Rendering

All Implemented Interfaces:
```
public interface PromptRunner.Rendering

                    
```
Fluent interface for rendering templates and generating LLM responses. Provides operations for:
- Creating strongly-typed objects from rendered templates
- Generating text from rendered templates
- Responding in conversations with templates as system prompts
Instances are obtained via PromptRunner.rendering.

Nested Class Summary

Nested Classes
Modifier and Type	Class	Description

Field Summary

Fields
Modifier and Type	Field	Description

Constructor Summary

Constructors
Constructor	Description

Enum Constant Summary

Enum Constants
Enum Constant	Description

Method Summary

Modifier and Type	Method	Description
`abstract <T extends Any> T`	`createObject(Class<T> outputClass, Map<String, Object> model)`	Create an object of the given type using the given model to render the template and LLM options from context.
`abstract String`	`generateText(Map<String, Object> model)`	Generate text using the given model to render the template and LLM options from context.
`abstract AssistantMessage`	`respondWithSystemPrompt(Conversation conversation, Map<String, Object> model)`	Respond in the conversation using the rendered template as system prompt.

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Constructor Detail
- Method Detail
  - createObject
```
 abstract <T extends Any> T createObject(Class<T> outputClass, Map<String, Object> model)
```
    Create an object of the given type using the given model to render the template and LLM options from context.
    
    Parameters:
    
    outputClass - the class of objects to create
    
    model - the model data to use for template rendering
    
    Returns:
    
    the created object of type T
  - generateText
```
 abstract String generateText(Map<String, Object> model)
```
    Generate text using the given model to render the template and LLM options from context.
    
    Parameters:
    
    model - the model data to use for template rendering
    
    Returns:
    
    the generated text
  - respondWithSystemPrompt
```
 abstract AssistantMessage respondWithSystemPrompt(Conversation conversation, Map<String, Object> model)
```
    Respond in the conversation using the rendered template as system prompt.
    
    Parameters:
    
    conversation - the conversation so far
    
    model - the model data to render the system prompt template with.
    
    Returns:
    
    the assistant message response