litai-research 0.1.4.dev202509110831

AI-powered academic paper synthesis tool

LitAI

Turn weeks of literature review into hours. LitAI lets you have research conversations with your entire paper collection - ask questions across multiple papers and get cited, contextual answers. Whether finding your research direction or unblocking active experiments, LitAI synthesizes literature to accelerate discovery.

Table of Contents

• Background
  • The Problem
  • The LitAI Difference: Synthesis
  • Who Benefits
• Installation
  • Quick Install
  • Prerequisites
  • API Key Setup
  • Package Installation
  • Updates
• Usage
  • 1. Launch LitAI
  • 2. Set Up Your Research Profile
  • 3. How LitAI Works
  • 4. Example Workflows
• Data Storage
  • Database Management
• FAQ
  • Why do paper searches sometimes fail?
• Support
• Roadmap
• Contributing
  • Installing the development version
• Authors and Acknowledgments
• License

Background

The Problem

Literature reviews take weeks. You read dozens of papers, lose track of insights, and struggle to synthesize findings across documents. Existing tools help you find or store papers - but not understand them together.

The LitAI Difference: Synthesis

LitAI is the only tool that lets you have research conversations with your entire paper collection:

1. Discovery: Search millions of papers using natural language
2. Collection: Save papers locally with automatic ArXiv PDF downloads
3. Context Building: Add your notes, select which papers and sections to analyze
4. Synthesis: Ask questions across multiple papers and get cited, contextual answers

This synthesis capability transforms how you work:

• Finding Your Research Question: Explore a field systematically, discover gaps, understand contradictions
• Active Research Support: Get immediate answers to operational questions that arise during experiments, debugging, or analysis

Unlike AI writing tools, LitAI helps you discover your research direction through literature understanding, not by choosing for you.

Who Benefits

• Graduate Students: Navigate unfamiliar literature to find and refine research questions
• Active Researchers: Unblock experiments with immediate synthesis of relevant methods
• Engineers: Find academic solutions to technical problems in production
• Research Teams: Build shared understanding across collaborative projects

Installation

Quick Install (if you know what you're doing)

uv tool install litai-research && export OPENAI_API_KEY=sk-... && litai

Prerequisites

• Python 3.11 or higher
• OpenAI API key (Get one here)

[!WARNING] Currently, papers can only be downloaded from ArXiv. Support for importing your own PDFs is coming soon via /import.

API Key Setup

Get your API key from platform.openai.com/api-keys

Permanent setup (recommended):

macOS:

echo 'export OPENAI_API_KEY="sk-..."' >> ~/.zshrc && source ~/.zshrc

Linux:

echo 'export OPENAI_API_KEY="sk-..."' >> ~/.bashrc && source ~/.bashrc

Current session only:

export OPENAI_API_KEY=sk-...

Package Installation

First install uv, then:

# Using uv (recommended)
uv tool install litai-research

# Alternative: using pipx
pipx install litai-research

[!TIP] If litai command not found, restart your terminal.

Updates

# Get latest stable updates
uv tool upgrade litai-research

# Alternative: using pipx
pipx upgrade litai-research

Usage

1. Launch LitAI

litai

2. Set Up Your Research Profile (Recommended)

Tell LitAI about your research focus for better responses:

/prompt

This opens an editor where you can describe your background, interests, and preferences. LitAI includes this in every conversation to tailor its responses.

3. How LitAI Works

The Workflow:

1. Find: Search for papers → "find papers on transformers" or /find transformers
2. Save: Add to collection → "add papers 1-3" or /add 1-3
3. Organize: Add notes/tags → "add a note" or /note
4. Analyze: Build context → "add paper to context" or /cadd <paper>
5. Synthesize: Ask questions → "what methods do they use?" or /synthesize

[!IMPORTANT] Only papers in your context are analyzed. Collection stores everything; context is your active analysis set.

[!NOTE] LitAI understands natural language - just chat with it. Want more control? Use /commands instead. Mix both freely.

Commands: For a complete list of commands, use /help in LitAI. For detailed information about any specific command, use <command> --help (e.g., /add --help).

AI Models: LitAI uses two models for optimal performance:

• Large model (GPT-5): Used for /synthesis queries
• Small model (GPT-5-nano): Used for search, extraction, and simple operations

These can be customized in settings, but we recommend the defaults for best results.

4. Example Workflows

Exploring a new field:

→ Find recent papers on vision transformers
→ Add the top 5 papers to my collection
→ Add ViT and DINO papers to context with abstracts
→ What are the main architectural innovations?

Debugging your implementation:

→ Find papers about transformer memory efficiency
→ Add papers 1-3 about flash attention
→ Add them to context with full text
→ How do they handle the quadratic complexity problem?

Finding research gaps:

→ Search for graph neural network survey papers
→ Save all the recent surveys
→ Add top 3 surveys to context
→ What problems do they identify as unsolved?

Data Storage

LitAI stores all data locally in ~/.litai/:

• litai.db - SQLite database with paper metadata and extractions
• pdfs/ - Downloaded PDF files
• logs/litai.log - Application logs for debugging
• config.json - User configuration
• user_prompt.txt - Personal research profile

Database Management

The LitAI database (~/.litai/db/litai.db) is a standard SQLite database that you can explore and manage with any SQLite-compatible tool. We recommend Beekeeper Studio for its user-friendly interface, but you can use any database tool you prefer.

To open the database in Beekeeper Studio:

1. Download and install Beekeeper Studio
2. Open Beekeeper Studio and click "New Connection"
3. Select "SQLite" as the database type
4. Click "Browse" and navigate to: ~/.litai/db/litai.db
   • macOS tip: Hidden files (starting with .) may not be visible in Finder by default. Press Command + Shift + . to show hidden files
5. Click "Connect"

You can now browse tables, run queries, and explore your research data directly.

FAQ

Why do paper searches sometimes fail?

Semantic Scholar's public API can experience high load, leading to search failures. If you encounter frequent issues:

• Wait a few minutes and try again
• Consider requesting a free API key for higher rate limits: Semantic Scholar API Key Form

Support

• Email issues to [e-mail]
• Logs for debugging: ~/.litai/logs/litai.log

Roadmap

Coming soon: Support for importing your own PDFs via /import.

Contributing

We welcome contributions! Guidelines coming soon.

Installing the development version

# Using uv (recommended)
uv tool install --prerelease=allow litai-research

# Using pipx
pipx install --prerelease litai-research

Authors and Acknowledgments

• Created by Harmon Bhasin and Alex Wilf
• Powered by Semantic Scholar API and OpenAI API

License

This project is open source and available under the MIT License.