Template Syntax

When you need to scale your prompting, writing a new prompt for every unique scenario is not sustainable. Prompt templates solve this by letting you define a single, reusable blueprint that you can dynamically populate with structured data from a JSON payload. Each variable field in your template maps directly to a key in your JSON input, giving you full control over the generated output.

Insert Values

The most fundamental pattern is inserting a dynamic value directly into your prompt. Use the {{.key}} syntax to reference a specific field from your JSON payload.

Input

{
  "name": "Alice",
  "topic": "refunds"
}

Template

You are a customer support agent.

Greet {{.name}} and help them with {{.topic}}.

Result

You are a customer support agent.

Greet Alice and help them with refunds.

To ensure seamless integration, the key name in your template must match the key name in your JSON payload exactly.

If the JSON payload does not contain the specified key, the template engine safely renders <no value> instead of raising an error or failing the execution.

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Conditional Logic

Not all instructions apply to every scenario. You can conditionally include or exclude sections of your prompt by using if, else, and end blocks. This ensures your model only receives instructions relevant to the current context, saving context window tokens and reducing model confusion.

Input

{
  "name": "Bob",
  "isPremium": true
}

Template

Hello {{.name}}.

{{if .isPremium}}
This customer has priority support.
Respond with the fastest available resolution.
{{else}}
This customer is on the standard plan.
Offer upgrade options when relevant.
{{end}}

Result

Hello Bob.

This customer has priority support.
Respond with the fastest available resolution.

While conditional blocks are ideal for boolean flags, they also serve as presence checks.

The engine treats empty strings, empty lists, nil, and zero values as false, allowing you to safely handle optional user inputs.

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Iterate Over Lists

When your input data contains an array of items, use the range block to repeat a prompt segment for each element. This is useful for passing batch tasks, search results, or user options directly into the prompt.

Input

{
  "tasks": [
    "password reset",
    "billing question",
    "account deletion"
  ]
}

Template

The user needs help with:

{{range .tasks}}
- {{.}}
{{end}}

Address each item individually.

Result

The user needs help with:

- password reset
- billing question
- account deletion

Address each item individually.

Within the scope of a range block, the dot notation {{.}} refers directly to the current item being processed.

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Iterate Over Structured Lists

Lists often contain structured objects rather than simple text values. Within a range loop, you can access the fields of each individual object directly using dot notation.

Input

{
  "messages": [
    {
      "role": "user",
      "text": "How do I reset my password?"
    },
    {
      "role": "assistant",
      "text": "Click the forgot password link."
    }
  ]
}

Template

Conversation history:

{{range .messages}}
{{.role}}: {{.text}}
{{end}}

Write the next response.

Result

Conversation history:

user: How do I reset my password?
assistant: Click the forgot password link.

Write the next response.

This structure is highly effective for injecting multi-turn conversation histories, support tickets, search database results, and other complex data records.

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Access Nested Data

JSON payloads frequently contain hierarchical, nested objects. You can navigate these deeper data structures directly within your prompt template by chaining keys with dot notation.

Input

{
  "user": {
    "name": "Carol",
    "status": {
      "tier": "gold"
    }
  }
}

Template

Customer: {{.user.name}}
Membership: {{.user.status.tier}}

Result

Customer: Carol
Membership: gold

You can extend this chain as deeply as your database schema or nested JSON structure requires.

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Provide Default Values

To protect your prompts from incomplete or missing input fields, you can define fallback values using the default function. This prevents rendering empty spaces or generic text when a user or upstream system provides sparse data.

Input

{
  "tone": ""
}

Template

Use a {{default "helpful and professional" .tone}} tone.

Result

Use a helpful and professional tone.

This mechanism guarantees that your prompts remain reliable and fully structured even when handling optional parameters.

You can apply defaults to preserve fallback instructions for system roles, tones, response languages, or formatting preferences.

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Comprehensive Example

Real-world prompts often combine multiple design patterns to handle complex application logic. The following example demonstrates how value insertion, conditional blocks, loops, and default fallbacks work together to form a highly resilient and adaptable prompt template.

Input

{
  "role": "expert customer advisor",
  "userName": "Dana",
  "isPremium": false,
  "tone": "empathetic",
  "topics": [
    "shipping delay",
    "damaged packaging"
  ]
}

Template

You are an {{default "assistant" .role}}.

Customer: {{.userName}}

{{if .isPremium}}
This is a priority account.
Provide the fastest resolution path.
{{else}}
Handle the request using standard support procedures.
{{end}}

Topics to address:

{{range .topics}}
- {{.}}
{{end}}

Respond in an {{default "professional" .tone}} tone.

Result

You are an expert customer advisor.

Customer: Dana

Handle the request using standard support procedures.

Topics to address:

- shipping delay
- damaged packaging

Respond in an empathetic tone.

By combining these building blocks, you can construct robust prompt templates that dynamically adapt to any incoming payload while maintaining consistent instructions for the language model.