Integrating AI capabilities into your Xano backend can significantly enhance your application's functionality.
1. Connecting to External AI APIs
If you've wanted to create a chatbot or use AI Image generation within your projects, we make it as easy as possible to get started. Prakash walks you through how to connect OpenAI to Xano in this guide.
2. Setting Up Vector Databases in Xano
Maybe you've wanted to think bigger and build out AI systems within your application.
Vector embeddings are essential for AI and machine learning models to understand complex data relationships and semantics.
Xano supports vector embeddings through the pgVector extension, allowing you to store and query embeddings within your database. You can find out how to do more here.
3. Building AI-Driven Features
AI's can be fully integrated into your users' workflows and experiences. Read more on what this looks like!
4. Best Practices
Security: Always secure your API keys and sensitive data. Use environment vs security features to protect your application.
Performance Optimization: Index your vector fields and optimize API calls to ensure your application runs efficiently.
Testing: Thoroughly test your AI integrations to ensure they function as expected and handle edge cases gracefully.