X-Financial/web/tests/workbench-ai-intent-planner-model.test.mjs

import assert from 'node:assert/strict'
import { readFileSync } from 'node:fs'
import test from 'node:test'
import { fileURLToPath } from 'node:url'

import {
  WORKBENCH_AI_INTENT_SOURCE_MODEL,
  WORKBENCH_AI_INTENT_SOURCE_RULE_FALLBACK,
  WORKBENCH_AI_STEP_BUILD_APPLICATION_PREVIEW,
  WORKBENCH_AI_STEP_SAVE_APPLICATION_DRAFT,
  WORKBENCH_AI_STEP_RUN_DUPLICATE_PRECHECK,
  WORKBENCH_AI_STEP_SUBMIT_APPLICATION,
  WORKBENCH_AI_STEP_VALIDATE_REQUIRED_FIELDS,
  buildRuleFallbackWorkbenchAiIntentPlan,
  isLowConfidenceTravelApplicationPlan,
  normalizeWorkbenchAiIntentPlan,
  resolveExecutableTravelApplicationPlan,
  shouldRequestWorkbenchAiIntentPlan
} from '../src/composables/workbenchAiMode/workbenchAiIntentPlannerModel.js'
import { buildInlineApplicationPreview } from '../src/composables/workbenchAiMode/workbenchAiApplicationPreviewModel.js'
import { createWorkbenchAiMessageRuntime } from '../src/composables/workbenchAiMode/workbenchAiMessageModel.js'

const personalWorkbenchAiModeScript = readFileSync(
  fileURLToPath(new URL('../src/composables/workbenchAiMode/usePersonalWorkbenchAiMode.js', import.meta.url)),
  'utf8'
)
const stewardFlowScript = readFileSync(
  fileURLToPath(new URL('../src/composables/workbenchAiMode/useWorkbenchAiStewardFlow.js', import.meta.url)),
  'utf8'
)
const applicationPreviewFlowScript = readFileSync(
  fileURLToPath(new URL('../src/composables/workbenchAiMode/useWorkbenchAiApplicationPreviewFlow.js', import.meta.url)),
  'utf8'
)
const planningThinkingModelScript = readFileSync(
  fileURLToPath(new URL('../src/composables/workbenchAiMode/workbenchAiPlanningThinkingModel.js', import.meta.url)),
  'utf8'
)

test('workbench AI intent planner normalizes model travel application submit plan into executable steps', () => {
  const plan = normalizeWorkbenchAiIntentPlan({
    planning_source: 'llm_function_call',
    tasks: [{
      task_type: 'expense_application',
      assigned_agent: 'application_assistant',
      requested_action: 'submit',
      confidence: 0.91,
      ontology_fields: {
        time_range: '2026-02-20 至 2026-02-23',
        location: '上海',
        reason: '辅助国网仿生产服务器部署',
        transport_mode: '火车'
      }
    }]
  }, {
    prompt: '去上海出差，辅助国网仿生产服务器部署，交通火车，直接提交'
  })

  assert.equal(plan.source, WORKBENCH_AI_INTENT_SOURCE_MODEL)
  assert.equal(plan.intent, 'create_travel_application')
  assert.equal(plan.requestedAction, 'submit')
  assert.deepEqual(plan.steps, [
    WORKBENCH_AI_STEP_BUILD_APPLICATION_PREVIEW,
    WORKBENCH_AI_STEP_VALIDATE_REQUIRED_FIELDS,
    WORKBENCH_AI_STEP_RUN_DUPLICATE_PRECHECK,
    WORKBENCH_AI_STEP_SUBMIT_APPLICATION
  ])
  assert.deepEqual(plan.ontologyFields, {
    time_range: '2026-02-20 至 2026-02-23',
    location: '上海',
    reason: '辅助国网仿生产服务器部署',
    transport_mode: '火车'
  })
  assert.deepEqual(plan.slots, {
    timeRange: '2026-02-20 至 2026-02-23',
    location: '上海',
    reason: '辅助国网仿生产服务器部署',
    transportMode: '火车'
  })
})

