> For the complete documentation index, see [llms.txt](https://docs.qolaba.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.qolaba.ai/chatbot/starting-a-new-chat.md).

# Starting a New Chat

Each chat in Qolaba is an isolated conversation thread tied to your current workspace. Starting a new chat gives you a clean context, a fresh message thread, and no influence from previous conversations.

#### Creating a New Chat

1. Open your **Workspace** from the left navigation panel
2. Select **Chatbot**
3. Click **New Chat** in the top right
4. Enter your first prompt and send

A new conversation thread is created automatically, saved to your workspace history, and begins consuming credits from your first message.

***

#### How Conversation Context Works

Every chat maintains its own **context window** — a memory of everything said within that thread, including your prompts, AI responses, follow-up instructions, and any files attached during the session.

This allows the AI to:

* Build on earlier instructions without you repeating them
* Refine outputs progressively across multiple turns
* Handle complex, multi-step tasks within a single conversation

{% hint style="info" %}
Context is chat-specific. Starting a new chat resets conversational memory entirely. AI has no memory of previous chat sessions.
{% endhint %}

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#### When to Start a New Chat

Start a new chat when you are:

* Switching to a different topic or task
* Working on a new client or project
* Deliberately isolating results from a previous session

{% hint style="info" %}
**Best practice:** One chat per objective. It keeps your history clean, your outputs traceable, and your context uncontaminated.
{% endhint %}

***

#### Resetting Context

The cleanest way to reset context is to **start a new chat**. This ensures the AI has no memory of earlier instructions, files, or outputs — giving you a reliable baseline for experimentation or benchmarking.

Carrying over unintended context can cause the AI to reference outdated instructions, produce inconsistent comparisons, or generate outputs biased by earlier constraints.