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OneDrive can be used as the storage backend for personal and workspace files in place of Azure Blob Storage. When enabled, every user’s uploaded files (workspace uploads and personal files attached inside shared chats) are written into a dedicated folder in their own OneDrive for Business, then indexed into a single shared Azure AI Search index that is security-trimmed per user via an UserIds ACL filter.
ℹ️ This is a different feature from the OneDrive Tools that flow agents use to list/search/upload files on behalf of a user. Those tools use delegated (OBO) permissions and are documented under Tool Setup Guide → OneDrive Tools. The setup below is for the personal-files storage backend only.

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What it changes

AspectDefault (Azure Files)OneDrive backend
Where workspace files liveAzure Blob Private/ per userUser’s OneDrive at {oneDriveFolderName}/Workspace/
Where personal-files-in-shared-chat liveAzure Blob Private/ per userUser’s OneDrive at {oneDriveFolderName}/AttachedFiles/{chatId}/
Search indexOne per user (auto-provisioned)One shared index (oneDriveSharedIndexName, default personal-onedrive-shared) with UserIds ACL filter
Document text extractionAzure Search skillsetsServer-side via Azure Document Intelligence + chunking + embeddings
Indexing triggerIndexer scheduleOn-demand on every upload (immediate)
Retention / cleanuppersonalFolderRetentionInHours purge job (Blob)OneDrive purge job removes inactive users’ folders and their docs from the shared index
External / guest usersSupportedNot supported — external users automatically fall back to Azure Blob (their tenant’s OneDrive is unreachable)

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Prerequisites

  1. The Server App Registration (graphClientId) must be configured with a client secret (graphClientSecret). Managed Identity is not supported for OneDrive — it requires client-credentials flow to call users/{userId}/drive/... endpoints.
  2. An Azure AI Search endpoint configured in Admin → AI Search Endpoints ([#/admin/search], setting key aiSearchEndpoints).
  3. A text embedding endpoint (or textEmbeddingModelEndpointId on the search endpoint) — required to generate vectors during indexing.
  4. An Azure Document Intelligence resource (or compatible documentIntelligenceEndpoint on the search endpoint) — required to extract text from PDF/Office/image files. Plain-text and code files bypass Document Intelligence.

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Step 1 — Grant Graph application permission

In the Azure Portal → App Registrations, open the Server App (graphClientId):
PermissionTypeWhy
Files.ReadWrite.AllApplicationLets the server list, upload, index, and purge files in any user’s OneDrive app folder
Add the permission and click “Grant admin consent for [tenant]”. This must be the server app, not the client SPA app.
The app folder scoping ({oneDriveFolderName}) is enforced at the application layer — Files.ReadWrite.All itself grants tenant-wide access. Treat the server app secret accordingly.

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Step 2 — Configure Findable

In Admin → Personal Workspace ([#/admin/workspace], setting key adminNav.personalWorkspace) → Personal File Location, switch the backend:
SettingRequired valueNotes
personalFileLocationOneDriveDefault is AzureFiles
oneDriveFolderNamee.g. AIAssistantDefault AIAssistant. This is the root folder created in each user’s OneDrive.
oneDriveSharedIndexNamee.g. personal-onedrive-sharedDefault personal-onedrive-shared. The shared, ACL-filtered Azure AI Search index.
The shared index is created lazily on the first upload — no manual provisioning step is required.

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Step 3 — (Optional) Enable client-side direct uploads

For drag-and-drop uploads that go straight from the browser to OneDrive (bypassing the server), also add Files.ReadWrite (Delegated) to the Client App Registration and grant admin consent. Without this, uploads still work — they just go through the server instead.

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Step 4 — Verify

  1. Sign in as a tenant user, open the workspace, and upload a small file.
  2. In the user’s OneDrive, confirm the folder layout: 
    {oneDriveFolderName}/
├── Workspace/                  ← workspace uploads
└── AttachedFiles/{chatId}/     ← personal files attached inside shared chats
  3. In Admin → Health ([#/admin/about]), confirm the Graph Files.ReadWrite.All scope is healthy.
  4. Run a workspace query — the document should be retrievable. Repeat as a different user and confirm the second user cannot see the first user’s content (ACL trim via UserIds).

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How indexing & ACL work

  • On every upload, the server downloads the file, extracts text (Document Intelligence for PDF/Office/images, direct UTF-8 for text/code), chunks it (4 KB chunks, 200-char overlap), generates embeddings, and upserts into the shared index.
  • Each indexed chunk carries UserIds: [userOid]. Every query is forced to include UserIds/any(u: u eq '{currentUserOid}') plus a path-prefix filter (onedrive://{userOid}/Workspace/... for workspace queries, AttachedFiles/{chatId}/ for chat-attached files).
  • If the server cannot resolve a caller’s OID, the query is rejected rather than falling back to an unscoped search.
  • A background purge job removes documents from the shared index (and the OneDrive folder) for users inactive longer than personalFolderRetentionInHours.

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Limitations

  • External / guest users (#EXT# in UPN) are excluded — they automatically use the Azure Blob fallback even when personalFileLocation = OneDrive.
  • Managed-identity Graph auth is not supported for OneDrive — graphClientSecret is required.
  • Files indexed before switching backends are not migrated. Switching personalFileLocation only affects new uploads.