test('workbench AI intent planner keeps reimbursement task after first application task', () => {
  const reimbursementTask = {
    task_id: 'task-reimbursement-2',
    task_type: 'reimbursement',
    assigned_agent: 'reimbursement_assistant',
    title: '业务招待费报销',
    summary: '报销昨天的业务招待费 2000 元',
    requested_action: 'preview',
    confidence: 0.9,
    ontology_fields: {
      expense_type: 'entertainment',
      expense_type_label: '业务招待费',
      time_range: '2026-06-25',
      amount: '2000元',
      reason: '业务招待'
    },
    missing_fields: []
  }
  const plan = normalizeWorkbenchAiIntentPlan({
    planning_source: 'llm_function_call',
    tasks: [{
      task_id: 'task-application-1',
      task_type: 'expense_application',
      assigned_agent: 'application_assistant',
      requested_action: 'preview',
      confidence: 0.93,
      ontology_fields: {
        expense_type: 'travel',
        time_range: '2026-02-20 至 2026-02-23',
        location: '上海',
        reason: '服务国网服务器部署'
      },
      missing_fields: ['transport_mode']
    }, reimbursementTask]
  }, {
    prompt: '2月20-23日去上海出差3天，服务国网服务器部署，并且报销昨天的业务招待费2000元'
  })

  assert.deepEqual(plan.stewardRemainingTasks, [reimbursementTask])
  assert.deepEqual(resolveExecutableTravelApplicationPlan(plan).stewardRemainingTasks, [reimbursementTask])
})

test('workbench AI intent planner prefers server action steps when present', () => {
  const plan = normalizeWorkbenchAiIntentPlan({
    planning_source: 'llm_function_call',
    tasks: [{
      task_type: 'expense_application',
      assigned_agent: 'application_assistant',
      requested_action: 'submit',
      confidence: 0.91,
      ontology_fields: {
        time_range: '2026-02-20 至 2026-02-23',
        location: '上海',
        reason: '辅助国网仿生产服务器部署',
        transport_mode: '火车'
      },
      action_steps: [
        { action_type: 'fill_application_fields' },
        { action_type: 'build_application_preview' },
        { action_type: 'validate_required_fields' },
        { action_type: 'save_application_draft' }
      ]
    }]
  }, {
    prompt: '2026-02-20 至 2026-02-23，去上海出差，辅助国网仿生产服务器部署，交通火车，直接提交'
  })

  assert.deepEqual(plan.steps, [
    WORKBENCH_AI_STEP_BUILD_APPLICATION_PREVIEW,
    WORKBENCH_AI_STEP_VALIDATE_REQUIRED_FIELDS,
    WORKBENCH_AI_STEP_SAVE_APPLICATION_DRAFT
  ])
})

test('workbench AI intent planner falls back to rule plan for compact travel direct submit', () => {
  const plan = buildRuleFallbackWorkbenchAiIntentPlan('去上海出差，辅助国网仿生产服务器部署，交通火车，直接提交')

  assert.equal(plan.source, WORKBENCH_AI_INTENT_SOURCE_RULE_FALLBACK)
  assert.equal(plan.intent, 'create_travel_application')
  assert.equal(plan.requestedAction, 'submit')
  assert.deepEqual(plan.steps, [
    WORKBENCH_AI_STEP_BUILD_APPLICATION_PREVIEW,
    WORKBENCH_AI_STEP_VALIDATE_REQUIRED_FIELDS,
    WORKBENCH_AI_STEP_RUN_DUPLICATE_PRECHECK,
    WORKBENCH_AI_STEP_SUBMIT_APPLICATION
  ])
})

test('workbench AI intent planner detects compact travel save-draft variant before rules are enough', () => {
  const prompt = '2026-02-20 至 2026-02-23，上海出差，国网仿生产服务器部署，火车，保存草稿。'
  const plan = buildRuleFallbackWorkbenchAiIntentPlan(prompt)

