> ## Documentation Index
> Fetch the complete documentation index at: https://docs.zeptar.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Managing documents in your knowledge base

> Create, organize, refresh, and search documents from the dashboard or via the API.

A knowledge base grows with your product. Three ways to add documents:

## Creating documents

**From text** — paste reference content directly. Best for short docs
you author in-house: brand voice, FAQs, persona definitions, escalation
scripts.

**From a file** — upload PDFs, Word docs, EPUBs, HTML, Markdown, or
plain text. The server extracts the text, chunks it, and indexes it
for retrieval. The original file stays accessible via the document's
source-file URL.

**From a URL** — link to a public webpage. The server fetches the page,
extracts text, and ingests it. Use the **Refresh** action later to
re-ingest if the source page changes.

## Organizing with folders

Documents live in folders (or at the root). Use the **Move to folder**
action — either from a single document's row menu or in bulk by
selecting multiple documents and using the toolbar. See the [Folders
guide](/agents/operate/knowledge-base-folders) for the folder model.

## Refreshing URL-typed documents

A URL-typed document was fetched once at creation. To pull the latest
content from the source URL:

* API: `POST /v1/knowledge-base/documents/:id/refresh`
* Dashboard: open the document and choose **Refresh**.

The refresh is transactional — the previous content + chunks aren't
removed until the new content is fully ingested. Refresh on a text- or
file-typed document is rejected with a 400.

## Replacing a file

When you have a newer version of a file-typed document:

* API: `PATCH /v1/knowledge-base/documents/:id/file` (multipart with `file`).
* Dashboard: open the document and choose **Replace file**.

Same transactional semantics as refresh.

## Searching

Vector similarity search over your KB's indexed chunks:

* API: `GET /v1/knowledge-base/search?query=<your query>`
* Returns documents sorted by relevance with a snippet of the matched
  text.
* Filter by document type with `types=text` etc.

Search is the same mechanism that powers per-turn agent retrieval — if
search returns the right docs, your agents will too.

## Inspecting chunks

Chunks are the units of retrieval. To inspect what an agent actually
sees when it fetches context from a document:

* `GET /v1/knowledge-base/documents/:id/chunks` — paginated.
* `GET /v1/knowledge-base/documents/:id/chunks/:chunkId` — single chunk
  with `character_start`/`character_end` positions in the source text.

## Knowing which agents use a document

`GET /v1/knowledge-base/documents/:id/agents` lists every agent in
your organization that depends on this document. Useful before you
delete or replace it.