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Yalin Li
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[DI] Add samples for getting raw json result (Azure#37725)
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‎sdk/documentintelligence/azure-ai-documentintelligence/README.md‎

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@@ -202,7 +202,8 @@ The following section provides several code snippets covering some of the most c
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* [Build a Custom Model](#build-a-custom-model "Build a custom model")
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* [Analyze Documents Using a Custom Model](#analyze-documents-using-a-custom-model "Analyze Documents Using a Custom Model")
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* [Manage Your Models](#manage-your-models "Manage Your Models")
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* [Add-on capabilities](#add-on-capabilities "Add-on Capabilities")
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* [Add-on Capabilities](#add-on-capabilities "Add-on Capabilities")
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* [Get Raw JSON Result](#get-raw-json-result "Get Raw JSON Result")
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### Extract Layout
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@@ -896,6 +897,74 @@ The following add-on capabilities are available in this SDK:
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Note that some add-on capabilities will incur additional charges. See pricing: https://azure.microsoft.com/pricing/details/ai-document-intelligence/.
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### Get Raw JSON Result
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Can get the HTTP response by passing parameter `raw_response_hook` to any client method.
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<!-- SNIPPET:sample_get_raw_response.raw_response_hook -->
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```python
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import os
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from azure.core.credentials import AzureKeyCredential
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from azure.ai.documentintelligence import DocumentIntelligenceAdministrationClient
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endpoint = os.environ["DOCUMENTINTELLIGENCE_ENDPOINT"]
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key = os.environ["DOCUMENTINTELLIGENCE_API_KEY"]
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client = DocumentIntelligenceAdministrationClient(endpoint=endpoint, credential=AzureKeyCredential(key))
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responses = {}
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def callback(response):
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responses["status_code"] = response.http_response.status_code
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responses["response_body"] = response.http_response.json()
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client.get_resource_info(raw_response_hook=callback)
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print(f"Response status code is: {responses["status_code"]}")
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response_body = responses["response_body"]
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print(
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f"Our resource has {response_body['customDocumentModels']['count']} custom models, "
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f"and we can have at most {response_body['customDocumentModels']['limit']} custom models."
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f"The quota limit for custom neural document models is {response_body['customNeuralDocumentModelBuilds']['quota']} and the resource has"
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f"used {response_body['customNeuralDocumentModelBuilds']['used']}. The resource quota will reset on {response_body['customNeuralDocumentModelBuilds']['quotaResetDateTime']}"
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)
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```
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<!-- END SNIPPET -->
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Also, can use the `send_request` method to send custom HTTP requests and get raw JSON result from HTTP responses.
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<!-- SNIPPET:sample_send_request.send_request -->
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```python
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import os
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from azure.core.credentials import AzureKeyCredential
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from azure.core.rest import HttpRequest
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from azure.ai.documentintelligence import DocumentIntelligenceAdministrationClient
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endpoint = os.environ["DOCUMENTINTELLIGENCE_ENDPOINT"]
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key = os.environ["DOCUMENTINTELLIGENCE_API_KEY"]
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client = DocumentIntelligenceAdministrationClient(endpoint=endpoint, credential=AzureKeyCredential(key))
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# The `send_request` method can send custom HTTP requests that share the client's existing pipeline,
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# Now let's use the `send_request` method to make a resource details fetching request.
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# The URL of the request should be absolute, and append the API version used for the request.
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request = HttpRequest(method="GET", url=f"{endpoint}/documentintelligence/info?api-version=2024-07-31-preview")
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response = client.send_request(request)
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response.raise_for_status()
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response_body = response.json()
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print(
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f"Our resource has {response_body['customDocumentModels']['count']} custom models, "
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f"and we can have at most {response_body['customDocumentModels']['limit']} custom models."
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f"The quota limit for custom neural document models is {response_body['customNeuralDocumentModelBuilds']['quota']} and the resource has"
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f"used {response_body['customNeuralDocumentModelBuilds']['used']}. The resource quota will reset on {response_body['customNeuralDocumentModelBuilds']['quotaResetDateTime']}"
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)
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```
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<!-- END SNIPPET -->
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## Troubleshooting
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### General

‎sdk/documentintelligence/azure-ai-documentintelligence/azure/ai/documentintelligence/_operations/_patch.py‎

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@@ -39,6 +39,7 @@ def _parse_operation_id(operation_location_header):
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regex = "[^:]+://[^/]+/documentintelligence/.+/([^?/]+)"
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return re.match(regex, operation_location_header).group(1)
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def _finished(status) -> bool:
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if hasattr(status, "value"):
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status = status.value

