.

apps/blogai/app/[locale]/morphic/action.tsx

@@ -11,6 +11,25 @@ import { Section } from '@/components/mpv2/section'
 import { FollowupPanel } from '@/components/mpv2/followup-panel'
 import { inquire, researcher, taskManager, querySuggestor } from '@/lib/agents'
 
+// ✅ 初始状态
+const initialAIState: ExperimentalMessage[] = []
+
+const initialUIState: {
+  id: number
+  isGenerating: StreamableValue<boolean>
+  component: React.ReactNode
+}[] = []
+
+// ✅ 先创建 AI
+export const AI = createAI({
+  actions: {
+    submit
+  },
+  initialUIState,
+  initialAIState
+})
+
+// ✅ 再定义 submit，才能引用 AI
 async function submit(formData?: FormData, skip?: boolean) {
   'use server'
 
@@ -19,7 +38,6 @@ async function submit(formData?: FormData, skip?: boolean) {
   const isGenerating = createStreamableValue(true)
 
   const messages: ExperimentalMessage[] = aiState.get() as any
-  // Get the user input from the form data
   const userInput = skip
     ? `{"action": "skip"}`
     : (formData?.get('input') as string)
@@ -28,7 +46,7 @@ async function submit(formData?: FormData, skip?: boolean) {
     : formData
       ? JSON.stringify(Object.fromEntries(formData))
       : null
-  // Add the user message to the state
+
   if (content) {
     const message = { role: 'user', content }
     messages.push(message as ExperimentalMessage)
@@ -39,11 +57,9 @@ async function submit(formData?: FormData, skip?: boolean) {
     uiStream.update(<Spinner />)
 
     let action: any = { object: { next: 'proceed' } }
-    // If the user skips the task, we proceed to the search
     if (!skip) action = await taskManager(messages)
 
     if (action.object.next === 'inquire') {
-      // Generate inquiry
       const inquiry = await inquire(uiStream, messages)
 
       uiStream.done()
@@ -55,12 +71,10 @@ async function submit(formData?: FormData, skip?: boolean) {
       return
     }
 
-    //  Generate the answer
     let answer = ''
     let errorOccurred = false
     const streamText = createStreamableValue<string>()
     while (answer.length === 0) {
-      // Search the web and generate the answer
       const { fullResponse, hasError } = await researcher(
         uiStream,
         streamText,
@@ -72,10 +86,7 @@ async function submit(formData?: FormData, skip?: boolean) {
     streamText.done()
 
     if (!errorOccurred) {
-      // Generate related queries
       await querySuggestor(uiStream, messages)
-
-      // Add follow-up panel
       uiStream.append(
         <Section title="Follow-up">
           <FollowupPanel />
@@ -96,47 +107,3 @@ async function submit(formData?: FormData, skip?: boolean) {
     component: uiStream.value
   }
 }
-
-// Define the initial state of the AI. It can be any JSON object.
-const initialAIState: {
-  role: 'user' | 'assistant' | 'system' | 'function' | 'tool'
-  content: string
-  id?: string
-  name?: string
-}[] = []
-
-// The initial UI state that the client will keep track of, which contains the message IDs and their UI nodes.
-const initialUIState: {
-  id: number
-  isGenerating: StreamableValue<boolean>
-  component: React.ReactNode
-}[] = []
-
-// AI is a provider you wrap your application with so you can access AI and UI state in your components.
-// export const AI = createAI({
-//   actions: {
-//     submit
-//   },
-//   // Each state can be any shape of object, but for chat applications
-//   // it makes sense to have an array of messages. Or you may prefer something like { id: number, messages: Message[] }
-//   initialUIState,
-//   initialAIState
-// })
-
-// ✅ 第一步：先创建 AI
-const AI = createAI({
-  actions: { submit },
-  initialUIState,
-  initialAIState
-})
-
-// ✅ 第二步：解构出 Provider 和 hooks
-export const {
-  AIProvider,
-  useUIState,
-  useAIState,
-  useActions
-} = AI
-
-// ✅ 第三步：导出 AI 给 getMutableAIState 用
-export { AI }