Knowledge Sets
The Knowledge Sets page (/admin/knowledge-sets) lets workspace administrators manage knowledge sets. Only admin users can access this page.
A knowledge set is a knowledge base (RAG corpus): a collection of documents and external sources that is prepared ("embedded") for semantic search. Agents can access one or more knowledge sets to ground their answers in your own content.
Overview
The list view shows all knowledge sets in a table with the following columns:
| Column | Content |
|---|---|
| Name | Name of the knowledge set |
| Description | Data description (truncated) |
| Files | Number of contained files |
| Embedding Model | Model used for embedding |
| Created | Creation date |
Use the search field (Search knowledge sets...) to filter the list by name or description. Use the checkboxes at the start of each row to select multiple knowledge sets and remove them together with the Delete button (which shows the number of selected entries).
Creating a Knowledge Set
- Click Create Knowledge Set
- BasePeak.AI creates the knowledge set and opens its detail page directly
- Give it a name there and populate the knowledge set with sources or files
The Embedding Model comes from your configured model providers (see Model Providers). Make sure at least one suitable model is available.
Editing Details
On a knowledge set's detail page, you edit the Name and Data Description. Both fields are saved automatically (Saving... appears while saving). A meaningful description helps agents recognize when this knowledge base is relevant.
A metadata bar at the top of the page shows the most important figures: Created, Files (count), Total Size, Embedding Model, as well as usage by Agents and Threads.
Knowledge flow
In the Advanced section at the bottom of the detail page, you set how a knowledge set reads in, splits, and searches documents — its knowledge flow. The default suits most sets; you don't need to change anything here.
Pick a ready-made processing profile:
| Profile | Best for |
|---|---|
| Standard (balanced) | Most content — the default. |
| High quality (hybrid) | Combines meaning-based and keyword search; better recall on names, IDs, and exact terms. |
| Large context | Keeps larger, coherent passages together — for questions that need the whole section. |
| Legal documents | Splits by legal structure (sections, articles, clauses) — for statutes, contracts, and ordinances. |
Alternatively, upload a custom configuration file (YAML) that applies to just this knowledge set. A downloadable template gets you started.
Changing the flow on a set that already contains files affects only newly added files at first. BasePeak.AI therefore offers to re-ingest all existing files so the new setting applies everywhere. Sets you don't change keep working unchanged.
Knowledge Sources
In the Knowledge Sources section, you connect external data sources that are synchronized automatically. Click Add Source to create a source and select the source type:
| Type | Description |
|---|---|
| Website | Crawl one or more URLs |
| OneDrive | Shared OneDrive links |
| Notion | Notion workspace |
| Nextcloud | Nextcloud instance |
| SMB / Network Share | Network share (SMB) |
| WebDAV | WebDAV server |
| S3 / Object Storage | S3-compatible object storage |
| SFTP | SFTP server |
| Council Information System (RIS) | Municipal council information system |
| State Law (NRW) | State law for a Bundesland (currently North Rhine-Westphalia) from recht.nrw.de |
Depending on the type, you enter the necessary connection details and, where applicable, credentials. Optionally, you set a Sync Schedule (e.g. Hourly, Daily, or a custom cron expression) and enable Auto-approve files.
For State Law (NRW), you first choose the Bundesland (currently North Rhine-Westphalia) and then search a browsable catalogue for the laws, ordinances, and administrative regulations you want to bring into the knowledge set.
Content comes from recht.nrw.de (SGV.NRW) and is a non-official consolidated version.
Each source shows a status badge:
| Status | Meaning |
|---|---|
| Pending | Sync is still pending |
| Syncing | Sync is currently running |
| Synced | Source was imported successfully |
| Error | Sync failed (details via View error) |
While sources are syncing, the page updates the status automatically. From a source's actions you can Sync Now, View Files, edit it, or Remove Source.
Knowledge Files
In the Knowledge Files section, you upload documents directly. Click Upload Files and select one or more files. Supported formats include the following:
PDF, TXT, DOC, DOCX, MD, HTML, ODT, RTF, CSV, IPYNB, JSON, PPTX, PPT, and PAGES.
After uploading, each file goes through processing (ingestion and embedding). The processing state is displayed:
| State | Meaning |
|---|---|
| Pending Approval | File was detected but not yet processed |
| In Progress | File is currently being processed |
| Ingested | File is processed and searchable |
| Unsupported | File type is not supported |
| Error | Processing failed |
The page automatically refreshes pending files until processing is complete. Individual files can be permanently removed from the knowledge base via their respective Delete action.
Exporting and Importing
With Export, you create a package (.zip) from a knowledge set that optionally contains the Include knowledge set manifest (name + description) and the Include source files. Created packages appear under Recent exports with phase, size, and expiration time, and are available there for Download.
Using the Import button in the list view, you can re-import a previously exported package. You can Name override (optional) and Description override (optional) or Use manifest from package.
Deleting a Knowledge Set
You delete a knowledge set via Delete Knowledge Set (on the detail page or via the actions menu in the list). Before deleting, BasePeak.AI checks whether the knowledge set is still in use.
A knowledge set that is still in use by agents or threads cannot be deleted. The message This knowledge set is currently in use and cannot be deleted. appears. During bulk deletion, knowledge sets that are in use are automatically skipped.
Notes
- The Embedding Model is set at creation time and comes from the configured Model Providers.
- Sources with credentials (SMB, WebDAV, SFTP, S3) remain in the Pending status until a valid password is stored.
- When deleting a knowledge set, all contained files and sources are lost irretrievably.