Merge pull request #257725 from MicrosoftDocs/main

11/6/2023 PM Publish

Author: Taojunshen

.openpublishing.redirection.json

@@ -555,6 +555,11 @@
       "redirect_url": "/previous-versions/azure/cognitive-services/Bing-Web-Search/hit-highlighting",
       "redirect_document_id": false
     },
+    {
+      "source_path": "articles/cognitive-services/Bing-Web-Search/index.yml",
+      "redirect_url": "/previous-versions/azure/cognitive-services/Bing-Web-Search/overview",
+      "redirect_document_id": false
+    },
     {
       "source_path": "articles/cognitive-services/Bing-Web-Search/language-support.md",
       "redirect_url": "/previous-versions/azure/cognitive-services/Bing-Web-Search/language-support",

articles/ai-services/openai/concepts/use-your-data.md

@@ -122,7 +122,7 @@ You can modify the following additional settings in the **Data parameters** sect
 
 |Parameter name  | Description  |
 |---------|---------|
-|**Retrieved documents**     |  Specifies the number of top-scoring documents from your data index used to generate responses. You might want to increase the value when you have short documents or want to provide more context. The default value is 3. This is the `topNDocuments` parameter in the API.     |
+|**Retrieved documents**     |  Specifies the number of top-scoring documents from your data index used to generate responses. You might want to increase the value when you have short documents or want to provide more context. The default value is 5. This is the `topNDocuments` parameter in the API.     |
 | **Strictness**     | Sets the threshold to categorize documents as relevant to your queries. Raising the value means a higher threshold for relevance and filters out more less-relevant documents for responses. Setting this value too high might cause the model to fail to generate responses due to limited available documents. The default value is 3.         |
 
 ## Virtual network support & private endpoint support

articles/ai-services/openai/faq.yml

@@ -7,7 +7,7 @@ metadata:
   manager: nitinme
   ms.service: azure-ai-openai
   ms.topic: faq
-  ms.date: 10/16/2023
+  ms.date: 11/06/2023
   ms.author: mbullwin
   author: mrbullwinkle
 title: Azure OpenAI Service frequently asked questions
@@ -22,6 +22,10 @@ sections:
           Azure OpenAI doesn't use customer data to retrain models. For more information, see the [Azure OpenAI data, privacy, and security guide](/legal/cognitive-services/openai/data-privacy?context=/azure/ai-services/openai/context/context).    
   - name: General
     questions:
+      - question: |
+          Does Azure OpenAI work with the latest Python library released by OpenAI (version>=1.0)?
+        answer: |
+          Azure OpenAI is supported by the latest release of the [OpenAI Python library (version>=1.0)](https://pypi.org/project/openai/). However, it is important to note migration of your codebase using `openai migrate` is not supported and will not work with code that targets Azure OpenAI.  
       - question: |
           Does Azure OpenAI support GPT-4?
         answer: |
@@ -77,7 +81,7 @@ sections:
 
           Ultimately, the model is performing next [token](/semantic-kernel/prompt-engineering/tokens) prediction in response to your question. The model doesn't have any native ability to query what model version is currently being run to answer your question. To answer this question, you can always go to **Azure OpenAI Studio** > **Management** > **Deployments** > and consult the model name column to confirm what model is currently associated with a given deployment name.
 
-          The questions, "What model are you running?" or "What is the latest model from OpenAI?" produce similar quality results to asking the model what the weather will be today. It might return the correct result, but purely by chance. On its own, the model has no real-world information other than what was part of its training/training data. In the case of GPT-4, as of August 2023 the underlying training data goes only up to September 2021. GPT-4 was not released until March 2023, so barring OpenAI releasing a new version with updated training data, or a new version that is fine-tuned to answer those specific questions, it's expected behavior for GPT-4 to respond that GPT-3 is the latest model release from OpenAI.
+          The questions, "What model are you running?" or "What is the latest model from OpenAI?" produce similar quality results to asking the model what the weather will be today. It might return the correct result, but purely by chance. On its own, the model has no real-world information other than what was part of its training/training data. In the case of GPT-4, as of August 2023 the underlying training data goes only up to September 2021. GPT-4 wasn't released until March 2023, so barring OpenAI releasing a new version with updated training data, or a new version that is fine-tuned to answer those specific questions, it's expected behavior for GPT-4 to respond that GPT-3 is the latest model release from OpenAI.
 
           If you wanted to help a GPT based model to accurately respond to the question "what model are you running?", you would need to provide that information to the model through techniques like [prompt engineering of the model's system message](/azure/ai-services/openai/concepts/advanced-prompt-engineering?pivots=programming-language-chat-completions), [Retrieval Augmented Generation (RAG)](/azure/machine-learning/concept-retrieval-augmented-generation?view=azureml-api-2) which is the technique used by [Azure OpenAI on your data](/azure/ai-services/openai/concepts/use-your-data) where up-to-date information is injected to the system message at query time, or via [fine-tuning](/azure/ai-services/openai/how-to/fine-tuning?pivots=programming-language-studio) where you could fine-tune specific versions of the model to answer that question in a certain way based on model version. 
 
