OpenCode
68a9071cf1
Local branch had diverged from origin/master (sibling commits on the same base). Rewrote local history linearly on top of origin/master, folding in all local content: exa/hot-platform discovery hunters, leaks ledger, nightly sweep orchestrator, updated .gitignore and skill docs, plus the latest hunt output and vault state. Remote-only files (vault keys, channel scripts) were restored rather than dropped, so the resulting tree is a full union of both sides.
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43 KiB
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1 line
43 KiB
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{"repo": "cheems-cn/mindcap", "files": {"mindcap-mvp/server/server.js": {"7f601ede3e216c58c7ce8332c36201c0a3619cfa": {"t": 1786068490.4737842, "n": 36891, "h": "ef57f9ce4cfee8e5", "c": "const http = require(\"http\");\nconst fs = require(\"fs\");\nconst path = require(\"path\");\nconst { URL } = require(\"url\");\nconst { BufferWindowMemory, VectorStoreRetrieverMemory, CombinedMemory } = require(\"@langchain/classic/memory\");\nconst { MemoryVectorStore } = require(\"@langchain/classic/vectorstores/memory\");\nconst { Embeddings } = require(\"@langchain/core/embeddings\");\nconst db = require(\"./db\");\nconst { parseEEGFile, getAvailableModels } = require(\"./eeg-parser\");\nconst { createPopulatedVectorStore, persistContext } = require(\"./memory-store\");\n\nconst HOST = \"127.0.0.1\";\nconst PORT = process.env.PORT ? Number(process.env.PORT) : 5050;\nconst PUBLIC_DIR = path.join(__dirname, \"..\", \"public\");\nconst DEEPSEEK_API_KEY = process.env.DEEPSEEK_API_KEY || \"\";\nconst DEEPSEEK_BASE_URL = (process.env.DEEPSEEK_BASE_URL || \"https://api.deepseek.com\").replace(/\\/+$/, \"\");\nconst DEEPSEEK_MODEL = process.env.DEEPSEEK_MODEL || \"deepseek-v4-flash\";\nconst DEEPSEEK_TIMEOUT_MS = process.env.DEEPSEEK_TIMEOUT_MS ? Number(process.env.DEEPSEEK_TIMEOUT_MS) : 25000;\nconst LANGCHAIN_EMBED_DIM = 128;\n\nconst sseClients = new Map();\nconst langchainMemoryRegistry = new Map();\n\n// ── Deterministic Embeddings (same as before) ───────────────────────\n\nclass DeterministicEmbeddings extends Embeddings {\n constructor() {\n super({});\n this.dimension = LANGCHAIN_EMBED_DIM;\n }\n\n hashToken(token) {\n let h = 2166136261;\n for (let i = 0; i < token.length; i += 1) {\n h ^= token.charCodeAt(i);\n h = Math.imul(h, 16777619);\n }\n return Math.abs(h >>> 0);\n }\n\n textToVector(text) {\n const vector = new Array(this.dimension).fill(0);\n const tokens = String(text || \"\").toLowerCase().replace(/[^\\p{L}\\p{N}\\s]/gu, \" \").split(/\\s+/).filter(Boolean);\n if (!tokens.length) return vector;\n for (const token of tokens) {\n const h = this.hashToken(token);\n const idx = h % this.dimension;\n const sign = h % 2 === 0 ? 1 : -1;\n vector[idx] += sign;\n }\n const norm = Math.sqrt(vector.reduce((sum, x) => sum + x * x, 0)) || 1;\n return vector.map((x) => x / norm);\n }\n\n async embedDocuments(documents) {\n return documents.map((doc) => this.textToVector(doc));\n }\n\n async embedQuery(document) {\n return this.textToVector(document);\n }\n}\n\n// ── LangChain Memory ────────────────────────────────────────────────\n\nfunction buildProfileSeedRecords(user) {\n const records = [];\n const triggers = user?.longTermProfile?.triggers || [];\n const preferred = user?.longTermProfile?.preferredInterventions || [];\n const effective = user?.verifiedEffectiveStrategies || [];\n const shortMem = user?.shortTermMemory || [];\n\n if (triggers.length) records.push(`用户压力触发因素：${triggers.join(\"、\")}`);\n if (preferred.length) records.push(`用户偏好干预方式：${preferred.join(\"、\")}`);\n if (effective.length) records.push(`历史有效策略：${effective.join(\"、\")}`);\n for (const line of shortMem.slice(0, 4)) records.push(`短期记忆：${line}`);\n return records;\n}\n\nasync function createLangChainMemoryRuntime(user) {\n const embeddings = new DeterministicEmbeddings();\n\n // Create vector store populated from SQLite (survives restart)\n const vectorStore = await createPopulatedVectorStore(user.id, embeddings);\n\n const longMemory = new VectorStoreRetrieverMemory({\n vectorStoreRetriever: vectorStore.asRetriever(4),\n memoryKey: \"long_term_memory\",\n inputKey: \"input\",\n returnDocs: false,\n metadata: { userId: user.id }\n });\n const shortMemory = new BufferWindowMemory({\n memoryKey: \"recent_memory\",\n inputKey: \"input\",\n outputKey: \"output\",\n returnMessages: false,\n k: 6\n });\n const combinedMemory = new CombinedMemory({\n memories: [shortMemory, longMemory],\n inputKey: \"input\",\n outputKey: \"output\"\n });\n return { vectorStore, longMemory, shortMemory, combinedMemory, seeded: false, embeddings };\n}\n\nasync function ensureLangChainMemoryRuntime(user) {\n if (!user) return null;\n let runtime = langchainMemoryRegistry.get(user.id);\n if (!runtime) {\n runtime = await createLangChainMemoryRuntime(user);\n langchainMemoryRegistry.set(user.id, runtime);\n }\n if (!runtime.seeded) {\n const seeds = buildProfileSeedRecords(user);\n for (const seed of seeds) {\n await runtime.longMemory.saveContext({ input: seed }, { output: `画像归档:${seed}` });\n }\n runtime.seeded = true;\n }\n return runtime;\n}\n\nasync function loadLangChainMemoryContext(runtime, message) {\n if (!runtime) return { recentMemory: \"\", longTermMemory: \"\" };\n const memoryVars = await runtime.combinedMemory.loadMemoryVariables({ input: message });\n return {\n recentMemory: String(memoryVars.recent_memory || \"\"),\n longTermMemory: String(memoryVars.long_term_memory || \"\")\n };\n}\n\nasync function persistLangChainMemory(runtime, userText, assistantText) {\n if (!runtime) return;\n\n // Save to in-memory LangChain store\n await runtime.combinedMemory.saveContext({ input: userText }, { output: assistantText });\n\n // Also persist to SQLite so it survives restart\n const userId = runtime.longMemory?.metadata?.userId || null;\n await persistContext(userId, userText, assistantText, runtime.embeddings);\n}\n\n// ── HTTP helpers ────────────────────────────────────────────────────\n\nfunction sendJson(res, statusCode, payload) {\n res.writeHead(statusCode, { \"Content-Type\": \"application/json; charset=utf-8\" });\n res.end(JSON.stringify(payload));\n}\n\nfunction parseBody(req) {\n return new Promise((resolve, reject) => {\n let data = \"\";\n req.on(\"data\", (chunk) => {\n data += chunk.toString(\"utf8\");\n if (data.length > 1_000_000) { reject(new Error(\"Payload too large\")); req.destroy(); }\n });\n req.on(\"end\", () => {\n if (!data) { resolve({}); return; }\n try { resolve(JSON.parse(data)); } catch (err) { reject(new Error(\"Invalid JSON\")); }\n });\n req.on(\"error\", reject);\n });\n}\n\nfunction getMimeType(filePath) {\n const ext = path.extname(filePath).toLowerCase();\n if (ext === \".html\") return \"text/html; charset=utf-8\";\n if (ext === \".css\") return \"text/css; charset=utf-8\";\n if (ext === \".js\") return \"application/javascript; charset=utf-8\";\n if (ext === \".json\") return \"application/json; charset=utf-8\";\n return \"application/octet-stream\";\n}\n\nfunction serveStatic(req, res, pathname) {\n const cleanPath = pathname === \"/\" ? \"/index.html\" : pathname;\n const resolved = path.resolve(PUBLIC_DIR, `.${cleanPath}`);\n if (!resolved.startsWith(PUBLIC_DIR)) { sendJson(res, 403, { error: \"Forbidden\" }); return; }\n fs.readFile(resolved, (err, content) => {\n if (err) { sendJson(res, 404, { error: \"Not found\" }); return; }\n res.writeHead(200, { \"Content-Type\": getMimeType(resolved) });\n res.end(content);\n });\n}\n\nfunction clipText(value, maxLen = 220) {\n const text = String(value || \"\").replace(/\\s+/g, \" \").trim();\n if (text.length <= maxLen) return text;\n return `${text.slice(0, maxLen)}...`;\n}\n\n// ── SSE ─────────────────────────────────────────────────────────────\n\nfunction publishSessionEvent(sessionId, eventName, payload) {\n const set = sseClients.get(sessionId);\n if (!set) return;\n const line = `event: ${eventName}\\ndata: ${JSON.stringify(payload)}\\n\\n`;\n for (const res of set) res.write(line);\n}\n\n// ── Intervention tracks ─────────────────────────────────────────────\n\nconst interventionTracks = {\n breathing: {\n name: \"呼吸稳定\",\n keywords: [\"焦虑\", \"紧张\", \"心慌\", \"stress\", \"anxiety\", \"呼吸\", \"胸闷\"],\n steps: [\n [\n \"做60秒方块呼吸：吸4秒-停4秒-呼4秒-停4秒。\",\n \"试试方块呼吸法：慢慢吸气4秒，屏住4秒，缓缓呼出4秒，再屏住4秒。重复60秒。\",\n \"我们先从呼吸锚定开始：4秒吸气、4秒停顿、4秒呼气、4秒停顿。跟着我的节奏来。\"\n ],\n [\n \"继续90秒呼气延长：吸4秒、呼6秒，观察肩颈是否放松。\",\n \"这次让呼气更长一些：吸4秒、呼6秒，把注意力放在肩膀下沉的感觉上。\",\n \"进阶呼吸：吸气不变，但让呼气拉长到6秒，感受横膈膜慢慢放松。\"\n ],\n [\n \"把身体感受写成三词（例如：心跳快、肩紧、手冷），只做观察不评判。\",\n \"用三个简单的词描述你现在身体的感觉，只是观察，不加评判。\",\n \"扫描身体，找一个词描述头部感受、一个词描述胸口、一个词描述手脚。只观察不改变。\"\n ]\n ]\n },\n task: {\n name: \"任务减压\",\n keywords: [\"考试\", \"任务\", \"ddl\", \"作业\", \"进度\", \"效率\", \"压力\"],\n steps: [\n [\n \"列出当前最困扰的3件事，并圈出今天必须完成的1件。\",\n \"拿出一张纸或打开备忘录，写下让你感到压力的3件事。然后只圈出今天必须完成的1件。\",\n \"我们先做减法：把所有要做的事写出来，然后问自己'今天必须完成的是哪一件？'\"\n ],\n [\n \"把这1件事拆成一个15分钟动作，马上启动计时。\",\n \"把选中的任务拆解到最小可执行单元——一个15分钟内能完成的动作。现在就启动倒计时。\",\n \"只做一件事：把你圈出的任务拆成第一个15分钟行动，然后立刻开始。不需要想后面的步骤。\"\n ],\n [\n \"完成后写一句复盘：这一步比预想更难还是更容易。\",\n \"15分钟到了！写一句简单的复盘，关注难度感受而非结果好坏。\",\n \"停一下，问问自己：实际做的感觉和预想有什么不同？记录这个差距就好。