Source code for pm4py.algo.querying.llm.abstractions.stream_to_descr
'''
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 Optional, Dict, Any, Union
from pm4py.objects.log.obj import EventLog, EventStream
from enum import Enum
from pm4py.util import exec_utils, constants, xes_constants
from pm4py.objects.conversion.log import converter as log_converter
import pandas as pd
[docs]
class Parameters(Enum):
RESPONSE_HEADER = "response_header"
TIMESTAMP_KEY = constants.PARAMETER_CONSTANT_TIMESTAMP_KEY
MAX_LEN = "max_len"
[docs]
def apply(
log_obj: Union[EventLog, EventStream, pd.DataFrame],
parameters: Optional[Dict[Any, Any]] = None,
) -> str:
"""
Given a log object, returns a representation of the (last) events of a stream corresponding to the log object.
Parameters
--------------
log_obj
Log object
parameters
Parameters of the algorithm, including:
- Parameters.RESPONSE_HEADER => includes the header in the response
- Parameters.TIMESTAMP_KEY => the attribute to be used as timestamp
- Parameters.MAX_LEN => maximum length of the resulting stream
Returns
--------------
descr
String representing the stream of events
"""
if parameters is None:
parameters = {}
parameters["stream_postprocessing"] = True
event_stream = log_converter.apply(
log_obj,
variant=log_converter.Variants.TO_EVENT_STREAM,
parameters=parameters,
)._list
timestamp_key = exec_utils.get_param_value(
Parameters.TIMESTAMP_KEY,
parameters,
xes_constants.DEFAULT_TIMESTAMP_KEY,
)
response_header = exec_utils.get_param_value(
Parameters.RESPONSE_HEADER, parameters, True
)
max_len = exec_utils.get_param_value(
Parameters.MAX_LEN, parameters, constants.OPENAI_MAX_LEN
)
event_stream.sort(key=lambda x: x[timestamp_key], reverse=True)
ret = ["\n"]
interet = []
summ = 2
if response_header:
header = "If I have the following stream of events:\n"
summ += len(header) + 1
ret.append(header)
for ev in event_stream:
if summ > max_len:
break
stru = str(ev)
summ += len(stru) + 1
interet.append(stru)
interet.reverse()
ret = ret + interet + ["\n"]
return "\n".join(ret)