feat: AI 场景路由、ASR 服务及前后端全链路同步

- 新增 AI 场景路由控制器和管理接口 - 新增 ASR 语音识别服务及前后端集成 - 同步 AI Runtime 客户端到 Web/小程序/Life-Script - 完善 AI 配置测试修复和管理后台路由配置 - 新增数据库迁移脚本 Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-05-23 13:25:21 +08:00
parent d77090aa5e
commit 89fc42819d
72 changed files with 4584 additions and 383 deletions
@@ -1,78 +1,45 @@
-/**
- * AI 服务模块
- * 封装 OpenRouter API 调用
- */
+import { streamAiScene } from './aiRuntime';

-const API_KEY = "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";
-const BASE_URL = "https://openrouter.ai/api/v1/chat/completions";
-
-/**
- * 调用 AI API
- * @param {string} prompt - 用户提示
- * @param {string} systemMsg - 系统消息
- * @returns {Promise<string>} AI 响应内容
- */
-const fetchAI = async (prompt, systemMsg) => {
-  try {
-    const response = await fetch(BASE_URL, {
-      method: 'POST',
-      headers: {
-        'Authorization': `Bearer ${API_KEY}`,
-        'Content-Type': 'application/json'
-      },
-      body: JSON.stringify({
-        model: "deepseek/deepseek-chat-v3-0324:free",
-        messages: [
-          { role: "system", content: systemMsg },
-          { role: "user", content: prompt }
-        ]
-      })
-    });
-    
-    const data = await response.json();
-    return data.choices[0].message.content;
-  } catch (error) {
-    console.error('AI API Error:', error);
-    return "（AI 暂时陷入了沉思，请稍后再试）";
-  }
+const runScene = async (sceneCode, inputs, callbacks = {}) => {
+  const result = await streamAiScene({
+    sceneCode,
+    inputs,
+    onStart: callbacks.onStart,
+    onDelta: callbacks.onDelta,
+    onDone: callbacks.onDone,
+    onError: callbacks.onError
+  });
+  return result.output;
 };

-/**
- * 分析生命事件
- * @param {Object} event - 事件对象 { title, time, content }
- * @returns {Promise<string>} AI 分析反馈
- */
-export const analyzeLifeEvent = async (event) => {
-  const system = "你是一位温柔的生命引路人，擅长从平凡事件中发掘成长的力量。请分析用户记录的事件，提供情感价值、成长总结和疗愈鼓励。保持字数在150字左右。";
-  const prompt = `事件标题：${event.title}\n时间：${event.time}\n内容：${event.content}`;
-  return fetchAI(prompt, system);
+export const analyzeLifeEvent = async (event, callbacks = {}) => {
+  return runScene('life_healing', {
+    mode: 'life_event_analysis',
+    prompt: `请分析这段人生事件，并给出温和、具体、可执行的反馈。\n标题：${event.title || ''}\n时间：${event.time || ''}\n内容：${event.content || ''}`,
+    title: event.title,
+    time: event.time,
+    content: event.content
+  }, callbacks);
 };

-/**
- * 生成爽文剧本
- * @param {Object} params - 参数对象 { theme, style, length, character }
- * @param {Array} events - 生命事件数组
- * @returns {Promise<string>} 生成的剧本内容
- */
-export const generateEpicScript = async (params, events = []) => {
-  const system = `你是一位金牌爽文编剧。根据用户的角色设定和过往经历，生成一段符合用户设定、充满爽感的未来人生剧本。剧本必须包含起承转合，使用【标题】标记段落。`;
-  
-  const charInfo = `姓名：${params.character.nickname}, 性格：${params.character.mbti}, 兴趣：${params.character.hobbies?.join(',') || ''}, 星座：${params.character.zodiac}`;
-  const eventSummary = events.map(e => e.title).join(', ');
-  
-  const prompt = `角色信息：${charInfo}\n过往经历关键词：${eventSummary}\n用户指定主题：${params.theme}\n指定风格：${params.style}\n篇幅要求：${params.length}\n\n请以此创作一段热血、精彩的人生剧本。`;
-  
-  return fetchAI(prompt, system);
+export const generateEpicScript = async (params, events = [], callbacks = {}) => {
+  return runScene('script_generate', {
+    prompt: params.theme,
+    theme: params.theme,
+    style: params.style,
+    length: params.length,
+    events,
+    character: params.character,
+    useSocialInsights: params.useSocialInsights
+  }, callbacks);
 };

-/**
- * 生成实现路径
- * @param {string} script - 剧本内容
- * @returns {Promise<string>} 生成的路径内容
- */
-export const generatePath = async (script) => {
-  const system = "你是一位人生规划导师。请将用户生成的剧本拆解为现实中可操作的路径。使用【阶段名称】加上具体建议。务必客观、可执行。";
-  return fetchAI(script, system);
+export const generatePath = async (script, callbacks = {}) => {
+  return runScene('life_healing', {
+    mode: 'path_generate',
+    prompt: `请把下面的人生剧本拆解成现实中可执行的路径，按阶段输出。\n\n${script || ''}`,
+    script
+  }, callbacks);
 };

 export default {
@@ -0,0 +1,81 @@
+const API_BASE_URL = import.meta.env.VITE_API_BASE_URL || 'http://localhost:8080';
+
+const parseSseFrame = (frame) => {
+  const event = { type: 'message', data: '' };
+  frame.split(/\r?\n/).forEach((line) => {
+    if (line.startsWith('event:')) event.type = line.slice(6).trim();
+    if (line.startsWith('data:')) event.data += line.slice(5).trim();
+  });
+  if (!event.data) return null;
+  try {
+    return JSON.parse(event.data);
+  } catch {
+    return { type: event.type, content: event.data };
+  }
+};
+
+export const streamAiScene = async ({
+  sceneCode,
+  inputs = {},
+  onStart,
+  onDelta,
+  onDone,
+  onError
+}) => {
+  const token = localStorage.getItem('access_token');
+  const response = await fetch(`${API_BASE_URL}/ai/runtime/stream`, {
+    method: 'POST',
+    headers: {
+      'Content-Type': 'application/json',
+      ...(token ? { Authorization: `Bearer ${token}` } : {})
+    },
+    body: JSON.stringify({ sceneCode, inputs })
+  });
+
+  if (!response.ok || !response.body) {
+    const message = `AI流式请求失败(${response.status})`;
+    onError?.(message);
+    throw new Error(message);
+  }
+
+  const reader = response.body.getReader();
+  const decoder = new TextDecoder('utf-8');
+  let buffer = '';
+  let output = '';
+
+  const consumeText = (text) => {
+    buffer += text;
+    const frames = buffer.split(/\r?\n\r?\n/);
+    buffer = frames.pop() || '';
+    frames.forEach((frame) => {
+      const event = parseSseFrame(frame);
+      if (!event) return;
+      if (event.type === 'start') {
+        onStart?.(event);
+      } else if (event.type === 'delta') {
+        const delta = event.content || '';
+        output += delta;
+        onDelta?.(delta, output, event);
+      } else if (event.type === 'done') {
+        onDone?.(event, output);
+      } else if (event.type === 'error') {
+        const message = event.message || event.code || 'AI流式请求失败';
+        onError?.(message, event);
+        throw new Error(message);
+      }
+    });
+  };
+
+  while (true) {
+    const { value, done } = await reader.read();
+    if (done) break;
+    consumeText(decoder.decode(value, { stream: true }));
+  }
+  consumeText(decoder.decode());
+  if (buffer.trim()) consumeText('\n\n');
+  return { output };
+};
+
+export default {
+  streamAiScene
+};