pj0235-eai_agentplatform/eai_agentplatform/frontend/src/api/ai.js

import http from './http'

// 会话持久化：列出当前用户的 AI 对话会话
export function listChatConversations() {
  return http.get('/ai-chat/conversations')
}

// 会话持久化：获取某个会话的历史消息
export function getChatConversationMessages(conversationId) {
  return http.get(`/ai-chat/conversations/${conversationId}/messages`)
}

export function quickActions() {
  return http.get('/ai-chat/quick-actions')
}

export function quickAction(actionId, params) {
  return http.post('/ai-chat/quick-action', { action_id: actionId, params })
}

// 用量聚合（管理员 = 全量；员工 = 本人，后端按角色过滤）
export function getAiUsage(params) {
  return http.get('/ai/usage', { params })
}

// 管理员：按用户聚合用量 + 剩余点数
export function getAiUsageUsers() {
  return http.get('/ai/usage/users')
}

// 管理员：AI 配置（ai_config.json）读 / 写 / 热重载 / 密钥状态
export function getAiConfig() {
  return http.get('/ai/config')
}
export function putAiConfig(config) {
  return http.put('/ai/config', config)
}
export function reloadAiConfig() {
  return http.post('/ai/reload')
}
export function getSecretsStatus() {
  return http.get('/ai/secrets-status')
}

// 管理员：AI 通路测试 —— 获取某路由的候选模型清单（配置 model ∪ 自动发现）
export function getRouteTestModels(routeId) {
  return http.post('/ai/route-test/models', { route_id: routeId })
}

// 管理员：AI 通路测试 —— 对单个模型或候选模型逐个发起真实测试
// models 为空 → 只测配置 model；填多个 → 逐个试跑
export function runRouteTest(params) {
  return http.post('/ai/route-test/run', params || {})
}

// SSE 流式对话：后端 text/event-stream，每行 "data: {json}\n\n"
// conversationId 可选：传入后请求体会携带 conversation_id，用于会话持久化
export async function streamChat(message, context, history, handlers, conversationId = '') {
  const token = localStorage.getItem('token')
  const onChunk = typeof handlers === 'function' ? handlers : handlers?.onChunk
  const onMeta = typeof handlers === 'function' ? null : handlers?.onMeta
  const onDone = typeof handlers === 'function' ? null : handlers?.onDone
  const aiRouteId = typeof handlers === 'function' ? '' : (handlers?.aiRouteId || '')
  const payload = { message, context, history, ai_route_id: aiRouteId }
  if (conversationId) {
    payload.conversation_id = conversationId
  }
  const resp = await fetch('/api/ai-chat/message', {
    method: 'POST',
    headers: {
      'Content-Type': 'application/json',
      Authorization: `Bearer ${token}`,
    },
    body: JSON.stringify(payload),
  })

  if (!resp.ok) {
    let msg = 'LLM 请求失败'
    let raw = ''
    try {
      raw = await resp.text()
      const j = JSON.parse(raw)
      msg = j.message || j.error || msg
    } catch {
      /* ignore */
    }
    throw new Error(msg)
  }

  const reader = resp.body.getReader()
  const decoder = new TextDecoder()
  let buffer = ''

  // eslint-disable-next-line no-constant-condition
  while (true) {
    const { done, value } = await reader.read()
    if (done) break
    buffer += decoder.decode(value, { stream: true })

    let idx
    while ((idx = buffer.indexOf('\n\n')) !== -1) {
      const raw = buffer.slice(0, idx).trim()
      buffer = buffer.slice(idx + 2)
      if (!raw.startsWith('data:')) continue
      const payload = raw.slice(5).trim()
      if (!payload) continue
      let obj
      try {
        obj = JSON.parse(payload)
      } catch {
        continue
      }
      if (obj.type === 'text') {
        onChunk?.(obj.content)
      } else if (obj.type === 'meta') {
        onMeta?.(obj)
      } else if (obj.type === 'error') {
        throw new Error(obj.message || 'LLM 请求失败')
      } else if (obj.type === 'done') {
        onDone?.()
        return
      }
    }
  }
}