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‎articles/ai-services/agents/faq.yml

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ms.service: azure-ai-agent-service
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ms.topic: faq
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ms.date: 12/20/2024
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ms.date: 01/15/2025
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ms.author: aahi
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author: aahill
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title: Azure AI Agent Service frequently asked questions
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* If you've enabled the Code Interpreter tool - for example your agent calls Code Interpreter simultaneously in two different threads, this would create two Code Interpreter sessions, each of which would be charged. Each session is active by default for one hour, which means that you would only pay this fee once if your user keeps giving instructions to Code Interpreter in the same thread for up to one hour.
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* File search is billed based on the vector storage used.
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For more information, see the [pricing page](https://azure.microsoft.com/pricing/details/cognitive-services/openai-service/).
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For more information, see the [pricing page](https://azure.microsoft.com/pricing/details/ai-foundry/).
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Is there any additional pricing or quota for using AI Agent Service?
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answer: |

‎articles/ai-services/agents/how-to/use-your-own-resources.md

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ms.service: azure-ai-agent-service
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ms.topic: how-to
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ms.date: 12/11/2024
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ms.date: 01/15/2025
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author: fosteramanda
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ms.custom: azure-ai-agents
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Use this article if you want to use the Azure Agent Service with resources you already have.
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> [!NOTE]
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> If you use an existing AI Services / Azure OpenAI Service resource, no model will be deployed. You can deploy a model to the resource after the agent setup is complete.
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> * If you use an existing AI Services / Azure OpenAI Service resource, no model will be deployed. You can deploy a model to the resource after the agent setup is complete.
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> * Make sure your Azure OpenAI resource and Azure AI Foundry project are in the same region.
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## Choose basic or standard agent setup
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‎articles/ai-services/document-intelligence/concept/add-on-capabilities.md

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ms.topic: conceptual
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ms.date: 11/19/2024
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ms.date: 01/15/2025
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monikerRange: '>=doc-intel-3.1.0'
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---
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|Add-on Capability| Add-On/Free|**2024-11-30 (GA)**|[`2023-07-31` (GA)](/rest/api/aiservices/document-models/analyze-document?view=rest-aiservices-2023-07-31&preserve-view=true&tabs=HTTP)|[`2022-08-31` (GA)](/rest/api/aiservices/document-models/analyze-document?view=rest-aiservices-v3.0%20(2022-08-31)&preserve-view=true&tabs=HTTP)|[v2.1 (GA)](/rest/api/aiservices/analyzer?view=rest-aiservices-v2.1&preserve-view=true)|
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|----------------|-----------|---|--|---|---|
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|Font property extraction|Add-On| ✔️| ✔️| n/a| n/a|
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|Formula extraction|Add-On| ✔️| ✔️| n/a| n/a|
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|High resolution extraction|Add-On| ✔️| ✔️| n/a| n/a|
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|Barcode extraction|Free| ✔️| ✔️| n/a| n/a|
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|Language detection|Free| ✔️| ✔️| n/a| n/a|
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|Key value pairs|Free| ✔️|n/a|n/a| n/a|
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|Query fields|Add-On*| ✔️|n/a|n/a| n/a|
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|Searhable pdf|Add-On**| ✔️|n/a|n/a| n/a|
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|Searchable PDF|Free| ✔️|n/a|n/a| n/a|
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|Font property extraction|**Add-On**| ✔️| ✔️| n/a| n/a|
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|Formula extraction|**Add-On**| ✔️| ✔️| n/a| n/a|
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|High resolution extraction|**Add-On**| ✔️| ✔️| n/a| n/a|
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|Query fields|**Add-On**| ✔️|n/a|n/a| n/a|
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✱ Add-On - Query fields are priced differently than the other add-on features. See [pricing](https://azure.microsoft.com/pricing/details/ai-document-intelligence/) for details. </br>
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** Add-On - Searchable pdf is available only with Read model as an add-on feature.

‎articles/ai-services/openai/includes/model-matrix/global-batch.md

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| **Region** | **gpt-4o**, **2024-05-13** | **gpt-4o**, **2024-08-06** | **gpt-4o**, **2024-11-20** | **gpt-4o-mini**, **2024-07-18** | **gpt-4**, **0613** | **gpt-4**, **turbo-2024-04-09** | **gpt-35-turbo**, **0613** | **gpt-35-turbo**, **1106** | **gpt-35-turbo**, **0125** |
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|:-------------------|:--------------------------:|:--------------------------:|:--------------------------:|:-------------------------------:|:-------------------:|:-------------------------------:|:--------------------------:|:--------------------------:|:--------------------------:|
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| australiaeast | ✅ | ✅ | - | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| brazilsouth | ✅ | ✅ | - | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| canadaeast | ✅ | ✅ | - | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| australiaeast | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| brazilsouth | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| canadaeast | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| eastus | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| eastus2 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| francecentral | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| germanywestcentral | ✅ | ✅ | - | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| japaneast | ✅ | ✅ | - | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| koreacentral | ✅ | ✅ | - | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| northcentralus | ✅ | ✅ | - | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| norwayeast | ✅ | ✅ | - | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| polandcentral | ✅ | ✅ | - | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| southafricanorth | ✅ | ✅ | - | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| germanywestcentral | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| japaneast | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| koreacentral | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| northcentralus | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| norwayeast | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| polandcentral | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| southafricanorth | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| southcentralus | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| southindia | ✅ | ✅ | - | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| southindia | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| swedencentral | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| switzerlandnorth | ✅ | ✅ | - | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| uksouth | ✅ | ✅ | - | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| switzerlandnorth | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| uksouth | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| westeurope | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| westus | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| westus3 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |
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| westus3 | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ |

