Lean Copilot: An AI Tool that Allows Large Language Models (LLMs) to be used in Lean for Proof Automation

Theorem Proving and Lean Copilot: A Practical AI Solution

Theorem proving is a critical aspect of formal mathematics and computer science, but it can be challenging and time-consuming. Mathematicians and researchers often spend significant time and effort constructing proofs, which can be tedious and error-prone. To address these challenges, the development of tools that can automate parts of this process is necessary to save time and reduce errors.

Traditional Tools and Limitations

Traditional proof assistants provide environments for users to write and check proofs. However, these tools require manual outlining of steps and tactics, relying heavily on user input and not fully automating the proof construction process.

Introducing Lean Copilot

Lean Copilot is a new AI tool designed to integrate large language models (LLMs) with Lean, aiming to automate parts of the proof construction process by suggesting tactics, searching for proofs, and selecting relevant premises. This makes the proof construction process more efficient and less reliant on manual input.

Key Features

suggest_tactics: Generates tactic suggestions for users to use in their proofs.
search_proof: Combines LLM-generated tactics with the aesop framework to find multi-tactic proofs.
select_premises: Retrieves potentially useful premises from a database.

Value and Considerations

Despite its powerful features, Lean Copilot may occasionally experience crashes and the select_premises function may not always align with user expectations. However, temporary workarounds can help mitigate these challenges.

Conclusion

Lean Copilot offers a promising solution to the challenges of theorem proving by integrating large language models with Lean. Its features automate parts of the proof construction process, making it more efficient and less reliant on manual input. While there are some caveats, Lean Copilot’s capabilities demonstrate its potential to significantly enhance the workflow of mathematicians and researchers in formal mathematics and computer science.

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