feat: 新增高铁游与车宿徒步游技能及相关基础设施

2026-09-30 13:47:51 +08:00
parent bbc7ca6523
commit ac475b6659
66 changed files with 14572 additions and 0 deletions
@@ -0,0 +1,233 @@
+/* ============================================================
+ * debug_dashscope_image_models.js —— 探测百炼（DashScope）可用的文生图模型
+ *
+ * 目的：项目此前只用了 chat/completions 与 TTS，没有文生图调用。
+ *       本脚本枚举候选模型与候选端点，找出「本账号实际能用」的组合，
+ *       并把生成的图落盘到临时目录做 MD5 比对，确认不同 prompt 出的是不同的图。
+ *
+ * 运行：node dev_test_scripts/debug/debug_dashscope_image_models.js
+ * 说明：只读探测，不写入仓库任何文件（产物落在系统临时目录）。
+ * ============================================================ */
+const fs = require('fs')
+const path = require('path')
+const crypto = require('crypto')
+
+// 载入本机私有凭据（与项目其他模块同一份文件，不进仓库）
+const envPath = path.join(process.env.USERPROFILE || 'C:\\Users\\Administrator', 'Toolbox_local_creds.env.local')
+if (fs.existsSync(envPath)) {
+  const text = fs.readFileSync(envPath, 'utf8')
+  for (const line of text.split(/\r?\n/)) {
+    if (!line || /^\s*#/.test(line)) continue
+    const i = line.indexOf('=')
+    if (i < 0) continue
+    const k = line.slice(0, i).trim()
+    const v = line.slice(i + 1).trim().replace(/^["']|["']$/g, '')
+    if (k && !(k in process.env)) process.env[k] = v
+  }
+}
+
+const KEY = process.env.DASHSCOPE_API_KEY || ''
+const MaaS = (process.env.DASHSCOPE_API_HOST_FOR_OPENAI || '').replace(/\/+$/, '')
+const PUBLIC_BASE = 'https://dashscope.aliyuncs.com'
+
+const OUT = path.join(process.env.TEMP || 'C:\\Windows\\Temp', 'tc_img_probe')
+fs.mkdirSync(OUT, { recursive: true })
+
+const promptA = 'coastal embankment above tidal flat, wind turbines, autumn afternoon'
+const promptB = 'old Chinese town stone lane with grey brick houses and red lanterns'
+
+console.log('[env] KEY 已加载:', !!KEY, KEY ? '(len=' + KEY.length + ')' : '')
+console.log('[env] MaaS host:', MaaS ? MaaS.replace(/\/compatible-mode.*$/, '/…') : '(空)')
+console.log('[out]', OUT)
+
+const get = async (url, headers) => {
+  const r = await fetch(url, { headers, signal: AbortSignal.timeout(25000) })
+  const t = await r.text()
+  return { status: r.status, body: t }
+}
+
+/* ---------- 1. 先看这个 MaaS 端点声明了哪些模型 ---------- */
+async function listModels() {
+  console.log('\n======== 1. 列出 MaaS 端点的模型 ========')
+  if (!MaaS) { console.log('无 MaaS host，跳过'); return [] }
+  try {
+    const r = await get(MaaS + '/models', { Authorization: 'Bearer ' + KEY })
+    console.log('status=', r.status)
+    if (r.status !== 200) { console.log(r.body.slice(0, 400)); return [] }
+    let j = null
+    try { j = JSON.parse(r.body) } catch { console.log(r.body.slice(0, 400)); return [] }
+    const ids = (j.data || []).map((m) => m.id)
+    console.log('模型数 =', ids.length)
+    const likely = ids.filter((id) => /image|t2i|wanx|wan2|flux|sd|diffus/i.test(id))
+    console.log('疑似文生图相关:', likely.length ? likely.join(', ') : '(无)')
+    console.log('全部模型（前 60）:\n  ' + ids.slice(0, 60).join('\n  '))
+    return ids
+  } catch (e) { console.log('ERR', e.message) ; return [] }
+}
+
+/* ---------- 2. 探 text2image/image-synthesis 端点 ---------- */
+const WANX_MODELS = [
+  'wanx2.1-t2i-turbo',
+  'wanx2.1-t2i-plus',
+  'wanx2.0-t2i-turbo',
+  'wanx-v1',
+  'wan2.2-t2i-flash',
+  'wan2.2-t2i-plus',
+  'wan2.5-t2i-preview',
+  'wan2.7-t2i-plus'
+]
+
+async function tryImageSynthesis(model) {
+  const url = PUBLIC_BASE + '/api/v1/services/aigc/text2image/image-synthesis'
+  try {
+    const r = await fetch(url, {
