RAG tutorials

Discover how to build, deploy and run RAG applications in production on Koyeb. The fastest way to deploy applications globally.

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Use FLUX, PyTorch, and Streamlit to Build an AI Image Generation App

Rishi Raj Jain

Use FLUX, PyTorch, and Streamlit to Build an AI Image Generation App

Learn how to use the FLUX model to generate images based on prompts in real-time.

Nov 20, 2024

10 min read

Using LlamaIndex and MongoDB to Build a Job Search Assistant

Rishi Raj Jain

Using LlamaIndex and MongoDB to Build a Job Search Assistant

Learn how to build a job search assistant with LlamaIndex using Retrieval-Augmented Generation (RAG) and MongoDB.

May 14, 2024

21 min read

Use LlamaIndex to Build a Retrieval-Augmented Generation (RAG) Application

Chuks Opia

Use LlamaIndex to Build a Retrieval-Augmented Generation (RAG) Application

Learn how to build a retrieval-augmented generation application to query general AI models with specific contextual information.

Mar 27, 2024

21 min read

Build a Retrieval-Augmented Generation Chatbot using pgvector

Rishi Raj Jain

Build a Retrieval-Augmented Generation Chatbot using pgvector

In this tutorial, we show how to deploy an RAG chatbot built with the OpenAI embedding API, Replicate, pgvector, and the Koyeb Managed PostgreSQL service.

Feb 28, 2024

33 min read

RAG tutorials

Use FLUX, PyTorch, and Streamlit to Build an AI Image Generation App

Using LlamaIndex and MongoDB to Build a Job Search Assistant

Use LlamaIndex to Build a Retrieval-Augmented Generation (RAG) Application

Build a Retrieval-Augmented Generation Chatbot using pgvector

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