__artifacts_v2__ = {

"queryPredictions": {

"name": "Query Predictions",

"description": "Message query predictions from query_predictions.db",

"author": "",

"creation_date": "2026-06-23",

"last_update_date": "2026-07-03",

"requirements": "none",

"category": "SMS & iMessage",

"notes": "",

"paths": ('**/query_predictions.db',),

"output_types": "standard",

"artifact_icon": "message",

"data_views": {

"conversation": {

"conversationDiscriminatorColumn": "Conversation ID",

"textColumn": "Content",

"directionColumn": "Is Sent?",

"directionSentValue": 1,

"timeColumn": "Timestamp"

}

},

}

}

from scripts.ilapfuncs import artifact_processor, get_sqlite_db_records

@artifact_processor

def queryPredictions(context):

data_headers = (('Timestamp', 'datetime'), 'Content', 'Is Sent?', 'Conversation ID', 'ID', 'UUID')

data_list = []

source_path = ''

for file_found in context.get_files_found():

file_found = str(file_found)

if file_found.endswith('query_predictions.db'):

source_path = file_found

break

if not source_path:

return data_headers, data_list, ''

query = '''

SELECT datetime(creationTimestamp, 'unixepoch'), content, isSent, conversationId, id, uuid

FROM messages

'''

for row in get_sqlite_db_records(source_path, query):

data_list.append(tuple(row))

return data_headers, data_list, context.get_relative_path(source_path)