Merge branch 'content-safety-updates' of https://github.com/PatrickFarley/azure-docs-pr into content-safety-updates

PatrickFarley · PatrickFarley · commit 962a6268d2c8 · 2024-07-15T21:45:24.000-04:00
diff --git a/articles/ai-services/content-safety/concepts/custom-categories.md b/articles/ai-services/content-safety/concepts/custom-categories.md
@@ -61,15 +61,15 @@ Then, you collect a balanced dataset with **positive** and (optionally) **negati
 
 ### Step 2: Model training
  
-Once your dataset is ready, the Azure AI Content Safety service uses it to train a new machine learning model. During training, the AI analyzes the data and learns to distinguish between content that matches the category and content that doesn't.
+After you prepare your dataset and define categories, the Azure AI Content Safety service trains a new machine learning model. This model uses your definitions and uploaded dataset to perform data augmentation using a large language model. As a result, the training dataset is made larger and of higher quality. During training, the AI model analyzes the data and learns to differentiate between content that aligns with the specified category and content that does not.
 
 ### Step 3: Model inferencing
  
 After training, you need to evaluate the model to ensure it meets your accuracy requirements. Test the model with new content that it hasn't received before. The evaluation phase helps you identify any potential adjustments you need to make deploying the model into a production environment.
 
 ### Step 4: Model usage
 
-You use the **analyzeCustomCategory** API to analyze text content and determine whether it matches the custom category you've defined. The service will return a score indicating the likelihood that the content matches the category.
+You use the **analyzeCustomCategory** API to analyze text content and determine whether it matches the custom category you've defined. The service will return a Boolean indicating whether the content aligns with the specified category
 
 #### [Custom categories (rapid) API](#tab/rapid)
 
@@ -95,12 +95,11 @@ See the following table for the input limitations of the custom categories (stan
 | Object           | Limitation   |
 | ---------------- | ------------ |
 | Supported languages | English only |
-|  Number of categories per user     |         5     |
-|  Number of versions per category   |        5      |
+|  Number of categories per user     |         3     |
+|  Number of versions per category   |        3      |
 |  Number of concurrent builds (processes) per category      |       1       |
-|  Inference operations per second           |    10          |
-|  Number of custom categories in one text analyze request          |       5  |
-|  Number of samples in a category version          |        minimum 50, maximum 10K (no duplicate samples allowed)      |
+|  Inference operations per second           |    5         |
+|  Number of samples in a category version          |        Positive samples(required):minimum 50, maximum 5K<br>In total (both negative and positive samples): 10K<br>No duplicate samples allowed.      |
 | Sample file size       |     maximum 128000 bytes         |
 | Length of a text sample           |          maximum 125K characters   |
 | Length of a category definition          |       maximum 1000 chars     |
diff --git a/articles/ai-services/content-safety/concepts/response-codes.md b/articles/ai-services/content-safety/concepts/response-codes.md
@@ -24,3 +24,9 @@ The content APIs may return the following error codes:
 | InternalError       | Some unexpected situations on the server side have been triggered. | You may want to retry a few times after a small period and see it the issue happens again.  <br/>             Contact Azure Support if this issue persists. |
 | ServerBusy          | The server side cannot process the request temporarily.      | You may want to retry a few times after a small period and see it the issue happens again.  <br/>Contact Azure Support if this issue persists. |
 | TooManyRequests     | The current RPS has exceeded the quota for your current SKU. | Check the pricing table to understand the RPS quota.   <br/>Contact Azure Support if you need more QPS. |
+
+
+## Azure AI Studio error messages
+
+If you encounter the error **Your account does not have access to this resource, please contact your resource owner to get access**, please ensure your account is assigned the role of `Cognitive Services User` for the Content Safety resource or Azure AI Services resource you are using.
+
diff --git a/articles/ai-services/content-safety/how-to/custom-categories.md b/articles/ai-services/content-safety/how-to/custom-categories.md
@@ -12,10 +12,10 @@ ms.date: 04/11/2024
 ms.author: pafarley
 ---
 
-# Use the custom category API
+# Use the custom categories (standard) API
 
 
-The custom category API lets you create your own content categories for your use case and train Azure AI Content Safety to detect them in new content.
+The custom categories (standard) API lets you create your own content categories for your use case and train Azure AI Content Safety to detect them in new content.
 
 > [!IMPORTANT]
 > This feature is only available in certain Azure regions. See [Region availability](../overview.md#region-availability).
@@ -86,8 +86,20 @@ curl -X PUT "<your_endpoint>/contentsafety/text/categories/<your_category_name>?
 
