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Kickstart Your Local RAG Setup: A Beginner's Guide to Using Llama 3 with Ollama, Milvus, and Langchain

Blog post from Zilliz

Post Details
Company
Date Published
Author
By Stephen Batifol
Word Count
844
Company Posts That Month
21
Language
English
Hacker News Points
8
Post removed?
No
Summary

This guide provides a beginner's approach to setting up a Retrieval Augmented Generation (RAG) system using Ollama, Llama 3, Milvus, and Langchain. The RAG technique enhances large language models (LLMs) by integrating additional data sources. In this tutorial, we will build a question-answering chatbot that can answer questions about specific information. Key components of the setup include indexing data using Milvus, retrieval and generation with Llama 3, and interaction with data using Langchain. The guide assumes familiarity with Docker and Docker Compose, as well as installation of Milvus Standalone, Ollama, and other necessary tools.

Trends Found in this Post
Trend Post Mentions Total Month Mentions Posts Companies MoM
RAG 18 1,867 232 78 +54%
LLM 14 3,669 412 154 +40%
Vector Search 10 2,722 279 102 +43%
Local AI 1 12 9 7 -45%
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