\"\n ]\n ]\n },\n sleep: {\n name: \"睡眠修复\",\n keywords: [\"失眠\", \"睡眠\", \"入睡\", \"夜醒\", \"疲惫\"],\n steps: [\n [\n \"今晚固定一个关灯时间，并提前30分钟关闭高刺激内容（短视频、游戏、刺眼灯）。\",\n \"给今晚设一个'光线切换点'：在这个时间关掉主灯，切换到暖黄夜灯模式，告诉大脑要准备休息了。\",\n \"今晚试试'数字日落'：提前30分钟放下手机/电脑，用纸质书或播客替代屏幕。\"\n ],\n [\n \"做2分钟腹式呼吸，把注意力放在呼气变长。\",\n \"躺下后做腹式呼吸：手放肚子上，吸气感觉肚子鼓起，呼气感觉手下降。呼气越长越好。\",\n \"睡前呼吸练习：用鼻子缓慢吸气4秒，用嘴巴微微呼气6-8秒，感受身体一点点变沉。\"\n ],\n [\n \"若20分钟仍未入睡，起身做低刺激活动5分钟（折衣服、翻杂志）再回床。\",\n \"如果躺了20分钟还睡不着，不要硬躺。起来做一件无聊的小事，困意会自然回来。\",\n \"睡不着就起来'重启'：离开床5分钟，喝一小口温水，做几个温和拉伸，然后重新躺下试试。\"\n ]\n ]\n },\n social: {\n name: \"社交安定\",\n keywords: [\"社交\", \"发言\", \"陌生人\", \"尴尬\", \"评价\"],\n steps: [\n [\n \"先写一句可复述开场白，并默念3遍。\",\n \"准备一句万能开场白写下来：'你好，我是XX，今天这个活动/会议我一直在期待'。默念到自然。\",\n \"社交的紧张来自不确定性。我们先给大脑一个确定的脚本：写好第一句话，反复读三遍。\"\n ],\n [\n \"为下一次社交设定最小目标：只完成一次主动问候。\",\n \"把社交目标降到最低：不是'表现完美'，而是'说一句你好'。完成即胜利。\",\n \"下一个社交场合，给自己唯一的任务：找到一个友善的面孔，微笑着说'你好'。不需要更多。\"\n ],\n [\n \"事后记录1个做得好的点，强化可复制动作。\",\n \"社交结束后，不要复盘'哪里出错了'，而是找到1个你做对了的时刻，记住它。\",\n \"给自己一个正面反馈：写下今天社交中哪怕最微小的成功（'我准时到达了'也算）。积累即是信心。\"\n ]\n ]\n },\n grounding: {\n name: \"情绪落地\",\n keywords: [\"低落\", \"悲伤\", \"空虚\", \"无力\", \"sad\"],\n steps: [\n [\n \"做30秒5-4-3-2-1感官定位：现在看到5样东西、触到4样、听到3种声音、闻到2种气味、尝到1种味道。\",\n \"着陆技术：找到5个你能看到的东西，4个你能摸到的物品，3种你能听到的声音，2种气味，1种味道。\",\n \"我们一起回到当下：说出你周围5样物品的颜色，感受4样东西的质地，听3种声音。\"\n ],\n [\n \"给自己一句非苛责陈述：'我现在很难受，但我在尝试自救'，在心里重复3遍。\",\n \"对自己说一句温柔的话：'这种感觉会过去的，我只需要度过接下来的5分钟'。\",\n \"如果好朋友正在经历你现在的心情，你会对TA说什么？把这句话说给自己听。\"\n ],\n [\n \"选择一个2分钟微行动（洗脸、喝温水、站立伸展、开窗透气），做完后感受一下掌控感是不是回来了一点。\",\n \"做一个小到不可能失败的动作：站起来伸展手臂、用冷水冲一下手、或者整理桌上的三样东西。\",\n \"找回掌控感的最小单位：给自己倒一杯温水，慢慢喝完。感受水从喉咙流过的温度。这就是'我能做到的事'。\"\n ]\n ]\n }\n};\n\nfunction matchTrackByContext(contextText, preferredInterventions, currentMessage) {\n const combined = String(contextText || \"\").toLowerCase();\n const current = String(currentMessage || \"\").toLowerCase();\n const preferred = (preferredInterventions || []).join(\"、\").toLowerCase();\n let bestKey = \"task\";\n let bestScore = -1;\n\n for (const [key, track] of Object.entries(interventionTracks)) {\n let score = 0;\n for (const keyword of track.keywords) {\n if (combined.includes(keyword.toLowerCase())) score += 2;\n if (current.includes(keyword.toLowerCase())) score += 5;\n }\n if (preferred && track.keywords.some((kw) => preferred.includes(kw.toLowerCase()))) score += 1;\n if (score > bestScore) { bestScore = score; bestKey = key; }\n }\n return bestKey;\n}\n\nfunction updateInterventionState(session, selectedTrackKey, emotionLabel) {\n if (!session.interventionState || !session.interventionState.trackKey) {\n const state = { trackKey: selectedTrackKey, stepIndex: 0, lastEmotion: emotionLabel || \"neutral\" };\n db.updateSessionIntervention(session.id, selectedTrackKey, 0, emotionLabel || \"neutral\");\n return state;\n }\n\n const state = session.interventionState;\n if (state.trackKey !== selectedTrackKey) {\n db.updateSessionIntervention(session.id, selectedTrackKey, 0, emotionLabel || \"neutral\");\n return { trackKey: selectedTrackKey, stepIndex: 0, lastEmotion: emotionLabel || \"neutral\" };\n }\n\n const track = interventionTracks[state.trackKey] || interventionTracks.task;\n const shouldAdvance = session.chatTurns.length >= 1;\n const newStepIndex = shouldAdvance && state.stepIndex < track.steps.length - 1 ? state.stepIndex + 1 : state.stepIndex;\n db.updateSessionIntervention(session.id, state.trackKey, newStepIndex, emotionLabel || \"neutral\");\n return { trackKey: state.trackKey, stepIndex: newStepIndex, lastEmotion: emotionLabel || \"neutral\" };\n}\n\nfunction buildMemoryAwareSuggestions({ session, user, emotion, memoryContext, currentMessage }) {\n const contextText = [\n memoryContext?.recentMemory || \"\",\n memoryContext?.longTermMemory || \"\",\n (user?.longTermProfile?.triggers || []).join(\"、\"),\n (user?.shortTermMemory || []).join(\"、\"),\n emotion?.label || \"\"\n ].join(\" \");\n\n let defaultTrackKey = \"task\";\n if (emotion?.label === \"anxiety\" || emotion?.label === \"stress\") defaultTrackKey = \"breathing\";\n if (emotion?.label === \"sad\") defaultTrackKey = \"grounding\";\n\n const selectedTrackKey = matchTrackByContext(contextText, user?.longTermProfile?.preferredInterventions, currentMessage) || defaultTrackKey;\n const interventionState = updateInterventionState(session, selectedTrackKey, emotion?.label);\n const track = interventionTracks[interventionState.trackKey] || interventionTracks.task;\n const step = Math.max(0, Math.min(interventionState.stepIndex, track.steps.length - 1));\n const stepVariants = Array.isArray(track.steps[step]) ? track.steps[step] : [track.steps[step]];\n const chosenStep = stepVariants[Math.floor(Math.random() * stepVariants.length)];\n\n const memoryAnchor =\n (user?.verifiedEffectiveStrategies || [])[0] ||\n (user?.longTermProfile?.preferredInterventions || [])[0] ||\n \"先稳定呼吸再做最小动作\";\n\n return [\n `延续方案【${track.name}】第${step + 1}步：${chosenStep}`,\n `记忆锚点：你历史上更有效的方式是「${memoryAnchor}」，本轮优先沿用。