Running a RAG Chatbot with Ollama on Fly.io

Retrieval-Augmented Generation (RAG) is a cutting-edge framework in natural language processing that enhances chatbots by combining retrieval-based and generation-based methods for more accurate and contextually relevant responses. The blog post provides a detailed guide on building a RAG chatbot using Mistral AI's 7B model on Ollama as the language model and Upstash Vector as the retriever, both deployed on Fly.io. The process involves creating a serverless vector database with Upstash Vector, deploying the LLM on Fly.io using Ollama, and developing a Next.js application for the chatbot's user interface. The chatbot API is implemented using LangChain and Vercel AI SDK to handle message streaming and responses. The guide culminates in deploying the chatbot on Fly.io, demonstrating a basic, proof-of-concept application that can be expanded with improved resources and UI.

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