Update samples from sdk

.gitignore

@@ -164,3 +164,4 @@ cython_debug/
 # VSCode
 .vscode
 .azure
+test_output/

docs/set_env_for_training_data_and_reference_doc.md

@@ -22,14 +22,14 @@ The folders [document_training](../data/document_training/) and [field_extractio
             - Note: **Write** permission is required for uploading, modifying, or appending blobs.  
         - Click the **Create** button.  
         <img src="./get-access-signature.png" height="600" /> <img src="./choose-signature-options.png" height="600" />  
-        - **Copy the SAS URL:** After creating the SAS, click **Copy** to get the URL with the token. This URL will be used as the value for either **TRAINING_DATA_SAS_URL** or **REFERENCE_DOC_SAS_URL** when running the sample code.  
+        - **Copy the SAS URL:** After creating the SAS, click **Copy** to get the URL with the token. This URL will be used as the value for either **training_data_sas_url** or **REFERENCE_DOC_SAS_URL** when running the sample code.  
             <img src="./copy-access-signature.png" width="600" />
 
         - Set the following variables in the [.env](../notebooks/.env) file:  
-            > **Note:** The value for **REFERENCE_DOC_SAS_URL** can be the same as **TRAINING_DATA_SAS_URL** to reuse the same blob container.
-            - For [analyzer_training](../notebooks/analyzer_training.ipynb): Add the SAS URL as the value of **TRAINING_DATA_SAS_URL**.  
+            > **Note:** The value for **REFERENCE_DOC_SAS_URL** can be the same as **training_data_sas_url** to reuse the same blob container.
+            - For [analyzer_training](../notebooks/analyzer_training.ipynb): Add the SAS URL as the value of **training_data_sas_url**.  
                 ```env
-                TRAINING_DATA_SAS_URL=<Blob container SAS URL>
+                training_data_sas_url=<Blob container SAS URL>
                 ```
             - For [field_extraction_pro_mode](../notebooks/field_extraction_pro_mode.ipynb): Add the SAS URL as the value of **REFERENCE_DOC_SAS_URL**.  
                 ```env
@@ -53,9 +53,9 @@ The folders [document_training](../data/document_training/) and [field_extractio
 5. **Set Folder Prefixes in the `.env` File:**  
    Depending on the sample you will run, set the required environment variables in the [.env](../notebooks/.env) file.
 
-    - For [analyzer_training](../notebooks/analyzer_training.ipynb): Add a prefix for **TRAINING_DATA_PATH**. You can choose any folder name within the blob container. For example, use `training_files`.  
+    - For [analyzer_training](../notebooks/analyzer_training.ipynb): Add a prefix for **training_data_path**. You can choose any folder name within the blob container. For example, use `training_files`.  
         ```env
-        TRAINING_DATA_PATH=<Designated folder path under the blob container>
+        training_data_path=<Designated folder path under the blob container>
         ```
     - For [field_extraction_pro_mode](../notebooks/field_extraction_pro_mode.ipynb): Add a prefix for **REFERENCE_DOC_PATH**. You can choose any folder name within the blob container. For example, use `reference_docs`.  
         ```env

notebooks/.env.sample

@@ -1 +1,37 @@
-AZURE_AI_ENDPOINT=
+# Azure Content Understanding Service Configuration
+# Copy this file to <repository-root>/.env and update with your actual values
+
+# Your Azure Content Understanding service endpoint
+# Example: https://your-resource-name.services.ai.azure.com/
+# If you need help to create one, please see the Prerequisites section in:
+#   https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/quickstart/use-rest-api?tabs=document#prerequisites
+# As of 2025/05, 2025-05-01-preview is only available in the regions documented in 
+#   Content Understanding region and language support (https://learn.microsoft.com/en-us/azure/ai-services/content-understanding/language-region-support).
+
+# Azure Content Understanding Test Configuration
+
+# Required for Content Understanding SDK and testing
+AZURE_CONTENT_UNDERSTANDING_ENDPOINT=https://your-resource-name.services.ai.azure.com/
+
+# Authentication Options:
+# Option 1: Use Azure Key (FOR TESTING ONLY - Less secure)
+# Set this value if you want to use key-based authentication
+# WARNING: Keys are less secure and should only be used for testing/development
+# Leave empty to use DefaultAzureCredential (recommended)
+AZURE_CONTENT_UNDERSTANDING_KEY=
+
+# Option 2: Use DefaultAzureCredential (RECOMMENDED for production and development)
+# If AZURE_CONTENT_UNDERSTANDING_KEY is empty, the script will use DefaultAzureCredential
+# 
+# Most common development scenario:
+#   1. Install Azure CLI: https://docs.microsoft.com/en-us/cli/azure/install-azure-cli
+#   2. Login: az login
+#   3. Run the script (no additional configuration needed)
+#
+# This also supports:
+#   - Environment variables (AZURE_CLIENT_ID, AZURE_CLIENT_SECRET, AZURE_TENANT_ID)
+#   - Managed Identity (for Azure-hosted applications)
+#   - Visual Studio Code authentication
+#   - Azure PowerShell authentication
+# For more info: https://learn.microsoft.com/en-us/python/api/overview/azure/identity-readme#defaultazurecredential
+