[textanalytics] Add healthcare action samples (Azure#25210)

* add healthcare action samples

* feedback

* update readme

sdk/textanalytics/azure-ai-textanalytics/samples/README.md

@@ -33,6 +33,7 @@ These sample programs show common scenarios for the Text Analytics client's offe
 |[sample_single_label_classify.py][single_label_classify_sample] and [sample_single_label_classify_async.py][single_label_classify_sample_async]|Use a custom model to classify documents into a single category|
 |[sample_multi_category_classify.py][multi_category_classify_sample] and [sample_multi_category_classify_async.py][multi_category_classify_sample_async]|Use a custom model to classify documents into multiple categories|
 |[sample_model_version.py][sample_model_version] and [sample_model_version_async.py][sample_model_version_async]|Set the model version for pre-built Text Analytics models|
+|[sample_analyze_healthcare_action.py][sample_analyze_healthcare_action] and [sample_analyze_healthcare_action_async.py][sample_analyze_healthcare_action_async]|Run a healthcare and PII analysis together|
 
 ## Prerequisites
 * Python 3.6 or later is required to use this package
@@ -109,6 +110,8 @@ what you can do with the Azure Text Analytics client library.
 [multi_category_classify_sample_async]: https://github.com/Azure/azure-sdk-for-python/blob/main/sdk/textanalytics/azure-ai-textanalytics/samples/async_samples/sample_multi_category_classify_async.py
 [sample_model_version]: https://github.com/Azure/azure-sdk-for-python/blob/main/sdk/textanalytics/azure-ai-textanalytics/samples/sample_model_version.py
 [sample_model_version_async]: https://github.com/Azure/azure-sdk-for-python/blob/main/sdk/textanalytics/azure-ai-textanalytics/samples/async_samples/sample_model_version_async.py
+[sample_analyze_healthcare_action]: https://github.com/Azure/azure-sdk-for-python/blob/main/sdk/textanalytics/azure-ai-textanalytics/samples
+[sample_analyze_healthcare_action_async]: https://github.com/Azure/azure-sdk-for-python/blob/main/sdk/textanalytics/azure-ai-textanalytics/samples
 [pip]: https://pypi.org/project/pip/
 [azure_subscription]: https://azure.microsoft.com/free/
 [azure_language_account]: https://docs.microsoft.com/azure/cognitive-services/cognitive-services-apis-create-account?tabs=singleservice%2Cwindows

sdk/textanalytics/azure-ai-textanalytics/samples/async_samples/sample_analyze_healthcare_action_async.py