+      method: 'POST',
+      headers: {
+        Authorization: 'Bearer ' + KEY,
+        'Content-Type': 'application/json',
+        'X-DashScope-Async': 'enable'
+      },
+      body: JSON.stringify({
+        model,
+        input: { prompt: promptA },
+        parameters: { size: '1024*576', n: 1 }
+      }),
+      signal: AbortSignal.timeout(25000)
+    })
+    const t = await r.text()
+    let j = null
+    try { j = JSON.parse(t) } catch {}
+    if (r.status === 200 && j && j.output && j.output.task_id) {
+      console.log('  ✓ ' + model + '  task=' + j.output.task_id)
+      return j.output.task_id
+    }
+    const msg = (j && (j.message || (j.output && j.output.task_status))) || t.slice(0, 160)
+    console.log('  ✗ ' + model + '  HTTP ' + r.status + '  ' + String(msg).slice(0, 160))
+    return null
+  } catch (e) {
+    console.log('  ✗ ' + model + '  ERR ' + e.message)
+    return null
+  }
+}
+
+async function poll(taskId, maxTry) {
+  const url = PUBLIC_BASE + '/api/v1/tasks/' + taskId
+  for (let i = 0; i < (maxTry || 20); i++) {
+    await new Promise((r) => setTimeout(r, 3000))
+    const r = await get(url, { Authorization: 'Bearer ' + KEY })
+    let j = null
+    try { j = JSON.parse(r.body) } catch {}
+    const st = j && j.output && j.output.task_status
+    if (st === 'SUCCEEDED') {
+      const results = (j.output.results || []).map((x) => x.url).filter(Boolean)
+      return { status: st, urls: results }
+    }
+    if (st === 'FAILED' || st === 'UNKNOWN') {
+      return { status: st, msg: j.message || (j.output && j.output.message) }
+    }
+  }
+  return { status: 'TIMEOUT' }
+}
+
+/* ---------- 3. 探多模态生成端点（qwen-image 走 messages） ---------- */
+const QWEN_IMAGE_MODELS = ['qwen-image', 'qwen-image-plus', 'qwen-image-max']
+
+async function tryMultimodal(model) {
+  const url = PUBLIC_BASE + '/api/v1/services/aigc/multimodal-generation/generation'
+  try {
+    const r = await fetch(url, {
+      method: 'POST',
+      headers: { Authorization: 'Bearer ' + KEY, 'Content-Type': 'application/json' },
+      body: JSON.stringify({
+        model,
+        input: { messages: [{ role: 'user', content: [{ text: promptA }] }] },
+        parameters: { size: '1024*576', n: 1 }
+      }),
+      signal: AbortSignal.timeout(40000)
+    })
+    const t = await r.text()
+    let j = null
+    try { j = JSON.parse(t) } catch {}
+    const content = j && j.output && j.output.choices && j.output.choices[0] &&
+      j.output.choices[0].message && j.output.choices[0].message.content
+    const urls = Array.isArray(content) ? content.map((c) => c.image).filter(Boolean) : []
+    if (r.status === 200 && urls.length) { console.log('  ✓ ' + model + '  直接返回图片'); return { status: 'SUCCEEDED', urls } }
+    if (r.status === 200 && j && j.output && j.output.task_id) { console.log('  ✓ ' + model + '  task=' + j.output.task_id); return { status: 'TASK', task: j.output.task_id } }
+    const msg = (j && j.message) || t.slice(0, 160)
+    console.log('  ✗ ' + model + '  HTTP ' + r.status + '  ' + String(msg).slice(0, 160))
+    return null
+  } catch (e) { console.log('  ✗ ' + model + '  ERR ' + e.message); return null }
+}
+
+/* ---------- 4. 下载两张图，比对 MD5 ---------- */
+async function download(url, name) {
+  const r = await fetch(url, { signal: AbortSignal.timeout(60000) })
+  if (!r.ok) throw new Error('HTTP ' + r.status)
+  const buf = Buffer.from(await r.arrayBuffer())
+  const file = path.join(OUT, name)