  assert.equal(shouldRequestWorkbenchAiIntentPlan(prompt), true)
  assert.equal(shouldRequestWorkbenchAiIntentPlan('帮我查询上海差旅标准'), true)
  assert.equal(shouldRequestWorkbenchAiIntentPlan('1'), false)
  assert.equal(plan.source, WORKBENCH_AI_INTENT_SOURCE_RULE_FALLBACK)
  assert.equal(plan.intent, 'create_travel_application')
  assert.equal(plan.requestedAction, 'save_draft')
  assert.deepEqual(plan.steps, [
    WORKBENCH_AI_STEP_BUILD_APPLICATION_PREVIEW,
    WORKBENCH_AI_STEP_VALIDATE_REQUIRED_FIELDS,
    WORKBENCH_AI_STEP_SAVE_APPLICATION_DRAFT
  ])
  assert.deepEqual(resolveExecutableTravelApplicationPlan(plan), {
    expenseType: 'travel',
    expenseTypeLabel: '差旅费',
    sourceText: prompt,
    ontologyFields: {},
    autoSubmit: false,
    autoSaveDraft: true,
    requestedSubmit: false,
    submitRequiresConfirmation: false
  })
})

test('workbench AI intent planner turns model fields and action into executable application preview payload', () => {
  const prompt = '2026-02-20 至 2026-02-23，上海出差，国网仿生产服务器部署，火车，保存草稿。'
  const plan = normalizeWorkbenchAiIntentPlan({
    planning_source: 'llm_function_call',
    tasks: [{
      task_type: 'expense_application',
      assigned_agent: 'application_assistant',
      requested_action: 'save_draft',
      confidence: 0.95,
      ontology_fields: {
        time_range: '2026-02-20 至 2026-02-23',
        location: '上海',
        reason: '国网仿生产服务器部署',
        transport_mode: '火车'
      },
      missing_fields: []
    }]
  }, { prompt })

  assert.deepEqual(resolveExecutableTravelApplicationPlan(plan), {
    expenseType: 'travel',
    expenseTypeLabel: '差旅费',
    sourceText: prompt,
    ontologyFields: {
      time_range: '2026-02-20 至 2026-02-23',
      location: '上海',
      reason: '国网仿生产服务器部署',
      transport_mode: '火车'
    },
    autoSubmit: false,
    autoSaveDraft: true,
    requestedSubmit: false,
    submitRequiresConfirmation: false
  })
})

test('workbench AI intent planner turns single application candidate flow into executable preview payload', () => {
  const prompt = '2026-02-20 至 2026-02-23，去上海出差，辅助国网仿生产服务器部署，交通火车'
  const plan = normalizeWorkbenchAiIntentPlan({
    planning_source: 'rule_fallback',
    plan_status: 'needs_flow_confirmation',
    pending_flow_confirmation: {
      status: 'pending',
      candidate_flows: [{
        flow_id: 'travel_application',
        label: '先发起出差申请',
        confidence: 0.86,
        ontology_fields: {
          expense_type: 'travel',
          time_range: '2026-02-20 至 2026-02-23',
          location: '上海',
          reason: '辅助国网仿生产服务器部署',
          transport_mode: '火车'
        },
        missing_fields: []
      }]
    }
  }, { prompt })

  assert.equal(plan.source, WORKBENCH_AI_INTENT_SOURCE_RULE_FALLBACK)
  assert.equal(plan.intent, 'create_travel_application')
  assert.equal(plan.requestedAction, 'preview')
  assert.deepEqual(resolveExecutableTravelApplicationPlan(plan), {
    expenseType: 'travel',
    expenseTypeLabel: '差旅费',
    sourceText: prompt,
    ontologyFields: {
      expense_type: 'travel',
      time_range: '2026-02-20 至 2026-02-23',
      location: '上海',
      reason: '辅助国网仿生产服务器部署',
      transport_mode: '火车'
    },
    autoSubmit: false,
    autoSaveDraft: false,
    requestedSubmit: false,
    submitRequiresConfirmation: false
  })
})

test('workbench AI application preview prefers model ontology fields over local text guesses', () => {
  const preview = buildInlineApplicationPreview(
    '差旅费',
    '2026-02-20 至 2026-02-23，上海出差，国网仿生产服务器部署，火车，保存草稿。',
    { name: '李文静', grade: 'P5', location: '武汉' },
    {
      ontologyFields: {
        time_range: '2026-02-20 至 2026-02-23',
        location: '上海',
        reason: '国网仿生产服务器部署',
        transport_mode: '火车'
      }
    }
  )

  assert.equal(preview.fields.time, '2026-02-20 至 2026-02-23')
  assert.equal(preview.fields.location, '上海')
  assert.equal(preview.fields.reason, '国网仿生产服务器部署')
  assert.equal(preview.fields.transportMode, '火车')
})

