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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_send_request_async.py
DESCRIPTION:
This sample demonstrates how to make custom HTTP requests through a client pipeline.
USAGE:
python sample_send_request_async.py
Set the environment variables with your own values before running the sample:
1) DOCUMENTINTELLIGENCE_ENDPOINT - the endpoint to your Form Recognizer resource.
2) DOCUMENTINTELLIGENCE_API_KEY - your Form Recognizer API key
"""
import asyncio
import os
from azure.core.credentials import AzureKeyCredential
from azure.core.rest import HttpRequest
from azure.ai.documentintelligence.aio import DocumentIntelligenceAdministrationClient
async def sample_send_request():
endpoint = os.environ["DOCUMENTINTELLIGENCE_ENDPOINT"]
key = os.environ["DOCUMENTINTELLIGENCE_API_KEY"]
client = DocumentIntelligenceAdministrationClient(endpoint=endpoint, credential=AzureKeyCredential(key))
async with client:
# The `send_request` method can send custom HTTP requests that share the client's existing pipeline,
# Now let's use the `send_request` method to make a resource details fetching request.
# The URL of the request should be absolute, and append the API version used for the request.
request = HttpRequest(method="GET", url=f"{endpoint}/documentintelligence/info?api-version=2024-11-30")
response = await client.send_request(request)
response.raise_for_status()
response_body = response.json()
print(
f"Our resource has {response_body['customDocumentModels']['count']} custom models, "
f"and we can have at most {response_body['customDocumentModels']['limit']} custom models."
f"The quota limit for custom neural document models is {response_body['customNeuralDocumentModelBuilds']['quota']} and the resource has"
f"used {response_body['customNeuralDocumentModelBuilds']['used']}. The resource quota will reset on {response_body['customNeuralDocumentModelBuilds']['quotaResetDateTime']}"
)
async def main():
await sample_send_request()
if __name__ == "__main__":
from azure.core.exceptions import HttpResponseError
from dotenv import find_dotenv, load_dotenv
try:
load_dotenv(find_dotenv())
asyncio.run(main())
except HttpResponseError as error:
# 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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