": type('Event', (), { | |
| 'transcript': f"통역 오류: {str(e)}" | |
| })(), | |
| "language": "", | |
| "mode": "error" | |
| } | |
| await self.output_queue.put(AdditionalOutputs(error_data)) | |
| finally: | |
| # Clear the audio buffer | |
| self.audio_buffer = [] | |
| self.is_recording = False | |
| self.silence_frames = 0 | |
| def get_translation_instructions(self): | |
| """Get instructions for translation based on target language""" | |
| if not self.target_language or self.interpretation_mode: | |
| return "" | |
| language_name = SUPPORTED_LANGUAGES.get(self.target_language, self.target_language) | |
| return ( | |
| f"\n\nIMPORTANT: You must respond in {language_name} ({self.target_language}). " | |
| f"Translate all your responses to {language_name}. " | |
| f"This includes both spoken and written responses." | |
| ) | |
| async def start_up(self): | |
| """Connect to realtime API or setup interpretation mode""" | |
| # First check if we have the most recent settings | |
| if connection_settings: | |
| recent_ids = sorted(connection_settings.keys(), | |
| key=lambda k: connection_settings[k].get('timestamp', 0), | |
| reverse=True) | |
| if recent_ids: | |
| recent_id = recent_ids[0] | |
| settings = connection_settings[recent_id] | |
| self.web_search_enabled = settings.get('web_search_enabled', False) | |
| self.target_language = settings.get('target_language', '') | |
| self.system_prompt = settings.get('system_prompt', '') | |
| self.interpretation_mode = settings.get('interpretation_mode', False) | |
| self.interpretation_language = settings.get('interpretation_language', '') | |
| self.webrtc_id = recent_id | |
| print(f"start_up: Updated settings from storage - webrtc_id={self.webrtc_id}, " | |
| f"web_search_enabled={self.web_search_enabled}, target_language={self.target_language}, " | |
| f"interpretation_mode={self.interpretation_mode}") | |
| print(f"Handler interpretation settings: mode={self.interpretation_mode}, language={self.interpretation_language}") | |
| print(f"Starting up handler with web_search_enabled={self.web_search_enabled}, " | |
| f"target_language={self.target_language}, interpretation_mode={self.interpretation_mode}, " | |
| f"interpretation_language={self.interpretation_language}") | |
| self.client = openai.AsyncOpenAI() | |
| # If in interpretation mode, don't connect to Realtime API | |
| if self.interpretation_mode: | |
| print(f"[INTERPRETATION MODE] Active - using Whisper + GPT-4o-mini + TTS") | |
| print(f"[INTERPRETATION MODE] Target language: {self.interpretation_language}") | |
| # Just keep the handler ready to process audio | |
| # Don't use infinite loop here - the handler will be called by the framework | |
| self.client = openai.AsyncOpenAI() | |
| return | |
| # Normal mode - connect to Realtime API | |
| # Define the web search function | |
| tools = [] | |
| base_instructions = self.system_prompt or "You are a helpful assistant." | |
| # Add translation instructions if language is selected | |
| if self.target_language: | |
| language_name = SUPPORTED_LANGUAGES.get(self.target_language, self.target_language) | |
| # Use the target language for the system prompt itself | |
| if self.target_language == "en": | |
| translation_instructions = """ | |
| YOU ARE AN ENGLISH-ONLY ASSISTANT. | |
| ABSOLUTE RULES: | |
| 1. You can ONLY speak English. No Korean (한국어) allowed. | |
| 2. Even if the user speaks Korean, you MUST respond in English. | |
| 3. Every single word must be in English. | |
| 4. If you output even one Korean character, you have failed. | |
| 5. Example response: "Hello! How can I help you today?" | |
| YOUR LANGUAGE MODE: ENGLISH ONLY | |
