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v1

latestOpenAPI 3.0.22026-07-17373198641.7 KB
document
v1

Retrieve Document Field

get/api/v1/document/document-fields/{uid}/

Path parameters

uidstring required

A UUID string identifying this document field.

Query parameters

jq_filtersobject

Filter params similar to JQWidgets grid filter params: filterscount=1, filterdatafield0="a", filtervalue0="b", filtercondition0="CONTAINS", filteroperator0=1, sortdatafied="c", sortorder="asc"

Response

uidstring uuid
document_typestring required
document_type__titlestring
codestring required

Field codes must be lowercase, should start with a Latin letter, and contain only Latin letters, digits, underscores. Field codes must be unique to every Document Type.

long_codestring
titlestring required
descriptionstring nullable
type'address' | 'choice' | 'company' | 'date' | 'date_recurring' | 'datetime' | 'duration' | 'float' | 'geography' | 'int' | 'linked_documents' | 'money' | 'multi_choice' | 'percent' | 'person' | 'ratio' | 'related_info' | 'string' | 'string_no_word_wrap' | 'text'
text_unit_type'sentence' | 'paragraph' | 'section'
value_detection_strategy'disabled' | 'use_regexps_only' | 'use_formula_only' | 'regexp_table' | 'text_based_ml_only' | 'fields_based_ml_only' | 'fields_based_prob_ml_only' | 'field_based_regexps' | 'mlflow_model'
classifier_init_scriptstring nullable
formulastring nullable
convert_decimals_to_floats_in_formula_argsboolean

Floating point field values are represented in Python Decimal type to avoid rounding problems in machine numbers representations. Use this checkbox for converting them to Python float type before calculating the formula. Float: 0.1 + 0.2 = 0.30000000000000004. Decimal: 0.1 + 0.2 = 0.3.

value_regexpstring nullable

This regular expression is run on the sentence found by a Field Detector and extracts a specific string value from a Text Unit. If the regular expression returns multiple matching groups, then the first matching group will be used by the Field. This is only applicable to String Fields.

depends_on_fieldsstring[]
value_detection_strategy_namestring
confidence'High' | 'Medium' | 'Low' nullable
requires_text_annotationsboolean
read_onlyboolean
categorystring
familyinteger nullable
default_valueobject nullable

If populated, the Default Value will be displayed for this Field if no other value is found by the chosen Value Detection Strategy. Leave this form blank to have the Field Value remain empty by default. Please wrap entries with quotes, example: “landlord”. This is only applicable to Choice and Multi Choice Fields.

choicesstring[]
allow_values_not_specified_in_choicesboolean
metadataobject nullable
training_finishedboolean
dirtyboolean
orderinteger
trained_after_documents_numberinteger
hidden_alwaysboolean
hide_until_pythonstring nullable
hide_until_jsstring nullable
is_value_detection_strategy_disabledboolean
display_yes_noboolean

Checking this box will display “Yes” if Related Info text is found, and display “No” if no text is found.

value_awareboolean
created_by__namestring
modified_by__namestring
created_datestring date-time
modified_datestring date-time
vectorizer_stop_wordsstring nullable

Stop words for vectorizers user in field-based ML field detection. These stop words are excluded from going into the feature vector part build based on this field. In addition to these words the standard sklearn "english" word list is used. Format: each word on new line

unsure_choice_valuestring nullable

Makes sense for machine learning strategies with "Unsure" category. The strategy will return this value if probabilities of all other categories appear lower than the specified threshold.

unsure_thresholds_by_valueobject nullable

Makes sense for machine learning strategies with "Unsure" category. The strategy will return concrete result (one of choice values) only if the probability of the detected value is greater than this threshold. Otherwise the strategy returns None or the choice value specified in "Unsure choice value" field. Format: { "value1": 0.9, "value2": 0.5, ...}. Default: 0.9

mlflow_model_uristring nullable

MLFlow model URI understandable by the MLFlow artifact downloading routines.

mlflow_detect_on_document_levelboolean

If true - whole document text will be sent to the MLFlow model and the field value will be returned for the whole text with no annotations. If false - each text unit will be sent separately.

Example response

{
  "classifier_init_script": "classifier_init_script",
  "vectorizer_stop_words": "vectorizer_stop_words",
  "metadata": "{}",
  "code": "code",
  "allow_values_not_specified_in_choices": true,
  "description": "description",
  "modified_by__name": "modified_by__name",
  "long_code": "long_code",
  "title": "title",
  "type": "address",
  "value_regexp": "value_regexp",
  "trained_after_documents_number": 314780941,
  "unsure_choice_value": "unsure_choice_value",
  "uid": "046b6c7f-0b8a-43b9-b35d-6489e6daee91",
  "read_only": true,
  "depends_on_fields": [
    "046b6c7f-0b8a-43b9-b35d-6489e6daee91",
    "046b6c7f-0b8a-43b9-b35d-6489e6daee91"
  ],
  "value_aware": true,
  "requires_text_annotations": true,
  "created_by__name": "created_by__name",
  "hide_until_python": "hide_until_python",
  "document_type": "document_type",
  "order": 19750,
  "convert_decimals_to_floats_in_formula_args": true,
  "dirty": true,
  "confidence": "High",
  "hide_until_js": "hide_until_js",
  "default_value": "{}",
  "value_detection_strategy_name": "value_detection_strategy_name",
  "modified_date": "2000-01-23T04:56:07.000+00:00",
  "unsure_thresholds_by_value": "{}",
  "text_unit_type": "sentence",
  "mlflow_model_uri": "mlflow_model_uri",
  "document_type__title": "document_type__title",
  "display_yes_no": true,
  "training_finished": true,
  "mlflow_detect_on_document_level": true,
  "formula": "formula",
  "value_detection_strategy": "disabled",
  "hidden_always": true,
  "created_date": "2000-01-23T04:56:07.000+00:00",
  "category": "category",
  "family": 0,
  "choices": [
    "choices",
    "choices"
  ],
  "is_value_detection_strategy_disabled": true
}