# AllAboutAI-YT/easy-local-rag

SuperEasy 100% Local RAG with Ollama + Email RAG

Repository: https://github.com/AllAboutAI-YT/easy-local-rag
Canonical: https://ross.abutalabs.com/products/easy-local-rag
Language: Python
License: MIT
License Family: permissive
Last push: 2024-06-04T21:59:14+00:00

## Health v2 (maintenance only)
Score: 15/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 8, longevity 62
- inputs: {"age_days": 870, "days_push": 820, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1220, forks 334 (observed 2026-08-28T04:04:01.902653+00:00)

## What it is
A Python application providing 100% local retrieval-augmented generation (RAG) using Ollama for LLM inference and embeddings. It supports ingesting PDFs, text, and JSON files, plus a Gmail-based email RAG mode, with query rewriting and conversation history.

## Use cases
- chat with my pdf documents locally
- run RAG without sending data to the cloud
- ask questions about my gmail emails with a local LLM
- set up a simple local RAG pipeline with Ollama
- query my text and JSON files with llama3
- improve retrieval on vague questions with query rewriting

## When to choose
- you want a fully local, privacy-preserving RAG setup with Ollama
- you want a simple, tutorial-backed starter project for document or email Q&A
- you prefer running llama3/mistral and embeddings on your own machine

## When to avoid
- you need a production-grade, scalable RAG service with a web UI
- you require multi-user or cloud deployment features
- you want a maintained library with an API rather than scripts

## Facets
- artifact type: application
- maturity: active
- function: rag, llm-inference, chatbot, search-engine
- domain: large-language-models, artificial-intelligence, email
- platform: python, cli, self-hosted
- tags: ollama, local-llm, email-rag, embeddings, tutorial-project, retrieval-augmented-generation

## Member repositories
- AllAboutAI-YT/easy-local-rag (main) score 15

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:01.902653+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:15:54.566097+00:00, confidence not recorded.
  - readme: https://github.com/AllAboutAI-YT/easy-local-rag (fetched 2026-08-28T04:04:01.902653+00:00, sha 65deca744959)
- Data as of 2026-08-30T08:39:29.467469+00:00.