atypica.AI 如何在不破坏千万级聊天记录的前提下迁移到 AI SDK v5

// v4 Message{  id: "msg1",  role: "assistant",  content: "The weather is sunny",  // 字符串表示  parts: [                           // 结构化数据（可选）    { type: "text", text: "The weather is " },    { type: "tool-invocation", toolInvocation: { ... } },    { type: "text", text: "sunny" }  ]}

// v5 UIMessage{  id: "msg1",  role: "assistant",  parts: [                           // 唯一的数据源    { type: "text", text: "The weather is " },    { type: "tool-getWeather", toolCallId: "...", state: "output-available", output: {...} },    { type: "text", text: "sunny" }  ],  content: "The weather is sunny"   // 自动生成，只读}

// v4 模式 - 直接访问 contentconst lastMessage = messages[messages.length - 1];if (lastMessage.content.includes("weather")) {  // ...}
// 生成标题const title = message.content.substring(0, 50);
// 日志记录logger.info({ userMessage: message.content });

// messageUtils.tsexport function getTextFromParts(parts: UIMessage["parts"]): string {  return parts    .filter((part) => part.type === "text")    .map((part) => part.text)    .join("");}
// 使用方式const text = getTextFromParts(message.parts);if (text.includes("weather")) {  // ...}

{  type: "tool-invocation",  toolInvocation: {    state: "result",    toolCallId: "call_123",    toolName: "searchPersonas",    args: { query: "coffee lovers" },    result: { personas: [...] }  }}

{  type: "tool-searchPersonas",      // 类型化为 tool-${toolName}  toolCallId: "call_123",  state: "output-available",        // 状态重命名  input: { query: "coffee lovers" }, // args → input  output: { personas: [...] }        // result → output}

// v4{ type: "reasoning", reasoning: "Let me think..." }
// v5{ type: "reasoning", text: "Let me think..." }

export type V4ToolInvocation =  | { state: "call"; toolCallId: string; toolName: string; args: any }  | { state: "result"; toolCallId: string; toolName: string; args: any; result: any };
export type V4MessagePart =  | { type: "text"; text: string }  | { type: "reasoning"; reasoning: string } // v4 格式  | { type: "tool-invocation"; toolInvocation: V4ToolInvocation };
export type V5MessagePart = UIMessage["parts"][number];
export function convertToV5MessagePart(part: V4MessagePart | V5MessagePart): V5MessagePart {  // text parts 在 v4 和 v5 中相同  if (part.type === "text") {    return part;  }
  // Reasoning：reasoning 字段 → text 字段  if (part.type === "reasoning") {    if ("reasoning" in part) {      return { type: "reasoning", text: part.reasoning };    }    return part; // 已经是 v5 格式  }
  // Tool invocation：嵌套 → 扁平，args/result → input/output  if (part.type === "tool-invocation" && "toolInvocation" in part) {    const inv = part.toolInvocation;    return {      type: `tool-${inv.toolName}`,      toolCallId: inv.toolCallId,      state: inv.state === "result" ? "output-available" : "input-available",      input: inv.args,      output: inv.state === "result" ? inv.result : undefined,    } as V5MessagePart;  }
  // 已经是 v5 格式  return part as V5MessagePart;}

// messageUtils.tsexport async function convertDBMessagesToAIMessages(userChatId: string): Promise<UIMessage[]> {  const dbMessages = await prisma.chatMessage.findMany({    where: { userChatId },    orderBy: { createdAt: "asc" },  });
  return dbMessages.map((msg) => ({    id: msg.messageId,    role: msg.role as "user" | "assistant",    parts: (msg.parts as V4MessagePart[]).map(convertToV5MessagePart),  }));}

