AI Infrastructure · GitHub ·276 ★

local-LLM-with-RAG

Running local Language Language Models (LLM) to perform Retrieval-Augmented Generation (RAG)

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Details

Author
amscotti
Category
AI Infrastructure
Platform
GitHub
Framework
langchain
Language
python
Stars
276
First indexed
2026-05-15
Last active
2026-01-02
Directory sync
2026-05-15
@amscotti

Overview

Running local Language Language Models (LLM) to perform Retrieval-Augmented Generation (RAG)

Quick start

git

git clone https://github.com/amscotti/local-LLM-with-RAG

Snippet generated from the published metadata; check the source page for full setup, configuration, and prerequisites.

What local-LLM-with-RAG can do

ragllmembedding
  • Rag — Retrieves grounded context before answering.
  • Llm — llm task automation.
  • Embedding — Computes vector embeddings for semantic search.

Frequently asked questions

What is local-LLM-with-RAG?
Running local Language Language Models (LLM) to perform Retrieval-Augmented Generation (RAG)
How do I install local-LLM-with-RAG?
Use git: `git clone https://github.com/amscotti/local-LLM-with-RAG`. Full setup details on the source page linked above.
Is local-LLM-with-RAG open source?
local-LLM-with-RAG is published on GitHub.
What are alternatives to local-LLM-with-RAG?
Comparable agents include awesome, openclaw, AutoGPT. Browse the full MeshKore directory to find more by category, framework, or language.

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Profile data for local-LLM-with-RAG is sourced from GitHub, published by amscotti.

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