test('workbench AI intent planner rejects policy question and requires confirmation for direct-submit request', () => {
  assert.equal(buildRuleFallbackWorkbenchAiIntentPlan('帮我查询上海差旅标准'), null)

  const request = resolveExecutableTravelApplicationPlan(
    buildRuleFallbackWorkbenchAiIntentPlan('去上海出差，辅助国网仿生产服务器部署，交通火车，直接提交')
  )

  assert.deepEqual(request, {
    expenseType: 'travel',
    expenseTypeLabel: '差旅费',
    sourceText: '去上海出差，辅助国网仿生产服务器部署，交通火车，直接提交',
    ontologyFields: {},
    autoSubmit: false,
    autoSaveDraft: false,
    requestedSubmit: true,
    submitRequiresConfirmation: true
  })
})

test('workbench AI message runtime persists direct-submit confirmation metadata', () => {
  const { createInlineMessage, normalizeRuntimeMessage, serializeRuntimeMessage } = createWorkbenchAiMessageRuntime()
  const message = createInlineMessage('assistant', '申请核对表', {
    applicationPreview: { fields: { location: '上海' } },
    requestedSubmit: true,
    submitRequiresConfirmation: true
  })

  const serialized = serializeRuntimeMessage(message)
  assert.equal(serialized.requestedSubmit, true)
  assert.equal(serialized.submitRequiresConfirmation, true)

  const normalized = normalizeRuntimeMessage(serialized)
  assert.equal(normalized.requestedSubmit, true)
  assert.equal(normalized.submitRequiresConfirmation, true)
})

test('workbench AI mode asks steward model plan before fallback execution', () => {
  assert.match(stewardFlowScript, /async function resolveInlineExecutionPlan\(prompt, entry = \{\}, files = \[\], options = \{\}\)/)
  assert.match(stewardFlowScript, /fetchStewardPlan\(planRequest/)
  assert.match(stewardFlowScript, /timeoutMs:\s*35000/)
  assert.match(personalWorkbenchAiModeScript, /async function executeModelPlannedWorkbenchIntent\(cleanPrompt, entry = \{\}, files = \[\]\)/)
  assert.match(personalWorkbenchAiModeScript, /await stewardFlow\.resolveInlineExecutionPlan\(cleanPrompt, entry, files,\s*\{/)
  assert.match(personalWorkbenchAiModeScript, /normalizeWorkbenchAiIntentPlan\(modelPlan,\s*\{\s*prompt:\s*cleanPrompt/)
  assert.match(personalWorkbenchAiModeScript, /buildRuleFallbackWorkbenchAiIntentPlan\(cleanPrompt\)/)
  assert.match(personalWorkbenchAiModeScript, /shouldRequestWorkbenchAiIntentPlan\(cleanPrompt\)/)
  assert.match(personalWorkbenchAiModeScript, /resolveExecutableTravelApplicationPlan\(intentPlan\)/)
  assert.doesNotMatch(personalWorkbenchAiModeScript, /fallbackIntentPlan/)
  assert.match(personalWorkbenchAiModeScript, /autoSaveDraft:\s*travelApplicationRequest\.autoSaveDraft/)
  assert.match(personalWorkbenchAiModeScript, /requestedSubmit:\s*travelApplicationRequest\.requestedSubmit/)
  assert.match(personalWorkbenchAiModeScript, /submitRequiresConfirmation:\s*travelApplicationRequest\.submitRequiresConfirmation/)
  assert.match(personalWorkbenchAiModeScript, /ontologyFields:\s*travelApplicationRequest\.ontologyFields/)
  assert.match(personalWorkbenchAiModeScript, /stewardRemainingTasks:\s*travelApplicationRequest\.stewardRemainingTasks/)
  assert.match(personalWorkbenchAiModeScript, /onPreviewReadyForNextTask:\s*startModelPlannedNextTask/)
  assert.match(personalWorkbenchAiModeScript, /onApplicationActionCompleted:\s*startModelPlannedNextTask/)
  assert.match(applicationPreviewFlowScript, /options\.autoSaveDraft/)
  assert.match(applicationPreviewFlowScript, /options\.onPreviewReadyForNextTask/)
  assert.match(applicationPreviewFlowScript, /onApplicationActionCompleted\(\s*targetMessage\.stewardRemainingTasks/)
  assert.doesNotMatch(applicationPreviewFlowScript, /options\.autoSubmit && normalizeApplicationPreview\(preview\)\.readyToSubmit/)
  assert.match(applicationPreviewFlowScript, /ontologyFields:\s*options\.ontologyFields/)
  assert.match(applicationPreviewFlowScript, /executeInlineApplicationPreviewAction\(AI_APPLICATION_ACTION_SAVE_DRAFT/)
  assert.match(applicationPreviewFlowScript, /buildInlineApplicationPreview\([\s\S]*ontologyFields:\s*options\.ontologyFields/)
  assert.doesNotMatch(personalWorkbenchAiModeScript, /const travelApplicationRequest = resolveInlineTravelApplicationRequest\(cleanPrompt\)/)
})

