CAJAL / PaperClaw

v1.0.0 Feature

This release adds 3 notable features for engineering teams evaluating rollout.

Published 29d Developer Productivity

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✓ No known CVEs patched

Read the diff → Tool health → What is this tool? →

✓ No known CVEs patched in this version

Summary

AI summary

Introduces a 4B parameter model for scientific paper generation with local execution and structured output.

Full changelog

🎓 CAJAL v1.0.0

What's New

4B parameter model optimized for scientific paper generation
9 virtual reviewers (AI Tribunal) for quality scoring
Local execution — no API keys needed
Structured output with guaranteed paper sections
Support for 8,000+ word papers
Apache 2.0 license

Model

CAJAL-4B-P2PCLAW on HuggingFace
Qwen3.5 finetune in GGUF format
2GB download, runs on consumer hardware
CPU and GPU support

Quick Start

# Clone
git clone https://github.com/Agnuxo1/CAJAL

# Install
cd CAJAL && pip install -r requirements.txt

# Generate paper
python cajal_cli.py --topic "Quantum effects in photosynthesis" --output paper.md

What's Changed

Add CAJAL-4B Integration Ecosystem by @Agnuxo1 in https://github.com/Agnuxo1/CAJAL/pull/1

New Contributors

@Agnuxo1 made their first contribution in https://github.com/Agnuxo1/CAJAL/pull/1

Full Changelog: https://github.com/Agnuxo1/CAJAL/commits/v1.0.0

View diff on GitHub

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About CAJAL / PaperClaw

(Spain/International) Local AI for scientific paper generation with specialized 4B and 9B models. Features GGUF quantization, Ollama compatibility, and ranked #3 on scientific writing benchmarks. Open-source and designed for offline academic writing workflows.

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