‎articles/ai-services/speech-service/how-to-recognize-speech.md

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‎articles/ai-services/speech-service/includes/how-to/recognize-speech/cpp.md

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Some of the limitations of semantic segmentation are as follows:
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- You need the Speech SDK version 1.41 or later to use semantic segmentation.
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- Semantic segmentation is only intended for use in [continuous recognition](#continuous-recognition). This includes scenarios such as transcription and captioning. It shouldn't be used in the single recognition and dictation mode.
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- Semantic segmentation is only intended for use in [continuous recognition](#continuous-recognition). This includes scenarios such as dictation and captioning. It shouldn't be used in the single recognition mode or interactive scenarios.
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- Semantic segmentation isn't available for all languages and locales. Currently, semantic segmentation is only available for English (en) locales such as en-US, en-GB, en-IN, and en-AU.
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- Semantic segmentation doesn't yet support confidence scores and NBest lists. As such, we don't recommend semantic segmentation if you're using confidence scores or NBest lists.

‎articles/ai-services/speech-service/includes/how-to/recognize-speech/csharp.md

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Some of the limitations of semantic segmentation are as follows:
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- You need the Speech SDK version 1.41 or later to use semantic segmentation.
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- Semantic segmentation is only intended for use in [continuous recognition](#use-continuous-recognition). This includes scenarios such as transcription and captioning. It shouldn't be used in the single recognition and dictation mode.
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- Semantic segmentation is only intended for use in [continuous recognition](#use-continuous-recognition). This includes scenarios such as dictation and captioning. It shouldn't be used in the single recognition mode or interactive scenarios.
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- Semantic segmentation isn't available for all languages and locales. Currently, semantic segmentation is only available for English (en) locales such as en-US, en-GB, en-IN, and en-AU.
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- Semantic segmentation doesn't yet support confidence scores and NBest lists. As such, we don't recommend semantic segmentation if you're using confidence scores or NBest lists.

‎articles/ai-services/speech-service/includes/how-to/recognize-speech/java.md

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Some of the limitations of semantic segmentation are as follows:
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- You need the Speech SDK version 1.41 or later to use semantic segmentation.
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- Semantic segmentation is only intended for use in [continuous recognition](#use-continuous-recognition). This includes scenarios such as transcription and captioning. It shouldn't be used in the single recognition and dictation mode.
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- Semantic segmentation is only intended for use in [continuous recognition](#use-continuous-recognition). This includes scenarios such as dictation and captioning. It shouldn't be used in the single recognition mode or interactive scenarios.
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- Semantic segmentation isn't available for all languages and locales. Currently, semantic segmentation is only available for English (en) locales such as en-US, en-GB, en-IN, and en-AU.
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- Semantic segmentation doesn't yet support confidence scores and NBest lists. As such, we don't recommend semantic segmentation if you're using confidence scores or NBest lists.

‎articles/ai-services/speech-service/includes/how-to/recognize-speech/python.md

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Some of the limitations of semantic segmentation are as follows:
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- Semantic segmentation is only intended for use in [continuous recognition](#use-continuous-recognition). This includes scenarios such as transcription and captioning. It shouldn't be used in the single recognition and dictation mode.
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- Semantic segmentation is only intended for use in [continuous recognition](#use-continuous-recognition). This includes scenarios such as dictation and captioning. It shouldn't be used in the single recognition mode or interactive scenarios.
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- Semantic segmentation isn't available for all languages and locales. Currently, semantic segmentation is only available for English (en) locales such as en-US, en-GB, en-IN, and en-AU.
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- Semantic segmentation doesn't yet support confidence scores and NBest lists. As such, we don't recommend semantic segmentation if you're using confidence scores or NBest lists.

‎articles/ai-studio/reference/reference-model-inference-api.md

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* [Get info](reference-model-inference-info.md): Returns the information about the model deployed under the endpoint.
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* [Text embeddings](reference-model-inference-embeddings.md): Creates an embedding vector representing the input text.
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* [Text completions](reference-model-inference-completions.md): Creates a completion for the provided prompt and parameters.
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* [Chat completions](reference-model-inference-chat-completions.md): Creates a model response for the given chat conversation.
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* [Image embeddings](reference-model-inference-images-embeddings.md): Creates an embedding vector representing the input text and image.
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