Unqork documentation is available in two workspaces: UnqorkAI for the latest AI-first platform, and legacy Unqork for previous versions. Use the drop-down near the logo to switch.

This article covers UnqorkAI features. UnqorkAI requires an active AI capabilities agreement. To upgrade from Unqork 9.0 or learn more, contact your Unqork representative.

Understanding AI Model Settings

Prev Next

AI components expose settings that control how the AI model generates its responses. Which models are available, and which settings a model reads, depend on the LLM credential the component runs on.

Chat Agent Smart Component: These settings also apply to the Chat Agent Smart Component, but they are configured in Settings > LLM Configs inside the LLM Config rather than directly on the component itself.

Instructions

Instructions tell the AI model its role, tone, and constraints before the conversation or task begins.

In AI terminology, this field is also called a system prompt or system instruction. The component label is Instructions.

Example instructions:

You are a customer support specialist for a retail brand. Answer questions politely and concisely. If you do not know the answer, say so and suggest the customer contact support.

You are a document summarizer. Summarize the provided text in three bullet points. Focus on key decisions, action items, and deadlines.

Tips for writing effective instructions:

  • Be specific about the role and tone.

  • Define what the model should do when it does not know an answer.

  • If output format matters, specify it: bullet points, paragraph, numbered list, and so on.

Temperature

Temperature sets the variability of the model's output. Lower values produce more focused, consistent responses; higher values produce more varied, creative ones. The UI exposes a 0–2 scale. Most models do not honor the full range; behavior varies by model.

Value

Effect

0–0.3

Responses are more focused, consistent, and predictable. Use for factual Q&A, document retrieval, or any context where accuracy matters more than variety.

0.4–0.8

Balanced responses. Good for most use cases.

0.9–2

Responses are more varied and creative. Use for brainstorming or scenarios where novelty is valuable.

The AI Summarizer defaults to 0.5.

Model behavior varies. The 0–2 range applies as configured only for Gemini 3.x and Nova 2 Lite. Other models handle temperature differently:

Model

Temperature behavior

Gemini 3.x, Nova 2 Lite

Applied as configured (0–2)

GPT-5.x, Haiku 4.5

Pinned to 1.0 — any value is silently clamped

Opus 4.8, Sonnet 5, Fable 5

Temperature not supported — the parameter is ignored

The UI accepts 0–2 regardless of model and clamps silently where needed.

Thinking Level

Thinking Level is a simplified control for reasoning depth. Which setting the model reads depends on the model; the Creator does not choose between them.

Level

Effect

Off

No internal reasoning. Fastest responses.

Medium

Moderate reasoning. Good for longer documents or content that requires nuance.

High

Extended reasoning. Use for complex content where accuracy is critical.

Which models read Thinking Level:

Setting read

Models

Thinking Level

GPT-5.x, Gemini 3.x, Opus 4.8, Sonnet 5

Thinking Token Budget

Haiku 4.5 only

Neither (both ignored)

Fable 5, Nova 2 Lite

Thinking Token Budget

The Thinking Token Budget controls how much internal reasoning the model performs before generating a response. This setting applies only to Haiku 4.5. On all other models it is ignored.

Values below 1024 are clamped to 1024, giving a practical range of 1024 to 4096.

Value

Effect

~1024

Minimal internal reasoning. Fast responses, suitable for straightforward tasks.

~2048

Moderate reasoning. Good for questions that require the model to consider multiple factors.

~4096

Extended reasoning. Use for complex multi-step problems or scenarios where accuracy is critical.

The AI Summarizer defaults to 1024. Increasing the Thinking Token Budget increases processing time and cost.

Chat Agent Smart Component: For the Chat Agent, the LLM Config handles thinking settings and replaces the need to set the Thinking Token Budget directly in most use cases.

Max Output Tokens

Max  Tokens sets the maximum length of the model's response. One token is roughly equivalent to four characters of text.

Value

Approximate output

1024

Several paragraphs

2048

A detailed multi-paragraph response

4096

A long, comprehensive response

The AI Summarizer defaults to 2048. The maximum value varies by model:

Model

Max output tokens

Gemini models

65,535

Sonnet 5, Haiku 4.5, Nova 2 Lite

64,000

GPT-5.x, Opus 4.8, Fable 5

128,000

Values above the model's maximum are clamped to that maximum. If responses are being cut off mid-sentence, increase this value. If responses are unnecessarily long, decrease it.

Max Output Tokens sets a ceiling, not a target. The model generates as much text as needed up to the limit.

Choosing Settings

Most use cases work well with the default settings. Adjust when you notice the following issues:

Issue

Adjustment

Responses feel generic or repetitive

Increase Temperature (Gemini 3.x and Nova 2 Lite only)

Responses are inconsistent or off-topic

Decrease Temperature (Gemini 3.x and Nova 2 Lite only)

The model struggles with complex content

Increase Thinking Level (GPT-5.x, Gemini 3.x, Opus 4.8, Sonnet 5) or Thinking Token Budget (Haiku 4.5)

Summaries lack depth or miss nuance

Increase Thinking Level

Responses are cut off before finishing

Increase Max Output Tokens

Responses are unnecessarily long

Decrease Max Output Tokens


Changelog

Date

Change

2026-09-12

Rewrote with model-specific behavior for Temperature, Thinking Level, Thinking Token Budget, and Max Output Tokens; added model-compatibility table; renamed System Prompt to Instructions; added AI Agent LLM Config notes; fixed incorrect "retired AI Agent" reference (EN-8106 SME review).

2026-08-19

Clarified that available models and applicable settings come from the LLM credential.

Initial publication.