Full stack framework for building cross-platform mobile AI apps supporting LLM real-time / streaming text and chat UIs, image services and natural language to images with multiple models, and image processing.
Check out the video tutorial here
- LLM support for OpenAI ChatGPT, Anthropic Claude, Cohere, Cohere Web, Gemini, and Mistral
- An array of image models provided by Fal.ai
- Real-time / streaming responses from all providers
- OpenAI Assistants including code interpreter and retrieval
- Server proxy to easily enable authentication and authorization with auth provider of choice.
- Theming (comes out of the box with 5 themes) - easily add additional themes with just a few lines of code.
- Image processing with ByteScale
Generate a new project by running:
npx rn-ai
Next, either configure your environment variables with the CLI, or do so later.
Change into the app directory and run:
npm start
Change into the server directory and run:
npm run dev
The server environment variables are available in server/.env.example
. If already not present, update this file name to .env.example
to configure server environment variables.
To add a new theme, open app/src/theme.ts
and add a new theme with the following configuration:
const christmas = {
// extend an existing theme or start from scratch
...lightTheme,
name: 'Christmas',
label: 'christmas',
tintColor: '#ff0000',
textColor: '#378b29',
tabBarActiveTintColor: '#378b29',
tabBarInactiveTintColor: '#ff0000',
placeholderTextColor: '#378b29',
}
At the bottom of the file, export the new theme:
export {
lightTheme, darkTheme, hackerNews, miami, vercel, christmas
}
Here is how to add new or remove existing LLM models.
You can add or configure a model by updating MODELS
in constants.ts
.
For removing models, just remove the models you do not want to support.
For adding models, once the model definition is added to the MODELS
array, you should update src/screens/chat.tsx
to support the new model:
- Create local state to hold new model data
- Update
chat()
function to handle new model type - Create
generateModelReponse
function to call new model - Update
getChatType
inutils.ts
to configure the LLM type that will correspond with your server path. - Render new model in UI
{
chatType.label.includes('newModel') && (
<FlatList
data={newModelReponse.messages}
renderItem={renderItem}
scrollEnabled={false}
/>
)
}
Create a new file in the server/src/chat
folder that corresponds to the model type you created in the mobile app. You can probably copy and re-use a lot of the streaming code from the other existing paths to get you started.
Next, update server/src/chat/chatRouter
to use the new route.
Here is how to add new or remove existing Image models.
You can add or configure a model by updating IMAGE_MODELS
in constants.ts
.
For removing models, just remove the models you do not want to support.
For adding models, once the model definition is add to the IMAGE_MODELS
array, you should update src/screens/images.tsx
to support the new model.
Main consideration is input. Does the model take text, image, or both as inputs?
The app is configured to handle both, but you must update the generate
function to pass the values to the API accordingly.
In server/src/images/fal
, update the handler function to take into account the new model.
Create a new file in server/src/images/modelName
, update the handler function to handle the new API call.
Next, update server/src/images/imagesRouter
to use the new route.