Source code for pm4py.algo.querying.llm.injection.db_knowledge.algorithm
'''
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
'''
from typing import Union, Optional, Dict, Any
import pandas as pd
from sqlite3 import Connection as SQ3_Connection
from pm4py.objects.ocel.obj import OCEL
from pm4py.util import pandas_utils, exec_utils
from pm4py.algo.querying.llm.injection.db_knowledge.variants import (
pandas_duckdb,
sqlite3_traditional,
)
[docs]
def apply(
db: Union[pd.DataFrame, SQ3_Connection, OCEL],
variant=None,
parameters: Optional[Dict[Any, Any]] = None,
) -> str:
"""
Provides a string containing the required database knowledge for database querying
(in order for the LLM to produce meaningful queries).
Parameters
---------------
db
Database
variant
Variant of the method to be used (pandas_duckdb, sqlite3_traditional)
parameters
Variant-specific parameters
Returns
---------------
db_knowledge
String containing the required database knowledge.
"""
if parameters is None:
parameters = {}
if variant is None:
if pandas_utils.check_is_pandas_dataframe(db):
variant = pandas_duckdb
elif isinstance(db, SQ3_Connection):
variant = sqlite3_traditional
if variant is None:
return "\n\n"
return exec_utils.get_variant(variant).apply(db, parameters)