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

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### Files
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Files can be uploaded via Studio, or programmatically. The `file_ids` parameter is required to give tools like `code_interpreter` access to files. When using the File upload endpoint, you must have the `purpose` set to assistants to be used with the Assistants API.
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Files can be uploaded via Studio, or programmatically. The `file_ids` parameter is required to give tools like `code_interpreter` access to files. When using the File upload endpoint, you must have the `purpose` set to `assistants` to be used with the Assistants API.
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## Assistants playground
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articles/ai-studio/how-to/fine-tune-serverless.md

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Once your model is fine-tuned, you can deploy it and use it in your own application, in the playground, or in prompt flow. For more information on how to use deployed models, see [How to use Mistral premium chat models](./deploy-models-mistral.md).
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---
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## Supported enterprise scenarios for finetuning
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Several enterprise scenarios are supported for MaaS finetuning. The table below outlines the supported configurations for user storage networking and authentication to ensure smooth operation within enterprise scenarios:
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>[!Note]
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>- Data connections auth can be changed via AI Studio by clicking on the datastore connection which your dataset is stored in, and navigating to the **Access details** > **Authentication Method** setting.
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>- Storage auth can be changed in Azure Storage > **Settings** > **Configurations** page > **Allow storage account key access**.
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>- Storage networking can be changed in Azure Storage > **Networking** page.
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| **Storage Networking** | **Storage Auth** | **Data Connection Auth** | **Support** |
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| ------------------------------------------------------------ | ------------------------------ | --------------------------------- | ----------------------- |
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| Public Network Access = Enabled | Account key enabled | SAS/Account Key | Yes, UX and SDK |
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| Public Network Access = Enabled | Account key disabled | Entra-Based Auth (Credentialless) | Yes, UX and SDK <br><br> *Note:* for UX, you may need to add Storage Blob Data Reader or Storage Blob Data Contributor for your user ID on the storage account, or change the connection's authentication to use Account key/SAS token | | | |
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| Enabled from selected virtual networks and IP addresses | Account key enabled | Account key | Yes, UX and SDK <br><br> *Note:*: for UX, the IP of the compute running the browser must be in the selected list |
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| Enabled from selected virtual networks and IP addresses | Account key enabled | SAS | Yes, UX and SDK <br><br> *Note:*: for UX, the IP of the compute running the browser must be in the selected list |
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| Enabled from selected virtual networks and IP addresses | Account key disabled | Entra-Based Auth (Credentialless) | Yes, UX and SDK. <br><br>*Note:* for UX, you may need to add Storage Blob Data Reader or Storage Blob Data Contributor for your user ID on the storage account, or change the connection's authentication to use Account key/SAS token. Also ensure the IP of the compute running the browser must be in the selected list | | | |
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| Public Network Access = Disabled | Account key enabled | SAS/Account Key | Yes, UX and SDK. <br><br> *Note:* for UX data upload and submission to work, the workspace _needs to be accessed from within the Vnet_ that has appropriate access to the storage |
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| Public Network Access = Disabled | Account key disabled | Entra-Based Auth (Credentialless) | Yes, UX and SDK. <br><br> *Note:* for UX data upload and submission to work, the workspace _needs to be accessed from within the Vnet_ that has appropriate access to the storage |
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The scenarios above should work in a Managed Vnet workspace as well. See setup of Managed Vnet AI Studio hub here: [How to configure a managed network for Azure AI Foundry hubs](./configure-managed-network.md)
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Customer-Managed Keys (CMKs) is **not** a supported enterprise scenario with MaaS finetuning.
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Issues finetuning with unique network setups on the workspace and storage usually points to a networking setup issue.
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articles/search/vector-search-how-to-quantization.md

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- Binary quantization converts floats into binary bits, which takes up 1 bit. This results in up to 28 times reduced vector index size.
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>[!Note]
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> While free services support quantization, they may not demonstrate the full storage savings due to the limited storage quota.
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## Add "compressions" to a search index
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The following example shows a partial index definition with a fields collection that includes a vector field, and a `vectorSearch.compressions` section.

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