Source code for pm4py.algo.querying.llm.injection.pm_knowledge.variants.traditional

'''
    PM4Py – A Process Mining Library for Python
Copyright (C) 2024 Process Intelligence Solutions UG (haftungsbeschränkt)

This program is free software: you can redistribute it and/or modify
it under the terms of the GNU Affero General Public License as
published by the Free Software Foundation, either version 3 of the
License, or any later version.

This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU Affero General Public License for more details.

You should have received a copy of the GNU Affero General Public License
along with this program.  If not, see this software project's root or
visit <https://www.gnu.org/licenses/>.

Website: https://processintelligence.solutions
Contact: info@processintelligence.solutions
'''
import pandas as pd
from typing import Optional, Dict, Any, Union
from sqlite3 import Connection as SQ3_Connection




def apply(
    db: Union[pd.DataFrame, SQ3_Connection],
    parameters: Optional[Dict[Any, Any]] = None,
) -> str:
    """
    Provides a string containing the required process mining domain knowledge for traditional process mining structures
    (in order for the LLM to produce meaningful queries).

    Parameters
    ---------------
    db
        Database
    parameters
        Optional parameters of the method

    Returns
    --------------
    pm_knowledge
        String containing the required process mining knowledge
    """
    if parameters is None:
        parameters = {}

    descr = """
If you need it, the process variant for a case can be obtained as concatenation of the activities of a case.
If you need it, the duration of a case can be obtained as difference between the timestamp of the first and the last event.
    """

    return descr