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# Knowledge Base

> Create knowledge bases in Sarvam Voice Agents so agents answer from your files, attach them to agents, and learn how retrieval and KB descriptions work.

Give an agent domain knowledge so it answers from your content instead of guessing. A knowledge base (KB) is a named, described group of files the agent can search mid-conversation.

## What a knowledge base is

* A **knowledge base** is a **named** group of **files** with a **description**.
* The **description is what the agent reads to decide when to search this KB**, so write it well.
* Files are part of a KB (added when you create or edit the KB). Supported formats: **PDF, DOCX/DOC, CSV/TSV, TXT, MD**.

## Creating a knowledge base

1. Open the **Knowledge base** section in your workspace.
2. Create a KB with a **name**, a **description**, and one or more **files**.
3. Wait for processing to finish (ingestion is asynchronous) before attaching it to an agent.

You can edit a KB's files or description at any time; changes apply wherever the KB is used.

## Attaching a KB to an agent

Attach a KB from the agent's [Settings](/voice-agents/build/conversation-settings#knowledge-bases). Doing so **automatically adds the KB query tool** to the agent, you don't add the tool by hand. On the query tool you can then add or remove KBs, or create a new KB inline.

## How retrieval works

When the agent needs a fact, it calls the query tool with two parameters:

* **knowledge\_base**: which KB to search (the agent picks based on each KB's description).
* **query**: a cleaned, self-contained search query.

The platform embeds the query, searches the KB, reranks, and returns the **top chunks** (about 500 tokens) for the agent to answer from. Each chunk is tagged with its **source file** for attribution. This single-stage chunk retrieval keeps latency low.

## Editing the tool's descriptions

The query tool ships with sensible default descriptions (the tool description and both parameter descriptions), all editable in the [Tools](/voice-agents/build/tools) UI. Most authors just write clear **KB names and descriptions**, which flow into the tool automatically, and leave the defaults alone.

Good descriptions are what keep retrieval accurate: they tell the model when to search a KB (reference content) and when not to (personal account data, greetings, unrelated requests).

## Managing knowledge bases

* **Workspace KB library**: create, edit, and delete KBs. A KB attached to a live agent can't be deleted, you'll see which agents use it.
* **Removing vs deleting**: removing a KB from a query tool detaches it from that agent but keeps it in the library; deleting removes it from the library entirely (blocked while it's attached to a live agent).
* **Storage**: KB storage is tier-based, with a usage indicator. Over-quota uploads are blocked with a clear message and upgrade path.

## Writing good knowledge bases

* **Lead with the description.** It's what the model routes on, make it specific about what's inside.
* **Keep a KB coherent.** If files are too varied to describe in one line, split them into separate, more focused KBs, they route better.
* **Prefer reference content.** KBs are for policies, pricing, product details, and FAQs, not personal account data.