pm4py.llm.abstract_log_features

pm4py.llm.abstract_log_features(log_obj: DataFrame | EventLog | EventStream, max_len: int = 10000, include_header: bool = True, activity_key: str = 'concept:name', timestamp_key: str = 'time:timestamp', case_id_key: str = 'case:concept:name') → str

Abstracts the machine learning features obtained from a log by reporting the top features until the desired length is achieved.

Return type:

str

Parameters:

• log_obj – The log object from which to extract features.

• max_len (int) – Maximum length of the string abstraction (default: constants.OPENAI_MAX_LEN).

• include_header (bool) – Whether to include a header in the abstraction.

• activity_key (str) – The column name to be used as activity.

• timestamp_key (str) – The column name to be used as timestamp.

• case_id_key (str) – The column name to be used as case identifier.

Returns:

The log features abstraction as a string.

import pm4py

log = pm4py.read_xes("tests/input_data/roadtraffic100traces.xes")
print(pm4py.llm.abstract_log_features(log))