+  fs.writeFileSync(file, buf)
+  return { file, size: buf.length, md5: crypto.createHash('md5').update(buf).digest('hex') }
+}
+
+async function main() {
+  const available = await listModels()
+
+  console.log('\n======== 2. text2image/image-synthesis 候选模型 ========')
+  const hit = []
+  for (const m of WANX_MODELS) {
+    const t = await tryImageSynthesis(m)
+    if (t) hit.push({ model: m, task: t, kind: 'synthesis' })
+  }
+
+  console.log('\n======== 3. multimodal-generation 候选模型 ========')
+  for (const m of QWEN_IMAGE_MODELS) {
+    if (available.length && available.indexOf(m) < 0) { console.log('  - ' + m + '  不在 MaaS 模型列表，仍试一次'); }
+    const r = await tryMultimodal(m)
+    if (r && r.status === 'SUCCEEDED') hit.push({ model: m, urls: r.urls, kind: 'multimodal' })
+    else if (r && r.status === 'TASK') hit.push({ model: m, task: r.task, kind: 'multimodal' })
+  }
+
+  if (!hit.length) { console.log('\n结论：没有可用的文生图模型组合。'); return }
+
+  const first = hit[0]
+  console.log('\n======== 4. 用可用模型 ' + first.model + ' 跑两张不同 prompt，比对 MD5 ========')
+  let urls = first.urls
+  if (!urls) {
+    const p = await poll(first.task, 30)
+    console.log('poll:', p.status, p.msg || '')
+    urls = p.urls || []
+  }
+  if (!urls.length) { console.log('未拿到图片 URL，无法比对'); return }
+  console.log('URL 数 =', urls.length, urls[0].slice(0, 100))
+
+  const a1 = await download(urls[0], 'probe_A.jpg')
+  console.log('A:', a1.size, a1.md5)
+
+  // 换 prompt 再生成一张
+  let taskB = null
+  if (first.kind === 'synthesis') taskB = await tryImageSynthesisWith(first.model, promptB)
+  if (taskB) {
+    const p = await poll(taskB, 30)
+    if (p.urls && p.urls.length) {
+      const b1 = await download(p.urls[0], 'probe_B.jpg')
+      console.log('B:', b1.size, b1.md5)
+      console.log('\n两张图 MD5 是否相同：', a1.md5 === b1.md5 ? '❌ 相同（模型没区分 prompt）' : '✓ 不同（模型正常按 prompt 出图）')
+    } else console.log('B 图未生成:', p.status)
+  }
+}
+
+async function tryImageSynthesisWith(model, prompt) {
+  const url = PUBLIC_BASE + '/api/v1/services/aigc/text2image/image-synthesis'
+  try {
+    const r = await fetch(url, {
+      method: 'POST',
+      headers: { Authorization: 'Bearer ' + KEY, 'Content-Type': 'application/json', 'X-DashScope-Async': 'enable' },
+      body: JSON.stringify({ model, input: { prompt }, parameters: { size: '1024*576', n: 1 } }),
+      signal: AbortSignal.timeout(25000)
+    })
+    const j = JSON.parse(await r.text())
+    return j && j.output && j.output.task_id ? j.output.task_id : null
+  } catch { return null }
+}
+
+main().catch((e) => console.error('FATAL', e && e.message))
@@ -0,0 +1,88 @@
+/* ============================================================
+ * debug_probe_max_tokens.js —— 探测 chat 模型可接受的 max_tokens 上限
+ *
+ * 背景：「游山玩水」整份行程 JSON 约 1.2-1.6 万 output token，
+ *       用 qwen-plus-latest + max_tokens=8000 会截断（finish_reason=length）。
+ *       本脚本用极短的 prompt 试不同 max_tokens，找出模型实际能接受的上限，
+ *       顺便列出可用 chat 模型。
+ *
+ * 运行：node dev_test_scripts/debug/debug_probe_max_tokens.js
+ * 说明：只读探测，用极短 prompt（输出 1-2 个 token），几乎不产生费用。
+ * ============================================================ */
+const fs = require('fs')
+const path = require('path')
+
+const envPath = path.join(process.env.USERPROFILE || 'C:\\Users\\Administrator', 'Toolbox_local_creds.env.local')
+if (fs.existsSync(envPath)) {
+  for (const line of fs.readFileSync(envPath, 'utf8').split(/\r?\n/)) {
+    if (!line || /^\s*#/.test(line)) continue
