paulbjerk/Airqiv

The Airqiv Document Explorer and AI-Assistant is a Retrieval Augmented Generation (RAG) process for Apple M-series Mac computers. It uses Ollama and ChromaDB, and is written in Python.

23
/ 100
Experimental

No commits in the last 6 months.

Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 2 / 25
Maturity 9 / 25
Community 12 / 25

How are scores calculated?

Stars

2

Forks

1

Language

Python

License

BSD-3-Clause

Category

academic-research-rag

Last pushed

Jan 21, 2025

Commits (30d)

0

GitHub
Academic Research RAG · 192 tools

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/rag/paulbjerk/Airqiv"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.

Higher-rated alternatives

LearningCircuit/local-deep-research

Local Deep Research achieves ~95% on SimpleQA benchmark (tested with GPT-4.1-mini). Supports...

89

NVIDIA-AI-Blueprints/rag

This NVIDIA RAG blueprint serves as a reference solution for a foundational Retrieval Augmented...

74

Denis2054/RAG-Driven-Generative-AI

This repository provides programs to build Retrieval Augmented Generation (RAG) code for...

53

0verL1nk/PaperSage

📚 AI-powered research reading workbench. Project-based paper Q&A with Hybrid RAG, multi-agent...

52

RapidFireAI/rapidfireai

RapidFire AI: Rapid AI Customization from RAG to Fine-Tuning

51

Explore RAG Tools

All categories Trending RAG directory Insights