Box Collection

SearchBlox provides a crawler that allows you to index files and folders stored in Box. This feature enables SearchBlox to securely connect to your Box account and crawl the selected content for indexing. You can create a Box Collection using the steps below.

Creating a Box Collection

You can create a Box Collection by following these steps:

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

  • Select Box 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 Box Collection.

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


Box Settings

The Box Settings section allows you to configure the connection between SearchBlox and your Box account. By providing the required authentication credentials, SearchBlox can securely access your Box storage and crawl files and folders for indexing.

Once configured, SearchBlox will retrieve documents from the specified Box folders and make them searchable within the platform. You can optionally specify a root folder to control where the crawler begins indexing content.

Configuring Box Settings

To configure Box for your collection, follow these steps:

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

  2. Enter the Client ID.
    This is the client ID of your Box application used for authentication.

  3. Enter the Client Secret.
    Provide the client secret associated with your Box application.

  4. Enter the Access Token.
    This is the OAuth 2.0 access token used to authorize requests to the Box API.

  5. Enter the Refresh Token.
    The refresh token is used to generate a new access token when the existing access token expires.

  6. Enter the Enterprise ID (Optional).
    Provide the enterprise ID if you are using a Box enterprise account.

  7. Enter the Root Folder ID (Optional).
    Specify the Box folder ID from which the crawler should start indexing content.
    If not specified, the crawler will start from the root folder (0).

  8. Click Save to store the configuration and enable SearchBlox to access and crawl your Box content.


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 box collections

ActivityDescription
Enable Scheduler for IndexingOnce enabled, you can set the Start Date and Frequency
ScheduleFor each collection, indexing can be scheduled based on the above options.
View all SchedulesRedirects to the Schedules section, where all the Collection Schedules are listed.

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".


Box 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.