test('workbench AI mode shows a visible planning response before waiting for steward model plan', () => {
  assert.match(personalWorkbenchAiModeScript, /function startModelPlanningConversation\(cleanPrompt, entry = \{\}\)/)
  assert.match(personalWorkbenchAiModeScript, /conversationMessages\.value\.push\(createInlineMessage\('user', cleanPrompt\)\)/)
  assert.match(personalWorkbenchAiModeScript, /正在识别意图，准备拆解申请、报销和附件任务/)
  assert.match(
    personalWorkbenchAiModeScript,
    /const plannerPendingMessage = startModelPlanningConversation\(cleanPrompt, entry\)[\s\S]*await stewardFlow\.resolveInlineExecutionPlan\(cleanPrompt, entry, files,\s*\{/
  )
  assert.match(
    personalWorkbenchAiModeScript,
    /pendingMessageId:\s*plannerPendingMessage\?\.id/
  )
  assert.match(applicationPreviewFlowScript, /options\.pendingMessageId/)
})

test('workbench AI mode streams planning thinking into the pending message', () => {
  assert.match(planningThinkingModelScript, /buildModelPlanningProgressSchedule/)
  assert.match(planningThinkingModelScript, /判断办理意图/)
  assert.match(planningThinkingModelScript, /抽取关键信息/)
  assert.match(planningThinkingModelScript, /规划执行步骤/)
  assert.match(planningThinkingModelScript, /准备兜底策略/)
  assert.match(personalWorkbenchAiModeScript, /function startModelPlanningProgressUpdates\(messageId\)/)
  assert.match(personalWorkbenchAiModeScript, /globalThis\.setTimeout\(\(\) => \{\s*updateModelPlanningThinkingEvent\(messageId, event\)/)
  assert.match(personalWorkbenchAiModeScript, /const stopPlanningProgressUpdates = startModelPlanningProgressUpdates\(plannerPendingMessage\.id\)/)
  assert.match(personalWorkbenchAiModeScript, /stopPlanningProgressUpdates\(\)/)
  assert.match(
    personalWorkbenchAiModeScript,
    /await stewardFlow\.resolveInlineExecutionPlan\(cleanPrompt, entry, files,\s*\{\s*pendingMessageId:\s*plannerPendingMessage\.id\s*\}\)/
  )
  assert.match(stewardFlowScript, /async function resolveInlineExecutionPlan\(prompt, entry = \{\}, files = \[\], options = \{\}\)/)
  assert.match(stewardFlowScript, /fetchInlineStewardPlan\(planningMessageId, planRequest,\s*\{[\s\S]*includeAnswerDelta:\s*false/)
  assert.match(applicationPreviewFlowScript, /mergeWorkbenchAiThinkingEvents\(previousThinkingEvents,\s*\[/)
})

test('workbench AI mode reuses planning pending message for regular steward replies', () => {
  assert.match(
    personalWorkbenchAiModeScript,
    /stewardFlow\.requestInlineAssistantReply\(cleanPrompt, entry, files,\s*\{\s*pendingMessageId:\s*plannerPendingMessage\.id\s*\}\)/
  )
  assert.doesNotMatch(
    personalWorkbenchAiModeScript,
    /replaceInlineMessage\(plannerPendingMessage\.id,\s*createInlineMessage\('assistant', '已完成意图识别，继续为您整理回复。'/
  )
  assert.match(stewardFlowScript, /async function requestInlineAssistantReply\(prompt, entry = \{\}, files = \[\], options = \{\}\)/)
  assert.match(stewardFlowScript, /const reusablePendingMessageId = String\(options\.pendingMessageId \|\| ''\)\.trim\(\)/)
  assert.match(stewardFlowScript, /reusablePendingMessageId \? replaceInlineMessage\(reusablePendingMessageId, pendingMessage\) : conversationMessages\.value\.push\(pendingMessage\)/)
})