@@ -164,7 +168,7 @@ sections:
       - question: |
           Will my web app be overwritten when I deploy the app again from the Azure AI Studio?
         answer:
-          Your app code will not be overwritten when you update your app. The app will be updated to use the Azure OpenAI resource, Azure Cognitive Search index (if you're using Azure OpenAI on your data), and model settings selected in the Azure OpenAI Studio without any change to the appearance or functionality. 
+          Your app code won't be overwritten when you update your app. The app will be updated to use the Azure OpenAI resource, Azure Cognitive Search index (if you're using Azure OpenAI on your data), and model settings selected in the Azure OpenAI Studio without any change to the appearance or functionality. 
   - name: Using your data
     questions:
       - question: |

articles/ai-services/openai/how-to/embeddings.md

@@ -48,7 +48,7 @@ embeddings = response['data'][0]['embedding']
 print(embeddings)
 ```
 
-# [OpenAI Python 1.0](#tab/python-new)
+# [OpenAI Python 1.x](#tab/python-new)
 
 ```python
 import os

articles/ai-services/openai/includes/chat-completion.md

@@ -69,7 +69,7 @@ JSON formatting added artificially for ease of reading.
 
 ```
 
-# [OpenAI Python 1.0](#tab/python-new)
+# [OpenAI Python 1.x](#tab/python-new)
 
 ```python
 import os
@@ -330,7 +330,7 @@ while True:
     print("\n" + response['choices'][0]['message']['content'] + "\n")
 ```
 
-# [OpenAI Python 1.0](#tab/python-new)
+# [OpenAI Python 1.x](#tab/python-new)
 
 ```python
 import os
@@ -452,7 +452,7 @@ while True:
     print("\n" + response['choices'][0]['message']['content'] + "\n")
 ```
 
-# [OpenAI Python 1.0](#tab/python-new)
+# [OpenAI Python 1.x](#tab/python-new)
 
 ```python
 import tiktoken

articles/ai-services/openai/includes/chatgpt-python.md

@@ -36,7 +36,7 @@ Install the OpenAI Python client library with:
 pip install openai==0.28.1
 ```
 
-# [OpenAI Python 1.0](#tab/python-new)
+# [OpenAI Python 1.x](#tab/python-new)
 
 ```console
 pip install openai
@@ -86,7 +86,7 @@ print(response)
 print(response['choices'][0]['message']['content'])
 ```
 
-# [OpenAI Python 1.0](#tab/python-new)
+# [OpenAI Python 1.x](#tab/python-new)
 
 You need to set the `model` variable to the deployment name you chose when you deployed the GPT-3.5-Turbo or GPT-4 models. Entering the model name will result in an error unless you chose a deployment name that is identical to the underlying model name.
 

articles/ai-services/openai/includes/python.md

@@ -35,7 +35,7 @@ Install the OpenAI Python client library with:
 pip install openai==0.28.1
 ```
 
-# [OpenAI Python 1.0](#tab/python-new)
+# [OpenAI Python 1.x](#tab/python-new)
 
 ```console
 pip install openai
@@ -95,7 +95,7 @@ text = response['choices'][0]['text'].replace('\n', '').replace(' .', '.').strip
 print(start_phrase+text)
 ```
 
-# [OpenAI Python 1.0](#tab/python-new)
+# [OpenAI Python 1.x](#tab/python-new)
 
 ```python
 import os

articles/ai-services/openai/reference.md

@@ -6,7 +6,7 @@ services: cognitive-services
 manager: nitinme
 ms.service: azure-ai-openai
 ms.topic: conceptual
-ms.date: 10/05/2023
+ms.date: 11/06/2023
 author: mrbullwinkle
 ms.author: mbullwin
 recommendations: false
@@ -392,7 +392,7 @@ The following parameters can be used inside of the `parameters` field inside of
 | `indexName` | string | Required | null | The search index to be used. |
 | `fieldsMapping` | dictionary | Optional | null | Index data column mapping.   |
 | `inScope` | boolean | Optional | true | If set, this value will limit responses specific to the grounding data content.  |
-| `topNDocuments` | number | Optional | 3 | Specifies the number of top-scoring documents from your data index used to generate responses. You might want to increase the value when you have short documents or want to provide more context. This is the *retrieved documents* parameter in Azure OpenAI studio.   |
+| `topNDocuments` | number | Optional | 5 | Specifies the number of top-scoring documents from your data index used to generate responses. You might want to increase the value when you have short documents or want to provide more context. This is the *retrieved documents* parameter in Azure OpenAI studio.   |
 | `queryType` | string | Optional | simple |  Indicates which query option will be used for Azure Cognitive Search. Available types: `simple`, `semantic`, `vector`, `vectorSimpleHybrid`, `vectorSemanticHybrid`. |
 | `semanticConfiguration` | string | Optional | null |  The semantic search configuration. Only required when `queryType` is set to `semantic` or  `vectorSemanticHybrid`.  |
 | `roleInformation` | string | Optional | null |  Gives the model instructions about how it should behave and the context it should reference when generating a response. Corresponds to the "System Message" in Azure OpenAI Studio. See [Using your data](./concepts/use-your-data.md#system-message) for more information. There’s a 100 token limit, which counts towards the overall token limit.|

articles/ai-services/policy-reference.md

@@ -1,7 +1,7 @@
 ---
 title: Built-in policy definitions for Azure AI services
 description: Lists Azure Policy built-in policy definitions for Azure AI services. These built-in policy definitions provide common approaches to managing your Azure resources.
-ms.date: 11/03/2023
+ms.date: 11/06/2023
 author: nitinme
 ms.author: nitinme
 ms.service: azure-ai-services

articles/ai-services/speech-service/embedded-speech.md

@@ -132,7 +132,7 @@ Follow these steps to install the Speech SDK for Java using Apache Maven:
             <dependency>
             <groupId>com.microsoft.cognitiveservices.speech</groupId>
             <artifactId>client-sdk-embedded</artifactId>
-            <version>1.32.1</version>
+            <version>1.33.0</version>
             </dependency>
         </dependencies>
     </project>
@@ -153,19 +153,19 @@ Be sure to use the `@aar` suffix when the dependency is specified in `build.grad
 
