From 3b9d6d48291cdc6afb5c438560b3598334177651 Mon Sep 17 00:00:00 2001 From: bielie Date: Mon, 16 Feb 2026 21:41:06 +0800 Subject: [PATCH] remove unused duplicate story-summary llm-service module --- modules/story-summary/llm-service.js | 378 --------------------------- 1 file changed, 378 deletions(-) delete mode 100644 modules/story-summary/llm-service.js diff --git a/modules/story-summary/llm-service.js b/modules/story-summary/llm-service.js deleted file mode 100644 index 7539d2b..0000000 --- a/modules/story-summary/llm-service.js +++ /dev/null @@ -1,378 +0,0 @@ -// ═══════════════════════════════════════════════════════════════════════════ -// 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] - -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) - ---- -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: -`, - - 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: -`, - - 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 -`, - - 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 -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 -`, - - 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` }, - { role: 'assistant', content: LLM_PROMPT_CONFIG.assistantAskContent }, - { role: 'user', content: `<新对话内容>（${historyRange}）\n${newHistoryText}\n` } - ]; - - // 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; -}