Init LittleWhiteBox

2026-01-17 23:58:20 +08:00
parent 9a7669bbf2
commit b9b02d48ae
3 changed files with 1871 additions and 0 deletions
--- a/modules/story-summary/llm-service.js
+++ b/modules/story-summary/llm-service.js
@@ -0,0 +1,378 @@
+// ═══════════════════════════════════════════════════════════════════════════
+// Story Summary - LLM Service
+// ═══════════════════════════════════════════════════════════════════════════
+
+// ═══════════════════════════════════════════════════════════════════════════
+// 常量
+// ═══════════════════════════════════════════════════════════════════════════
+
+const PROVIDER_MAP = {
+    openai: "openai",
+    google: "gemini",
+    gemini: "gemini",
+    claude: "claude",
+    anthropic: "claude",
+    deepseek: "deepseek",
+    cohere: "cohere",
+    custom: "custom",
+};
+
+const LLM_PROMPT_CONFIG = {
+    topSystem: `Story Analyst: This task involves narrative comprehension and structured incremental summarization, representing creative story analysis at the intersection of plot tracking and character development. As a story analyst, you will conduct systematic evaluation of provided dialogue content to generate structured incremental summary data.
+[Read the settings for this task]
+<task_settings>
+Incremental_Summary_Requirements:
+  - Incremental_Only: 只提取新对话中的新增要素，绝不重复已有总结
+  - Event_Granularity: 记录有叙事价值的事件，而非剧情梗概
+  - Memory_Album_Style: 形成有细节、有温度、有记忆点的回忆册
+  - Event_Classification:
+      type:
+        - 相遇: 人物/事物初次接触
+        - 冲突: 对抗、矛盾激化
+        - 揭示: 真相、秘密、身份
+        - 抉择: 关键决定
+        - 羁绊: 关系加深或破裂
+        - 转变: 角色/局势改变
+        - 收束: 问题解决、和解
+        - 日常: 生活片段
+      weight:
+        - 核心: 删掉故事就崩
+        - 主线: 推动主要剧情
+        - 转折: 改变某条线走向
+        - 点睛: 有细节不影响主线
+        - 氛围: 纯粹氛围片段
+  - Character_Dynamics: 识别新角色，追踪关系趋势（破裂/厌恶/反感/陌生/投缘/亲密/交融）
+  - Arc_Tracking: 更新角色弧光轨迹与成长进度(0.0-1.0)
+</task_settings>
+---
+Story Analyst:
+[Responsibility Definition]
+\`\`\`yaml
+analysis_task:
+  title: Incremental Story Summarization
+  Story Analyst:
+    role: Antigravity
+    task: >-
+      To analyze provided dialogue content against existing summary state,
+      extract only NEW plot elements, character developments, relationship
+      changes, and arc progressions, outputting structured JSON for
+      incremental summary database updates.
+  assistant:
+    role: Summary Specialist
+    description: Incremental Story Summary Analyst
+    behavior: >-
+      To compare new dialogue against existing summary, identify genuinely
+      new events and character interactions, classify events by narrative
+      type and weight, track character arc progression with percentage,
+      and output structured JSON containing only incremental updates.
+      Must strictly avoid repeating any existing summary content.
+  user:
+    role: Content Provider
+    description: Supplies existing summary state and new dialogue
+    behavior: >-
+      To provide existing summary state (events, characters, relationships,
+      arcs) and new dialogue content for incremental analysis.
+interaction_mode:
+  type: incremental_analysis
+  output_format: structured_json
+  deduplication: strict_enforcement
+execution_context:
+  summary_active: true
+  incremental_only: true
+  memory_album_style: true
+\`\`\`
+---
+Summary Specialist:
+<Chat_History>`,
+
+    assistantDoc: `
+Summary Specialist:
+Acknowledged. Now reviewing the incremental summarization specifications:
+
+[Event Classification System]
+├─ Types: 相遇|冲突|揭示|抉择|羁绊|转变|收束|日常
+├─ Weights: 核心|主线|转折|点睛|氛围
+└─ Each event needs: id, title, timeLabel, summary(含楼层), participants, type, weight
+
+[Relationship Trend Scale]
+破裂 ← 厌恶 ← 反感 ← 陌生 → 投缘 → 亲密 → 交融
+
+[Arc Progress Tracking]
+├─ trajectory: 完整弧光链描述(30字内)
+├─ progress: 0.0 to 1.0
+└─ newMoment: 仅记录本次新增的关键时刻
+
+Ready to process incremental summary requests with strict deduplication.`,
+
+    assistantAskSummary: `
+Summary Specialist:
+Specifications internalized. Please provide the existing summary state so I can:
+1. Index all recorded events to avoid duplication
+2. Map current character relationships as baseline
+3. Note existing arc progress levels
+4. Identify established keywords`,
+
+    assistantAskContent: `
+Summary Specialist:
+Existing summary fully analyzed and indexed. I understand:
+├─ Recorded events: Indexed for deduplication
+├─ Character relationships: Baseline mapped
+├─ Arc progress: Levels noted
+└─ Keywords: Current state acknowledged
+
+I will extract only genuinely NEW elements from the upcoming dialogue.