‎sdk/documentintelligence/azure-ai-documentintelligence/samples/async_samples/sample_get_raw_response_async.py‎

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# coding: utf-8
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# -------------------------------------------------------------------------
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# Copyright (c) Microsoft Corporation. All rights reserved.
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# Licensed under the MIT License. See License.txt in the project root for
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# license information.
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# --------------------------------------------------------------------------
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"""
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FILE: sample_raw_response_hook_async.py
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DESCRIPTION:
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This sample demonstrates how to get raw response via "raw_response_hook".
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USAGE:
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python sample_raw_response_hook_async.py
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Set the environment variables with your own values before running the sample:
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1) DOCUMENTINTELLIGENCE_ENDPOINT - the endpoint to your Document Intelligence resource.
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2) DOCUMENTINTELLIGENCE_API_KEY - your Document Intelligence API key.
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"""
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import asyncio
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import os
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from azure.core.credentials import AzureKeyCredential
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from azure.ai.documentintelligence.aio import DocumentIntelligenceAdministrationClient
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async def sample_raw_response_hook():
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endpoint = os.environ["DOCUMENTINTELLIGENCE_ENDPOINT"]
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key = os.environ["DOCUMENTINTELLIGENCE_API_KEY"]
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client = DocumentIntelligenceAdministrationClient(endpoint=endpoint, credential=AzureKeyCredential(key))
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responses = {}
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def callback(response):
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responses["status_code"] = response.http_response.status_code
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responses["response_body"] = response.http_response.json()
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async with client:
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await client.get_resource_info(raw_response_hook=callback)
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print(f"Response status code is: {responses['status_code']}")
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response_body = responses["response_body"]
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print(
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f"Our resource has {response_body['customDocumentModels']['count']} custom models, "
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f"and we can have at most {response_body['customDocumentModels']['limit']} custom models."
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f"The quota limit for custom neural document models is {response_body['customNeuralDocumentModelBuilds']['quota']} and the resource has"
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f"used {response_body['customNeuralDocumentModelBuilds']['used']}. The resource quota will reset on {response_body['customNeuralDocumentModelBuilds']['quotaResetDateTime']}"
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)
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async def main():
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await sample_raw_response_hook()
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if __name__ == "__main__":
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from azure.core.exceptions import HttpResponseError
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from dotenv import find_dotenv, load_dotenv
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try:
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load_dotenv(find_dotenv())
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asyncio.run(main())
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except HttpResponseError as error:
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# Examples of how to check an HttpResponseError
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# Check by error code:
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if error.error is not None:
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if error.error.code == "InvalidImage":
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print(f"Received an invalid image error: {error.error}")
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if error.error.code == "InvalidRequest":
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print(f"Received an invalid request error: {error.error}")
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# Raise the error again after printing it
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raise
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# If the inner error is None and then it is possible to check the message to get more information:
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if "Invalid request".casefold() in error.message.casefold():
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print(f"Uh-oh! Seems there was an invalid request: {error}")
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# Raise the error again
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raise

‎sdk/documentintelligence/azure-ai-documentintelligence/samples/async_samples/sample_send_request_async.py‎

