How to export LLM human preference annotations and sample export formats.
Deprecating Export V1
Starting in April 2024, we will begin sunsetting Export V1 for customers on a rolling basis. For more details, see this guide.
Export JSON annotations
# Set the export params to include/exclude certain fields. Make sure each of these fields are correctly grabbed
export_params= {
"attachments": True,
"metadata_fields": True,
"data_row_details": True,
"project_details": True,
"label_details": True,
"performance_details": True
}
# You can set the range for last_activity_at and label_created_at.
# For context, last_activity_at captures the creation and modification of labels, metadata, status, comments and reviews.
# Note: This is an AND logic between the filters, so usually using one filter is sufficient.
filters= {
"last_activity_at": ["2000-01-01 00:00:00", "2050-01-01 00:00:00"],
}
export_task = project.export_v2(params=export_params, filters=filters)
export_task.wait_till_done()
if export_task.errors:
print(export_task.errors)
export_json = export_task.result
print("results: ", export_json)
# Set the export params to include/exclude certain fields.
export_params= {
"attachments": True,
"metadata_fields": True,
"data_row_details": True,
"project_details": True,
"label_details": True,
"performance_details": True,
"interpolated_frames": True
}
# Note: Filters follow AND logic, so typically using one filter is sufficient.
filters= {
"last_activity_at": ["2000-01-01 00:00:00", "2050-01-01 00:00:00"],
"workflow_status": "<wkf-status>"
}
client.enable_experimental = True
export_task = project.export(params=export_params, filters=filters)
export_task.wait_till_done()
# Return JSON output strings from export task results/errors, one by one:
# Callback used for JSON Converter
def json_stream_handler(output: lb.JsonConverterOutput):
print(output.json_str)
if export_task.has_errors():
export_task.get_stream(
converter=lb.JsonConverter(),
stream_type=lb.StreamType.ERRORS
).start(stream_handler=lambda error: print(error))
if export_task.has_result():
export_json = export_task.get_stream(
converter=lb.JsonConverter(),
stream_type=lb.StreamType.RESULT
).start(stream_handler=json_stream_handler)
print("file size: ", export_task.get_total_file_size(stream_type=lb.StreamType.RESULT))
print("line count: ", export_task.get_total_lines(stream_type=lb.StreamType.RESULT))
Annotation export formats
Classification - Radio
{
"feature_id": "clp8gzc7a000h07iu2uqcfziq",
"feature_schema_id": "clp8fepqc02nd071phl4tck59",
"name": "Choose the best response",
"radio_answer": {
"feature_id": "clp8gzc7a000i07iu46z39uwl",
"feature_schema_id": "clp8fepqc02ng071p9ufm76xj",
"name": "Response B",
"classifications": []
}
}
Classification - Free-form text
{
"feature_id": "clph8rvw700013b6pbsq1lwcg",
"feature_schema_id": "clp8fepqc02nl071p8z948pd4",
"name": "Provide a reason for your choice",
"text_answer": {
"content": "Clear recommendation"
}
}
Classification - Checklist
{
"feature_id": "clpiyav9m00053b6mpe2qk0im",
"feature_schema_id": "clpiya8h507dx072efo9kb97j",
"name": "Evaluations done",
"checklist_answers": [
{
"feature_id": "clpiyav9m00043b6mvhur1p19",
"name": "Usefulness",
"classifications": []
},
{
"feature_id": "clpiyax4d00073b6mqyyt0504",
"name": "Toxicity",
"classifications": []
}
]
}
Sample project export
{
"data_row": {
"id": "clpiqgsvn4lxr079096g5mt9v",
"global_key": "0914c7da-5999-464b-b621-054a5247cf48",
"row_data": "https://storage.googleapis.com/labelbox-developer-testing-assets/Pranoy/shopping_3.json",
"details": {
"dataset_id": "clpiqgrsr00f60737sqeiaf4v",
"dataset_name": "pairwise_demo_42454af2-b7b5-45c0-a25a-90f97efd49be",
"created_at": "2023-11-28T19:30:49.729+00:00",
"updated_at": "2023-11-28T19:30:50.609+00:00",
"last_activity_at": "2023-11-28T23:11:08.000+00:00",
"created_by": "[email protected]"
}
},
"media_attributes": {
"mime_type": "application/vnd.labelbox.conversational",
"labelable_ids": [
"message-1",
"message-3"
],
"message_count": 4
},
"attachments": [],
"metadata_fields": [],
"projects": {
"clpiy2itz08vg0705akh60zc1": {
"name": "Test LLM Human Preference",
"labels": [
{
"label_kind": "Default",
"version": "1.0.0",
"id": "clpiyah63071f07e4756yer2d",
"label_details": {
"created_at": "2023-11-28T23:11:08.000+00:00",
"updated_at": "2023-11-28T23:11:07.000+00:00",
"created_by": "[email protected]",
"content_last_updated_at": "2023-11-28T23:11:07.568+00:00",
"reviews": []
},
"annotations": {
"objects": [],
"classifications": [
{
"feature_id": "clpiybl7h000g3b6mil1amjme",
"feature_schema_id": "clpiqh0v104mq0729homqffup",
"name": "Choose the best response",
"radio_answer": {
"feature_id": "clpiybl7h000f3b6m03fn8ry3",
"feature_schema_id": "clpiqh0v104mt0729atflgvvw",
"name": "Response B",
"classifications": []
}
},
{
"feature_id": "clpiybzp3000h3b6m9uowaci4",
"feature_schema_id": "clpiqh0v104my072907gt7id0",
"name": "Provide a reason for your choice",
"text_answer": {
"content": "Direct approach that is convenient"
}
},
{
"feature_id": "clpiyc10q000j3b6m01i2d1pv",
"feature_schema_id": "clpiya8h507dx072efo9kb97j",
"name": "Evaluations done",
"checklist_answers": [
{
"feature_id": "clpiyc10q000i3b6mhhvhdzqs",
"name": "Relevance",
"classifications": []
},
{
"feature_id": "clpiyc1ie000l3b6m3kpff0lp",
"name": "Usefulness",
"classifications": []
}
]
}
],
"relationships": []
}
}
],
"project_details": {
"ontology_id": "clpiqh0ud04mp0729adeoccsl",
"task_id": "33e77b4d-424f-49ba-8792-628c1cb746b7",
"task_name": "Initial review task",
"batch_id": "66882c10-8e42-11ee-8f8d-71857f06db2f",
"batch_name": "test_llm_human_preference_batch_1",
"workflow_status": "IN_REVIEW",
"priority": 5,
"consensus_expected_label_count": 1,
"workflow_history": [
{
"action": "Move",
"created_at": "2023-11-28T23:11:07.654+00:00",
"created_by": "[email protected]",
"previous_task_name": "Initial labeling task",
"previous_task_id": "8f9917a7-6030-0914-befc-ac06f59a7ec9",
"next_task_name": "Initial review task",
"next_task_id": "33e77b4d-424f-49ba-8792-628c1cb746b7"
},
{
"action": "Move",
"created_at": "2023-11-28T23:11:07.631+00:00",
"created_by": "[email protected]",
"next_task_name": "Initial labeling task",
"next_task_id": "8f9917a7-6030-0914-befc-ac06f59a7ec9"
}
]
}
}
}
}