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

# Context window

> Understand the context indicator and how Babbily keeps long chats usable.

Every model has a context window. This is the amount of conversation, file content, and tool output the model can consider for one reply.

Babbily shows a context indicator near the composer so you can see how full the current chat is.

## What the indicator means

The context indicator estimates how much of the active model's window your chat is using. The details are approximate because models count conversation, file, and tool context differently.

* **Used** shows the percentage consumed.
* **Usage** shows the estimated context used out of the model's window.
* **Remaining** shows the approximate space left for the next message and reply.
* **Auto compact** shows when Babbily may summarize older parts of the chat.

The indicator updates as you send messages, attach files, receive replies, and switch models.

## Automatic compaction

In saved chats, when a long thread approaches the selected model's limit, Babbily can compact older conversation history into a shorter summary. Your visible chat history remains available, and the current conversation can keep going.

Compaction helps:

* Preserve recent messages in detail.
* Keep the thread within the active model's limit.
* Continue long-running work without forcing a new chat immediately.

<Note>
  A compacted summary is still part of the model's context. Your usage percentage may drop, but it will not reset to zero.
</Note>

Temporary Chats do not use automatic compaction. If they reach the limit, start a saved thread to continue.

## Switching models

Different models support different context sizes. If you switch to a smaller model, Babbily recalculates the thread against that model's limit. If needed, Babbily may compact the thread before the next reply.

## When a chat gets too full

If a thread reaches the limit, Babbily may ask you to start a new thread. Memory and connectors can still help you carry important context forward.

<Tip>
  Long files, deep research output, and pasted code can fill context quickly. Start a new thread when your topic changes or when you no longer need earlier details.
</Tip>