lstar_lm 0.1.1

Algorithm for learning DFA from demonstrations, examples, and language.

L*LM

Implementation of L*LM algorithm algorithm. See project page for details.

Table of Contents

• Installation
• Usage

Installation

If you just need to use lstar_lm, you can just run:

$ pip install lstar_lm

For developers, note that this project uses the poetry python package/dependency management tool. Please familarize yourself with it and then run:

$ poetry install

Usage

The main entry point for using this library is the guess_dfa function.

from lstar_lm import guess_dfa

An invocation of guess_dfa takes the form.

dfa = guess_dfa(
    positive = ...,  # List of positive examples. Each example is a list of tuples of tokens.
    negative = ...,  # List of negative examples. Each example is a list of tuples of tokens.
    alphabet = ...,  # List of (hashable) tokens.
    task_description = ...,  # String of task description.
    allow_unsure = ...,      # Whether to allow unsure responses (default True).
    random_iters = ...,      # Number of random queries to oracle.
    active_queries = ...,    # Number of active queries to oracle.
    use_dfa_identify = ...,  # True if use SAT based DFA identification. False uses L* + SAT hybrid.
    llm_endpoint = ...,      # http endpoint for llama.cpp server (default "http://localhost:8080/completion").
)