Prompt Studio Interface

This reference documents the UI elements, configuration options, and actions available in the Prompt Studio interface.

Overview

Prompt Studio transforms datasets into structured, fine-tuning-ready examples for AI models. Each row in the output dataset represents a valid training example formatted as a conversation with system, user, and assistant messages. Path: My Models → Prompt Studio

Prompt Builder module

The Prompt Builder is the main workspace for configuring how dataset rows transform into conversation-formatted training examples.

Dataset selector

Element	Description
Dataset dropdown	Select the source dataset to transform
Row count	Displays total rows available for transformation

The selected dataset provides the fields available for macro substitution in prompts.

Role configuration panels

Three panels allow you to configure prompts for each conversation role:

Role	Purpose	Typical content
System	Sets the AI’s behavior and context	Instructions, persona definition, constraints
User	Represents the human input	Questions, requests, data to analyze
Assistant	Represents the AI response	Expected output format, example responses

Each panel contains:

Element	Description
Select button	Opens the prompt editor for that role
Prompt text area	Displays the configured prompt with macro placeholders
Macro indicators	Visual badges showing embedded macros

Prompt editor

The prompt editor opens when you click Select on any role panel.

Text input area

Element	Description
Prompt text field	Multi-line text area for writing the prompt
Macro placeholder syntax	Use `{{macro_name}}` to insert dynamic values
Character count	Displays current prompt length

Macro configuration

After adding macro placeholders to your prompt text, configure each macro’s data source:

Macro type	Description	Use case
Field	Maps to a column in the source dataset	Pull values directly from dataset columns
NQL	Uses a Narrative Query Language expression	Compute derived values, transform data, combine fields
Literal	Fixed text value	Static content that doesn’t change per row

Macro configuration panel

Element	Description
Macro name	The identifier used in `{{macro_name}}` syntax
Type selector	Choose between Field, NQL, or Literal
Value configuration	Field picker, NQL editor, or text input based on type
Preview value	Sample resolved value from the first dataset row

Editor actions

Action	Description
Save	Saves the prompt configuration and returns to Prompt Builder
Cancel	Discards changes and returns to Prompt Builder

Preview screen

The Preview screen validates your prompt configuration by showing resolved output for each dataset row. Path: Click Preview in the Prompt Builder

Conversation display

Element	Description
System message	Resolved system prompt with all macros substituted
User message	Resolved user prompt with all macros substituted
Assistant message	Resolved assistant prompt with all macros substituted

Messages display in a conversational format, visually distinguishing each role.

Control	Description
Prev	Navigate to the previous dataset row
Next	Navigate to the next dataset row
Row indicator	Shows current row number and total (e.g., “Row 5 of 1,234”)

Validation indicators

Indicator	Meaning
Green checkmark	All macros resolved successfully
Yellow warning	Some macros returned empty or null values
Red error	Macro resolution failed (e.g., invalid NQL expression)

Output format

The transformed dataset contains rows formatted as structured conversations:

{
  "messages": [
    { "role": "system", "content": "You are a helpful assistant..." },
    { "role": "user", "content": "Analyze this customer data..." },
    { "role": "assistant", "content": "Based on the data provided..." }
  ]
}

This format is compatible with fine-tuning APIs from major AI model providers.

Actions reference

Builder actions

Action	Location	Description	Result
Select dataset	Dataset module	Choose source dataset	Dataset fields become available for macros
Configure role	Role panel	Open prompt editor for a role	Prompt editor opens
Preview	Prompt Builder toolbar	Validate prompt resolution	Preview screen opens

Editor actions

Action	Location	Description	Result
Add macro	Prompt text	Type `{{name}}` syntax	Macro placeholder created
Configure macro	Macro panel	Set type and value	Macro resolution configured
Save	Editor toolbar	Save prompt configuration	Returns to Prompt Builder

Preview actions

Action	Location	Description	Result
Navigate rows	Navigation controls	View different dataset rows	Conversation updates with new row data
Return to builder	Preview toolbar	Exit preview mode	Returns to Prompt Builder

Output actions

Action	Location	Description	Result
Generate dataset	Prompt Builder toolbar	Create materialized dataset	Opens Data Studio with prompt configuration

Workflow summary

Select dataset → Choose source data in the Dataset module
Configure prompts → Define system, user, and assistant prompts with macros
Configure macros → Map each macro to a field, NQL expression, or literal value
Preview output → Validate resolved prompts row by row
Generate dataset → Use Data Studio to materialize the transformed dataset

LLM Studio

Train and fine-tune models using prepared datasets

NQL Syntax

Reference for NQL expressions used in macros

Model Inference

Using AI models within your data plane

Creating Materialized Views

Generate datasets from your prompt configurations

Overview

Connectors

Integrations

Workflow Reference

Webhook Reference

Security Reference

Architecture Reference

Error Reference

Model Inference Reference

Rosetta Stone Reference

UI Reference

SDKs

Glossary

Billing

Overview

Prompt Builder module

Dataset selector

Role configuration panels

Prompt editor

Text input area

Macro configuration

Macro configuration panel

Editor actions

Preview screen

Conversation display

Navigation controls

Validation indicators

Output format

Actions reference

Builder actions

Editor actions

Preview actions

Output actions

Workflow summary

LLM Studio

NQL Syntax

Model Inference

Creating Materialized Views

​Overview

​Prompt Builder module

​Dataset selector

​Role configuration panels

​Prompt editor

​Text input area

​Macro configuration

​Macro configuration panel

​Editor actions

​Preview screen

​Conversation display

​Navigation controls

​Validation indicators

​Output format

​Actions reference

​Builder actions

​Editor actions

​Preview actions

​Output actions

​Workflow summary

​Related content

LLM Studio

NQL Syntax

Model Inference

Creating Materialized Views

Overview

Prompt Builder module

Dataset selector

Role configuration panels

Prompt editor

Text input area

Macro configuration

Macro configuration panel

Editor actions

Preview screen

Conversation display

Navigation controls

Validation indicators

Output format

Actions reference

Builder actions

Editor actions

Preview actions

Output actions

Workflow summary

Related content