openaireview 0.1.2

AI-powered academic paper reviewer

OpenAIReview

Our goal is provide thorough and detailed reviews to help researchers conduct the best research. See more examples here.

Installation

uv pip install openaireview

For development:

git clone https://github.com/ChicagoHAI/OpenAIReview.git
cd OpenAIReview
uv pip install -e .

PDF math support (optional)

For math-heavy PDFs, install Marker separately to get accurate LaTeX extraction. Without Marker, PDFs are processed with PyMuPDF which cannot extract math symbols correctly.

# Install Marker CLI in an isolated environment (avoids dependency conflicts)
uv tool install marker-pdf

Marker is used automatically when available on PATH. For papers with math, we recommend using .tex source or arXiv HTML URLs instead of PDF when possible — these always produce correct output.

Quick Start

First, set your OpenRouter API key (get one at openrouter.ai/keys):

export OPENROUTER_API_KEY=your_key_here

Or create a .env file in your working directory:

OPENROUTER_API_KEY=your_key_here

Then review a paper and visualize results:

# Review a local file
openaireview review paper.pdf

# Or review directly from an arXiv URL
openaireview review https://arxiv.org/html/2602.18458v1

# Visualize results
openaireview serve
# Open http://localhost:8080

CLI Reference

openaireview review <file_or_url>

Review an academic paper for technical and logical issues. Accepts a local file path or an arXiv URL.

Option	Default	Description
--method	incremental	Review method: zero_shot, local, incremental, incremental_full
--model	anthropic/claude-opus-4-6	Model to use
--output-dir	./review_results	Directory for output JSON files
--name	(from filename)	Paper slug name

openaireview serve

Start a local visualization server to browse review results.

Option	Default	Description
--results-dir	./review_results	Directory containing result JSON files
--port	8080	Server port

Supported Input Formats

• PDF (.pdf) — uses Marker for high-quality extraction with LaTeX math; falls back to PyMuPDF if Marker is not installed
• DOCX (.docx) — via python-docx
• LaTeX (.tex) — plain text with title extraction from \title{}
• Text/Markdown (.txt, .md) — plain text
• arXiv HTML — fetch and parse directly from https://arxiv.org/html/<id> or https://arxiv.org/abs/<id>

Environment Variables

Variable	Default	Description
OPENROUTER_API_KEY	(required)	Your OpenRouter API key
MODEL	anthropic/claude-opus-4-6	Default model

These can be set as environment variables or in a .env file. See .env.example for a template.

Supported Models & Pricing

All models available on OpenRouter are supported — use any model ID via --model. The following models have built-in pricing for accurate cost tracking in the visualization:

Model	Input ($/1M tokens)	Output ($/1M tokens)
anthropic/claude-opus-4-6	$5.00	$25.00
anthropic/claude-opus-4-5	$5.00	$25.00
openai/gpt-5.2-pro	$21.00	$168.00
google/gemini-3.1-pro-preview	$2.00	$12.00

For models not listed above, a default rate of $5.00/$25.00 per 1M tokens is used.

Review Methods

• zero_shot — single prompt asking the model to find all issues
• local — deep-checks each chunk with surrounding window context (no filtering)
• incremental — sequential processing with running summary, then consolidation
• incremental_full — same as incremental but returns all comments before consolidation

Benchmarks

Benchmark data and experiment scripts are in benchmarks/. See benchmarks/REPORT.md for results.