pm4py.llm

This file is part of PM4Py (More Info: https://pm4py.fit.fraunhofer.de).

PM4Py is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

PM4Py 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 General Public License for more details.

You should have received a copy of the GNU General Public License along with PM4Py. If not, see <https://www.gnu.org/licenses/>.

Functions

abstract_case(case[, ...])	Textually abstracts a case
abstract_declare(declare_model[, include_header])	Textually abstracts a DECLARE model
abstract_dfg(log_obj[, max_len, ...])	Obtains the DFG abstraction of a traditional event log
abstract_event_stream(log_obj[, max_len, ...])	Obtains the event stream abstraction of a traditional event log
abstract_log_attributes(log_obj[, max_len, ...])	Abstracts the attributes of a log (reporting their name, their type, and the top values)
abstract_log_features(log_obj[, max_len, ...])	Abstracts the machine learning features obtained from a log (reporting the top features until the desired length is obtained)
abstract_log_skeleton(log_skeleton[, ...])	Textually abstracts a log skeleton process model
abstract_ocel(ocel[, include_timestamps])	Obtains the abstraction of an object-centric event log, including the list of events and the objects of the OCEL
abstract_ocel_features(ocel, obj_type[, ...])	Obtains the abstraction of an object-centric event log, representing in text the features and their values.
abstract_ocel_ocdfg(ocel[, include_header, ...])	Obtains the abstraction of an object-centric event log, representing in text the object-centric directly-follows graph
abstract_petri_net(net, im, fm[, ...])	Obtain an abstraction of a Petri net
abstract_temporal_profile(temporal_profile)	Abstracts a temporal profile model to a string.
abstract_variants(log_obj[, max_len, ...])	Obtains the variants abstraction of a traditional event log
explain_visualization(vis_saver, *args[, ...])	Explains a process mining visualization by using LLMs (saving that first in a .png image, then providing the .png file to the Large Language Model along with possibly a description of the visualization).
openai_query(prompt[, api_key, ...])	Executes the provided prompt, obtaining the answer from the OpenAI APIs.