# This is an automatically generated code sample.
# To make this code sample work in your Oracle Cloud tenancy,
# please replace the values for any parameters whose current values do not fit
# your use case (such as resource IDs, strings containing ‘EXAMPLE’ or ‘unique_id’, and
# boolean, number, and enum parameters with values not fitting your use case).

import oci
from datetime import datetime

# Create a default config using DEFAULT profile in default location
# Refer to
# https://docs.cloud.oracle.com/en-us/iaas/Content/API/Concepts/sdkconfig.htm#SDK_and_CLI_Configuration_File
# for more info
config = oci.config.from_file()


# Initialize service client with default config file
ai_document_client = oci.ai_document.AIServiceDocumentClient(config)


# Send the request to service, some parameters are not required, see API
# doc for more info
analyze_document_response = ai_document_client.analyze_document(
    analyze_document_details=oci.ai_document.models.AnalyzeDocumentDetails(
        features=[
            oci.ai_document.models.DocumentLanguageClassificationFeature(
                feature_type="LANGUAGE_CLASSIFICATION",
                max_results=224)],
        document=oci.ai_document.models.InlineDocumentDetails(
            source="INLINE",
            data="6lm4vs5ET6OHtvAbQ1Zx"),
        compartment_id="ocid1.test.oc1..<unique_ID>EXAMPLE-compartmentId-Value",
        output_location=oci.ai_document.models.OutputLocation(
            namespace_name="EXAMPLE-namespaceName-Value",
            bucket_name="EXAMPLE-bucketName-Value",
            prefix="EXAMPLE-prefix-Value"),
        language="EXAMPLE-language-Value",
        document_type="CHECK",
        ocr_data=oci.ai_document.models.AnalyzeDocumentResult(
            document_metadata=oci.ai_document.models.DocumentMetadata(
                page_count=161,
                mime_type="EXAMPLE-mimeType-Value"),
            pages=[
                oci.ai_document.models.Page(
                    page_number=769,
                    dimensions=oci.ai_document.models.Dimensions(
                        width=6920.53,
                        height=3775.981,
                        unit="INCH"),
                    detected_document_types=[
                        oci.ai_document.models.DetectedDocumentType(
                            document_type="EXAMPLE-documentType-Value",
                            confidence=0.32475168)],
                    detected_languages=[
                        oci.ai_document.models.DetectedLanguage(
                            language="EXAMPLE-language-Value",
                            confidence=0.07101196)],
                    words=[
                        oci.ai_document.models.Word(
                            text="EXAMPLE-text-Value",
                            confidence=0.1731121,
                            bounding_polygon=oci.ai_document.models.BoundingPolygon(
                                normalized_vertices=[
                                    oci.ai_document.models.NormalizedVertex(
                                        x=0.9577057,
                                        y=0.44805598)]))],
                    lines=[
                        oci.ai_document.models.Line(
                            text="EXAMPLE-text-Value",
                            confidence=0.18269998,
                            bounding_polygon=oci.ai_document.models.BoundingPolygon(
                                normalized_vertices=[
                                    oci.ai_document.models.NormalizedVertex(
                                        x=0.49617696,
                                        y=0.98050463)]),
                            word_indexes=[22])],
                    tables=[
                        oci.ai_document.models.Table(
                            row_count=454,
                            column_count=521,
                            header_rows=[
                                oci.ai_document.models.TableRow(
                                    cells=[
                                        oci.ai_document.models.Cell(
                                            text="EXAMPLE-text-Value",
                                            row_index=948,
                                            column_index=102,
                                            confidence=0.16822588,
                                            bounding_polygon=oci.ai_document.models.BoundingPolygon(
                                                normalized_vertices=[
                                                    oci.ai_document.models.NormalizedVertex(
                                                        x=0.66899353,
                                                        y=0.007975042)]),
                                            word_indexes=[39])])],
                            confidence=0.9620186,
                            bounding_polygon=oci.ai_document.models.BoundingPolygon(
                                normalized_vertices=[
                                    oci.ai_document.models.NormalizedVertex(
                                        x=0.44859058,
                                        y=0.92368656)]))],
                    document_fields=[
                        oci.ai_document.models.DocumentField(
                            field_type="LINE_ITEM",
                            field_value=oci.ai_document.models.ValueTime(
                                value_type="TIME",
                                confidence=0.21327114,
                                bounding_polygon=oci.ai_document.models.BoundingPolygon(
                                    normalized_vertices=[
                                        oci.ai_document.models.NormalizedVertex(
                                            x=0.54601544,
                                            y=0.48824334)]),
                                word_indexes=[486],
                                value=datetime.strptime(
                                    "2046-10-18T10:18:01.719Z",
                                    "%Y-%m-%dT%H:%M:%S.%fZ"),
                                text="EXAMPLE-text-Value"),
                            field_label=oci.ai_document.models.FieldLabel(
                                name="EXAMPLE-name-Value",
                                confidence=0.45981306),
                            field_name=oci.ai_document.models.FieldName(
                                name="EXAMPLE-name-Value",
                                confidence=0.49310988,
                                bounding_polygon=oci.ai_document.models.BoundingPolygon(
                                    normalized_vertices=[
                                        oci.ai_document.models.NormalizedVertex(
                                            x=0.047706723,
                                            y=0.9585324)]),
                                word_indexes=[268]))])],
            detected_document_types=[
                oci.ai_document.models.DetectedDocumentType(
                    document_type="EXAMPLE-documentType-Value",
                    confidence=0.77669525)],
            detected_languages=[
                oci.ai_document.models.DetectedLanguage(
                    language="EXAMPLE-language-Value",
                    confidence=0.2833863)],
            document_classification_model_version="EXAMPLE-documentClassificationModelVersion-Value",
            language_classification_model_version="EXAMPLE-languageClassificationModelVersion-Value",
            text_extraction_model_version="EXAMPLE-textExtractionModelVersion-Value",
            key_value_extraction_model_version="EXAMPLE-keyValueExtractionModelVersion-Value",
            table_extraction_model_version="EXAMPLE-tableExtractionModelVersion-Value",
            errors=[
                oci.ai_document.models.ProcessingError(
                    code="EXAMPLE-code-Value",
                    message="EXAMPLE-message-Value")],
            searchable_pdf="Eq8wLwIGbjMOKTw1igxs")),
    if_match="EXAMPLE-ifMatch-Value",
    opc_request_id="HMAHY8KDODQGEQGCXIGN<unique_ID>")

# Get the data from response
print(analyze_document_response.data)