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# coding: utf-8
# -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
"""
FILE: sample_convert_to_and_from_dict.py
DESCRIPTION:
This sample demonstrates how to convert models returned from an analyze operation
to and from a dictionary. The dictionary in this sample is then converted to a
JSON file, then the same dictionary is converted back to its original model.
USAGE:
python sample_convert_to_and_from_dict.py
Set the environment variables with your own values before running the sample:
1) DOCUMENTINTELLIGENCE_ENDPOINT - the endpoint to your Document Intelligence resource.
2) DOCUMENTINTELLIGENCE_API_KEY - your Document Intelligence API key
"""
import os
import json
def convert_to_and_from_dict():
path_to_sample_documents = os.path.abspath(
os.path.join(
os.path.abspath(__file__),
"..",
"./sample_forms/forms/Form_1.jpg",
)
)
# [START convert]
from azure.core.credentials import AzureKeyCredential
from azure.ai.documentintelligence import DocumentIntelligenceClient
from azure.ai.documentintelligence.models import AnalyzeResult
endpoint = os.environ["DOCUMENTINTELLIGENCE_ENDPOINT"]
key = os.environ["DOCUMENTINTELLIGENCE_API_KEY"]
document_intelligence_client = DocumentIntelligenceClient(endpoint=endpoint, credential=AzureKeyCredential(key))
with open(path_to_sample_documents, "rb") as f:
poller = document_intelligence_client.begin_analyze_document("prebuilt-layout", body=f)
result: AnalyzeResult = poller.result()
# convert the received model to a dictionary
analyze_result_dict = result.as_dict()
# save the dictionary as JSON content in a JSON file
with open("data.json", "w") as output_file:
json.dump(analyze_result_dict, output_file, indent=4)
# convert the dictionary back to the original model
model = AnalyzeResult(analyze_result_dict)
# use the model as normal
print("----Converted from dictionary AnalyzeResult----")
print(f"Model ID: '{model.model_id}'")
print(f"Number of pages analyzed {len(model.pages)}")
print(f"API version used: {model.api_version}")
print("----------------------------------------")
# [END convert]
if __name__ == "__main__":
from azure.core.exceptions import HttpResponseError
from dotenv import find_dotenv, load_dotenv
try:
load_dotenv(find_dotenv())
convert_to_and_from_dict()
except HttpResponseError as error:
print(
"For more information about troubleshooting errors, see the following guide: "
"https://aka.ms/azsdk/python/formrecognizer/troubleshooting"
)
# Examples of how to check an HttpResponseError
# Check by error code:
if error.error is not None:
if error.error.code == "InvalidImage":
print(f"Received an invalid image error: {error.error}")
if error.error.code == "InvalidRequest":
print(f"Received an invalid request error: {error.error}")
# Raise the error again after printing it
raise
# If the inner error is None and then it is possible to check the message to get more information:
if "Invalid request".casefold() in error.message.casefold():
print(f"Uh-oh! Seems there was an invalid request: {error}")
# Raise the error again
raise
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