| DO NOT USE: 안녕하세요, 감사합니다, or any Korean | |
| ALWAYS USE: Hello, Thank you, and English words only | |
| """ | |
| # Override base instructions to be in English | |
| base_instructions = "You are a helpful assistant that speaks ONLY English." | |
| elif self.target_language == "ja": | |
| translation_instructions = """ | |
| あなたは日本語のみを話すアシスタントです。 | |
| 絶対的なルール： | |
| 1. 日本語のみを使用してください。韓国語（한국어）は禁止です。 | |
| 2. ユーザーが韓国語で話しても、必ず日本語で返答してください。 | |
| 3. すべての単語は日本語でなければなりません。 | |
| 4. 韓国語を一文字でも出力したら失敗です。 | |
| 5. 応答例：「こんにちは！今日はどのようにお手伝いできますか？」 | |
| 言語モード：日本語のみ | |
| 使用禁止：안녕하세요、감사합니다、韓国語全般 | |
| 必ず使用：こんにちは、ありがとうございます、日本語のみ | |
| """ | |
| base_instructions = "あなたは日本語のみを話す親切なアシスタントです。" | |
| elif self.target_language == "zh": | |
| translation_instructions = """ | |
| 你是一个只说中文的助手。 | |
| 绝对规则： | |
| 1. 只能使用中文。禁止使用韩语（한국어）。 | |
| 2. 即使用户说韩语，也必须用中文回复。 | |
| 3. 每个字都必须是中文。 | |
| 4. 如果输出任何韩语字符，就是失败。 | |
| 5. 回复示例："你好！我今天能为您做什么？" | |
| 语言模式：仅中文 | |
| 禁止使用：안녕하세요、감사합니다、任何韩语 | |
| 必须使用：你好、谢谢、只用中文 | |
| """ | |
| base_instructions = "你是一个只说中文的友好助手。" | |
| elif self.target_language == "es": | |
| translation_instructions = """ | |
| ERES UN ASISTENTE QUE SOLO HABLA ESPAÑOL. | |
| REGLAS ABSOLUTAS: | |
| 1. Solo puedes hablar español. No se permite coreano (한국어). | |
| 2. Incluso si el usuario habla coreano, DEBES responder en español. | |
| 3. Cada palabra debe estar en español. | |
| 4. Si produces aunque sea un carácter coreano, has fallado. | |
| 5. Respuesta ejemplo: "¡Hola! ¿Cómo puedo ayudarte hoy?" | |
| MODO DE IDIOMA: SOLO ESPAÑOL | |
| NO USAR: 안녕하세요, 감사합니다, o cualquier coreano | |
| SIEMPRE USAR: Hola, Gracias, y solo palabras en español | |
| """ | |
| base_instructions = "Eres un asistente útil que habla SOLO español." | |
| else: | |
| translation_instructions = f""" | |
| YOU MUST ONLY SPEAK {language_name.upper()}. | |
| RULES: | |
| 1. Output only in {language_name} | |
| 2. Never use Korean | |
| 3. Always respond in {language_name} | |
| """ | |
| base_instructions = f"You are a helpful assistant that speaks ONLY {language_name}." | |
| else: | |
| translation_instructions = "" | |
| if self.web_search_enabled and self.search_client: | |
| tools = [{ | |
| "type": "function", | |
| "function": { | |
| "name": "web_search", | |
| "description": "Search the web for current information. Use this for weather, news, prices, current events, or any time-sensitive topics.", | |
| "parameters": { | |
| "type": "object", | |
| "properties": { | |
| "query": { | |
| "type": "string", | |
| "description": "The search query" | |
| } | |
| }, | |
| "required": ["query"] | |
| } | |
| } | |
| }] | |
| print("Web search function added to tools") | |
| search_instructions = ( | |
| "\n\nYou have web search capabilities. " | |
| "IMPORTANT: You MUST use the web_search function for ANY of these topics:\n" | |
| "- Weather (날씨, 기온, 비, 눈)\n" | |
| "- News (뉴스, 소식)\n" | |
| "- Current events (현재, 최근, 오늘, 지금)\n" | |
| "- Prices (가격, 환율, 주가)\n" | |
| "- Sports scores or results\n" | |
| "- Any question about 2024 or 2025\n" | |
| "- Any time-sensitive information\n\n" | |
| "When in doubt, USE web_search. It's better to search and provide accurate information " | |
| "than to guess or use outdated information." | |
| ) | |
| # Combine all instructions | |
| if translation_instructions: | |
| # Translation instructions already include base_instructions | |
| instructions = translation_instructions + search_instructions | |
| else: | |
| instructions = base_instructions + search_instructions | |
| else: | |
| # No web search | |
| if translation_instructions: | |
| instructions = translation_instructions | |
| else: | |
| instructions = base_instructions | |