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# coding: utf-8
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# -------------------------------------------------------------------------
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# Copyright (c) Microsoft Corporation. All rights reserved.
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# Licensed under the MIT License. See License.txt in the project root for
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# license information.
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# --------------------------------------------------------------------------
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"""
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FILE: sample_send_request_async.py
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DESCRIPTION:
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This sample demonstrates how to make custom HTTP requests through a client pipeline.
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USAGE:
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python sample_send_request_async.py
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Set the environment variables with your own values before running the sample:
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1) DOCUMENTINTELLIGENCE_ENDPOINT - the endpoint to your Form Recognizer resource.
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2) DOCUMENTINTELLIGENCE_API_KEY - your Form Recognizer API key
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"""
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import asyncio
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import os
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from azure.core.credentials import AzureKeyCredential
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from azure.core.rest import HttpRequest
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from azure.ai.documentintelligence.aio import DocumentIntelligenceAdministrationClient
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async def sample_send_request():
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endpoint = os.environ["DOCUMENTINTELLIGENCE_ENDPOINT"]
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key = os.environ["DOCUMENTINTELLIGENCE_API_KEY"]
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client = DocumentIntelligenceAdministrationClient(endpoint=endpoint, credential=AzureKeyCredential(key))
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async with client:
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# The `send_request` method can send custom HTTP requests that share the client's existing pipeline,
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# Now let's use the `send_request` method to make a resource details fetching request.
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# The URL of the request should be absolute, and append the API version used for the request.
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request = HttpRequest(method="GET", url=f"{endpoint}/documentintelligence/info?api-version=2024-07-31-preview")
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response = await client.send_request(request)
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response.raise_for_status()
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response_body = response.json()
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print(
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f"Our resource has {response_body['customDocumentModels']['count']} custom models, "
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f"and we can have at most {response_body['customDocumentModels']['limit']} custom models."
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f"The quota limit for custom neural document models is {response_body['customNeuralDocumentModelBuilds']['quota']} and the resource has"
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f"used {response_body['customNeuralDocumentModelBuilds']['used']}. The resource quota will reset on {response_body['customNeuralDocumentModelBuilds']['quotaResetDateTime']}"
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)
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async def main():
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await sample_send_request()
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if __name__ == "__main__":
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from azure.core.exceptions import HttpResponseError
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from dotenv import find_dotenv, load_dotenv
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try:
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load_dotenv(find_dotenv())
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asyncio.run(main())
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except HttpResponseError as error:
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# Examples of how to check an HttpResponseError
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# Check by error code:
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if error.error is not None:
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if error.error.code == "InvalidImage":
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print(f"Received an invalid image error: {error.error}")
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if error.error.code == "InvalidRequest":
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print(f"Received an invalid request error: {error.error}")
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# Raise the error again after printing it
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raise
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# If the inner error is None and then it is possible to check the message to get more information:
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if "Invalid request".casefold() in error.message.casefold():
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print(f"Uh-oh! Seems there was an invalid request: {error}")
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# Raise the error again
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raise

‎sdk/documentintelligence/azure-ai-documentintelligence/samples/sample_get_raw_response.py‎

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# coding: utf-8
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# -------------------------------------------------------------------------
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# Copyright (c) Microsoft Corporation. All rights reserved.
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# Licensed under the MIT License. See License.txt in the project root for
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# license information.
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# --------------------------------------------------------------------------
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"""
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FILE: sample_get_raw_response.py
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DESCRIPTION:
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This sample demonstrates how to get raw response via "raw_response_hook".
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USAGE:
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python sample_get_raw_response.py
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Set the environment variables with your own values before running the sample:
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1) DOCUMENTINTELLIGENCE_ENDPOINT - the endpoint to your Document Intelligence resource.
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2) DOCUMENTINTELLIGENCE_API_KEY - your Document Intelligence API key.
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"""
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def sample_raw_response_hook():
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# [START raw_response_hook]
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import os
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from azure.core.credentials import AzureKeyCredential
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from azure.ai.documentintelligence import DocumentIntelligenceAdministrationClient
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endpoint = os.environ["DOCUMENTINTELLIGENCE_ENDPOINT"]
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key = os.environ["DOCUMENTINTELLIGENCE_API_KEY"]
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client = DocumentIntelligenceAdministrationClient(endpoint=endpoint, credential=AzureKeyCredential(key))
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responses = {}
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def callback(response):
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responses["status_code"] = response.http_response.status_code
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responses["response_body"] = response.http_response.json()
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client.get_resource_info(raw_response_hook=callback)
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print(f"Response status code is: {responses['status_code']}")
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response_body = responses["response_body"]
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print(
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f"Our resource has {response_body['customDocumentModels']['count']} custom models, "
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f"and we can have at most {response_body['customDocumentModels']['limit']} custom models."
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f"The quota limit for custom neural document models is {response_body['customNeuralDocumentModelBuilds']['quota']} and the resource has"
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f"used {response_body['customNeuralDocumentModelBuilds']['used']}. The resource quota will reset on {response_body['customNeuralDocumentModelBuilds']['quotaResetDateTime']}"
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)
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# [END raw_response_hook]
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if __name__ == "__main__":
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from azure.core.exceptions import HttpResponseError
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from dotenv import find_dotenv, load_dotenv
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try:
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load_dotenv(find_dotenv())
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sample_raw_response_hook()
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except HttpResponseError as error:
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# Examples of how to check an HttpResponseError
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# Check by error code:
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if error.error is not None:
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if error.error.code == "InvalidImage":
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print(f"Received an invalid image error: {error.error}")
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if error.error.code == "InvalidRequest":
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print(f"Received an invalid request error: {error.error}")
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# Raise the error again after printing it
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raise
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# If the inner error is None and then it is possible to check the message to get more information:
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if "Invalid request".casefold() in error.message.casefold():
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print(f"Uh-oh! Seems there was an invalid request: {error}")
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# Raise the error again
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raise

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