LLMLean
LLMlean integrates LLMs and Lean for tactic suggestions, proof completion, and more.
Here's an example of using LLMLean on problems from Mathematics in Lean:
https://github.com/user-attachments/assets/284a8b32-b7a5-4606-8240-effe086f2b82
You can use an LLM running on your laptop, or an LLM from the Open AI API or Together.ai API:
LLM on your laptop:
-
Install ollama.
-
Pull a language model:
ollama pull wellecks/ntpctx-llama3-8b
- Add
llmlean
to lakefile:
require llmlean from git
"https://github.com/cmu-l3/llmlean.git"
- Import:
import LLMlean
Now use a tactic described below.
LLM in the cloud (OpenAI):
-
Get an OpenAI API key.
-
Set 2 environment variables:
export LLMLEAN_API=openai
export LLMLEAN_API_KEY=your-openai-api-key
Then do steps (3) and (4) above. Now use a tactic described below.
LLM in the cloud (together.ai):
-
Get a together.ai API key.
-
Set 2 environment variables:
export LLMLEAN_API=together
export LLMLEAN_API_KEY=your-together-api-key
Then do steps (3) and (4) above. Now use a tactic described below.
llmstep
tactic
Next-tactic suggestions via llmstep "{prefix}"
. Examples:
-
llmstep ""
-
llmstep "apply "
The suggestions are checked in Lean.
llmqed
tactic
Complete the current proof via llmqed
. Examples:
The suggestions are checked in Lean.
For the best performance, especially for the llmqed
tactic, we recommend using the Open AI API.
Demo in PFR
As an example, we provide detailed instructions of using LLMLean in the Polynomial Freiman Ruzsa conjecture formalization. Please see the following:
Customization
Please see the following: