Merge pull request #2223 from MicrosoftDocs/main

1/9/2025 AM Publish

Author: Taojunshen

articles/ai-services/document-intelligence/language-support/prebuilt.md

@@ -207,7 +207,7 @@ Azure AI Document Intelligence models provide multilingual document processing s
 | • Spanish (`es`) |Spain (`es`)|
 | • Swedish (`sv`) | Sweden (`se`)|
 | • Thai (`th`) | Thailand (`th`)|
-| • Turkish (`tr`) | Turkey (`tr`)|
+| • Turkish (`tr`) | Türkiye (`tr`)|
 | • Ukrainian (`uk`) | Ukraine (`uk`)|
 | • Vietnamese (`vi`) | Vietnam (`vi`)|
 

articles/ai-services/language-service/language-detection/language-support.md

@@ -187,7 +187,7 @@ If you have content expressed in a less frequently used language, you can try La
 | Kannada                               | `kn`        | `Latn`, `Knda` |
 | Malayalam                             | `ml`        | `Latn`, `Mlym` |
 | Marathi	                            | `mr`        | `Latn`, `Deva` |
-| Oriya                                 | `or`        | `Latn`, `Orya` |
+| Odia                                  | `or`        | `Latn`, `Orya` |
 | Punjabi                               | `pa`        | `Latn`, `Guru` |
 | Tamil                                 | `ta`        | `Latn`, `Taml` |
 | Telugu                                | `te`        | `Latn`, `Telu` |

articles/ai-services/metrics-advisor/how-tos/onboard-your-data.md

@@ -115,7 +115,7 @@ Consider the following scenarios:
 
 * *"My data has already rolled up and the dimension value is represented by: NULL or Empty (Default), NULL only, Others."*
 
-    This option means Metrics Advisor doesn't need to roll up the data because the rows are already summed. For example, if you select *NULL only*, then the second data row in the below example will be seen as an aggregation of all countries and language *EN-US*; the fourth data row which has an empty value for *Country* however will be seen as an ordinary row which might indicate incomplete data.
+    This option means Metrics Advisor doesn't need to roll up the data because the rows are already summed. For example, if you select *NULL only*, then the second data row in the below example will be seen as an aggregation of all countries/regions and language *EN-US*; the fourth data row which has an empty value for *Country* however will be seen as an ordinary row which might indicate incomplete data.
 
     | Country/Region | Language | Income |
     |---------|----------|--------|

articles/ai-services/openai/assistants-reference.md

@@ -42,6 +42,62 @@ Create an assistant with a model and instructions.
 | response_format | string or object | Optional | Specifies the format that the model must output. Compatible with GPT-4 Turbo and all GPT-3.5 Turbo models since gpt-3.5-turbo-1106. Setting this parameter to `{ "type": "json_object" }` enables JSON mode, which guarantees the message the model generates is valid JSON. Importantly, when using JSON mode, you must also instruct the model to produce JSON yourself using a system or user message. Without this instruction, the model may generate an unending stream of whitespace until the generation reaches the token limit, resulting in a long-running and seemingly "stuck" request. Additionally, the message content may be partially cut off if you use `finish_reason="length"`, which indicates the generation exceeded `max_tokens` or the conversation exceeded the max context length. |
 | tool_resources | object | Optional | A set of resources that are used by the assistant's tools. The resources are specific to the type of tool. For example, the `code_interpreter` tool requires a list of file IDs, while the `file_search` tool requires a list of vector store IDs. |
 
+### response_format types
+
+**string**
+
+`auto` is the default value.
+
+**object**
+
+Possible `type` values: `text`, `json_object`, `json_schema`.
+
+***json_schema***
+
+| Name | Type | Description | Default | Required/Optional |
+|---  |---   |---       |--- |--- |
+| `description` | string | A description of what the response format is for, used by the model to determine how to respond in the format. |  | Optional |
+| `name` | string | The name of the response format. Must be a-z, A-Z, 0-9, or contain underscores and dashes, with a maximum length of 64. |  | Required |
+| `schema` | object | The schema for the response format, described as a JSON Schema object. |  | Optional |
+| `strict` | boolean or null | Whether to enable strict schema adherence when generating the output. If set to true, the model will always follow the exact schema defined in the `schema` field. Only a subset of JSON Schema is supported when `strict` is `true`. | false | Optional |
+
+### tool_resources properties
+
+**code_interpreter**
+
+| Name | Type | Description | Default |
+|---  |---   |---       |--- |
+| `file_ids` | array | A list of file IDs made available to the code_interpreter tool. There can be a maximum of 20 files associated with the tool. | `[]` |
+
+**file_search**
+
+| Name | Type | Description | Required/Optional |
+|---  |---   |---       |--- |
+| `vector_store_ids` | array | The vector store attached to this thread. There can be a maximum of 1 vector store attached to the thread. | Optional | 
+| `vector_stores` | array | A helper to create a vector store with file_ids and attach it to this thread. There can be a maximum of 1 vector store attached to the thread. | Optional |
+
+***vector_stores***
+
+| Name | Type | Description | Required/Optional |
+|---  |---   |---       |--- |
+| `file_ids` | array | A list of file IDs to add to the vector store. There can be a maximum of 10000 files in a vector store. | Optional | 
+| `chunking_strategy` | object | The chunking strategy used to chunk the file(s). If not set, will use the auto strategy. | Optional |
+| `metadata` | map | Set of 16 key-value pairs that can be attached to a vector store. This can be useful for storing additional information about the vector store in a structured format. Keys can be a maximum of 64 characters long and values can be a maximum of 512 characters long. | Optional |
+
+***chunking_strategy***
+
+| Name | Type | Description | Required/optional | 
+|---  |---   |---       |---|
+| `Auto Chunking Strategy` | object | The default strategy. This strategy currently uses a `max_chunk_size_tokens` of `800` and `chunk_overlap_tokens` of `400`. `type` is always `auto` | Required |
+| `Static Chunking Strategy` | object | `type` Always `static`  | Required |
+
+***Static Chunking Strategy***
+
+| Name | Type | Description | Required/Optional |
+|---  |---   |---       |--- |
+| `max_chunk_size_tokens` | integer | The maximum number of tokens in each chunk. The default value is `800`. The minimum value is `100` and the maximum value is `4096`. | Required |
+| `chunk_overlap_tokens` | integer | The number of tokens that overlap between chunks. The default value is `400`. Note that the overlap must not exceed half of `max_chunk_size_tokens`. | Required |
+
 ### Returns
 
 An [assistant](#assistant-object) object.

articles/ai-services/openai/concepts/models.md

@@ -34,7 +34,7 @@ The Azure OpenAI `o1` and `o1-mini` models are specifically designed to tackle r
 
 |  Model ID  | Description | Max Request (tokens) | Training Data (up to)  |
 |  --- |  :--- |:--- |:---: |
-| `o1` (2024-12-17) | The most capable model in the o1 series, offering enhanced reasoning abilities. <br> **Request access: [limited access model application](https://aka.ms/OAI/o1access)** <br> - Structured outputs<br> - Text, image processing <br> - Functions/Tools <br> | Input: 200,000 <br> Output: 100,000 | |  
+| `o1` (2024-12-17) | The most capable model in the o1 series, offering [enhanced reasoning abilities](../how-to/reasoning.md). <br> - Structured outputs<br> - Text, image processing <br> - Functions/Tools <br> <br> **Request access: [limited access model application](https://aka.ms/OAI/o1access)** | Input: 200,000 <br> Output: 100,000 | Oct 2023 |  
 |`o1-preview` (2024-09-12) | Older preview version | Input: 128,000  <br> Output: 32,768 | Oct 2023 |
 | `o1-mini` (2024-09-12) | A faster and more cost-efficient option in the o1 series, ideal for coding tasks requiring speed and lower resource consumption.| Input: 128,000  <br> Output: 65,536 | Oct 2023 |
 

articles/ai-services/speech-service/includes/release-notes/release-notes-tts.md

@@ -166,7 +166,7 @@ Added support and general availability for new voices in the following locales:
 | Locale (BCP-47) | Language | Text to speech voices |
 | ----- | ----- | ----- |
 | `as-IN` | Assamese (India) | `as-IN-YashicaNeural` (Female)<br/>`as-IN-PriyomNeural` (Male) |
-| `or-IN` | Oriya (India) | `or-IN-SubhasiniNeural` (Female)<br/>`or-IN-SukantNeural` (Male) |
+| `or-IN` | Odia (India) | `or-IN-SubhasiniNeural` (Female)<br/>`or-IN-SukantNeural` (Male) |
 | `pa-IN` | Punjabi (India) | `pa-IN-OjasNeural` (Male)<br/>`pa-IN-VaaniNeural` (Female) |
 
 The one voice in this table is generally available and supports only the 'en-IN' locale.
@@ -293,7 +293,7 @@ Text to speech avatar is now generally available. For more information, see [tex
   | `pt-PT`| Portuguese (Portugal)|
   | `sv-SE`| Swedish (Sweden)|
   | `th-TH`| Thai (Thailand)|
-  | `tr-TR`| Turkish (Turkey)|
+  | `tr-TR`| Turkish (Türkiye)|
   | `zh-CN`| Chinese (Mandarin, Simplified)|
   | `zh-HK`| Chinese (Cantonese, Traditional)|
   | `zh-TW`| Chinese (Taiwanese Mandarin, Traditional)|
@@ -306,8 +306,8 @@ Text to speech avatar is now generally available. For more information, see [tex
 
   | Locale | Language    | Text to speech voices  |
   |--------|-----------------|-------------------------|
-  | `or-IN`  | Oriya (India)   | `or-IN-SubhasiniNeural` (Female) |
-  | `or-IN`  | Oriya (India)   | `or-IN-SukantNeural` (Male)      | 
+  | `or-IN`  | Odia (India)   | `or-IN-SubhasiniNeural` (Female) |
+  | `or-IN`  | Odia (India)   | `or-IN-SukantNeural` (Male)      | 
   | `pa-IN`  | Punjabi (India) | `pa-IN-VaaniNeural` (Female)     |
   | `pa-IN`  | Punjabi (India) | `pa-IN-OjasNeural` (Male)        | 
   | `as-IN`  | Assamese (India)| `as-IN-YashicaNeural` (Female)   | 

articles/ai-studio/how-to/deploy-models-cohere-command.md

@@ -2129,7 +2129,7 @@ For more examples of how to use Cohere models, see the following examples and tu
 | Description                               | Language          | Sample                                                          |
 |-------------------------------------------|-------------------|-----------------------------------------------------------------|
 | Web requests                              | Bash              | [Command-R](https://aka.ms/samples/cohere-command-r/webrequests) - [Command-R+](https://aka.ms/samples/cohere-command-r-plus/webrequests) |
-| Azure AI Inference package for JavaScript | JavaScript        | [Link](https://aka.ms/azsdk/azure-ai-inference/javascript/samples)  |
+| Azure AI Inference package for JavaScript | JavaScript        | [Link](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/ai/ai-inference-rest/samples)  |
 | Azure AI Inference package for Python     | Python            | [Link](https://aka.ms/azsdk/azure-ai-inference/python/samples)      |
 | OpenAI SDK (experimental)                 | Python            | [Link](https://aka.ms/samples/cohere-command/openaisdk)             |
 | LangChain                                 | Python            | [Link](https://aka.ms/samples/cohere/langchain)                     |

articles/ai-studio/how-to/deploy-models-cohere-embed.md

@@ -631,7 +631,7 @@ Cohere Embed V3 models can optimize the embeddings based on its use case.
 | Description                               | Language          | Sample                                                          |
 |-------------------------------------------|-------------------|-----------------------------------------------------------------|
 | Web requests                              | Bash              | [cohere-embed.ipynb](https://aka.ms/samples/embed-v3/webrequests) |
-| Azure AI Inference package for JavaScript | JavaScript        | [Link](https://aka.ms/azsdk/azure-ai-inference/javascript/samples)  |
+| Azure AI Inference package for JavaScript | JavaScript        | [Link](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/ai/ai-inference-rest/samples)  |
 | Azure AI Inference package for Python     | Python            | [Link](https://aka.ms/azsdk/azure-ai-inference/python/samples)      |
 | OpenAI SDK (experimental)                 | Python            | [Link](https://aka.ms/samples/cohere-embed/openaisdk)             |
 | LangChain                                 | Python            | [Link](https://aka.ms/samples/cohere-embed/langchain)                     |

articles/ai-studio/how-to/deploy-models-jais.md

@@ -1169,7 +1169,7 @@ For more examples of how to use Jais models, see the following examples and tuto
 
 | Description                               | Language          | Sample                                                          |
 |-------------------------------------------|-------------------|-----------------------------------------------------------------|
-| Azure AI Inference package for JavaScript | JavaScript        | [Link](https://aka.ms/azsdk/azure-ai-inference/javascript/samples)  |
+| Azure AI Inference package for JavaScript | JavaScript        | [Link](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/ai/ai-inference-rest/samples)  |
 | Azure AI Inference package for Python     | Python            | [Link](https://aka.ms/azsdk/azure-ai-inference/python/samples)  |
 
 ## Cost and quota considerations for Jais models deployed as serverless API endpoints

articles/ai-studio/how-to/deploy-models-mistral-nemo.md

@@ -2016,7 +2016,7 @@ For more examples of how to use Mistral models, see the following examples and t
 | Description                               | Language          | Sample                                                          |
 |-------------------------------------------|-------------------|-----------------------------------------------------------------|
 | CURL request                              | Bash              | [Link](https://aka.ms/mistral-large/webrequests-sample)         |
-| Azure AI Inference package for JavaScript | JavaScript        | [Link](https://aka.ms/azsdk/azure-ai-inference/javascript/samples)  |
+| Azure AI Inference package for JavaScript | JavaScript        | [Link](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/ai/ai-inference-rest/samples)  |
 | Azure AI Inference package for Python     | Python            | [Link](https://aka.ms/azsdk/azure-ai-inference/python/samples)  |
 | Python web requests                       | Python            | [Link](https://aka.ms/mistral-large/webrequests-sample)         |
 | OpenAI SDK (experimental)                 | Python            | [Link](https://aka.ms/mistral-large/openaisdk)                  |