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Free text that provides context to the Omni Agent for all topics in the model. When a branch or workbook layer extends a model with ai_context, Omni uses patch-based merging to preserve parent context while allowing layer-specific modifications. This prevents child layers from overwriting parent context when making edits. Refer to the Optimizing models for AI guide for more information on best practices.

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Syntax

Value is on one line
ai_context: "<value>"
Value can contain linebreaks
ai_context: |
  <value>

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Properties

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ai_context
string
Free text that provides context to the Omni Agent. Can include behavioral prompting, instructions for tone, or other guidance to standardize AI outputs across the model.You can reference user attributes using ${omni_attributes.<attribute_name>} syntax to personalize the context for each user. Only user attribute references are allowed — field references and filter conditions are not supported.
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ai_context_patch
object
Server-managed field that stores how a branch or workbook layer modifies its parent’s ai_context. Omni automatically generates patches when you edit ai_context in a non-base layer.You can delete a patch by omitting the ai_context_patch: field from your YAML in Model mode, but you cannot manually create or edit patch contents. Omni automatically chooses the appropriate patch type.The literal ai_context is always persisted alongside the patch as the source of truth and fallback.

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Layer behavior

The patch-based merging described in this section only applies to model-level ai_context.
When you edit the model-level ai_context in a branch or workbook layer in:
1

Combined mode

Omni compares your edited context to the resolved parent context and automatically generates an ai_context_patch. Both the literal ai_context and the patch are stored.
2

Model mode

You see only the patch content (your layer’s contribution) when a patch exists. The literal ai_context is hidden but still persisted in the background.
When Omni resolves a model across layers (Shared > Branch > Workbook):
  1. If a layer has an ai_context_patch, Omni attempts to apply it against the resolved parent context
  2. If the patch applies successfully, the result becomes the resolved context for that layer
  3. If a diff patch cannot apply cleanly, such as due to parent changes, Omni falls back to the layer’s literal ai_context
  4. Append patches always apply successfully, making them ideal for layers that only add context

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Examples

Behavioral prompting
ai_context: |
  You are an analyst for an eCommerce retailer called BlobsRUs. After generating a query, always provide a summary of the data both English and Brazilian Portuguese.
Personalized context using user attributes
ai_context: |
  You are an analyst for a ${omni_attributes.company_type} company. Focus on metrics relevant to the ${omni_attributes.region} region.
Branch layer appending to parent context
# In the SHARED layer:
ai_context: |
  You are an analyst for BlobsRUs eCommerce.

# In a BRANCH layer, adding region-specific context:
ai_context: |
  You are an analyst for BlobsRUs eCommerce.
  
  Focus on the European market and use metric names in euros.
ai_context_patch:
  append: |
    
    Focus on the European market and use metric names in euros.
Workbook layer modifying parent context
# In the SHARED layer:
ai_context: |
  You are an analyst for BlobsRUs. Provide detailed explanations.

# In a WORKBOOK layer, changing tone:
ai_context: |
  You are an analyst for BlobsRUs. Keep responses concise.
ai_context_patch:
  diff: |
    @@ -1 +1 @@
    -You are an analyst for BlobsRUs. Provide detailed explanations.
    +You are an analyst for BlobsRUs. Keep responses concise.