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Daily Dose of Data Science | Avi Chawla | Substack

Meta released Llama-3.3, and this post provides a hands-on demo for building a RAG app using it. The app allows users to interact with a document via chat. It uses LlamaIndex for orchestration, Qdrant for a self-hosted vector database, and Ollama for serving Llama-3.3 locally. The implementation steps include loading and parsing a knowledge base, creating embeddings, indexing and storing them, defining a custom prompt template, and setting up a query engine.

Building a RAG app using Llama-3.3