`,\n \"执行后告诉我：情绪强度从0-10变成了几分，我会按同一方案继续下一步。\"\n ];\n}\n\n// ── Safety detection ────────────────────────────────────────────────\n\nconst builtInHighRiskRules = [\n { id: \"cn_suicide\", pattern: /自杀|想自杀|我想死|想死|去死|轻生/iu, reason: \"命中自杀/轻生意图\" },\n { id: \"cn_end_life\", pattern: /(结束|了结).{0,4}(生命|自己)/iu, reason: \"命中结束生命表达\" },\n { id: \"cn_not_live\", pattern: /不想活了?|活着没意义/iu, reason: \"命中绝望生存表达\" },\n { id: \"en_suicide\", pattern: /suicide|kill\\s*myself|end\\s*my\\s*life|don't\\s*want\\s*to\\s*live/iu, reason: \"命中英文自伤表达\" }\n];\n\nfunction normalizeRiskText(input) {\n return String(input || \"\").toLowerCase().replace(/[\\s\\r\\n\\t]/g, \"\").replace(/[.,!?;:，。！？；：、'\"`~\\-_/\\\\()[\\]{}<>]/g, \"\");\n}\n\nfunction detectHighRisk(text) {\n const raw = String(text || \"\");\n const normalized = normalizeRiskText(raw);\n\n for (const rule of builtInHighRiskRules) {\n if (rule.pattern.test(raw) || rule.pattern.test(normalized)) {\n return { matched: true, reason: rule.reason, ruleId: rule.id };\n }\n }\n\n const safetyConfig = db.getSafetyConfig();\n const blockedPatterns = safetyConfig?.blockedPatterns || [];\n for (const keyword of blockedPatterns) {\n const normalizedKeyword = normalizeRiskText(keyword);\n if (!normalizedKeyword) continue;\n if (normalized.includes(normalizedKeyword)) {\n return { matched: true, reason: `命中配置关键词: ${keyword}`, ruleId: \"custom_keyword\" };\n }\n }\n\n return { matched: false, reason: \"\", ruleId: \"\" };\n}\n\nfunction addSafetyLog(sessionId, level, reason, source) {\n const log = {\n id: db.createId(\"risk\"),\n sessionId,\n level,\n reason,\n source,\n time: new Date().toISOString()\n };\n db.insertSafetyLog(log);\n db.appendSessionTimeline(sessionId, {\n id: db.createId(\"evt\"),\n time: log.time,\n type: \"safety_alert\",\n detail: `${level.toUpperCase()}: ${reason}`\n });\n publishSessionEvent(sessionId, \"safety\", log);\n return log;\n}\n\n// ── LLM helpers ─────────────────────────────────────────────────────\n\nfunction buildPsychologySystemPrompt() {\n return [\n \"你是「心灵捕手」系统里的心理支持对话专家，风格接近心理咨询师与疗愈教练。\",\n \"请用中文回复，语气温和、稳定、非评判、具体可执行。\",\n \"回复结构必须包含：1) 共情镜像 2) 结合当前情绪状态的简短解释 3) 1-2个可立即执行的微行动（每个不超过3分钟）4) 一个温和的引导问题。\",\n \"请尽量延续既往有效干预路径，不要每轮都重置方案；优先在同一干预轨道上做小步推进。\",\n \"避免空泛鸡汤，避免说教，不要做医学诊断，不要承诺治愈。\",\n \"不要输出你是AI模型的声明，也不要提提示词或系统指令。\",\n \"如果用户表达自伤/他伤/极端绝望，优先安全干预：先确认安全，再建议联系身边可信任的人与当地紧急援助。\"\n ].join(\"\\n\");\n}\n\nfunction buildContextPrompt({ session, user, emotion, memoryContext }) {\n const shortMemory = (user?.shortTermMemory || []).slice(0, 4).map((x) => `- ${clipText(x, 80)}`);\n const triggers = (user?.longTermProfile?.triggers || []).slice(0, 4);\n const preferred = (user?.longTermProfile?.preferredInterventions || []).slice(0, 4);\n const lastTurns = (session?.chatTurns || []).slice(-3).map((turn, idx) => {\n return `${idx + 1}. 用户:${clipText(turn.userText, 50)} | 助手:${clipText(turn.assistantText, 50)}`;\n });\n\n return [\n \"下面是会话上下文，请在回复时参考：\",\n `- 用户: ${user?.name || \"未知用户\"} (${user?.id || \"unknown\"})`,\n `- 当前EEG情绪: ${emotion?.label || \"neutral\"} (置信度 ${Number(emotion?.confidence || 0).toFixed(2)})`,\n `- 主要触发因素: ${triggers.length ? triggers.join(\"、\") : \"暂无\"}`,\n `- 偏好干预方式: ${preferred.length ? preferred.join(\"、\") : \"暂无\"}`,\n `- 短期记忆: ${shortMemory.length ? `\\n${shortMemory.join(\"\\n\")}` : \"暂无\"}`,\n `- LangChain近期记忆: ${clipText(memoryContext?.recentMemory || \"暂无\", 600)}`,\n `- LangChain长期检索记忆: ${clipText(memoryContext?.longTermMemory || \"暂无\", 900)}`,\n `- 最近对话摘要: ${lastTurns.length ? `\\n${lastTurns.join(\"\\n\")}` : \"暂无\"}`\n ].join(\"\\n\");\n}\n\nfunction buildDeepSeekMessages({ session, user, emotion, message, memoryContext }) {\n const messages = [\n { role: \"system\", content: buildPsychologySystemPrompt() },\n { role: \"system\", content: buildContextPrompt({ session, user, emotion, memoryContext }) }\n ];\n const recentTurns = (session?.chatTurns || []).slice(-6);\n for (const turn of recentTurns) {\n messages.push({ role: \"user\", content: clipText(turn.userText, 600) });\n messages.push({ role: \"assistant\", content: clipText(turn.assistantText, 800) });\n }\n messages.push({ role: \"user\", content: clipText(message, 1200) });\n return messages;\n}\n\nfunction extractAssistantContent(payload) {\n const content = payload?.choices?.