Reliable, fully local RAG agents with LLaMA3.2-3b
LLaMA3.2 has released a new set of compact models designed for on-device use cases, such as locally running assistants. Here, we show how LangGraph can enable these types of local assistant by building a multi-step RAG agent – this combines ideas from 3 advanced RAG papers (Adaptive RAG, Corrective RAG, and Self-RAG) into a single control flow using LangGraph. But we show LangGraph makes it possible to run a complex agent locally.
Code:
Llama3.2:
