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Agent Settings is where you define how your agent thinks, responds, and behaves. Access these settings by selecting an agent and clicking Settings in the sidebar. This page covers the System Prompt, AI model settings (temperature, match count, guardrail level, reasoning), Rate Limiting, and the Playground.

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System prompt

The system prompt is a set of instructions given to the AI model that shapes how your agent behaves and responds. It acts as a foundational directive — the model follows these instructions throughout every conversation. Use the system prompt to define:
  • Personality and tone — formal, casual, friendly, concise
  • Behavioral rules — what topics to cover, what to avoid, when to escalate
  • Response language — which language(s) to respond in
  • Constraints — word limits, formatting preferences, disclosure rules
Write your instructions in the Instructions field. Click Insert Example Prompt to start from a template and customize it for your use case.
If you want the agent to format responses with bullet points, headings, and bold text, explicitly instruct it in the system prompt — for example: “Format your responses using Markdown with headings, bullet points, and bold text for key terms.”

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Displaying images in responses

The chat widget renders Markdown images. You can instruct your agent to include images in its responses by adding image URLs in Markdown format to the system prompt. For images to render correctly, the URL must end with a supported extension (.png, .jpg, .jpeg, .gif, .webp). Add a line like the following to your system prompt to display an image after each response:
You can also instruct the agent conditionally — for example, to show a specific image only when discussing a certain topic:
The image URL must be publicly accessible. Images behind authentication or private storage will not render in the chat widget.

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Example system prompts

These examples follow prompting best practices: they define a clear role, set behavioral boundaries, specify tone and formatting, and include fallback instructions. Adapt them to your use case and knowledge base content.
Want to improve your prompting skills? These resources cover techniques and best practices for writing effective system prompts:

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AI model settings

These settings fine-tune how the AI model generates responses. You can find them below the system prompt in Settings.

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Temperature

Temperature controls the randomness of the model’s output. Lower values produce more focused, deterministic responses. Higher values introduce more variety and creativity. The range is 0 to 1. For most customer-facing agents, keep the temperature between 0 and 0.3 for dependable, on-topic answers, but feel free to experiement as well.

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Match count

Match count determines how many relevant passages from your Knowledge Base are included as context when the model generates a response. The default is 5. A higher match count gives the model more information to work with, which can improve answer accuracy for broad topics. However, too many matches may introduce irrelevant content that dilutes the response quality.
Both the match count and the system prompt consume tokens from the model’s context window. A high match count combined with a lengthy system prompt leaves less room for the conversation itself, which can cause the model to lose track of earlier messages. Balance these settings and experiment — a concise system prompt with a moderate match count often outperforms a large prompt with many matches.
Start with the default of 5. If the agent frequently misses relevant information, try increasing to 7–9. If responses seem unfocused or include off-topic details, reduce it.

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Guardrail level

The guardrail level controls whether the agent restricts its answers to your Knowledge Base or can draw on its general knowledge. The default is High.
Setting the guardrail level to None allows the agent to answer any question using its general knowledge, even if the answer isn’t in your Knowledge Base. Test thoroughly before using this in production.

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Reasoning configuration

Some AI models — called reasoning-capable models — spend extra time “thinking” before they answer. When you select one of these models, two additional controls appear in Model Configuration. The temperature slider is hidden, since reasoning models don’t use it. Both settings are optional. Leave them unset to use the provider’s default.

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Reasoning effort

Controls how much the model reasons before responding. Higher effort generally produces better answers on complex questions, but responses are slower and consume more credits.
Start with Low or Medium and increase only if the agent is missing nuance on complex queries. High and xHigh are not suitable for day-to-day customer support or high-volume chat — at these levels, a single response can take tens of seconds and occasionally minutes before the visitor sees a reply, which leads to drop-off and a poor chat experience. Reserve them for internal tools, research assistants, or other use cases where visitors expect to wait for a considered answer.

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Reasoning summary

Controls whether the model returns a summary of its reasoning alongside the answer.
Not every reasoning model exposes both controls, and some models restrict which effort levels are available. The dropdown shows only the values supported by the currently selected model.

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Rate limiting

Rate limiting prevents individual users from sending too many messages in a short period, protecting your agent from spam and abuse. The limit is tracked per user and starts when they send their first message in a given window. To enable rate limiting, go to Settings → Rate Limits and toggle Enable Rate Limiting. Configure two values:
  • Message — the maximum number of messages a user can send within the window
  • Duration (minutes) — the time window in which messages are counted
Once a user reaches the limit, they see a feedback message and cannot send more messages until their window expires and a new one begins.

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Rate limit reached message

Customize the message users see when they hit the rate limit. This field supports per-language values when you have additional languages enabled.
Rate limits apply to each channel separately — activity on the web messenger does not affect WhatsApp rate limits. API requests authenticated with a valid API key are not rate limited.

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Playground

The Playground is a live preview of your messenger where you can test your agent’s responses without embedding it on your website. Access it from Playground in the sidebar. Use the Playground to:
  • Test system prompt changes and see how the agent responds
  • Verify Knowledge Base content is being retrieved correctly
  • Preview the messenger appearance (welcome messages, suggested messages, colors)
The Messages Sent counter at the top shows your current usage against your plan’s monthly message limit, along with the billing cycle dates. The Install tab next to Playground is where you find your embed code to add the agent to your website.