+    const i = line.indexOf('=')
+    if (i < 0) continue
+    const k = line.slice(0, i).trim()
+    const v = line.slice(i + 1).trim().replace(/^["']|["']$/g, '')
+    if (k && !(k in process.env)) process.env[k] = v
+  }
+}
+
+const HOST = (process.env.DASHSCOPE_API_HOST_FOR_OPENAI || '').replace(/\/+$/, '')
+const KEY = process.env.DASHSCOPE_API_KEY || ''
+const URL = HOST ? HOST + '/chat/completions' : ''
+
+const MODELS = [
+  'qwen-plus-latest',
+  'qwen-max-latest',
+  'qwen3-max',
+  'qwen3.5-plus',
+  'qwen3.5-plus-latest',
+  'qwen-turbo-latest'
+]
+const BUDGETS = [8192, 16384, 32000]
+
+const tryOne = async (model, maxTokens) => {
+  try {
+    const r = await fetch(URL, {
+      method: 'POST',
+      headers: { Authorization: 'Bearer ' + KEY, 'Content-Type': 'application/json' },
+      body: JSON.stringify({ model, messages: [{ role: 'user', content: '只回复两个字：好的' }], max_tokens: maxTokens }),
+      signal: AbortSignal.timeout(60000)
+    })
+    const t = await r.text()
+    let j = null
+    try { j = JSON.parse(t) } catch {}
+    if (r.status === 200 && j && j.choices) {
+      const u = j.usage || {}
+      return { ok: true, note: 'completion=' + (u.completion_tokens === undefined ? '?' : u.completion_tokens) }
+    }
+    return { ok: false, note: 'HTTP ' + r.status + ' ' + String((j && j.message) || t).slice(0, 130) }
+  } catch (e) {
+    return { ok: false, note: 'ERR ' + e.message }
+  }
+}
+
+const main = async () => {
+  console.log('host:', HOST ? '已配置' : '缺失', ' key:', KEY ? '已加载' : '缺失')
+
+  console.log('\n===== 可用 chat 模型（MaaS 声明） =====')
+  try {
+    const r = await fetch(HOST + '/models', { headers: { Authorization: 'Bearer ' + KEY } })
+    const j = JSON.parse(await r.text())
+    const ids = (j.data || []).map((m) => m.id)
+    const chat = ids.filter((id) => /qwen|deepseek|glm|kimi|llama|gpt/i.test(id) && !/image|vl|audio|asr|tts|voice|video|t2i|t2v|embed/i.test(id))
+    console.log('chat 类候选共 ' + chat.length + ' 个：\n  ' + chat.slice(0, 50).join('\n  '))
+  } catch (e) {
+    console.log('列模型失败：' + e.message)
+  }
+
+  console.log('\n===== max_tokens 上限探测 =====')
+  for (const m of MODELS) {
+    const line = []
+    for (const b of BUDGETS) {
+      const r = await tryOne(m, b)
+      line.push(b + ':' + (r.ok ? '✓' : '✗'))
+      if (!r.ok) { line.push('(' + r.note.slice(0, 90) + ')'); break }
+    }
+    console.log('  ' + m.padEnd(20) + ' ' + line.join('  '))
+  }
+}
+
+main().catch((e) => console.error('FATAL', e && e.message))
@@ -0,0 +1,112 @@
+/* ============================================================
+ * debug_rail_replay_wuyuan.js —— 用真实失败案例回放，验证修复有效
+ *
+ * 背景：2026-09-30 生成「婺源」时返回 payload_invalid，唯一 error 是
+ *   「第一天缺「夜逛」环节（night_stroll）」——但 AI 其实排了 19:00 的夜逛。
+ *   根因是校验器写死了 day.label 含「第一天」，而 AI 标的是「周六/周日」。
+ *
+ * 本脚本把那次失败响应的 payload 原样取出来，走一遍「修复 → 校验」，
+ * 用来证明修复后不再误报（同时也顺带检查其余 warning 是否已消除）。
+ *
+ * 用法：
+ *   node dev_test_scripts/debug/debug_rail_replay_wuyuan.js          只回放校验，不写任何文件
+ *   node dev_test_scripts/debug/debug_rail_replay_wuyuan.js --save   额外把这份结果写回
+ *                                                                   技能私有 data/last_result.json，
+ *                                                                   这样用户可在页面上点「载入最近一次生成」
+ *                                                                   直接看到并导出这份婺源行程（不必重烧 token）
+ *
+ * 为什么需要 --save：服务端只在「校验 0 errors」时才落盘，那次因误判被丢弃，
+ *   用户 4 分钟的生成白费了。这个开关是给「已经拿到完整 payload、只想补落盘」的补救场景用的。
