ai_context - Composite topics

Free text that can provide context to the Omni Agent. Refer to the Optimizing models for AI guide for more information on best practices.

Syntax

ai_context: "<context_text>"

Or for multiline context:

ai_context: |
  <multiline_context_text>

Properties

string

Free text that provides context to the Omni Agent. Can include behavioral prompting, instructions for tone, or other guidance to improve AI query results.The following references are supported for this field:

User attributes, referenced with {{omni_attributes.<attribute_name>}}. This allows you to personalize the context for each user.
Model constants, referenced using @{constant_name} syntax. This allows you to maintain reusable instruction blocks such as tone, privacy guidance, and domain context instead of duplicating them.

Behavior

When a composite topic is the active topic, the Omni Agent uses the composite topic’s own ai_context. The ai_context of the member topics is not included. Context defined on the model, on views, on fields, and on shared dimensions is still included.

Examples

Personalized context using user attributes

ai_context: |
  You are a marketing analyst. When someone asks about their region, always filter by region = {{omni_attributes.region}}.

Model-specific analysis depth

The following context will apply when the model tier is smartest.

Applies when the model tier is smartest

ai_context: |
  This composite topic compares orders revenue with marketing spend by activity_date and region.

  {{# omni_llm.smartest }}
  For questions that span both topics, explain which topic each measure comes from and how the shared dimensions align them.
  {{/ omni_llm.smartest }}

The following context will apply when the model tier is not smartest.

Applies when the model tier is not smartest

ai_context: |
  This composite topic compares orders revenue with marketing spend by activity_date and region.

  {{^ omni_llm.smartest }}
  Group by activity_date or region. Use one measure from each topic per query.
  {{/ omni_llm.smartest }}

Agent-specific context

The following context provides query guidance to the analyze agent while providing field relationship guidance to the build agent.

Agent-specific query and field guidance

ai_context: |
  This composite topic combines orders and marketing data.

  {{# omni_agent.analyze }}
  Always filter by activity_date before comparing revenue with spend. Both topics are large.
  {{/ omni_agent.analyze }}

  {{# omni_agent.build }}
  activity_date and region are shared dimensions. Revenue fields come from orders_topic. Spend fields come from marketing_topic.
  {{/ omni_agent.build }}

Using constant references

Reference constants to combine reusable context blocks with composite topic guidance:

Composite topic file with constant references

ai_context: |
  @{tone} @{domain_marketing}
  This composite topic compares orders revenue with marketing spend. One row is one activity_date per region.

The @{tone} and @{domain_marketing} references will be substituted with the constant values defined in the model file.

Behavioral prompting

ai_context: |
  you are the head of marketing. you want to know which campaigns drive revenue. you compare spend with revenue by month and by region, and you look for regions where spend went up but revenue did not.

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ai_context - Composite topics

Syntax

Properties

Behavior

Examples

Personalized context using user attributes

Model-specific analysis depth

Agent-specific context

Using constant references

Behavioral prompting

​Syntax

​Properties

​Behavior

​Examples

​Personalized context using user attributes

​Model-specific analysis depth

​Agent-specific context

​Using constant references

​Behavioral prompting

Syntax

Properties

Behavior

Examples

Personalized context using user attributes

Model-specific analysis depth

Agent-specific context

Using constant references

Behavioral prompting