 ### Start the category build process:
 
+After you receive the response, store the operation ID (referred to as `id`) in a temporary. You need this ID to retrieve the build status using the **Get status** API.
+
 ```bash
-curl -X POST "<your_endpoint>/contentsafety/text/categories/<your_category_name>:build?api-version=2024-02-15-preview" \
+curl -X POST "<your_endpoint>/contentsafety/text/categories/<your_category_name>:build?api-version=2024-02-15-preview&version={version}" \
+     -H "Ocp-Apim-Subscription-Key: <your_api_key>" \
+     -H "Content-Type: application/json"
+```
+
+### Get the category build status:
+
+To retrieve the status, utilize the `id` obtained from the previous API response and place it in the path of the API below.
+
+```bash
+curl -X GET "<your_endpoint>/contentsafety/text/categories/operations/<id>?api-version=2024-02-15-preview" \
      -H "Ocp-Apim-Subscription-Key: <your_api_key>" \
      -H "Content-Type: application/json"
 ```
@@ -172,6 +184,22 @@ result = trigger_category_build_process(category_name, version)
 print(result)
 ```
 
+### Get the category build status:
+
+To retrieve the status, utilize the `id` obtained from the previous response.
+
+```python
+def get_build_status(id):
+    url = f"{ENDPOINT}/contentsafety/text/categories/operations/{id}?api-version=2024-02-15-preview"
+    response = requests.get(url, headers=headers)
+    return response.status_code
+
+# Replace the parameter with your own value
+id = "your-operation-id"
+
+result = get_build_status(id)
+print(result)
+```
 
 ## Analyze text with a customized category
 
diff --git a/articles/ai-services/content-safety/includes/storage-account-access.md b/articles/ai-services/content-safety/includes/storage-account-access.md
@@ -16,10 +16,10 @@ Next, you need to give your Content Safety resource access to read from the Azur
 
     :::image type="content" source="/azure/ai-services/content-safety/media/role-assignment.png" alt-text="Screenshot of Azure portal enabling managed identity.":::
 
-1. Assign the role of **Storage Blob Data Contributor/Owner/Reader** to the Managed identity. Any roles highlighted below should work.
+1. Assign the role of **Storage Blob Data Contributor/Owner** to the Managed identity. Any roles highlighted below should work.
 
     :::image type="content" source="/azure/ai-services/content-safety/media/add-role-assignment.png" alt-text="Screenshot of the Add role assignment screen in Azure portal.":::
 
     :::image type="content" source="/azure/ai-services/content-safety/media/assigned-roles.png" alt-text="Screenshot of assigned roles in the Azure portal.":::
 
-    :::image type="content" source="/azure/ai-services/content-safety/media/managed-identity-role.png" alt-text="Screenshot of the managed identity role.":::
+    :::image type="content" source="/azure/ai-services/content-safety/media/managed-identity-role.png" alt-text="Screenshot of the managed identity role.":::
diff --git a/articles/ai-services/content-safety/overview.md b/articles/ai-services/content-safety/overview.md
@@ -124,12 +124,16 @@ See the following list for the input requirements for each feature.
 - **Protected material detection (preview)**: 
   - Default maximum length: 1K characters.
   - Default minimum length: 110 characters (for scanning LLM completions, not user prompts).
+- **Custom categories (standard)**:
+  - Maximum inference input length: 1K characters.
 
 
 ### Language support
 
 Content Safety models have been specifically trained and tested in the following languages: English, German, Japanese, Spanish, French, Italian, Portuguese, and Chinese. However, the service can work in many other languages, but the quality might vary. In all cases, you should do your own testing to ensure that it works for your application.
 
+Custom Categories currently only works well in English. You can try to use other languages with your own dataset, but the quality might vary across languages.
+
 For more information, see [Language support](/azure/ai-services/content-safety/language-support).
 
 ### Region availability
@@ -139,20 +143,20 @@ To use the Content Safety APIs, you must create your Azure AI Content Safety res
 |Region | Moderation APIs | Prompt Shields<br>(preview) |  Protected material<br>detection (preview) | Groundedness<br>detection (preview) | Custom categories<br>(rapid) (preview) | Custom categories<br>(standard) | Blocklists |
 |---|---|---|---|---|---|---|--|
 | East US | ✅ | ✅| ✅ |✅ |✅ |✅|✅ |
-| East US 2 | ✅ | | | ✅ | | |✅|
+| East US 2 | ✅ | | | ✅ |✅ | |✅|
 | West US | | | | | ✅ | | |
-| West US 2 | ✅ | | | |  | |✅ |
+| West US 2 | ✅ | | | |✅  | |✅ |
 | Central US | ✅ | | | | | |✅ |
-| North Central US | ✅ | | | | | | ✅|
-| South Central US | ✅ | | | | | |✅ |
-| Canada East | ✅ | | | | | | ✅|
-| Switzerland North | ✅ | | | | | | ✅|
+| North Central US | ✅ | | | |✅ | | ✅|
+| South Central US | ✅ | | | | ✅| |✅ |
+| Canada East | ✅ | | | | ✅| | ✅|
+| Switzerland North | ✅ | | | |✅ | ✅ | ✅|
 | Sweden Central | ✅ | | |✅ |✅ | | ✅|
-| UK South | ✅ | | | | | |✅ |
-| France Central | ✅ | | | | | | ✅|
-| West Europe | ✅ | ✅ |✅ | | | |✅ |
-| Japan East | ✅ | | | | | |✅ |
-| Australia East| ✅ | ✅ | | | | | ✅|
+| UK South | ✅ | | | | ✅| |✅ |
+| France Central | ✅ | | | |✅ | | ✅|
+| West Europe | ✅ | ✅ |✅ | |✅ | |✅ |
+| Japan East | ✅ | | | |✅ | |✅ |
+| Australia East| ✅ | ✅ | | |✅ | ✅| ✅|
 
 Feel free to [contact us](mailto:contentsafetysupport@microsoft.com) if you need other regions for your business.
 
diff --git a/articles/ai-services/content-safety/quickstart-custom-categories.md b/articles/ai-services/content-safety/quickstart-custom-categories.md
@@ -11,7 +11,7 @@ ms.date: 07/03/2024
 ms.author: pafarley
 ---
 
-# Quickstart: Custom categories
+# Quickstart: Custom categories (standard mode)
 
 Follow this guide to use Azure AI Content Safety Custom category REST API to create your own content categories for your use case and train Azure AI Content Safety to detect them in new text content.
 
@@ -69,13 +69,22 @@ curl -X PUT "<your_endpoint>/contentsafety/text/categories/survival-advice?api-v
 
 ### Start the category build process:
 
-Replace `<your_api_key>` and `<your_endpoint>` with your own values. Allow enough time for model training: the end-to-end execution of custom category training can take from around five hours to ten hours. Plan your moderation pipeline accordingly.
+Replace `<your_api_key>` and `<your_endpoint>` with your own values. Allow enough time for model training: the end-to-end execution of custom category training can take from around five hours to ten hours. Plan your moderation pipeline accordingly. After you receive the response, store the operation ID (referred to as `id`) in a temporary location. This ID will be necessary for retrieving the build status using the **Get status** API in the next section.
 