| print(f"[NORMAL MODE] Base instructions: {base_instructions[:100]}...") | |
| print(f"[NORMAL MODE] Translation instructions: {translation_instructions[:200] if translation_instructions else 'None'}...") | |
| print(f"[NORMAL MODE] Combined instructions length: {len(instructions)}") | |
| print(f"[NORMAL MODE] Target language: {self.target_language}") | |
| async with self.client.beta.realtime.connect( | |
| model="gpt-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", | |
| "temperature": 0.7, | |
| "max_response_output_tokens": 4096, | |
| "modalities": ["text", "audio"], | |
| "voice": "alloy" # Default voice | |
| } | |
| # Use appropriate voice for the language | |
| if self.target_language: | |
| # Force language through multiple mechanisms | |
| # 1. Use voice that's known to work well with the language | |
| voice_map = { | |
| "en": "nova", # Nova has clearer English | |
| "es": "nova", # Nova works for Spanish | |
| "fr": "shimmer", # Shimmer for French | |
| "de": "echo", # Echo for German | |
| "ja": "alloy", # Alloy can do Japanese | |
| "zh": "alloy", # Alloy can do Chinese | |
| "ko": "nova", # Nova for Korean | |
| } | |
| session_update["voice"] = voice_map.get(self.target_language, "nova") | |
| # 2. Add language to modalities (experimental) | |
| session_update["modalities"] = ["text", "audio"] | |
| # 3. Set output format | |
| session_update["output_audio_format"] = "pcm16" | |
| # 4. Add language hint to the system (if supported by API) | |
| if self.target_language in ["en", "es", "fr", "de", "ja", "zh"]: | |
| session_update["language"] = self.target_language # Try setting language directly | |
| print(f"[TRANSLATION MODE] Session update: {json.dumps(session_update, indent=2)}") | |
| await conn.session.update(session=session_update) | |
| self.connection = conn | |
| print(f"Connected with tools: {len(tools)} functions, voice: {session_update.get('voice', 'default')}") | |
| async for event in self.connection: | |
| # Debug logging for function calls | |
| if event.type.startswith("response.function_call"): | |
| print(f"Function event: {event.type}") | |
| if event.type == "response.audio_transcript.done": | |
| print(f"[RESPONSE] Transcript: {event.transcript[:100]}...") | |
| print(f"[RESPONSE] Expected language: {self.target_language}") | |
| output_data = { | |
| "event": event, | |
| "language": SUPPORTED_LANGUAGES.get(self.target_language, "") if self.target_language else "" | |
| } | |
| await self.output_queue.put(AdditionalOutputs(output_data)) | |
| elif event.type == "response.audio.delta": | |
| await self.output_queue.put( | |
| ( | |
| self.output_sample_rate, | |
| np.frombuffer( | |
| base64.b64decode(event.delta), dtype=np.int16 | |
| ).reshape(1, -1), | |
| ), | |
| ) | |
| # Handle function calls (only in non-interpretation mode) | |
| elif event.type == "response.function_call_arguments.start" and not self.interpretation_mode: | |
| print(f"Function call started") | |
| self.function_call_in_progress = True | |
| self.current_function_args = "" | |
| self.current_call_id = getattr(event, 'call_id', None) | |
| elif event.type == "response.function_call_arguments.delta" and not self.interpretation_mode: | |
| if self.function_call_in_progress: | |
| self.current_function_args += event.delta | |
| elif event.type == "response.function_call_arguments.done" and not self.interpretation_mode: | |
| if self.function_call_in_progress: | |
| print(f"Function call done, args: {self.current_function_args}") | |
| try: | |
| args = json.loads(self.current_function_args) | |
| query = args.get("query", "") | |
| # Emit search event to client | |
| await self.output_queue.put(AdditionalOutputs({ | |
| "type": "search", | |
