Playground

The playground is your test harness. It runs your agent exactly as a real customer would experience it — same retrieval, same prompt, same model — but with the tools you need to see why the agent answered the way it did and to fix it on the spot.

Use the playground continuously: while you build, after every data change, and as a debugging tool when a customer reports a bad answer. Open it from your agent's Playground tab.

Chatting with your agent

Type a question and the agent replies the same way it would on your website widget. Start with the questions that matter most:

• "How long do I have to return something?"
• "Where is my order?"
• "Do you ship to Canada?"
• "What's your warranty on this?"

Every answer is grounded in your data and carries citations. The playground reflects the live agent, so a source you just trained or a Q&A pair you just added is testable immediately.

Inspecting sources

Expand the sources under any answer to see the exact chunks the agent retrieved and the document each came from. This is the fastest way to debug:

• If the cited chunk is right but the answer is wrong, the issue is the prompt or model — tune them in Agent settings.
• If the cited chunk is wrong or missing, the issue is the data — add or fix a source.
• If a Q&A pair was matched, you'll see it cited as the source, confirming the pin worked.

Inspect prompt

The Inspect prompt tool shows the exact, fully-assembled prompt that the chat runtime would send to the model for a given question — including your system prompt, the retrieved chunks, and the conversation — without actually calling the model or spending credits.

It's the ground truth for "what does the model actually see?" Use it when an answer is surprising: you can confirm whether the right chunks made it into context and whether your system prompt is doing what you think.

Rating and improving answers

Rate any answer thumbs-up or thumbs-down. Ratings feed Analytics and the Suggestions list on your Data sources tab, so a thumbs-down becomes a flagged gap you can act on.

Improve answer

When an answer is close but not quite right, use Improve answer to edit the reply and save it as a high-priority Q&A pair. The corrected version is ingested immediately and retrieved first the next time a similar question comes in — turning a one-off fix into a permanent improvement.

1. 1
   Spot a weak answer

   Ask a question and notice the reply is vague, incomplete, or off.
2. 2
   Edit the response

   Use Improve answer to write exactly what the agent should have said.
3. 3
   Save as Q&A

   Bookbag stores it as a high-priority Q&A source and retrains it on the spot.
4. 4
   Re-ask to confirm

   Ask the same question again — the agent now returns your approved answer.

A tuning loop that works

1. 1
   Ask

   Pose a real customer question.
2. 2
   Inspect

   Expand sources and, if needed, Inspect prompt to see what the model received.
3. 3
   Fix the cause

   Wrong chunk → fix the data. Right chunk, wrong answer → adjust the prompt or model. Close but off → Improve answer into a Q&A pair.
4. 4
   Re-test

   Ask again and confirm the fix. Repeat across your top questions.

What's next