description: Schema to represent a basic prompt for an LLM.

Prompt Template

The Prompt Template node enables the creation of structured prompts with dynamic placeholders, allowing for consistent and reusable prompt generation in Language Model interactions.

Parameters

Inputs

1. Template (Required)

• Type: string

• Rows: 4

• Placeholder: "What is a good name for a company that makes {product}?"

• Description: The prompt template with variables in curly braces { }, which will be replaced with actual values

2. Format Prompt Values (Optional)

• Type: json

• Accept Variable: true

• List: true

• Description: JSON object containing values for template variables

• Example:

  {
    "product": "eco-friendly water bottles"
  }```

## Functionality

1. Template Processing

  - Variable extraction

  - Placeholder validation

  - Format verification

  - Dynamic content insertion

2. Value Management

  - JSON parsing

  - Variable mapping

  - Type validation

  - Error checking


## Use Cases

1. Dynamic Content Generation

- Customized prompts

- Variable content

- Consistent formatting

- Template reuse

2. Standardization

- Format consistency

- Error reduction

- Quality control

- Pattern enforcement

## Integration Notes

- Supports variable injection

- Handles JSON formatting

- Validates template syntax

- Manages error states


## Best Practices

1. Template Design

- Clear variable naming

- Consistent formatting

- Descriptive placeholders

- Proper documentation

2. Value Management

- Valid JSON structure

- Complete variable sets

- Type consistency

- Error handling

3. Performance Optimization

- Efficient templates

- Minimal complexity

- Reusable patterns

- Clear structure

{% hint style="info" %}
This section is a work in progress. We appreciate any help you can provide in completing this section. Please check our [Contribution Guide](../../../contributing/) to get started.
{% endhint %}