[0]?.message?.content;\n if (typeof content === \"string\") return content.trim();\n if (Array.isArray(content)) {\n return content.map((item) => {\n if (typeof item === \"string\") return item;\n if (item && typeof item.text === \"string\") return item.text;\n return \"\";\n }).join(\"\").trim();\n }\n return \"\";\n}\n\nasync function callDeepSeekChat(messages) {\n const controller = new AbortController();\n const timeout = Number.isFinite(DEEPSEEK_TIMEOUT_MS) && DEEPSEEK_TIMEOUT_MS > 0 ? DEEPSEEK_TIMEOUT_MS : 25000;\n const timer = setTimeout(() => controller.abort(), timeout);\n\n try {\n const response = await fetch(`${DEEPSEEK_BASE_URL}/chat/completions`, {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/json\", Authorization: `Bearer ${DEEPSEEK_API_KEY}` },\n body: JSON.stringify({ model: DEEPSEEK_MODEL, messages, thinking: { type: \"disabled\" }, max_tokens: 500, temperature: 1.05, stream: false }),\n signal: controller.signal\n });\n\n const rawText = await response.text();\n if (!response.ok) throw new Error(`DeepSeek API ${response.status}: ${clipText(rawText, 260)}`);\n\n let payload;\n try { payload = JSON.parse(rawText); } catch (err) { throw new Error(`DeepSeek response parse failed: ${err.message}`); }\n\n const content = extractAssistantContent(payload);\n if (!content) throw new Error(\"DeepSeek returned empty assistant content\");\n return content;\n } catch (err) {\n if (err.name === \"AbortError\") throw new Error(`DeepSeek timeout after ${timeout}ms`);\n throw err;\n } finally {\n clearTimeout(timer);\n }\n}\n\nfunction buildMockAssistantReply({ message, emotion, session, user, memoryContext }) {\n const tone =\n emotion?.label === \"anxiety\" || emotion?.label === \"stress\"\n ? \"我听到你现在有些紧绷，我们先把状态稳下来。\"\n : \"谢谢你愿意说出来，我们一起慢慢梳理。\";\n const suggestions = buildMemoryAwareSuggestions({ session, user, emotion, memoryContext, currentMessage: message });\n return {\n safetyLevel: \"normal\",\n text: `${tone} 你刚才说的是：\"${clipText(message, 60)}\"。我建议先做一个最小动作，然后我再陪你看下一步。`,\n suggestions\n };\n}\n\nasync function buildAssistantReply({ message, emotion, session, user }) {\n const runtime = await ensureLangChainMemoryRuntime(user);\n const memoryContext = await loadLangChainMemoryContext(runtime, message);\n const riskResult = detectHighRisk(message);\n\n if (riskResult.matched) {\n const safetyConfig = db.getSafetyConfig();\n return {\n safetyLevel: \"high\",\n text: safetyConfig?.replacementTemplates?.high || \"我很重视你的安全。请优先联系身边可信任的人或当地紧急援助热线。\",\n suggestions: [\"如果你有立即风险，请马上联系当地紧急服务。\", \"可以先告诉我你现在是否独处，我会继续陪你。\"],\n llmSource: \"safety-template\",\n riskReason: riskResult.reason,\n memoryContext,\n runtime\n };\n }\n\n if (!DEEPSEEK_API_KEY) {\n const mockReply = buildMockAssistantReply({ message, emotion, session, user, memoryContext });\n return { ...mockReply, llmSource: \"mock-no-key\", memoryContext, runtime };\n }\n\n try {\n const messages = buildDeepSeekMessages({ session, user, emotion, message, memoryContext });\n const content = await callDeepSeekChat(messages);\n return {\n safetyLevel: \"normal\",\n text: content,\n suggestions: buildMemoryAwareSuggestions({ session, user, emotion, memoryContext, currentMessage: message }),\n llmSource: \"deepseek\",\n memoryContext,\n runtime\n };\n } catch (err) {\n const fallback = buildMockAssistantReply({ message, emotion, session, user, memoryContext });\n return {\n ...fallback,\n text: `${fallback.text}\\n\\n[系统提示] DeepSeek调用异常，已自动回退到样板回复。`,\n llmSource: \"mock-fallback\",\n llmError: err.message,\n memoryContext,\n runtime\n };\n }\n}\n\n// ── API handlers ────────────────────────────────────────────────────\n\nasync function handleApi(req, res, urlObj) {\n const { pathname } = urlObj;\n\n // GET /api/health\n if (req.method === \"GET\" && pathname === \"/api/health\") {\n sendJson(res, 200, {\n ok: true,\n time: new Date().toISOString(),\n llm: { provider: \"deepseek\", enabled: Boolean(DEEPSEEK_API_KEY), model: DEEPSEEK_MODEL, baseUrl: DEEPSEEK_BASE_URL }\n });\n return true;\n }\n\n // GET /api/users\n if (req.method === \"GET\" && pathname === \"/api/users\") {\n sendJson(res, 200, { users: db.getUsers() });\n return true;\n }\n\n // POST /api/session/start\n if (req.method === \"POST\" && pathname === \"/api/session/start\") {\n const body = await parseBody(req).catch((err) => ({ __error: err.message }));\n if (body.__error) { sendJson(res, 400, { error: body.