// src/ai/tools/types.ts - Study 系统export type StudyUITools = {  reasoningThinking: {    input: z.infer<typeof reasoningThinkingInputSchema>;    output: z.infer<typeof reasoningThinkingOutputSchema>;  };  searchPersonas: {    input: z.infer<typeof searchPersonasInputSchema>;    output: z.infer<typeof searchPersonasOutputSchema>;  };  // ... 20+ 其他工具};
export type TStudyMessageWithTool = UIMessage<unknown, UIDataTypes, StudyUITools>;
// src/app/(interviewProject)/tools/types.ts - Interview 系统export type TInterviewUITools = {  endInterview: {    input: z.infer<typeof endInterviewInputSchema>;    output: z.infer<typeof endInterviewOutputSchema>;  };  requestInteractionForm: {    input: z.infer<typeof requestInteractionFormInputSchema>;    output: z.infer<typeof requestInteractionFormOutputSchema>;  };};
export type TInterviewMessageWithTool = UIMessage<unknown, UIDataTypes, TInterviewUITools>;

// v4 组件export function ChatMessage({ message }: { message: Message }) {  return <div>{message.content}</div>;}

// v5 组件export function ChatMessage({ message }: { message: UIMessage }) {  return (    <div>      {message.parts.map((part, i) => {        if (part.type === "text") {          return <Markdown key={i}>{part.text}</Markdown>;        } else if (part.type === "reasoning") {          return <ReasoningBlock key={i}>{part.text}</ReasoningBlock>;        } else if (part.type.startsWith("tool-")) {          return <ToolDisplay key={i} toolPart={part} />;        }      })}    </div>  );}

// v4if (part.type === "tool-invocation") {  const toolName = part.toolInvocation.toolName;  const result = part.toolInvocation.result;}
// v5if (part.type.startsWith("tool-") && "toolCallId" in part) {  const toolName = part.type.replace("tool-", "");  const output = part.state === "output-available" ? part.output : undefined;}

{  role: "user",  parts: [{ type: "text", text: "Hello" }]}

{  role: "user",  content: [{ type: "text", text: "Hello" }]  // 注意：content，不是 parts}

import { UserModelMessage } from "ai";
const result = await streamText({  model: llm("gpt-4"),  messages: [    {      role: "user",      content: [{ type: "text", text: prompt }]  // 模型用 content    }  ] as UserModelMessage[],  tools: { ... }});

// v4const { append, reload, initialMessages } = useChat({  id: chatId,  experimental_prepareRequestBody({ messages, requestBody }) {    return { message: messages[messages.length - 1], ...requestBody };  },});
// v5const { sendMessage, regenerate, messages } = useChat({  transport: new DefaultChatTransport({    api: "/api/chat/study",    prepareSendMessagesRequest({ id, messages }) {      return {        body: {          id,          message: messages[messages.length - 1],          userChatToken: token,        },      };    },  }),});

// v4{  experimental_attachments: [{ name: "file.pdf", contentType: "application/pdf", url: "..." }];}
// v5 - 作为 parts 数组的一部分{  parts: [{ type: "file", filename: "file.pdf", mediaType: "application/pdf", data: "..." }];}

// v4 - 两者都检查if (streamingMessage.parts?.length && streamingMessage.content.trim()) {  await persistentAIMessageToDB(userChatId, streamingMessage);}
// v5 - 只检查 partsif (streamingMessage.parts?.length) {  await persistentAIMessageToDB(userChatId, streamingMessage);}

// v4 - 这样可以message.content = "New text";
// v5 - 这不起作用（content 是派生的）message.content = "New text"; // ❌ 静默忽略
// v5 - 正确做法message.parts = [{ type: "text", text: "New text" }]; // ✅

// v4if (message.content) { ... }
// v5 - 这可能产生误导if (message.content) { ... }  // content 是自动生成的，可能为空字符串
// v5 - 正确检查if (message.parts.some(p => p.type === "text" && p.text)) { ... }

// v4 状态"partial-call" | "call" | "result";
// v5 状态"input-available" | "output-available" | "output-error";

// 安全访问step.toolCalls.map((call) => call?.toolName ?? "unknown");

// v4onFinish: async ({ reasoning, text, usage }) => {};
// v5onFinish: async ({ reasoningText, text, usage }) => {};

await persistentAIMessageToDB(userChatId, {  ...newMessage,  id: newMessage.id ?? generateId(),});