How to Build a High-Performance RAG Pipeline with Ollama, Python and TypeScript

Building high-performance RAG pipelines using Ollama, Python, and TypeScript allows for local, privacy-first AI agents that query internal documents without third-party APIs. This architecture bypasses network overhead and API costs. Additionally, Dify and Ollama enable the creation of custom AI apps, chatbots, and agents on private hardware. Requirements include a GPU with 12GB+ VRAM and Docker. Using models like Qwen3 14B ensures strong general chat capabilities while keeping sensitive data securely within the local network.