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An overview of the TurboStarter AI starter kit.
TurboStarter AI is a starter kit with ready-to-use demo apps that helps you quickly build powerful AI applications without starting from scratch. Whether you're launching a small side project or a full-scale enterprise solution, it provides the structure you need to jump right into building your own unique AI application.
Features
TurboStarter AI comes packed with features designed to accelerate your development process:
Core framework
Monorepo setup
Powered by Turborepo for efficient code sharing and dependency management across web and mobile applications.
Next.js web app
Leverages Next.js for server-side rendering, static site generation, and API routes.
Hono API
Ultra-fast API framework optimized for edge computing with comprehensive TypeScript support.
React Native + Expo
Foundation for cross-platform mobile apps that share business logic with your web application.
AI
Vercel AI SDK
Complete toolkit for implementing advanced AI features like streaming responses and interactive chat interfaces.
LangChain
Powerful framework for building sophisticated AI applications with prompt management, memory systems, and agent capabilities.
Multiple AI providers
Seamless integration with OpenAI, Anthropic, Google AI, xAI, Meta, Deepseek, Replicate, Eleven Labs, and more through a unified interface.
Specialized models
Full support for text generation, structured output, image creation, voice synthesis, and embedding models.
One-line model switching
Effortlessly switch between AI models or providers with minimal code changes.
Data storage
Drizzle ORM
Type-safe ORM for efficient interaction with PostgreSQL (default) or other supported databases (MySQL, SQLite).
PostgreSQL database
Reliable storage for chat history, user data, and vector embeddings with optimized performance.
Vector embeddings
Built-in support for storing and retrieving vector embeddings for advanced retrieval-augmented generation.
Blob storage
Integrated S3-compatible storage for managing user uploads, AI-generated content, and documents.
Authentication
Better Auth integration
Secure authentication system starting with anonymous sessions, extensible to email/password, magic links, and OAuth providers.
Rate limiting
Intelligent protection for API endpoints against abuse and overuse.
Credits-based access
Flexible system to manage and control AI feature usage with customizable credit allocation.
Backend API key management
Security-first approach ensuring sensitive API keys remain protected on the server side.
User interface
Tailwind CSS & shadcn/ui
Utility-first CSS framework and pre-designed components for rapid UI development.
Radix UI
Accessible, unstyled components that provide the foundation for beautiful, functional interfaces.
Shared UI package
Centralized UI component library ensuring consistency across all applications in the monorepo.
Demo apps
TurboStarter AI includes several production-ready demo applications that showcase diverse AI capabilities. Use these examples to understand implementation patterns and jumpstart your own projects.
Chatbot
Build intelligent conversational experiences with an AI chatbot featuring contextual reasoning and real-time web search capabilities.
Image generation
Create compelling visuals with a versatile AI image generator supporting multiple models, styles, and output resolutions.
Chat with PDF
Extract valuable insights from documents by having natural conversations with your PDFs using context-aware AI.
Text to speech
Convert written content into lifelike speech with support for over 5,000+ voices across multiple languages and styles.
Agents
Develop autonomous AI agents capable of executing complex tasks by orchestrating multiple AI models and tools.
Scope of this documentation
This documentation focuses specifically on the AI features, architecture, and demo applications included in the TurboStarter AI kit. While we provide comprehensive coverage of AI integrations, for information about core framework elements (authentication, billing, etc.), please refer to the Core documentation.
Our goal is to guide you through setting up, customizing, and deploying the AI starter kit efficiently. Where relevant, we include links to official documentation for the integrated AI providers and libraries.
Setup
Getting started with TurboStarter AI requires configuring the core applications first. For detailed setup instructions, refer to:
Web app setup
Follow our step-by-step guide in the Core web documentation to set up your web application.
Mobile app setup
Use our detailed guide in the Core mobile documentation to configure your mobile application.
After establishing the core applications, you can configure specific AI providers and demo applications using the dedicated sections in this documentation (see sidebar). For a quick start, you might also want to check our TurboStarter CLI guide to bootstrap your project in seconds.
When working with the AI starter kit, remember to use the ai repository instead of core for Git commands. For example, use git clone turbostarter/ai rather than git clone turbostarter/core.
Deployment
Deploying TurboStarter AI follows the same process as deploying the core web application. Ensure you configure all necessary environment variables, including those for your selected AI providers (like OpenAI, Anthropic, etc.), in your deployment environment.
For comprehensive deployment instructions across various platforms, consult our core deployment guides:
Deployment checklist
General checklist before deploying the web app.
Vercel
Streamlined deployment process for Vercel hosting.
Railway
Step-by-step guide for deploying to Railway.
Docker
Container-based deployment using Docker.
Other Providers
Additional guides for Netlify, Render, AWS Amplify, Fly.io and more.
For mobile app store deployment, refer to our mobile publishing guides:
Publishing checklist
Comprehensive pre-publishing verification for mobile applications.
Updates
Best practices for managing updates to published mobile apps.
Each AI demo app may have specific deployment considerations, so check their dedicated documentation sections for additional guidance.
llms.txt
Access the complete TurboStarter documentation in Markdown format at /api/llms.txt. This file contains all documentation in an LLM-friendly format, enabling you to ask questions about TurboStarter using the most current information.
Example usage
To query an LLM about TurboStarter:
- Copy the documentation contents from /api/llms.txt
- Use this prompt format with your preferred LLM:
Documentation:
{paste documentation here}
---
Based on the above documentation, answer the following:
{your question}Let's build amazing AI!
We're excited to help you create innovative AI-powered applications quickly and efficiently. If you have questions, encounter issues, or want to showcase your creations, connect with our community:
Happy building! 🚀
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