41 lines
1.5 KiB
Markdown
41 lines
1.5 KiB
Markdown
# Introduction
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This is Pantograph, an machine-to-machine interaction interface for Lean 4.
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Its main purpose is to train and evaluate theorem proving agents. The main
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features are:
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1. Interfacing via the Python library, REPL, or C Library
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2. A mixture of expression-based and tactic-based proofs
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3. Pantograph has been designed with facilitating search in mind. A theorem
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proving agent can simultaneously explore multiple branches of the proof.
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4. Handling of metavariable coupling
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5. Reading/Adding symbols from the environment
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6. Extraction of tactic training data
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7. Support for drafting
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## Design Rationale
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The Lean 4 interface is not conducive to search. Readers familiar with Coq may
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know that the Coq Serapi was superseded by CoqLSP. In the opinion of the
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authors, this is a mistake. An interface conducive for human operators to write
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proofs is often not an interface conductive to search.
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Almost all of Pantograph's business logic is written in Lean, and Pantograph
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achieves tighter coupling between the data extraction and proof search
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components.
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## Referencing
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[Paper Link](https://arxiv.org/abs/2410.16429)
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```bib
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@misc{pantograph,
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title={Pantograph: A Machine-to-Machine Interaction Interface for Advanced Theorem Proving, High Level Reasoning, and Data Extraction in Lean 4},
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author={Leni Aniva and Chuyue Sun and Brando Miranda and Clark Barrett and Sanmi Koyejo},
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year={2024},
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eprint={2410.16429},
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archivePrefix={arXiv},
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primaryClass={cs.LO},
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url={https://arxiv.org/abs/2410.16429},
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}
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```
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