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articles/ai-services/computer-vision/how-to/video-retrieval.md

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After you add video files to the index, the ingestion process starts. It might take some time depending on the size and number of files. To ensure the ingestion is complete before performing searches, you can use the **[Get Ingestion](../reference-video-search.md)** API to check the status. Wait for this call to return `"state" = "Completed"` before proceeding to the next step.
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```bash
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curl.exe -v _X GET "https://<YOUR_ENDPOINT_URL>/computervision/retrieval/indexes/my-video-index/ingestions?api-version=2023-05-01-preview&$top=20" -H "ocp-apim-subscription-key: <YOUR_SUBSCRIPTION_KEY>"
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curl.exe -v -X GET "https://<YOUR_ENDPOINT_URL>/computervision/retrieval/indexes/my-video-index/ingestions?api-version=2023-05-01-preview&$top=20" -H "ocp-apim-subscription-key: <YOUR_SUBSCRIPTION_KEY>"
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```
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**Response:**
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To perform a search using the "vision" feature, use the [Search By Text](../reference-video-search.md) API with the `vision` filter, specifying the query text and any other desired filters.
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```bash
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POST -v -X "https://<YOUR_ENDPOINT_URL>/computervision/retrieval/indexes/my-video-index:queryByText?api-version=2023-05-01-preview" -H "Ocp-Apim-Subscription-Key: <YOUR_SUBSCRIPTION_KEY>" -H "Content-Type: application/json" --data-ascii "
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curl.exe -v -X POST "https://<YOUR_ENDPOINT_URL>/computervision/retrieval/indexes/my-video-index:queryByText?api-version=2023-05-01-preview" -H "Ocp-Apim-Subscription-Key: <YOUR_SUBSCRIPTION_KEY>" -H "Content-Type: application/json" --data-ascii "
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{
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'queryText': 'a man with black hoodie',
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'filters': {
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articles/ai-services/document-intelligence/quickstarts/try-document-intelligence-studio.md

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1. Start by creating a new CORS entry in the Blob service.
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1. Set the **Allowed origins** to `https://formrecognizer.appliedai.azure.com`.
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1. Set the **Allowed origins** to `https://documentintelligence.ai.azure.com`.
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:::image type="content" source="../media/quickstarts/cors-updated-image.png" alt-text="Screenshot that shows CORS configuration for a storage account.":::
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articles/ai-services/language-service/language-studio.md

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If you're sending conversational text to supported features in Language Studio, be aware of the following input requirements:
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* The text you send must be a conversational dialog between two or more participants.
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* Each line must start with the name of the participant, followed by a `:`, and followed by what they say.
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* Except issue/resolution summarization, each line must start with the name of the participant, followed by a `:`, and followed by what they say.
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* To use issue and resolution aspects in conversation summarization, each line must start with the role of the participant between "Customer" and "Agent" spelled in English, followed by a ':' before what they say in any supported languages. Names of participants, followed by the role, are optional.
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* Each participant must be on a new line. If multiple participants' utterances are on the same line, it will be processed as one line of the conversation.
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See the following example for how you should structure conversational text you want to send.

articles/ai-services/language-service/question-answering/concepts/confidence-score.md

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|Score Value|Score Meaning|Example Query|
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|--|--|--|
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|0.90 - 1.00|A near exact match of user query and a KB question|
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|> 70|High confidence - typically a good answer that completely answers the user's query|
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|> 0.70|High confidence - typically a good answer that completely answers the user's query|
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|0.50 - 0.70|Medium confidence - typically a fairly good answer that should answer the main intent of the user query|
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|0.30 - 0.50|Low confidence - typically a related answer, that partially answers the user's intent|
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|< 0.30|Very low confidence - typically does not answer the user's query, but has some matching words or phrases |

articles/ai-services/language-service/summarization/overview.md

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Conversation summarization supports the following features:
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* **Issue/resolution summarization**: A call center specific feature that gives a summary of issues and resolutions in conversations between customer-service agents and your customers.
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* **Chapter title summarization**: Gives suggested chapter titles of the input conversation.
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* **Narrative summarization**: Gives call notes, meeting notes or chat summaries of the input conversation.
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* **Chapter title summarization**: Segments a conversation into chapters based on the topics discussed in the conversation, and gives suggested chapter titles of the input conversation.
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* **Recap**: Summarizes a conversation into a brief paragraph.
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* **Narrative summarization**: Generates detail call notes, meeting notes or chat summaries of the input conversation.
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* **Follow-up tasks**: Gives a list of follow-up tasks discussed in the input conversation.
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## When to use issue and resolution summarization
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articles/ai-services/language-service/text-analytics-for-health/includes/features.md

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* Certainty
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* Conditionality
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* Association
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* Temporality
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> [!div class="mx-imgBorder"]
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> ![Text Analytics for health negation](../media/call-api/assertions.png)

articles/ai-services/language-service/text-analytics-for-health/language-support.md

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## Hosted API Service
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The hosted API service supports the English, Spanish, French, German, Italian, Portuguese and Hebrew languages.
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The hosted API service supports the English, Spanish, French, German, Italian, and Portuguese languages.
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When structuring the API request, the relevant language tags must be added for these languages:
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German – “de”
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Hebrew – “he”
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```
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```json
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]
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```
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## Details of the supported container tags:
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| Language Code | Featured Tag | Specific Tag |
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|:--------------------|:-------------------:|:------------------:|
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| `en` | latest | 3.0.59413252-onprem-amd64 |
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| `en`, `es`, `it`, `fr`, `de`, `pt` | latin | 3.0.60903415-latin-onprem-amd64 |
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| `he` | semitic | 3.0.60903415-semitic-onprem-amd64 |
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articles/ai-services/language-service/text-analytics-for-health/overview.md

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[!INCLUDE [Text Analytics for health](includes/features.md)]
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Text Analytics for health can receive unstructured text in English as part of its generally available offering. Additional languages such as German, French, Italian, Spanish, Portuguese, and Hebrew are currently supported in preview.
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Text Analytics for health can receive unstructured text in English, German, French, Italian, Spanish, Portuguese, and Hebrew.
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Additionally, Text Analytics for health can return the processed output using the Fast Healthcare Interoperability Resources (FHIR) structure which enables the service's integration with other electronic health systems.
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articles/ai-services/openai/toc.yml

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href: ./concepts/fine-tuning-considerations.md
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- name: Red teaming large language models (LLMs)
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- name: Image provenance
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- name: Content credentials
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href: ./concepts/content-credentials.md
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- name: Intro to prompt engineering
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href: ./concepts/prompt-engineering.md

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