 ```bash
 curl -X POST "<your_endpoint>/contentsafety/text/categories/survival-advice:build?api-version=2024-02-15-preview" \
      -H "Ocp-Apim-Subscription-Key: <your_api_key>" \
      -H "Content-Type: application/json"
 ```
+### Get the category build status:
+
+To retrieve the status, utilize the `id` obtained from the previous API response and place it in the path of the API below.
+
+```bash
+curl -X GET "<your_endpoint>/contentsafety/text/categories/operations/<id>?api-version=2024-02-15-preview" \
+     -H "Ocp-Apim-Subscription-Key: <your_api_key>" \
+     -H "Content-Type: application/json"
+```
 
 ## Analyze text with a customized category
 
@@ -141,7 +150,7 @@ print(result)
 
 ### Start the category build process
 
-You can start the category build process with the *category name* and *version number*. Allow enough time for model training: the end-to-end execution of custom category training can take from around five hours to ten hours. Plan your moderation pipeline accordingly.
+You can start the category build process with the *category name* and *version number*. Allow enough time for model training: the end-to-end execution of custom category training can take from around five hours to ten hours. Plan your moderation pipeline accordingly. After receiving the response, ensure that you store the operation ID (referred to as `id`) somewhere like your notebook. This ID will be necessary for retrieving the build status using the ‘get_build_status’ function in the next section.
 
 ```python
 def trigger_category_build_process(category_name, version):
@@ -157,6 +166,23 @@ result = trigger_category_build_process(category_name, version)
 print(result)
 ```
 
+### Get the category build status:
+
+To retrieve the status, utilize the `id` obtained from the previous response.
+
+```python
+def get_build_status(id):
+    url = f"{ENDPOINT}/contentsafety/text/categories/operations/{id}?api-version=2024-02-15-preview"
+    response = requests.get(url, headers=headers)
+    return response.status_code
+
+# Replace the parameter with your own value
+id = "your-operation-id"
+
+result = get_build_status(id)
+print(result)
+```
+
 
 ## Analyze text with a customized category
 
diff --git a/articles/ai-services/content-safety/whats-new.md b/articles/ai-services/content-safety/whats-new.md
@@ -16,12 +16,15 @@ ms.author: pafarley
 
 Learn what's new in the service. These items might be release notes, videos, blog posts, and other types of information. Bookmark this page to stay up to date with new features, enhancements, fixes, and documentation updates.
 
-## May 2024
+## July 2024
 
-### Custom category support in Content Safety moderation APIs
+### Custom categories (standard) API
 
 The custom categories API lets you create and train your own custom content categories and scan text for matches. See [Custom categories](./concepts/custom-categories.md) to learn more.
 
+## May 2024
+
+
 ### Custom categories (rapid) API
 
 The custom categories (rapid) API lets you quickly define emerging harmful content patterns and scan text and images for matches. See [Custom categories](./concepts/custom-categories.md) to learn more.