| "query": query | |
| })) | |
| # Perform the search | |
| search_results = await self.search_web(query) | |
| print(f"Search results length: {len(search_results)}") | |
| # Send function result back to the model | |
| if self.connection and self.current_call_id: | |
| await self.connection.conversation.item.create( | |
| item={ | |
| "type": "function_call_output", | |
| "call_id": self.current_call_id, | |
| "output": search_results | |
| } | |
| ) | |
| await self.connection.response.create() | |
| except Exception as e: | |
| print(f"Function call error: {e}") | |
| finally: | |
| self.function_call_in_progress = False | |
| self.current_function_args = "" | |
| self.current_call_id = None | |
| async def receive(self, frame: tuple[int, np.ndarray]) -> None: | |
| if self.interpretation_mode: | |
| # In interpretation mode, buffer audio and process with Whisper | |
| _, array = frame | |
| array = array.squeeze() | |
| # Simple voice activity detection | |
| audio_level = np.abs(array).mean() | |
| if audio_level > 200: # Lower threshold for better detection | |
| if not self.is_recording: | |
| print(f"[INTERPRETATION] Started recording, level: {audio_level:.1f}") | |
| self.is_recording = True | |
| self.silence_frames = 0 | |
| self.audio_buffer.append(array) | |
| elif self.is_recording: | |
| self.silence_frames += 1 | |
| self.audio_buffer.append(array) | |
| # If we've had enough silence, process the audio | |
| if self.silence_frames > self.silence_threshold and len(self.audio_buffer) > self.min_audio_length: | |
| print(f"[INTERPRETATION] Silence detected after {len(self.audio_buffer)} frames") | |
| # Process in the background to avoid blocking | |
| asyncio.create_task(self.process_interpretation()) | |
| else: | |
| # Normal mode - use Realtime API | |
| if not self.connection: | |
| return | |
| try: | |
| _, array = frame | |
| array = array.squeeze() | |
| audio_message = base64.b64encode(array.tobytes()).decode("utf-8") | |
| await self.connection.input_audio_buffer.append(audio=audio_message) | |
| except Exception as e: | |
| print(f"Error in receive: {e}") | |
| # Connection might be closed, ignore the error | |
| async def emit(self) -> tuple[int, np.ndarray] | AdditionalOutputs | None: | |
| # In interpretation mode, we need to keep checking for audio | |
| if self.interpretation_mode: | |
| # Use a timeout to prevent blocking forever | |
| try: | |
| item = await asyncio.wait_for(wait_for_item(self.output_queue), timeout=0.1) | |
| return item | |
| except asyncio.TimeoutError: | |
| return None | |
| else: | |
| # Normal mode | |
| item = await wait_for_item(self.output_queue) | |
| # Check if it's a dict with text message | |
| if isinstance(item, dict) and item.get('type') == 'text_message': | |
| await self.process_text_message(item['content']) | |
| return None | |
| return item | |
| async def shutdown(self) -> None: | |
| if self.interpretation_mode: | |
| # Clean up interpretation mode | |
| self.audio_buffer = [] | |
| self.is_recording = False | |
| print("[INTERPRETATION MODE] Shutdown complete") | |
| else: | |
| # Normal mode - close Realtime API connection | |
| if self.connection: | |
| await self.connection.close() | |
| self.connection = None | |
| # Create initial handler instance | |
| handler = OpenAIHandler(web_search_enabled=False, interpretation_mode=False) | |
| # Create components | |
| chatbot = gr.Chatbot(type="messages") | |
| # Create stream with handler instance | |
| stream = Stream( | |
| handler, # Pass instance, not factory | |
| mode="send-receive", | |
| modality="audio", | |
| additional_inputs=[chatbot], | |
| additional_outputs=[chatbot], | |