__error }); return true; }\n const user = db.getUserFull(body.userId);\n if (!user) { sendJson(res, 400, { error: \"Invalid userId\" }); return true; }\n\n const sessionId = db.createId(\"sess\");\n const startedAt = new Date().toISOString();\n db.createSession(sessionId, body.userId, startedAt);\n sendJson(res, 200, { sessionId, startedAt, user });\n return true;\n }\n\n // POST /api/session/end\n if (req.method === \"POST\" && pathname === \"/api/session/end\") {\n const body = await parseBody(req).catch((err) => ({ __error: err.message }));\n if (body.__error) { sendJson(res, 400, { error: body.__error }); return true; }\n const session = db.getSession(body.sessionId);\n if (!session) { sendJson(res, 404, { error: \"Session not found\" }); return true; }\n\n db.endSession(body.sessionId);\n db.appendSessionTimeline(body.sessionId, {\n id: db.createId(\"evt\"),\n time: new Date().toISOString(),\n type: \"session_end\",\n detail: \"会话结束\"\n });\n publishSessionEvent(body.sessionId, \"session_end\", { sessionId: body.sessionId, endedAt: new Date().toISOString() });\n\n const summary = db.getSession(body.sessionId);\n sendJson(res, 200, {\n ok: true,\n session: {\n id: summary.id,\n userId: summary.userId,\n status: summary.status,\n startedAt: summary.startedAt,\n endedAt: summary.endedAt,\n messageCount: summary.chatTurns.length,\n latestEmotion: summary.currentEmotion\n }\n });\n return true;\n }\n\n // POST /api/eeg/push\n if (req.method === \"POST\" && pathname === \"/api/eeg/push\") {\n const body = await parseBody(req).catch((err) => ({ __error: err.message }));\n if (body.__error) { sendJson(res, 400, { error: body.__error }); return true; }\n const session = db.getSession(body.sessionId);\n if (!session) { sendJson(res, 404, { error: \"Session not found\" }); return true; }\n\n const event = {\n id: db.createId(\"eeg\"),\n label: body.label || \"neutral\",\n confidence: Number(body.confidence || 0.5),\n time: body.time || new Date().toISOString()\n };\n\n db.insertEEGEvent(event.id, body.sessionId, event.label, event.confidence, event.time);\n db.updateSessionEmotion(body.sessionId, event.label, event.confidence, event.time);\n db.appendSessionTimeline(body.sessionId, {\n id: db.createId(\"evt\"),\n time: event.time,\n type: \"eeg_update\",\n detail: `${event.label} (${event.confidence.toFixed(2)})`\n });\n\n if ((event.label === \"sad\" || event.label === \"anxiety\" || event.label === \"stress\") && event.confidence >= 0.85) {\n addSafetyLog(body.sessionId, \"medium\", `EEG高置信负性情绪: ${event.label}`, \"eeg\");\n }\n\n publishSessionEvent(body.sessionId, \"eeg\", event);\n sendJson(res, 200, { ok: true, currentEmotion: { label: event.label, confidence: event.confidence, time: event.time } });\n return true;\n }\n\n // POST /api/chat/send\n if (req.method === \"POST\" && pathname === \"/api/chat/send\") {\n const body = await parseBody(req).catch((err) => ({ __error: err.message }));\n if (body.__error) { sendJson(res, 400, { error: body.__error }); return true; }\n const session = db.getSession(body.sessionId);\n if (!session) { sendJson(res, 404, { error: \"Session not found\" }); return true; }\n const userText = String(body.message || \"\").trim();\n if (!userText) { sendJson(res, 400, { error: \"Message is empty\" }); return true; }\n\n const user = db.getUserFull(session.userId);\n const reply = await buildAssistantReply({\n message: userText,\n emotion: session.currentEmotion,\n session,\n user\n });\n\n const turnId = db.createId(\"turn\");\n const now = new Date().toISOString();\n const turn = {\n id: turnId,\n sessionId: body.sessionId,\n userText,\n assistantText: reply.text,\n safetyLevel: reply.safetyLevel,\n emotionLabel: session.currentEmotion?.label,\n emotionConfidence: session.currentEmotion?.confidence,\n suggestions: reply.suggestions,\n llmSource: reply.llmSource || \"unknown\",\n llmError: reply.llmError || null,\n interventionTrackKey: session.interventionState?.trackKey || null,\n interventionStepIndex: session.interventionState?.stepIndex ?? null,\n time: now\n };\n\n db.insertChatTurn(turn);\n db.appendSessionTimeline(body.sessionId, {\n id: db.createId(\"evt\"),\n time: now,\n type: \"chat_turn\",\n detail: `用户输入 + AI回复 (${reply.safetyLevel})`\n });\n db.upsertUserMemory(session.userId, `最近对话要点: ${userText.slice(0, 32)}`);\n await persistLangChainMemory(reply.runtime, userText, reply.text);\n\n if (reply.safetyLevel === \"high\") {\n addSafetyLog(body.sessionId, \"high\", reply.riskReason || \"命中高风险关键词\", \"chat\");\n }\n\n // Refresh session to get updated intervention state\n const refreshedSession = db.getSession(body.sessionId);\n\n publishSessionEvent(body.sessionId, \"chat\", turn);\n sendJson(res, 200, {\n turnId,\n assistantMessage: reply.text,\n safetyLevel: reply.safetyLevel,\n suggestions: reply.suggestions,\n llmSource: reply.llmSource,\n interventionState: refreshedSession?.interventionState || null\n });\n return true;\n }\n\n // POST /api/feedback\n if (req.method === \"POST\" && pathname === \"/api/feedback\") {\n const body = await parseBody(req).catch((err) => ({ __error: err.message }));\n if (body.