
react-native-vercel-ai
🤖 ⚛️ Run Vercel AI package on React Native and Expo universal native apps (Mobile and web)
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Run Vercel AI package on React Native, Expo, Web and Universal apps. Currently React Native fetch API does not support streaming which is used as a default on Vercel AI. This package enables you to use AI library on React Native but the best usage is when used on Expo universal native apps. On mobile you get back responses without streaming with the same API of `useChat` and `useCompletion` and on web it will fallback to `ai/react`
README:
Run Vercel AI package on React Native, Expo, Web and Universal apps.
Currently React Native fetch API does not support streaming which is used as a default on Vercel AI. This package enables you to use AI library on React Native but the best usage is when used on Expo universal native apps.
On mobile you get back responses without streaming with the same API of useChat
and useCompletion
and on web it will fallback to ai/react
▶️ Play around using the example app which includes a functioning app that comes with anext-app
app inside of it with a/chat
route endpoint for you test the package right away.
npm install react-native-vercel-ai
Add this line to your metro.config.js
file in order to enable Package exports. This way we will be able to use ai/react
subfolder.
config.resolver.unstable_enablePackageExports = true;
On your React Native app import useChat
or useCompletion
from react-native-vercel-ai
. Same API as Vercel AI library.
import { useChat } from 'react-native-vercel-ai';
const { messages, input, handleInputChange, handleSubmit, data, isLoading } =
useChat({
api: 'http://localhost:3001/api/chat',
});
<View>
{messages.length > 0
? messages.map((m) => (
<Text key={m.id}>
{m.role === 'user' ? '🧔 User: ' : '🤖 AI: '}
{m.content}
</Text>
))
: null}
{isLoading && Platform.OS !== 'web' && (
<View>
<Text>Loading...</Text>
</View>
)}
<View>
<TextInput
value={input}
placeholder="Say something..."
onChangeText={(e) => {
handleInputChange(Platform.OS === 'web' ? { target: { value: e } } : e);
}}
/>
<Button onPress={handleSubmit} title="Send" />
</View>
</View>;
This example is using a Next.js API but you could use another type of API setup
Setup your responses depending of weather the request is coming from native mobile or the web.
For web:
- Follow normal AI library flows for web
For React Native:
- skip the
OpenAIStream
part of the web flow. We don't want the stream. - Set your provider stream option to be
false
. - return a response that has the latest message.
// /api/chat
// ./app/api/chat/route.ts
import OpenAI from 'openai';
import { OpenAIStream, StreamingTextResponse } from 'ai';
import { NextResponse, userAgent } from 'next/server';
// Create an OpenAI API client (that's edge friendly!)
const openai = new OpenAI({
apiKey: process.env.OPENAI_API_KEY || '',
});
// IMPORTANT! Set the runtime to edge
export const runtime = 'edge';
export async function POST(req: Request, res: Response) {
// Extract the `prompt` from the body of the request
const { messages } = await req.json();
const userAgentData = userAgent(req);
const isNativeMobile = userAgentData.ua?.includes('Expo');
if (!isNativeMobile) {
// Ask OpenAI for a streaming chat completion given the prompt
const response = await openai.chat.completions.create({
model: 'gpt-3.5-turbo',
stream: true,
messages,
});
// Convert the response into a friendly text-stream
const stream = OpenAIStream(response);
// Respond with the stream
return new StreamingTextResponse(stream);
} else {
// Ask OpenAI for a streaming chat completion given the prompt
const response = await openai.chat.completions.create({
model: 'gpt-3.5-turbo',
// Set your provider stream option to be `false` for native
stream: false,
messages: messages,
});
return NextResponse.json({ data: response.choices[0].message });
}
}
See the contributing guide to learn how to contribute to the repository and the development workflow.
Follow Rodrigo Figueroa, creator of react-native-vercel-ai
on Twitter: @bidah
MIT
Made with create-react-native-library
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