| additional_outputs_handler=update_chatbot, | |
| rtc_configuration=get_twilio_turn_credentials() if get_space() else None, | |
| concurrency_limit=5 if get_space() else None, | |
| time_limit=300 if get_space() else None, | |
| ) | |
| app = FastAPI() | |
| # Mount stream | |
| stream.mount(app) | |
| # Intercept offer to capture settings | |
| async def custom_offer(request: Request): | |
| """Intercept offer to capture settings""" | |
| body = await request.json() | |
| webrtc_id = body.get("webrtc_id") | |
| web_search_enabled = body.get("web_search_enabled", False) | |
| target_language = body.get("target_language", "") | |
| system_prompt = body.get("system_prompt", "") | |
| interpretation_mode = body.get("interpretation_mode", False) | |
| interpretation_language = body.get("interpretation_language", "") | |
| print(f"Custom offer - webrtc_id: {webrtc_id}, web_search_enabled: {web_search_enabled}, " | |
| f"target_language: {target_language}, interpretation_mode: {interpretation_mode}, " | |
| f"interpretation_language: {interpretation_language}") | |
| # Store settings with timestamp | |
| if webrtc_id: | |
| connection_settings[webrtc_id] = { | |
| 'web_search_enabled': web_search_enabled, | |
| 'target_language': target_language, | |
| 'system_prompt': system_prompt, | |
| 'interpretation_mode': interpretation_mode, | |
| 'interpretation_language': interpretation_language, | |
| 'timestamp': asyncio.get_event_loop().time() | |
| } | |
| # Remove our custom route temporarily | |
| custom_route = None | |
| for i, route in enumerate(app.routes): | |
| if hasattr(route, 'path') and route.path == "/webrtc/offer" and route.endpoint == custom_offer: | |
| custom_route = app.routes.pop(i) | |
| break | |
| # Forward to stream's offer handler | |
| response = await stream.offer(body) | |
| # Re-add our custom route | |
| if custom_route: | |
| app.routes.insert(0, custom_route) | |
| return response | |
| async def chat_text(request: Request): | |
| """Handle text chat messages using GPT-4o-mini""" | |
| try: | |
| body = await request.json() | |
| message = body.get("message", "") | |
| web_search_enabled = body.get("web_search_enabled", False) | |
| target_language = body.get("target_language", "") | |
| system_prompt = body.get("system_prompt", "") | |
| if not message: | |
| return {"error": "메시지가 비어있습니다."} | |
| # Process text chat | |
| result = await process_text_chat(message, web_search_enabled, target_language, system_prompt) | |
| return result | |
| except Exception as e: | |
| print(f"Error in chat_text endpoint: {e}") | |
| return {"error": "채팅 처리 중 오류가 발생했습니다."} | |
| 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"} | |
| async def outputs(webrtc_id: str): | |
| """Stream outputs including search events""" | |
| async def output_stream(): | |
| async for output in stream.output_stream(webrtc_id): | |
| if hasattr(output, 'args') and output.args: | |
| # Check if it's a search event | |
| if isinstance(output.args[0], dict) and output.args[0].get('type') == 'search': | |
| yield f"event: search\ndata: {json.dumps(output.args[0])}\n\n" | |
| # Regular transcript event with language info | |
| elif isinstance(output.args[0], dict) and 'event' in output.args[0]: | |
| event = output.args[0]['event'] | |
| if hasattr(event, 'transcript'): | |
| data = { | |
| "role": "assistant", | |
| "content": event.transcript, | |
| "language": output.args[0].get('language', ''), | |
| "mode": output.args[0].get('mode', 'normal') | |
| } | |
| yield f"event: output\ndata: {json.dumps(data)}\n\n" | |
| return StreamingResponse(output_stream(), media_type="text/event-stream") | |
| 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) |