/plushcap/analysis/zilliz/zilliz-local-agentic-rag-with-langraph-and-llama3

Local Agentic RAG with LangGraph and Llama 3

What's this blog post about?

LLMs can be empowered with important new capabilities through agents that use planning, memory, and tools to accomplish tasks. This post demonstrates how to build agents capable of tool-calling using LangGraph with Llama 3 and Milvus. Agents can perform actions such as web searching, browsing emails, correcting RAGs, and more. The process involves setting up LangGraph, Ollama & Llama 3, and Milvus Lite. Using these tools, a custom local Llama 3 powered RAG agent is built with different approaches like routing, fallback, and self-correction. Examples of agents include the Hallucination Grader and the Answer Grader. The post concludes by compiling the LangGraph graph and testing it.

Company
Zilliz

Date published
June 14, 2024

Author(s)
Stephen Batifol

Word count
1304

Hacker News points
None found.

Language
English


By Matt Makai. 2021-2024.