__error) { sendJson(res, 400, { error: body.__error }); return true; }\n const session = db.getSession(body.sessionId);\n if (!session) { sendJson(res, 404, { error: \"Session not found\" }); return true; }\n\n const fb = {\n id: db.createId(\"fb\"),\n sessionId: body.sessionId,\n turnId: body.turnId || null,\n helpful: Boolean(body.helpful),\n moodDelta: Number(body.moodDelta || 0),\n note: String(body.note || \"\"),\n time: new Date().toISOString()\n };\n db.insertFeedback(fb);\n db.appendSessionTimeline(body.sessionId, {\n id: db.createId(\"evt\"),\n time: fb.time,\n type: \"feedback\",\n detail: `helpful=${fb.helpful}, moodDelta=${fb.moodDelta}`\n });\n publishSessionEvent(body.sessionId, \"feedback\", fb);\n sendJson(res, 200, { ok: true, feedback: fb });\n return true;\n }\n\n // GET /api/sessions\n if (req.method === \"GET\" && pathname === \"/api/sessions\") {\n sendJson(res, 200, { sessions: db.getSessions() });\n return true;\n }\n\n // GET /api/session/:id/state\n if (req.method === \"GET\" && pathname.startsWith(\"/api/session/\") && pathname.endsWith(\"/state\")) {\n const sessionId = pathname.split(\"/\")[3];\n const session = db.getSession(sessionId);\n if (!session) { sendJson(res, 404, { error: \"Session not found\" }); return true; }\n const user = db.getUserFull(session.userId);\n sendJson(res, 200, { session, user });\n return true;\n }\n\n // GET /api/session/:id/stream (SSE)\n if (req.method === \"GET\" && pathname.startsWith(\"/api/session/\") && pathname.endsWith(\"/stream\")) {\n const sessionId = pathname.split(\"/\")[3];\n const session = db.getSession(sessionId);\n if (!session) { sendJson(res, 404, { error: \"Session not found\" }); return true; }\n\n res.writeHead(200, {\n \"Content-Type\": \"text/event-stream; charset=utf-8\",\n \"Cache-Control\": \"no-cache\",\n Connection: \"keep-alive\"\n });\n res.write(`event: ready\\ndata: ${JSON.stringify({ sessionId, time: new Date().toISOString() })}\\n\\n`);\n\n let set = sseClients.get(sessionId);\n if (!set) { set = new Set(); sseClients.set(sessionId, set); }\n set.add(res);\n\n req.on(\"close\", () => {\n const targetSet = sseClients.get(sessionId);\n if (!targetSet) return;\n targetSet.delete(res);\n if (targetSet.size === 0) sseClients.delete(sessionId);\n });\n return true;\n }\n\n // GET /api/dashboard\n if (req.method === \"GET\" && pathname === \"/api/dashboard\") {\n sendJson(res, 200, db.getDashboard());\n return true;\n }\n\n // GET /api/user/:id/profile\n if (req.method === \"GET\" && pathname.startsWith(\"/api/user/\") && pathname.endsWith(\"/profile\")) {\n const userId = pathname.split(\"/\")[3];\n const user = db.getUserFull(userId);\n if (!user) { sendJson(res, 404, { error: \"User not found\" }); return true; }\n sendJson(res, 200, { user });\n return true;\n }\n\n // GET /api/strategy\n if (pathname === \"/api/strategy\" && req.method === \"GET\") {\n sendJson(res, 200, { strategy: db.getStrategyConfig() });\n return true;\n }\n\n // PUT /api/strategy\n if (pathname === \"/api/strategy\" && req.method === \"PUT\") {\n const body = await parseBody(req).catch((err) => ({ __error: err.message }));\n if (body.__error) { sendJson(res, 400, { error: body.__error }); return true; }\n db.updateStrategyConfig(body);\n sendJson(res, 200, { ok: true, strategy: db.getStrategyConfig() });\n return true;\n }\n\n // GET /api/safety\n if (pathname === \"/api/safety\" && req.method === \"GET\") {\n sendJson(res, 200, {\n safety: db.getSafetyConfig(),\n logs: db.getSafetyLogs(200),\n analytics: db.getSafetyAnalytics()\n });\n return true;\n }\n\n // PUT /api/safety\n if (pathname === \"/api/safety\" && req.method === \"PUT\") {\n const body = await parseBody(req).catch((err) => ({ __error: err.message }));\n if (body.__error) { sendJson(res, 400, { error: body.__error }); return true; }\n db.updateSafetyConfig(body);\n const updated = {\n safety: db.getSafetyConfig(),\n logs: db.getSafetyLogs(200),\n analytics: db.getSafetyAnalytics()\n };\n sendJson(res, 200, { ok: true, ...updated });\n return true;\n }\n\n // GET /api/evaluation\n if (pathname === \"/api/evaluation\" && req.method === \"GET\") {\n sendJson(res, 200, db.getEvaluation());\n return true;\n }\n\n // POST /api/export\n if (pathname === \"/api/export\" && req.method === \"POST\") {\n const body = await parseBody(req).catch((err) => ({ __error: err.message }));\n if (body.__error) { sendJson(res, 400, { error: body.__error }); return true; }\n const record = {\n id: db.createId(\"export\"),\n kind: body.kind || \"unknown\",\n time: new Date().toISOString(),\n status: \"queued-sample\"\n };\n db.insertExport(record);\n sendJson(res, 200, { ok: true, export: record });\n return true;\n }\n\n // GET /api/models\n if (req.method === \"GET\" && pathname === \"/api/models\") {\n const models = await getAvailableModels();\n sendJson(res, 200, { models });\n return true;\n }\n\n // POST /api/eeg/import\n if (req.method === \"POST\" && pathname === \"/api/eeg/import\") {\n const body = await parseBody(req).catch((err) => ({ __error: err.message }));\n if (body.__error) { sendJson(res, 400, { error: body.__error }); return true; }\n\n if (!body.csvData || typeof body.csvData !== \"string\") {\n sendJson(res, 400, { error: \"Missing csvData field\" });\n return true;\n }\n if (!body.filename) {\n sendJson(res, 400, { error: \"Missing filename field\" });\n return true;\n }\n\n const session = body.sessionId ? db.getSession(body.sessionId) : null;\n if (body.sessionId && !session) {\n sendJson(res, 404, { error: \"Session not found\" });\n return true;\n }\n\n const model = body.model || \"auto\";\n const parseResult = await parseEEGFile(body.csvData, body.filename, body.sessionId || null, model);\n const importId = db.createId(\"eegimp\");\n const now = new Date().toISOString();\n\n const impRecord = { ...parseResult.imp, id: importId, sessionId: body.sessionId || null, time: now };\n db.createEEGImport(impRecord);\n\n // Insert channel records\n const channelRecords = [];\n for (const ch of parseResult.channels) {\n const chId = db.createId(\"eegch\");\n db.insertEEGChannel({ id: chId, importId, channelName: ch.channelName, band: ch.band || null, value: ch.value });\n channelRecords.push({ id: chId, channelName: ch.channelName, band: ch.band, value: ch.value });\n }\n\n // If session is active, also push as an EEG event\n if (session && session.status === \"active\") {\n const eegEventId = db.createId(\"eeg\");\n db.insertEEGEvent(eegEventId, body.sessionId, parseResult.emotion.label, parseResult.emotion.confidence, now);\n db.updateSessionEmotion(body.sessionId, parseResult.emotion.label, parseResult.emotion.confidence, now);\n db.appendSessionTimeline(body.sessionId, {\n id: db.createId(\"evt\"),\n time: now,\n type: \"eeg_import\",\n detail: `导入 ${body.filename} (${parseResult.imp.channelCount}通道, 判定: ${parseResult.emotion.label})`\n });\n publishSessionEvent(body.sessionId, \"eeg\", {\n id: eegEventId, label: parseResult.emotion.label, confidence: parseResult.emotion.confidence, time: now, source: \"import\"\n });\n }\n\n sendJson(res, 200, {\n ok: true,\n importId,\n format: parseResult.imp.formatType,\n channelCount: parseResult.imp.channelCount,\n channelPreview: channelRecords.slice(0, 20),\n emotion: parseResult.emotion,\n eegPushed: !!(session && session.status === \"active\")\n });\n return true;\n }\n\n // GET /api/eeg/imports\n if (req.method === \"GET\" && pathname === \"/api/eeg/imports\") {\n const sessionId = urlObj.searchParams.get(\"sessionId\");\n if (!sessionId) { sendJson(res, 400, { error: \"Missing sessionId query param\" }); return true; }\n sendJson(res, 200, { imports: db.getEEGImports(sessionId) });\n return true;\n }\n\n // GET /api/eeg/import/:id\n if (req.method === \"GET\" && pathname.startsWith(\"/api/eeg/import/\")) {\n const importId = pathname.split(\"/\")[4];\n if (!importId) { sendJson(res, 400, { error: \"Missing import ID\" }); return true; }\n const full = db.getEEGImportFull(importId);\n if (!full) { sendJson(res, 404, { error: \"Import not found\" }); return true; }\n sendJson(res, 200, { import: full });\n return true;\n }\n\n return false;\n}\n\n// ── Server ──────────────────────────────────────────────────────────\n\nconst server = http.createServer(async (req, res) => {\n try {\n const urlObj = new URL(req.url, `http://${req.headers.host}`);\n const isApiHandled = await handleApi(req, res, urlObj);\n if (!isApiHandled) {\n if (req.method !== \"GET\") { sendJson(res, 405, { error: \"Method not allowed\" }); return; }\n serveStatic(req, res, urlObj.pathname);\n }\n } catch (err) {\n sendJson(res, 500, { error: \"Internal server error\", detail: err.message });\n }\n});\n\nserver.listen(PORT, HOST, () => {\n console.log(`MindCap MVP server running at http://${HOST}:${PORT}`);\n console.log(`Database: ${path.join(__dirname, \"..\", \"data\", \"mindcap.db\")}`);\n});\n"}}}} |