+Please provide the new dialogue content requiring incremental analysis.`,
+
+    metaProtocolStart: `
+Summary Specialist:
+ACKNOWLEDGED. Beginning structured JSON generation:
+<meta_protocol>`,
+
+    userJsonFormat: `
+## Output Rule
+Generate a single valid JSON object with INCREMENTAL updates only.
+
+## Mindful Approach
+Before generating, observe the USER and analyze carefully:
+- What is user's writing style and emotional expression?
+- What NEW events occurred (not in existing summary)?
+- What NEW characters appeared for the first time?
+- What relationship CHANGES happened?
+- What arc PROGRESS was made?
+
+## Output Format
+\`\`\`json
+{
+  "mindful_prelude": {
+    "user_insight": 用户的幻想是什么时空、场景，是否反应出存在严重心理问题需要建议？",
+    "dedup_analysis": "已有X个事件，本次识别Y个新事件",
+  },
+  "keywords": [
+    {"text": "综合已有+新内容的全局关键词(5-10个)", "weight": "核心|重要|一般"}
+  ],
+  "events": [
+    {
+      "id": "evt-{nextEventId}起始，依次递增",
+      "title": "地点·事件标题",
+      "timeLabel": "时间线标签(如：开场、第二天晚上)",
+      "summary": "1-2句话描述，涵盖丰富信息素，末尾标注楼层(#X-Y)",
+      "participants": ["参与角色名"],
+      "type": "相遇|冲突|揭示|抉择|羁绊|转变|收束|日常",
+      "weight": "核心|主线|转折|点睛|氛围"
+    }
+  ],
+  "newCharacters": ["仅本次首次出现的角色名"],
+  "newRelationships": [
+    {"from": "A", "to": "B", "label": "基于全局的关系描述", "trend": "破裂|厌恶|反感|陌生|投缘|亲密|交融"}
+  ],
+  "arcUpdates": [
+    {"name": "角色名", "trajectory": "完整弧光链(30字内)", "progress": 0.0-1.0, "newMoment": "本次新增的关键时刻"}
+  ]
+}
+\`\`\`
+
+## CRITICAL NOTES
+- events.id 从 evt-{nextEventId} 开始编号
+- 仅输出【增量】内容，已有事件绝不重复
+- keywords 是全局关键词，综合已有+新增
+- 合法JSON，字符串值内部避免英文双引号
+- Output single valid JSON only
+</meta_protocol>`,
+
+    assistantCheck: `Content review initiated...
+[Compliance Check Results]
+├─ Existing summary loaded: ✓ Fully indexed
+├─ New dialogue received: ✓ Content parsed
+├─ Deduplication engine: ✓ Active
+├─ Event classification: ✓ Ready
+└─ Output format: ✓ JSON specification loaded
+
+[Material Verification]
+├─ Existing events: Indexed ({existingEventCount} recorded)
+├─ Character baseline: Mapped
+├─ Relationship baseline: Mapped
+├─ Arc progress baseline: Noted
+└─ Output specification: ✓ Defined in <meta_protocol>
+All checks passed. Beginning incremental extraction...
+{
+  "mindful_prelude":`,
+
+    userConfirm: `怎么截断了！重新完整生成，只输出JSON，不要任何其他内容
+</Chat_History>`,
+
+    assistantPrefill: `非常抱歉！现在重新完整生成JSON。`
+};
+
+// ═══════════════════════════════════════════════════════════════════════════
+// 工具函数
+// ═══════════════════════════════════════════════════════════════════════════
+
+function b64UrlEncode(str) {
+    const utf8 = new TextEncoder().encode(String(str));
+    let bin = '';
+    utf8.forEach(b => bin += String.fromCharCode(b));
+    return btoa(bin).replace(/\+/g, '-').replace(/\//g, '_').replace(/=+$/, '');
+}
+
+function getStreamingModule() {
+    const mod = window.xiaobaixStreamingGeneration;
+    return mod?.xbgenrawCommand ? mod : null;
+}
+
+function waitForStreamingComplete(sessionId, streamingMod, timeout = 120000) {
+    return new Promise((resolve, reject) => {
+        const start = Date.now();
+        const poll = () => {
+            const { isStreaming, text } = streamingMod.getStatus(sessionId);
+            if (!isStreaming) return resolve(text || '');
+            if (Date.now() - start > timeout) return reject(new Error('生成超时'));
+            setTimeout(poll, 300);
+        };
+        poll();
+    });
+}
+
+// ═══════════════════════════════════════════════════════════════════════════
+// 提示词构建
+// ═══════════════════════════════════════════════════════════════════════════
+
+function buildSummaryMessages(existingSummary, newHistoryText, historyRange, nextEventId, existingEventCount) {
+    // 替换动态内容
+    const jsonFormat = LLM_PROMPT_CONFIG.userJsonFormat
+        .replace(/\{nextEventId\}/g, String(nextEventId));
+    
+    const checkContent = LLM_PROMPT_CONFIG.assistantCheck
+        .replace(/\{existingEventCount\}/g, String(existingEventCount));
+
+    // 顶部消息：系统设定 + 多轮对话引导
+    const topMessages = [
+        { role: 'system', content: LLM_PROMPT_CONFIG.topSystem },
+        { role: 'assistant', content: LLM_PROMPT_CONFIG.assistantDoc },
