pip install leeroo-kapso.
The four pillars
Evolve
.evolve() runs iterative experiments to build software for a goal, using tree search, coding agents and knowledge-graph context. When a session needs a credential or a file only you can provide, the campaign asks and pauses until you reply.Learn
Two memories.
.learn() mines your own finished campaigns into evidence-priced lesson cards. .learn_knowledge() ingests repositories and research into the knowledge graph.Research
.research() runs deep web research and returns structured findings you can feed into the knowledge graph or pass as campaign context.Deploy
.deploy() turns a solution into running software, locally, in Docker, or on a cloud platform such as Modal.What a full run looks like
learn() mines your own finished campaigns; learn_knowledge() ingests outside sources. They are different memories.Results
IOAI 2026
Competing fully autonomously in the AI Model Track, Kapso scored 536.07 — above every one of the 471 human contestants — and took the IOAI² Grand Master Trophy, top 3 among all AI systems entered.
RelBench
Passes KumoRFM-v2 on outcome prediction and forecasting, and the best reported results on recommendations, on Stanford’s benchmark for predictive ML over relational data.
MLE-Bench
Top ranking among open-source systems on Kaggle machine-learning competitions.
ALE-Bench
Top ranking on long-horizon algorithmic discovery problems from AtCoder.
Kapso against KumoRFM-v2 on RelBench outcome prediction, forecasting and recommendations
What is inside
Leeroopedia MCP
Kapso connects to Leeroopedia, a curated knowledge base of ML and AI frameworks. Agents query it during ideation and implementation to look up APIs, build plans and diagnose failures. See Optional: Leeroopedia MCP.Start here
Installation
The CLIs, the package, and kapso doctor
Quickstart
Your first campaign
CLI reference
Every command and flag
pip install leeroo-kapso · Every page as plain text: llms.txt.