OpenMLRML Research Intern

Plans tasks, reads papers, writes drafts, and runs experiments — end to end.

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Plan

Structured questions with options, task breakdown, scope clarification before any work begins.

Research

Search OpenAlex, ArXiv, CrossRef. Read papers section-by-section. Crawl citation graphs. Find code on GitHub.

Write

Section-by-section paper drafting with bibliography management and Markdown/LaTeX export.

Execute

Docker-isolated code execution locally, on SSH remotes, or Modal cloud sandboxes.

What is OpenMLR?

OpenMLR is a self-hosted AI research assistant that works like an ML research intern. It plans, researches, writes, and executes ML tasks end-to-end using structured workflows and real tool access.

Key capabilities

Structured planning — the agent asks clarifying questions with 2-4 options (plus free-text) before starting work, then builds a task list
Paper research — searches OpenAlex (250M+ works), reads full papers from ArXiv, crawls citation graphs, finds related code and datasets
Academic writing — drafts papers section-by-section with inline citations, manages bibliography, exports to Markdown or LaTeX
Code execution — runs commands in Docker containers for isolation, with SSH and Modal cloud sandbox support
Task management — right-side panel tracks tasks and resources; completion reports auto-generated when tasks finish
Context awareness — tracks token usage, auto-compacts when approaching model limits, manages search budgets
Multi-provider LLMs — OpenAI, Anthropic, OpenRouter, plus litellm for 100+ models