# OpenAIReview

[![PyPI version](https://img.shields.io/pypi/v/openaireview.svg)](https://pypi.org/project/openaireview/)

Our goal is provide thorough and detailed reviews to help researchers conduct the best research. See more examples [here](https://openaireview.github.io/).

![Example](assets/example.png)

## Installation

```bash
uv venv && uv pip install openaireview
# or: pip install openaireview
```

For development:
```bash
git clone https://github.com/ChicagoHAI/OpenAIReview.git
cd OpenAIReview
uv venv && uv pip install -e .
# or: pip install -e .
```

### PDF math support (optional)

For math-heavy PDFs, install [Marker](https://github.com/VikParuchuri/marker) separately to get accurate LaTeX extraction. Without Marker, PDFs are processed with PyMuPDF which cannot extract math symbols correctly.

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

Marker is used automatically when available on PATH. It is most useful for math-heavy PDFs, but runs very slowly without a GPU. For papers with math, we recommend using `.tex` source, `.md`, or arXiv HTML URLs instead of PDF when possible — these always produce correct output without needing Marker.

## Quick Start

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

```bash
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:

```bash
# 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` | `progressive` | Review method: `zero_shot`, `local`, `progressive`, `progressive_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](https://github.com/VikParuchuri/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](https://openrouter.ai) 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)
- **progressive** — sequential processing with running summary, then consolidation
- **progressive_full** — same as progressive but returns all comments before consolidation

## Benchmarks

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