@@ -0,0 +1,126 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+
+"""
+FILE: sample_analyze_healthcare_action_async.py
+
+DESCRIPTION:
+    This sample demonstrates how to submit a collection of text documents for analysis, which uses the
+    AnalyzeHealthcareEntitiesAction and RecognizePiiEntitiesAction to recognize healthcare entities,
+    along with any PII entities.
+    The response will contain results from each of the individual actions specified in the request.
+
+USAGE:
+    python sample_analyze_healthcare_action_async.py
+
+    Set the environment variables with your own values before running the sample:
+    1) AZURE_LANGUAGE_ENDPOINT - the endpoint to your Language resource.
+    2) AZURE_LANGUAGE_KEY - your Language subscription key
+"""
+
+
+import os
+import asyncio
+
+
+async def sample_analyze_healthcare_action():
+    from azure.core.credentials import AzureKeyCredential
+    from azure.ai.textanalytics.aio import TextAnalyticsClient
+    from azure.ai.textanalytics import (
+        AnalyzeHealthcareEntitiesAction,
+        RecognizePiiEntitiesAction,
+    )
+
+    endpoint = os.environ["AZURE_LANGUAGE_ENDPOINT"]
+    key = os.environ["AZURE_LANGUAGE_KEY"]
+
+    text_analytics_client = TextAnalyticsClient(
+        endpoint=endpoint,
+        credential=AzureKeyCredential(key),
+    )
+
+    documents = [
+        """
+        Patient needs to take 100 mg of ibuprofen, and 3 mg of potassium. Also needs to take
+        10 mg of Zocor.
+        """,
+        """
+        Patient needs to take 50 mg of ibuprofen, and 2 mg of Coumadin.
+        """
+    ]
+
+    async with text_analytics_client:
+        poller = await text_analytics_client.begin_analyze_actions(
+            documents,
+            display_name="Sample Text Analysis",
+            actions=[
+                AnalyzeHealthcareEntitiesAction(),
+                RecognizePiiEntitiesAction(domain_filter="phi"),
+            ],
+        )
+
+        pages = await poller.result()
+
+        # To enumerate / zip for async, unless you install a third party library,
+        # you have to read in all of the elements into memory first.
+        # If you're not looking to enumerate / zip, we recommend you just asynchronously
+        # loop over it immediately, without going through this step of reading them into memory
+        document_results = []
+        async for page in pages:
+            document_results.append(page)
+
+        for doc, action_results in zip(documents, document_results):
+            print(f"\nDocument text: {doc}")
+            healthcare_entities_result = action_results[0]
+            print("...Results of Analyze Healthcare Entities Action:")
+            if healthcare_entities_result.is_error:
+                print("...Is an error with code '{}' and message '{}'".format(
+                    healthcare_entities_result.code, healthcare_entities_result.message
+                ))
+            else:
+                for entity in healthcare_entities_result.entities:
+                    print(f"Entity: {entity.text}")
+                    print(f"...Normalized Text: {entity.normalized_text}")
+                    print(f"...Category: {entity.category}")
+                    print(f"...Subcategory: {entity.subcategory}")
+                    print(f"...Offset: {entity.offset}")
+                    print(f"...Confidence score: {entity.confidence_score}")
+                    if entity.data_sources is not None:
+                        print("...Data Sources:")
+                        for data_source in entity.data_sources:
+                            print(f"......Entity ID: {data_source.entity_id}")
+                            print(f"......Name: {data_source.name}")
+                    if entity.assertion is not None:
+                        print("...Assertion:")
+                        print(f"......Conditionality: {entity.assertion.conditionality}")
+                        print(f"......Certainty: {entity.assertion.certainty}")
+                        print(f"......Association: {entity.assertion.association}")
+                for relation in healthcare_entities_result.entity_relations:
+                    print(f"Relation of type: {relation.relation_type} has the following roles")
+                    for role in relation.roles:
+                        print(f"...Role '{role.name}' with entity '{role.entity.text}'")
+            recognize_pii_entities_result = action_results[1]
+
+            print("Results of Recognize PII Entities action:")
+            if recognize_pii_entities_result.is_error:
+                print("...Is an error with code '{}' and message '{}'".format(
+                    recognize_pii_entities_result.code, recognize_pii_entities_result.message
+                ))
+            else:
+                for entity in recognize_pii_entities_result.entities:
+                    print(f"......Entity: {entity.text}")
+                    print(f".........Category: {entity.category}")
+                    print(f".........Confidence Score: {entity.confidence_score}")
+
+        print("------------------------------------------")
+
+
+async def main():
+    await sample_analyze_healthcare_action()
+
+
+if __name__ == '__main__':
+    asyncio.run(main())

sdk/textanalytics/azure-ai-textanalytics/samples/sample_analyze_healthcare_action.py

