Building a RAG-Powered Document Assistant from Scratch

📰 Medium · NLP

Learn to build a RAG-powered document assistant from scratch using FastAPI, Qdrant, Llama-3, and Next.js

advanced Published 6 Jul 2026

Action Steps

Build a RAG pipeline using Llama-3 and Qdrant
Configure FastAPI to handle API requests
Integrate Next.js for a user-friendly interface
Test the document assistant with sample documents
Deploy the application to a cloud platform

Who Needs to Know This

NLP engineers and developers can benefit from this tutorial to build a document assistant, while product managers can use this to improve their product's search functionality.

Key Insight

💡 RAG (Retrieval-Augmented Generation) can be used to build powerful document assistants

Key Takeaways

Learn to build a RAG-powered document assistant from scratch using FastAPI, Qdrant, Llama-3, and Next.js

Full Article

My end-to-end journey building a RAG document assistant using FastAPI, Qdrant, Llama-3, and Next.js Continue reading on Medium »

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