ai-research-os 1.5.4

A Self-Evolving Research OS for AI Researchers — manage papers, detect research gaps, generate insights

AI Research OS

A Self-Evolving Research Operating System for AI Researchers

What It Does

AI Research OS is a self-evolving research system that learns from your usage patterns. It's not just a paper manager — it's a research partner that grows smarter over time.

Feed it a paper (arXiv URL, DOI, or PDF). Get back a P-Note, C-Note, Radar entry, and Timeline entry — all structured, tagged, and cross-linked.

Input	Output
arXiv URL/ID	P-Note + C-Note + Radar + Timeline
DOI	P-Note + C-Note + Radar + Timeline
Local PDF	P-Note + C-Note + Radar + Timeline
Scanned PDF	Same (via OCR)

This is not a PDF manager. It is a Self-Evolving System that:

• Learns from your research patterns
• Improves answers over time
• Adapts to your specific domain

Core Features

Feature	Description
airos import	Import papers from arXiv, DOI, PDF
airos chat	RAG-powered Q&A with your papers
airos slides	Auto-generate presentations
airos kg	Knowledge graph visualization
Evolution	Self-improvement via Gene/Capsule patterns

Quick Start

pip install ai-research-os
airos-cli 2601.00155 --tags LLM,Agent

That's it — one paper imported in seconds. The above installs the package and imports an arXiv paper.

One line, three inputs

airos-cli 2601.00155                          # arXiv ID
airos-cli 10.48550/arXiv.2601.00155           # DOI
airos-cli --pdf paper.pdf --tags RAG            # Local PDF
airos-cli --pdf scanned.pdf --ocr --ocr-lang chi_sim+eng   # Scanned PDF

Three core commands

airos-cli import 2601.00155 10.1038/nature12373   # Add papers to DB
airos-cli search "attention mechanism" --tag LLM    # Search papers
airos-cli research "RLHF alignment" --limit 5       # Autonomous research loop

AI draft (optional)

export OPENAI_API_KEY="***"
export OPENAI_BASE_URL="https://dashscope.aliyuncs.com/compatible-mode/v1"
airos-cli 2601.00155 --tags LLM --ai

For full configuration, see API_CONFIG.md.

Research Tree

Papers are organized into 12 directories:

00-Radar/            Topic heat tracking
01-Foundations/      Foundational papers
02-Models/           Model papers
03-Training/         Training methods
04-Scaling/         Scaling laws
05-Alignment/        Alignment research
06-Agents/           Agent systems
07-Infrastructure/    Infrastructure
08-Optimization/     Optimization techniques
09-Evaluation/       Evaluation methods
10-Applications/     Applied research
11-Future-Directions/

Installation

pip install ai-research-os

Or install from source:

git clone https://github.com/shushuzn/ai_research_os.git
cd ai_research_os
pip install -e .

Documentation

Full documentation at ai-research-os.readthedocs.io.

Doc	Description
Architecture	System design and module overview
Configuration	LLM, DB, Search, Tool configuration
Benchmarks	Performance metrics and test coverage
Contributing	How to contribute to this project
Roadmap	Project roadmap and future plans

License

GPL-3.0-or-later. See LICENSE for details.