test('isLowConfidenceTravelApplicationPlan gates preview behind confirmation when model confidence is low', () => {
  const lowConfidenceModelPlan = normalizeWorkbenchAiIntentPlan({
    planning_source: 'llm_function_call',
    tasks: [{
      task_type: 'expense_application',
      assigned_agent: 'application_assistant',
      requested_action: 'preview',
      confidence: 0.4,
      ontology_fields: { location: '上海', reason: '部署' }
    }]
  }, { prompt: '上海那边好像要过去一趟搞部署' })

  assert.equal(lowConfidenceModelPlan.source, WORKBENCH_AI_INTENT_SOURCE_MODEL)
  assert.equal(isLowConfidenceTravelApplicationPlan(lowConfidenceModelPlan), true)

  const highConfidenceModelPlan = normalizeWorkbenchAiIntentPlan({
    planning_source: 'llm_function_call',
    tasks: [{
      task_type: 'expense_application',
      assigned_agent: 'application_assistant',
      requested_action: 'preview',
      confidence: 0.9,
      ontology_fields: { location: '上海' }
    }]
  }, { prompt: '去上海出差' })

  assert.equal(isLowConfidenceTravelApplicationPlan(highConfidenceModelPlan), false)

  const ruleFallbackPlan = buildRuleFallbackWorkbenchAiIntentPlan('去上海出差，辅助部署，交通火车')
  assert.equal(ruleFallbackPlan.source, WORKBENCH_AI_INTENT_SOURCE_RULE_FALLBACK)
  assert.equal(isLowConfidenceTravelApplicationPlan(ruleFallbackPlan), false)

  const explicitSubmitLowConfidence = normalizeWorkbenchAiIntentPlan({
    planning_source: 'llm_function_call',
    tasks: [{
      task_type: 'expense_application',
      assigned_agent: 'application_assistant',
      requested_action: 'submit',
      confidence: 0.3,
      ontology_fields: { location: '上海' }
    }]
  }, { prompt: '直接提交' })

  assert.equal(explicitSubmitLowConfidence.requestedAction, 'submit')
  assert.equal(isLowConfidenceTravelApplicationPlan(explicitSubmitLowConfidence), false)

  assert.equal(isLowConfidenceTravelApplicationPlan(null), false)
})

test('workbench AI mode routes low confidence travel application plan to confirmation prompt', () => {
  assert.match(personalWorkbenchAiModeScript, /isLowConfidenceTravelApplicationPlan\(intentPlan\)/)
  assert.match(personalWorkbenchAiModeScript, /function startModelPlannedTravelApplicationConfirmation\(/)
  assert.match(personalWorkbenchAiModeScript, /action_type:\s*'ai_application_confirm_intent'/)
  assert.match(personalWorkbenchAiModeScript, /需要确认：您是要发起出差申请吗/)
})

test('shouldRequestWorkbenchAiIntentPlan skips chitchat and only triggers on business keywords', () => {
  assert.equal(shouldRequestWorkbenchAiIntentPlan('你好'), false)
  assert.equal(shouldRequestWorkbenchAiIntentPlan('谢谢'), false)
  assert.equal(shouldRequestWorkbenchAiIntentPlan('嗯'), false)
  assert.equal(shouldRequestWorkbenchAiIntentPlan('ok'), false)
  assert.equal(shouldRequestWorkbenchAiIntentPlan('1'), false)

  assert.equal(shouldRequestWorkbenchAiIntentPlan('帮我查报销'), true)
  assert.equal(shouldRequestWorkbenchAiIntentPlan('我要出差'), true)
  assert.equal(shouldRequestWorkbenchAiIntentPlan('帮我查询上海差旅标准'), true)
  assert.equal(shouldRequestWorkbenchAiIntentPlan('删除3天前的草稿'), true)
})