refactor: adapt to vercel/ai v3

.github/workflows/build.yml

@@ -2,38 +2,23 @@ name: Build
 
 on:
   push:
-    branches: [ main ]
+    branches: [main]
   pull_request:
-    branches: [ main ]
+    branches: [main]
 
 jobs:
   build:
     name: Build
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v4
-      - uses: pnpm/action-setup@v2
-        name: Install pnpm
-        id: pnpm-install
-      - name: Use Node.js LTS
+      - name: Install pnpm
+        uses: pnpm/action-setup@v4
+      - name: Use Node.js
         uses: actions/setup-node@v3
         with:
-          node-version-file: '.nvmrc'
-          cache: 'pnpm'
-      - name: Get pnpm store directory
-        id: pnpm-cache
-        shell: bash
-        run: |
-          echo "STORE_PATH=$(pnpm store path)" >> $GITHUB_OUTPUT
-
-      - uses: actions/cache@v3
-        name: Setup pnpm cache
-        with:
-          path: ${{ steps.pnpm-cache.outputs.STORE_PATH }}
-          key: ${{ runner.os }}-pnpm-store-${{ hashFiles('**/pnpm-lock.yaml') }}
-          restore-keys: |
-            ${{ runner.os }}-pnpm-store-
-
+          node-version-file: ".nvmrc"
+          cache: "pnpm"
       - name: Install dependencies
         run: pnpm install
       - name: Build

.github/workflows/lint.yml

@@ -0,0 +1,23 @@
+name: Lint
+
+on:
+  push:
+  pull_request:
+
+jobs:
+  lint:
+    name: Lint
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - name: Install pnpm
+        uses: pnpm/action-setup@v4
+      - name: Use Node.js
+        uses: actions/setup-node@v3
+        with:
+          node-version-file: ".nvmrc"
+          cache: "pnpm"
+      - name: Install dependencies
+        run: pnpm install
+      - name: Lint
+        run: pnpm run lint

.nvmrc

@@ -1 +1 @@
-18
+20

README.md

@@ -17,55 +17,50 @@ yarn add ai jotai-ai
 `chatAtoms` is a collection of atoms for a chatbot like [`useChat`](https://sdk.vercel.ai/docs/api-reference/use-chat).
 
 ```js
-import { useAtomValue, useAtom, useSetAtom } from 'jotai'
-import { chatAtoms } from 'jotai-ai'
-
-const {
-  messagesAtom,
-  inputAtom,
-  submitAtom,
-  isLoadingAtom,
-} = chatAtoms()
-
-function Messages () {
-  const messages = useAtomValue(messagesAtom)
+import { useAtomValue, useAtom, useSetAtom } from "jotai";
+import { chatAtoms } from "jotai-ai";
+
+const { messagesAtom, inputAtom, submitAtom, isLoadingAtom } = chatAtoms();
+
+function Messages() {
+  const messages = useAtomValue(messagesAtom);
   return (
     <>
       {messages.length > 0
-        ? messages.map(m => (
-          <div key={m.id} className='whitespace-pre-wrap'>
-            {m.role === 'user' ? 'User: ' : 'AI: '}
-            {m.content}
-          </div>
-        ))
+        ? messages.map((m) => (
+            <div key={m.id} className="whitespace-pre-wrap">
+              {m.role === "user" ? "User: " : "AI: "}
+              {m.content}
+            </div>
+          ))
         : null}
     </>
-  )
+  );
 }
 
-function ChatInput () {
-  const [input, handleInputChange] = useAtom(inputAtom)
-  const handleSubmit = useSetAtom(submitAtom)
+function ChatInput() {
+  const [input, handleInputChange] = useAtom(inputAtom);
+  const handleSubmit = useSetAtom(submitAtom);
   return (
     <form onSubmit={handleSubmit}>
       <input
         value={input}
-        placeholder='Say something...'
+        placeholder="Say something..."
         onChange={handleInputChange}
       />
     </form>
-  )
+  );
 }
 
-function App () {
-  const isLoading = useAtomValue(isLoadingAtom)
+function App() {
+  const isLoading = useAtomValue(isLoadingAtom);
   return (
     <main>
-      <Messages/>
-      <ChatInput/>
+      <Messages />
+      <ChatInput />
       {isLoading ? <div>Loading...</div> : null}
     </main>
-  )
+  );
 }
 ```
 
@@ -89,53 +84,50 @@ offers an atomic global state management system that is both powerful and flexib
 For example, you can customize the `messagesAtom` to add more functionality, such as `clearMessagesAtom`:
 
 ```js
-const { messagesAtom } = chatAtoms()
+const { messagesAtom } = chatAtoms();
 
-const clearMessagesAtom = atom(
-  null,
-  async (get, set) => set(messagesAtom, [])
-)
+const clearMessagesAtom = atom(null, async (get, set) => set(messagesAtom, []));
 
 const Actions = () => {
-  const clear = useSetAtom(clearMessagesAtom)
-  return (
-    <button onClick={clear}>Clear Messages</button>
-  )
-}
+  const clear = useSetAtom(clearMessagesAtom);
+  return <button onClick={clear}>Clear Messages</button>;
+};
 ```
 
