prompt-executor-model

Core interfaces and models for executing prompts against language models.

Overview

This module defines the fundamental interfaces and models for executing prompts against language models. It provides the PromptExecutor interface which serves as the foundation for all prompt execution implementations, supporting both synchronous and streaming execution modes, with or without tool assistance.

Using in your project

Add the dependency to your project:

dependencies {
    implementation("ai.koog.prompt:prompt-executor-model:$version")
}

When implementing a custom prompt executor or working with existing implementations, you'll need to use the interfaces defined in this module:

// Using the PromptExecutor interface
val executor: PromptExecutor = getPromptExecutorImplementation() // obtain an implementation
val result = executor.execute(prompt, model)

Example of usage

// Creating a prompt executor implementation
class MyPromptExecutor : PromptExecutor {
    override suspend fun execute(prompt: Prompt, model: LLModel, tools: List<ToolDescriptor>): List<Message.Response> {
        // Implementation details
    }

    override suspend fun executeStreaming(prompt: Prompt, model: LLModel): Flow<String> {
        // Implementation details
    }
}

// Using a prompt executor
suspend fun processPrompt(executor: PromptExecutor, prompt: Prompt, model: LLModel) {
    val response = executor.execute(prompt, model)
    println("Response: $response")

    // With streaming
    executor.executeStreaming(prompt, model).collect { chunk ->
        print(chunk)
    }
}

Packages

ai.koog.prompt.executor.model

common