OneDrive Collection

SearchBlox provides a OneDrive Collection that allows you to index files and folders stored in OneDrive or SharePoint. This feature enables SearchBlox to securely connect to your Microsoft account using Azure AD authentication, crawl selected drives or directories, and retrieve document content. The indexed data can then be searched efficiently, making it easier to access, organize, and manage files across your OneDrive or SharePoint environment.

Creating a Onedrive Collection

You can create a Onedrive Collection by following these steps:

• Log in to the Admin Console, go to the Collections tab, and click Create or the “+” icon.

• Select Onedrive Collection as the collection type.

• Enter a unique name for the collection. The name must contain 3–36 alphanumeric characters, and only underscores (_) are allowed.

• Enable or disable RAG (Retrieval Augmented Generation) depending on your requirement. Enable it if the collection will be used for AI-powered search or chatbot responses.

• Enable Knowledge Graph if you want SearchBlox to extract entities and relationships from the documents in the collection.

• Choose whether the collection should be Private or Public. Enable Private Collection Access to restrict the collection to authenticated users only.

• Configure Collection Encryption if you want to encrypt document content or specific metadata fields.

• Select the Collection Language based on the language used in the documents. The default language is English.

• Click Create to create the OneDrive Collection.

• After the collection is created, you will be redirected to the OneDrive Settings / Authentication section to configure the connection and access details.

Configuring OneDrive Settings

To configure OneDrive or SharePoint integration for your collection, follow these steps:

1. Go to the OneDrive Settings tab within the collection.

2. Enter the Client ID.
   This is the Application (Client) ID obtained from your Azure Active Directory (Azure AD) app registration. It uniquely identifies your application.

3. Enter the Client Secret.
   Provide the client secret generated in your Azure AD app registration. This is used for secure authentication.

4. Enter the Access Token.
   This is the OAuth access token used to access Microsoft Graph APIs on behalf of the application. It allows temporary access to OneDrive or SharePoint resources.

5. Enter the Refresh Token.
   The refresh token is used to generate a new access token when the current one expires, ensuring continuous access without re-authentication.

6. Enter the Drive ID.
   Specify the unique ID of the OneDrive or SharePoint document library that you want to crawl and index.

7. Enter the Tenant ID.
   This is the Directory (Tenant) ID from your Azure AD. It identifies your organization within Microsoft’s cloud services.

8. Enter the Root Path.
   Define the starting path within the drive for crawling.

   • Use / for the root directory
   • Or specify a folder path like /Documents/Reports

9. Click Save to store the configuration and enable the system to access and index files from OneDrive or SharePoint.

Schedule and Index

Sets the frequency and the start date/time for indexing a collection. Schedule Frequency supported in SearchBlox is as follows:

• Once
• Hourly
• Daily
• Every 48 Hours
• Every 96 Hours
• Weekly
• Monthly

The following operation can be performed in Azure blob collections

Manage Documents Tab

• Using Manage Documents tab we can do the following operations:

  1. Filter
  2. View content
  3. View metadata
  4. Refresh
  5. Delete

• To delete a file from your collection, enter the file path and click "Delete".

• To see the status of an indexed file, click "View Metadata".

Data Fields Tab

Using Data Fields tab we can create custom fields for search and we can see the Default Data Fields with non-encrypted collection. SearchBlox supports 4 types of Data Fields as listed below:

Keyword
Number
Date
Text

• Once the Data fields are configured, collection must be cleared and re-indexed to take effect.

OneDrive Collection Models

The Models page allows you to configure and override AI models used for embeddings, reranking, and LLM-based features within the collection.

Embedding

• Provider specifies the embedding provider used to generate vector representations of documents.
• Model defines the embedding model used to convert document content into vectors for semantic search.

Reranker

• Provider specifies the reranker provider used for improving search result relevance.
• Model defines the reranker model used to re-score and reorder search results based on relevance.

LLM

• Provider specifies the Large Language Model provider used for AI-powered features.

• Model defines the LLM used for tasks such as document enrichment, summaries, and SmartFAQs.

• These settings override global configurations and apply only to the current collection.