 ```
 dependencies {
-    implementation 'com.microsoft.cognitiveservices.speech:client-sdk-embedded:1.32.1@aar'
+    implementation 'com.microsoft.cognitiveservices.speech:client-sdk-embedded:1.33.0@aar'
 }
 ```
 ::: zone-end
 
 
 ## Models and voices
 
-For embedded speech, you'll need to download the speech recognition models for [speech to text](speech-to-text.md) and voices for [text to speech](text-to-speech.md). Instructions will be provided upon successful completion of the [limited access review](https://aka.ms/csgate-embedded-speech) process.
+For embedded speech, you need to download the speech recognition models for [speech to text](speech-to-text.md) and voices for [text to speech](text-to-speech.md). Instructions are provided upon successful completion of the [limited access review](https://aka.ms/csgate-embedded-speech) process.
 
 The following [speech to text](speech-to-text.md) models are available: de-DE, en-AU, en-CA, en-GB, en-IE, en-IN, en-NZ, en-US, es-ES, es-MX, fr-CA, fr-FR, hi-IN, it-IT, ja-JP, ko-KR, nl-NL, pt-BR, ru-RU, sv-SE, tr-TR, zh-CN, zh-HK, and zh-TW.
 
-All text to speech locales [here](language-support.md?tabs=tts) (except fa-IR, Persian (Iran)) are available out of box with either 1 selected female and/or 1 selected male voices. We welcome your input to help us gauge demand for additional languages and voices. 
+All text to speech locales [here](language-support.md?tabs=tts) (except fa-IR, Persian (Iran)) are available out of box with either 1 selected female and/or 1 selected male voices. We welcome your input to help us gauge demand for more languages and voices. 
 
 ## Embedded speech configuration
 
@@ -275,15 +275,15 @@ Hybrid speech with the `HybridSpeechConfig` object uses the cloud speech service
 
 With hybrid speech configuration for [speech to text](speech-to-text.md) (recognition models), embedded speech is used when connection to the cloud service fails after repeated attempts. Recognition may continue using the cloud service again if the connection is later resumed.
 
-With hybrid speech configuration for [text to speech](text-to-speech.md) (voices), embedded and cloud synthesis are run in parallel and the result is selected based on which one gives a faster response. The best result is evaluated on each synthesis request.
+With hybrid speech configuration for [text to speech](text-to-speech.md) (voices), embedded and cloud synthesis are run in parallel and the final result is selected based on response speed. The best result is evaluated again on each new synthesis request.
 
 ## Cloud speech
 
 For cloud speech, you use the `SpeechConfig` object, as shown in the [speech to text quickstart](get-started-speech-to-text.md) and [text to speech quickstart](get-started-text-to-speech.md). To run the quickstarts for embedded speech, you can replace `SpeechConfig` with `EmbeddedSpeechConfig` or `HybridSpeechConfig`. Most of the other speech recognition and synthesis code are the same, whether using cloud, embedded, or hybrid configuration.
 
 ## Embedded voices capabilities
 
-For embedded voices, it is essential to note that certain SSML tags may not be currently supported due to differences in the model structure. For detailed information regarding the unsupported SSML tags, please refer to the table below.
+For embedded voices, it is essential to note that certain SSML tags may not be currently supported due to differences in the model structure. For detailed information regarding the unsupported SSML tags, refer to the following table.
 
 | Level 1            | Level 2        | Sub values                                           | Support in embedded NTTS |
 |-----------------|-----------|-------------------------------------------------------|--------------------------|