@@ -0,0 +1,111 @@
+# -------------------------------------------------------------------------
+# Copyright (c) Microsoft Corporation. All rights reserved.
+# Licensed under the MIT License. See License.txt in the project root for
+# license information.
+# --------------------------------------------------------------------------
+
+"""
+FILE: sample_analyze_healthcare_action.py
+
+DESCRIPTION:
+    This sample demonstrates how to submit a collection of text documents for analysis, which uses the
+    AnalyzeHealthcareEntitiesAction and RecognizePiiEntitiesAction to recognize healthcare entities,
+    along with any PII entities.
+    The response will contain results from each of the individual actions specified in the request.
+
+USAGE:
+    python sample_analyze_healthcare_action.py
+
+    Set the environment variables with your own values before running the sample:
+    1) AZURE_LANGUAGE_ENDPOINT - the endpoint to your Language resource.
+    2) AZURE_LANGUAGE_KEY - your Language subscription key
+"""
+
+
+import os
+
+
+def sample_analyze_healthcare_action():
+    from azure.core.credentials import AzureKeyCredential
+    from azure.ai.textanalytics import (
+        TextAnalyticsClient,
+        AnalyzeHealthcareEntitiesAction,
+        RecognizePiiEntitiesAction,
+    )
+
+    endpoint = os.environ["AZURE_LANGUAGE_ENDPOINT"]
+    key = os.environ["AZURE_LANGUAGE_KEY"]
+
+    text_analytics_client = TextAnalyticsClient(
+        endpoint=endpoint,
+        credential=AzureKeyCredential(key),
+    )
+
+    documents = [
+        """
+        Patient needs to take 100 mg of ibuprofen, and 3 mg of potassium. Also needs to take
+        10 mg of Zocor.
+        """,
+        """
+        Patient needs to take 50 mg of ibuprofen, and 2 mg of Coumadin.
+        """
+    ]
+
+    poller = text_analytics_client.begin_analyze_actions(
+        documents,
+        display_name="Sample Text Analysis",
+        actions=[
+            AnalyzeHealthcareEntitiesAction(),
+            RecognizePiiEntitiesAction(domain_filter="phi"),
+        ],
+    )
+
+    document_results = poller.result()
+    for doc, action_results in zip(documents, document_results):
+        print(f"\nDocument text: {doc}")
+        healthcare_entities_result = action_results[0]
+        print("...Results of Analyze Healthcare Entities Action:")
+        if healthcare_entities_result.is_error:
+            print("...Is an error with code '{}' and message '{}'".format(
+                healthcare_entities_result.code, healthcare_entities_result.message
+            ))
+        else:
+            for entity in healthcare_entities_result.entities:
+                print(f"Entity: {entity.text}")
+                print(f"...Normalized Text: {entity.normalized_text}")
+                print(f"...Category: {entity.category}")
+                print(f"...Subcategory: {entity.subcategory}")
+                print(f"...Offset: {entity.offset}")
+                print(f"...Confidence score: {entity.confidence_score}")
+                if entity.data_sources is not None:
+                    print("...Data Sources:")
+                    for data_source in entity.data_sources:
+                        print(f"......Entity ID: {data_source.entity_id}")
+                        print(f"......Name: {data_source.name}")
+                if entity.assertion is not None:
+                    print("...Assertion:")
+                    print(f"......Conditionality: {entity.assertion.conditionality}")
+                    print(f"......Certainty: {entity.assertion.certainty}")
+                    print(f"......Association: {entity.assertion.association}")
+            for relation in healthcare_entities_result.entity_relations:
+                print(f"Relation of type: {relation.relation_type} has the following roles")
+                for role in relation.roles:
+                    print(f"...Role '{role.name}' with entity '{role.entity.text}'")
+        recognize_pii_entities_result = action_results[1]
+
+        print("Results of Recognize PII Entities action:")
+        if recognize_pii_entities_result.is_error:
+            print("...Is an error with code '{}' and message '{}'".format(
+                recognize_pii_entities_result.code, recognize_pii_entities_result.message
+            ))
+        else:
+            for entity in recognize_pii_entities_result.entities:
+                print(f"......Entity: {entity.text}")
+                print(f".........Category: {entity.category}")
+                print(f".........Confidence Score: {entity.confidence_score}")
+
+        print("------------------------------------------")
+
+
+if __name__ == "__main__":
+    sample_analyze_healthcare_action()