[DI] Add a sample to README.md (Azure#39085)

Author: Yalin Li

sdk/documentintelligence/azure-ai-documentintelligence/README.md

@@ -205,6 +205,7 @@ The following section provides several code snippets covering some of the most c
 - [Manage Your Models](#manage-your-models "Manage Your Models")
 - [Add-on Capabilities](#add-on-capabilities "Add-on Capabilities")
 - [Get Raw JSON Result](#get-raw-json-result "Get Raw JSON Result")
+- [Parse analyzed result to JSON format](#parse-analyzed-result-to-json-format "Parse analyzed result to JSON format")
 
 ### Extract Layout
 
@@ -961,6 +962,46 @@ print(
 
 <!-- END SNIPPET -->
 
+### Parse analyzed result to JSON format
+
+The result from poller is not JSON parse-able by default, you should call `as_dict()` before parsing to JSON.
+
+<!-- SNIPPET:sample_convert_to_and_from_dict.convert -->
+
+```python
+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 SNIPPET -->
+
 ## Troubleshooting
 
 ### General

sdk/documentintelligence/azure-ai-documentintelligence/assets.json

@@ -2,5 +2,5 @@
   "AssetsRepo": "Azure/azure-sdk-assets",
   "AssetsRepoPrefixPath": "python",
   "TagPrefix": "python/documentintelligence/azure-ai-documentintelligence",
-  "Tag": "python/documentintelligence/azure-ai-documentintelligence_bfcdb2d242"
+  "Tag": "python/documentintelligence/azure-ai-documentintelligence_5f676bd131"
 }

sdk/documentintelligence/azure-ai-documentintelligence/samples/async_samples/sample_convert_to_dict_async.py renamed to sdk/documentintelligence/azure-ai-documentintelligence/samples/async_samples/sample_convert_to_and_from_dict_async.py

@@ -7,14 +7,15 @@
 # --------------------------------------------------------------------------
 
 """
-FILE: sample_convert_to_dict_async.py
+FILE: sample_convert_to_and_from_dict_async.py
 
 DESCRIPTION:
-    This sample demonstrates how to convert a model returned from an analyze operation
-    to a JSON serializable dictionary.
+    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_dict_async.py
+    python sample_convert_to_and_from_dict_async.py
 
     Set the environment variables with your own values before running the sample:
     1) DOCUMENTINTELLIGENCE_ENDPOINT - the endpoint to your Document Intelligence resource.
@@ -56,6 +57,17 @@ async def convert_to_and_from_dict_async():
     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("----------------------------------------")
+
 
 async def main():
     await convert_to_and_from_dict_async()

sdk/documentintelligence/azure-ai-documentintelligence/samples/sample_convert_to_dict.py renamed to sdk/documentintelligence/azure-ai-documentintelligence/samples/sample_convert_to_and_from_dict.py

@@ -7,14 +7,15 @@
 # --------------------------------------------------------------------------
 
 """
-FILE: sample_convert_to_dict.py
+FILE: sample_convert_to_and_from_dict.py
 
 DESCRIPTION:
-    This sample demonstrates how to convert a model returned from an analyze operation
-    to a JSON serializable dictionary.
+    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_dict.py
+    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.
@@ -34,6 +35,7 @@ def convert_to_and_from_dict():
         )
     )
 
+    # [START convert]
     from azure.core.credentials import AzureKeyCredential
     from azure.ai.documentintelligence import DocumentIntelligenceClient
     from azure.ai.documentintelligence.models import AnalyzeResult
@@ -52,6 +54,18 @@ def convert_to_and_from_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__":

sdk/documentintelligence/azure-ai-documentintelligence/tests/test_dac_analyze_layout.py

@@ -226,7 +226,6 @@ def test_layout_url_barcode(self, client):
         assert layout.pages[0].barcodes[0].polygon
         assert layout.pages[0].barcodes[0].confidence > 0.8
 
-    @pytest.mark.skip("Failing in playback. Tracking issue: https://github.com/Azure/azure-sdk-for-python/issues/38881")
     @skip_flaky_test
     @DocumentIntelligencePreparer()
     @recorded_by_proxy

sdk/documentintelligence/azure-ai-documentintelligence/tests/test_dac_analyze_layout_async.py

@@ -235,7 +235,6 @@ async def test_layout_url_barcodes(self, client):
         assert layout.pages[0].barcodes[0].polygon
         assert layout.pages[0].barcodes[0].confidence > 0.8
 
-    @pytest.mark.skip("Failing in playback. Tracking issue: https://github.com/Azure/azure-sdk-for-python/issues/38881")
     @skip_flaky_test
     @DocumentIntelligencePreparer()
     @recorded_by_proxy_async