AutoX-AI-Labs/AutoR
📦 Open Source ProjectAutoX-AI-Labs
An AI-powered research harness where humans set the direction and AI agents execute the experimentation.
AutoR is a specialized CLI-based framework built to augment the capabilities of AI scientists. At its core, the tool treats AI as an execution engine, allowing users to maintain control over the research trajectory while offloading repetitive tasks like data processing, model training, and result logging to the agent.
Key features include:
- Human-in-the-loop direction: Users define the research hypothesis and constraints, while the agent navigates the implementation.
- Artifact-first architecture: Every execution session is serialized into a structured research artifact on the local filesystem, enabling deep inspection and auditability of the AI's decision-making process.
- Integration-ready: Built with Python, it integrates seamlessly with modern LLM providers like Claude and OpenAI, acting as a harness for complex research pipelines.
- Reproducibility: By logging every step as a discrete artifact, AutoR ensures that research outcomes are not just generated, but are fully reproducible and easy to share within a team or community.
💡Highlights
- ├─Human-led, AI-executed research
- ├─Local artifact-first logging
- └─CLI-based research harness
🎯For
- ├─AI Researchers
- └─Data Scientists