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Merged
kristapratico merged 1 commit into from
Dec 7, 2020
Merged

[formrecognizer] update sample so it can run in ci #15691

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16 changes: 9 additions & 7 deletions ...gnizer/azure-ai-formrecognizer/samples/async_samples/sample_manage_custom_models_async.py
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Original file line number Diff line number Diff line change
Expand Up @@ -19,6 +19,7 @@
Set the environment variables with your own values before running the sample:
1) AZURE_FORM_RECOGNIZER_ENDPOINT - the endpoint to your Cognitive Services resource.
2) AZURE_FORM_RECOGNIZER_KEY - your Form Recognizer API key
3) CONTAINER_SAS_URL - The shared access signature (SAS) Url of your Azure Blob Storage container
"""

import os
Expand All @@ -28,14 +29,15 @@
class ManageCustomModelsSampleAsync(object):

async def manage_custom_models(self):
# [START get_account_properties_async]
from azure.core.credentials import AzureKeyCredential
from azure.core.exceptions import ResourceNotFoundError
from azure.ai.formrecognizer.aio import FormTrainingClient

endpoint = os.environ["AZURE_FORM_RECOGNIZER_ENDPOINT"]
key = os.environ["AZURE_FORM_RECOGNIZER_KEY"]
container_sas_url = os.environ["CONTAINER_SAS_URL"]

# [START get_account_properties_async]
async with FormTrainingClient(
endpoint=endpoint, credential=AzureKeyCredential(key)
) as form_training_client:
Expand All @@ -51,17 +53,17 @@ async def manage_custom_models(self):
custom_models = form_training_client.list_custom_models()

print("We have models with the following IDs:")

# Let's pull out the first model
first_model = await custom_models.__anext__()
print(first_model.model_id)
async for model in custom_models:
print(model.model_id)
# [END list_custom_models_async]

# Now we'll get information for the first custom model in the paged list
# let's train a model to use for this sample
poller = await form_training_client.begin_training(container_sas_url, use_training_labels=False)
model = await poller.result()

# Now we'll get information for the model we just trained
# [START get_custom_model_async]
custom_model = await form_training_client.get_custom_model(model_id=first_model.model_id)
custom_model = await form_training_client.get_custom_model(model_id=model.model_id)
print("\nModel ID: {}".format(custom_model.model_id))
print("Status: {}".format(custom_model.status))
print("Model name: {}".format(custom_model.model_name))
Expand Down
16 changes: 9 additions & 7 deletions sdk/formrecognizer/azure-ai-formrecognizer/samples/sample_manage_custom_models.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -19,6 +19,7 @@
Set the environment variables with your own values before running the sample:
1) AZURE_FORM_RECOGNIZER_ENDPOINT - the endpoint to your Cognitive Services resource.
2) AZURE_FORM_RECOGNIZER_KEY - your Form Recognizer API key
3) CONTAINER_SAS_URL - The shared access signature (SAS) Url of your Azure Blob Storage container
"""

import os
Expand All @@ -27,14 +28,15 @@
class ManageCustomModelsSample(object):

def manage_custom_models(self):
# [START get_account_properties]
from azure.core.credentials import AzureKeyCredential
from azure.core.exceptions import ResourceNotFoundError
from azure.ai.formrecognizer import FormTrainingClient

endpoint = os.environ["AZURE_FORM_RECOGNIZER_ENDPOINT"]
key = os.environ["AZURE_FORM_RECOGNIZER_KEY"]
container_sas_url = os.environ["CONTAINER_SAS_URL"]

# [START get_account_properties]
form_training_client = FormTrainingClient(endpoint=endpoint, credential=AzureKeyCredential(key))
# First, we see how many custom models we have, and what our limit is
account_properties = form_training_client.get_account_properties()
Expand All @@ -48,17 +50,17 @@ def manage_custom_models(self):
custom_models = form_training_client.list_custom_models()

print("We have models with the following IDs:")

# Let's pull out the first model
first_model = next(custom_models)
print(first_model.model_id)
for model in custom_models:
print(model.model_id)
# [END list_custom_models]

# Now we'll get information for the first custom model in the paged list
# let's train a model to use for this sample
poller = form_training_client.begin_training(container_sas_url, use_training_labels=False)
model = poller.result()

# Now we'll get information for the model we just trained
# [START get_custom_model]
custom_model = form_training_client.get_custom_model(model_id=first_model.model_id)
custom_model = form_training_client.get_custom_model(model_id=model.model_id)
print("\nModel ID: {}".format(custom_model.model_id))
print("Status: {}".format(custom_model.status))
print("Model name: {}".format(custom_model.model_name))
Expand Down