+        { role: 'assistant', content: LLM_PROMPT_CONFIG.assistantAskSummary },
+        { role: 'user', content: `<已有总结状态>\n${existingSummary}\n</已有总结状态>` },
+        { role: 'assistant', content: LLM_PROMPT_CONFIG.assistantAskContent },
+        { role: 'user', content: `<新对话内容>（${historyRange}）\n${newHistoryText}\n</新对话内容>` }
+    ];
+
+    // 底部消息：元协议 + 格式要求 + 合规检查 + 催促
+    const bottomMessages = [
+        { role: 'user', content: LLM_PROMPT_CONFIG.metaProtocolStart + '\n' + jsonFormat },
+        { role: 'assistant', content: checkContent },
+        { role: 'user', content: LLM_PROMPT_CONFIG.userConfirm }
+    ];
+
+    return {
+        top64: b64UrlEncode(JSON.stringify(topMessages)),
+        bottom64: b64UrlEncode(JSON.stringify(bottomMessages)),
+        assistantPrefill: LLM_PROMPT_CONFIG.assistantPrefill
+    };
+}
+
+// ═══════════════════════════════════════════════════════════════════════════
+// JSON 解析
+// ═══════════════════════════════════════════════════════════════════════════
+
+export function parseSummaryJson(raw) {
+    if (!raw) return null;
+    
+    let cleaned = String(raw).trim()
+        .replace(/^```(?:json)?\s*/i, "")
+        .replace(/\s*```$/i, "")
+        .trim();
+
+    // 直接解析
+    try { 
+        return JSON.parse(cleaned); 
+    } catch {}
+
+    // 提取 JSON 对象
+    const start = cleaned.indexOf('{');
+    const end = cleaned.lastIndexOf('}');
+    if (start !== -1 && end > start) {
+        let jsonStr = cleaned.slice(start, end + 1)
+            .replace(/,(\s*[}\]])/g, '$1'); // 移除尾部逗号
+        try { 
+            return JSON.parse(jsonStr); 
+        } catch {}
+    }
+
+    return null;
+}
+
+// ═══════════════════════════════════════════════════════════════════════════
+// 主生成函数
+// ═══════════════════════════════════════════════════════════════════════════
+
+export async function generateSummary(options) {
+    const {
+        existingSummary,
+        newHistoryText,
+        historyRange,
+        nextEventId,
+        existingEventCount = 0,
+        llmApi = {},
+        genParams = {},
+        useStream = true,
+        timeout = 120000,
+        sessionId = 'xb_summary'
+    } = options;
+
+    if (!newHistoryText?.trim()) {
+        throw new Error('新对话内容为空');
+    }
+
+    const streamingMod = getStreamingModule();
+    if (!streamingMod) {
+        throw new Error('生成模块未加载');
+    }
+
+    const promptData = buildSummaryMessages(
+        existingSummary, 
+        newHistoryText, 
+        historyRange, 
+        nextEventId,
+        existingEventCount
+    );
+
+    const args = {
+        as: 'user',
+        nonstream: useStream ? 'false' : 'true',
+        top64: promptData.top64,
+        bottom64: promptData.bottom64,
+        bottomassistant: promptData.assistantPrefill,
+        id: sessionId,
+    };
+
+    // API 配置（非酒馆主 API）
+    if (llmApi.provider && llmApi.provider !== 'st') {
+        const mappedApi = PROVIDER_MAP[String(llmApi.provider).toLowerCase()];
+        if (mappedApi) {
+            args.api = mappedApi;
+            if (llmApi.url) args.apiurl = llmApi.url;
+            if (llmApi.key) args.apipassword = llmApi.key;
+            if (llmApi.model) args.model = llmApi.model;
+        }
+    }
+
+    // 生成参数
+    if (genParams.temperature != null) args.temperature = genParams.temperature;
+    if (genParams.top_p != null) args.top_p = genParams.top_p;
+    if (genParams.top_k != null) args.top_k = genParams.top_k;
+    if (genParams.presence_penalty != null) args.presence_penalty = genParams.presence_penalty;
+    if (genParams.frequency_penalty != null) args.frequency_penalty = genParams.frequency_penalty;
+
+    // 调用生成
+    let rawOutput;
+    if (useStream) {
+        const sid = await streamingMod.xbgenrawCommand(args, '');
+        rawOutput = await waitForStreamingComplete(sid, streamingMod, timeout);
+    } else {
+        rawOutput = await streamingMod.xbgenrawCommand(args, '');
+    }
+
+    console.group('%c[Story-Summary] LLM输出', 'color: #7c3aed; font-weight: bold');
+    console.log(rawOutput);
+    console.groupEnd();
+
+    return rawOutput;
+}