Provepy – A Python decorator that proves your code using Lean and LLMs
Formal verification via Python decorator—Lean proofs generated by LLMs on the fly.
OpenATP is an open-source Python package providing a common interface for Automated Theorem Proving (ATP)
Common interface for AI theorem provers when each tool has different setup.
Formal verification researchers and mathematicians using Lean
LeanDojo · ProofNet · DraftSketcher
open-atp prove Lemma.lean result/ claude
I took a class on formal verification back in 2022 when I was an undergraduate. There was something incredibly satisfying about constructing proofs in Coq and knowing my statements were now formally verified. However, formal methods were so time consuming that they weren't practical in most industry settings. The rise of AI has changed that story: https://blog.janestreet.com/formal-methods-at-jane-street-in....
AI is producing algorithms and mathematical proofs far faster than humans can review them and formal methods offer a solution. Automated theorem provers take a statement formalized in a proof assistant like Lean and attempt to supply a proof. Unlike natural language proofs, these proofs can be machine-checked, reducing the burden of review on humans.
AI agents are powerful automated theorem provers. Even general purpose coding agents, like Claude Code, can be effective provers with the right skills and tooling. However, these methods are currently challenging to run. They require configuring Docker containers with the proper Lean environment and agent tooling (skills, plugins, MCP, credentials). Furthermore, there is not a common interface to existing provers.
OpenATP aims to solve both of these challenges! It makes it easy to run methods locally in Docker or remotely in Modal. It currently supports the following provers: https://open-atp.henryrobbins.com/en/latest/provers/index.ht....
Formal verification via Python decorator—Lean proofs generated by LLMs on the fly.
Beats Lean's `nlinarith` on nonlinear inequalities using Python-backed SOS decompositions.
Formal verification for LLM workflows—CTL model checking, Z3 proofs, zero hallucination math.
Solid Lean tutorial, but implementing insertion sort proofs is a standard exercise in the field.
Solid walkthrough of Lean basics, but just another 'insertion sort proof' in a sea of tutorials.
LLM generates Lean 4 theorems from your code—formal verification without the PhD.