+ * ============================================================ */
+const fs = require('fs')
+const path = require('path')
+const os = require('os')
+
+const SRC = path.join(
+  os.homedir(), 'AppData', 'Roaming', 'Trae CN', 'User', 'workspaceStorage',
+  '540d38674b58f7802a478abf6956abc7', 'long-text', '6ab1e0ff40ac82e5fecf1de9',
+  'munlta58-u92r', '当前状态__失败__....txt'
+)
+
+const SKILL = path.join(process.cwd(), 'src', 'server', 'thought_lab', 'labs', 'travel_citytour', 'skills', 'sh_2d_rail_hike')
+const skillIndex = require(path.join(SKILL, 'index.js'))
+const { validatePayload } = require(path.join(SKILL, 'validate.js'))
+const { repairPayload } = require(path.join(SKILL, 'repair.js'))
+
+if (!fs.existsSync(SRC)) {
+  console.log('找不到失败响应文件（可能已被清理）：' + SRC)
+  process.exit(0)
+}
+
+const raw = fs.readFileSync(SRC, 'utf-8')
+
+// 响应体从「返回结果」后的第一个 '{' 开始，到「错误信息」之前结束
+const startMark = raw.indexOf('返回结果')
+const start = raw.indexOf('{', startMark)
+const endMark = raw.indexOf('错误信息', start)
+const text = raw.slice(start, endMark > 0 ? endMark : undefined).trim()
+
+let envelope = null
+try {
+  envelope = JSON.parse(text)
+} catch (e) {
+  // 兜底：按大括号配平截取
+  let depth = 0, endIdx = -1
+  for (let i = start; i < raw.length; i++) {
+    if (raw[i] === '{') depth++
+    else if (raw[i] === '}') { depth--; if (depth === 0) { endIdx = i; break } }
+  }
+  envelope = JSON.parse(raw.slice(start, endIdx + 1))
+}
+
+const payload = envelope.payload
+const bundle = skillIndex.loadBundle()
+
+console.log('===== 婺源失败案例回放 =====')
+console.log('原文 error：' + JSON.stringify(envelope.check && envelope.check.errors))
+console.log('day.label 实际写法：' + ((payload.timeline && payload.timeline.days) || []).map((d) => JSON.stringify(d.label)).join(' / '))
+console.log('AI 是否排了夜逛行：' + ((payload.timeline && payload.timeline.days) || [])
+  .reduce((a, d) => a.concat(d.rows || []), [])
+  .some((r) => r.anchor_id === 'night_stroll'))
+console.log('')
+
+const repaired = repairPayload(JSON.parse(JSON.stringify(payload)), bundle)
+const chk = validatePayload(repaired.payload, bundle)
+
+console.log('— 修复说明 —')
+repaired.fixes.forEach((f) => console.log('  · ' + f))
+console.log('')
+console.log('— 修复后校验结果 —')
+console.log('errors  : ' + chk.errors.length + (chk.errors.length ? '\n  ✗ ' + chk.errors.join('\n  ✗ ') : ''))
+console.log('warnings: ' + chk.warnings.length + (chk.warnings.length ? '\n  ! ' + chk.warnings.join('\n  ! ') : ''))
+console.log('')
+console.log(chk.errors.length === 0
+  ? '✓ 回放通过：这份真实失败的 payload 修复后 0 errors，不再被误判'
+  : '✗ 仍有 error，需继续排查')
+
+// --save：把修复后的结果补落盘，供页面「载入最近一次生成」使用
+if (process.argv.indexOf('--save') >= 0) {
+  if (chk.errors.length) {
+    console.log('\n⚠ 仍有 error，拒绝落盘（避免把不合格结果写进 last_result）')
+    process.exit(1)
+  }
+  const outEnvelope = {
+    ok: true,
+    payload: repaired.payload,
+    report_spec: bundle.report_spec || {},
+    destination_override: null,
+    check: chk,
+    meta: Object.assign({}, envelope.meta, {
+      repairs: repaired.fixes,
+      recovered_from: 'payload_invalid 误判（校验器已修复）'
+    })
+  }
+  const dataDir = path.join(SKILL, 'data')
+  fs.mkdirSync(dataDir, { recursive: true })
+  const out = path.join(dataDir, 'last_result.json')
+  fs.writeFileSync(out, JSON.stringify(outEnvelope), 'utf-8')
+  console.log('\n✓ 已补落盘：' + out)
+  console.log('  下一步：打开本技能页面 → 点「载入最近一次生成」即可查看/导出这份婺源行程')
+}
+
+process.exit(chk.errors.length === 0 ? 0 : 1)