 Also, `chatAtoms` is created out of the Component lifecycle,
 so you can share the state between different components easily.
 
 ```js
-const { messagesAtom } = chatAtoms()
+const { messagesAtom } = chatAtoms();
 
 const Messages = () => {
-  const messages = useAtomValue(messagesAtom)
+  const messages = useAtomValue(messagesAtom);
   return (
     <div>
-      {messages.map(m => (
-        <div key={m.id} className='whitespace-pre-wrap'>
-          {m.role === 'user' ? 'User: ' : 'AI: '}
+      {messages.map((m) => (
+        <div key={m.id} className="whitespace-pre-wrap">
+          {m.role === "user" ? "User: " : "AI: "}
           {m.content}
         </div>
       ))}
     </div>
-  )
-}
+  );
+};
 
 const UserMessages = () => {
-  const messages = useAtomValue(messagesAtom)
+  const messages = useAtomValue(messagesAtom);
   return (
     <div>
-      {messages.filter(m => m.role === 'user').map(m => (
-        <div key={m.id} className='whitespace-pre-wrap'>
-          User: {m.content}
-        </div>
-      ))}
+      {messages
+        .filter((m) => m.role === "user")
+        .map((m) => (
+          <div key={m.id} className="whitespace-pre-wrap">
+            User: {m.content}
+          </div>
+        ))}
     </div>
-  )
-}
+  );
+};
 ```
 
 #### Load messages on demand with React Suspense
@@ -144,80 +136,74 @@ const UserMessages = () => {
 by `useChat`.
 
 ```js
-const {
-  messagesAtom,
-  inputAtom,
-  submitAtom
-} = chatAtoms({
+const { messagesAtom, inputAtom, submitAtom } = chatAtoms({
   initialMessages: async () => {
     // fetch messages from anywhere
-    const messages = await fetchMessages()
-    return messages
-  }
-})
+    const messages = await fetchMessages();
+    return messages;
+  },
+});
 ```
 
 With the combination with [`jotai-effect`](https://github.com/jotaijs/jotai-effect),
 you can create a chatbot with local storage support.
 
 ```js
-const {
-  messagesAtom
-} = chatAtoms({
+const { messagesAtom } = chatAtoms({
   initialMessages: async () => {
     /**
      * call `noSSR` function if you are using next.js.
      * @link https://foxact.skk.moe/no-ssr
      */
-      // noSSR()
-    const idb = await import('idb-keyval')
-    return (await idb.get('messages')) ?? []
-  }
-})
+    // noSSR()
+    const idb = await import("idb-keyval");
+    return (await idb.get("messages")) ?? [];
+  },
+});
 
-import { atomEffect } from 'jotai-effect'
+import { atomEffect } from "jotai-effect";
 
 const saveMessagesEffectAtom = atomEffect((get, set) => {
-  const messages = get(messagesAtom)
-  const idbPromise = import('idb-keyval')
-  const abortController = new AbortController()
-  idbPromise.then(async idb => {
+  const messages = get(messagesAtom);
+  const idbPromise = import("idb-keyval");
+  const abortController = new AbortController();
+  idbPromise.then(async (idb) => {
     if (abortController.signal.aborted) {
-      return
+      return;
     }
-    await idb.set('messages', await messages)
-  })
+    await idb.set("messages", await messages);
+  });
   return () => {
-    abortController.abort()
-  }
-})
+    abortController.abort();
+  };
+});
 
 const Messages = () => {
-  const messages = useAtomValue(messagesAtom)
+  const messages = useAtomValue(messagesAtom);
   return (
     <>
       {messages.length > 0
-        ? messages.map(m => (
-          <div key={m.id} className="whitespace-pre-wrap">
-            {m.role === 'user' ? 'User: ' : 'AI: '}
-            {m.content}
-          </div>
-        ))
+        ? messages.map((m) => (
+            <div key={m.id} className="whitespace-pre-wrap">
+              {m.role === "user" ? "User: " : "AI: "}
+              {m.content}
+            </div>
+          ))
         : null}
     </>
-  )
-}
+  );
+};
 
 const App = () => {
-  useAtomValue(saveMessagesEffectAtom)
+  useAtomValue(saveMessagesEffectAtom);
   return (
     <main>
       <Suspense fallback="loading messages...">
-        <Messages/>
+        <Messages />
       </Suspense>
     </main>
-  )
-}
+  );
+};
 ```
 
 ## LICENSE

examples/llamaindex-straming/app/api/chat/llamaindex-stream.ts

@@ -4,7 +4,7 @@ import {
   trimStartOfStreamHelper,
   type AIStreamCallbacksAndOptions,
 } from "ai";
-import type { Response } from 'llamaindex'
+import type { Response } from "llamaindex";
 
 function createParser(res: AsyncIterable<Response>) {
   const trimStartOfStream = trimStartOfStreamHelper();

examples/llamaindex-straming/app/api/chat/route.ts

@@ -3,7 +3,7 @@ import { OpenAI } from "llamaindex";
 import { NextRequest, NextResponse } from "next/server";
 import { createChatEngine } from "./engine";
 import { LlamaIndexStream } from "./llamaindex-stream";
-import type { MessageType } from 'llamaindex/llm/types'
+import type { MessageType } from "llamaindex/llm/types";
 
 export const runtime = "nodejs";
 export const dynamic = "force-dynamic";
@@ -30,13 +30,13 @@ export async function POST(request: NextRequest) {
     const chatEngine = await createChatEngine(llm);
 
     const response = await chatEngine.chat({
-      message : lastMessage.content,
-      chatHistory : messages.map((message) => ({
+      message: lastMessage.content,
+      chatHistory: messages.map((message) => ({
         content: message.content,
         role: message.role as MessageType,
       })),
-      stream: true
-    })
+      stream: true,
+    });
 
     // Transform the response into a readable stream
     const stream = LlamaIndexStream(response);