Text Generation

TextGenerator provides a fluent builder for generating text from LLM providers. It supports prompt templates, model parameters, tool usage, caching, and lifecycle callbacks.

Basic Usage

import sdk "github.com/xraph/ai-sdk"

result, err := sdk.NewTextGenerator(ctx, llmManager, logger, metrics).
    WithPrompt("Explain concurrency in Go.").
    Execute()
if err != nil {
    return err
}

fmt.Println(result.Text)

Prompt Templates

Use {{.var}} syntax for template variables:

result, err := sdk.NewTextGenerator(ctx, llmManager, logger, metrics).
    WithPrompt("Translate the following to {{.language}}: {{.text}}").
    WithVar("language", "French").
    WithVar("text", "Hello, world!").
    Execute()

Model Configuration

result, err := sdk.NewTextGenerator(ctx, llmManager, logger, metrics).
    WithProvider("openai").
    WithModel("gpt-4").
    WithPrompt("Write a haiku about Go.").
    Execute()

Generation Parameters

result, err := sdk.NewTextGenerator(ctx, llmManager, logger, metrics).
    WithPrompt("Generate creative ideas for a startup.").
    WithTemperature(0.9).
    WithMaxTokens(500).
    WithTopP(0.95).
    WithStop([]string{"\n\n"}).
    Execute()

Method	Description
`WithTemperature(float64)`	Controls randomness (0.0 = deterministic, 1.0 = creative)
`WithMaxTokens(int)`	Maximum tokens in the response
`WithTopP(float64)`	Nucleus sampling threshold
`WithTopK(int)`	Top-K sampling
`WithStop([]string)`	Stop sequences

System Prompt

result, err := sdk.NewTextGenerator(ctx, llmManager, logger, metrics).
    WithSystemPrompt("You are an expert Go developer. Answer concisely.").
    WithPrompt("What is a channel?").
    Execute()

Message History

Pass existing conversation history:

result, err := sdk.NewTextGenerator(ctx, llmManager, logger, metrics).
    WithMessages([]llm.ChatMessage{
        {Role: "user", Content: "What is Go?"},
        {Role: "assistant", Content: "Go is a statically typed programming language..."},
    }).
    WithPrompt("How does it handle concurrency?").
    Execute()

Tools

Attach tools for function calling:

result, err := sdk.NewTextGenerator(ctx, llmManager, logger, metrics).
    WithPrompt("What is the weather in Tokyo?").
    WithTools(weatherTool).
    WithToolChoice("auto").
    Execute()

Caching

Enable response caching to reduce costs for repeated prompts:

result, err := sdk.NewTextGenerator(ctx, llmManager, logger, metrics).
    WithPrompt("What are Go's main features?").
    WithCache(true).
    WithCacheTTL(1 * time.Hour).
    Execute()

Timeouts

result, err := sdk.NewTextGenerator(ctx, llmManager, logger, metrics).
    WithPrompt("Summarize this document...").
    WithTimeout(30 * time.Second).
    Execute()

Callbacks

React to generation lifecycle events:

result, err := sdk.NewTextGenerator(ctx, llmManager, logger, metrics).
    WithPrompt("Write an essay about AI safety.").
    OnStart(func() {
        log.Println("Generation started")
    }).
    OnComplete(func(r sdk.Result) {
        log.Printf("Generated %d tokens", r.Usage.TotalTokens)
    }).
    OnError(func(err error) {
        log.Printf("Generation failed: %v", err)
    }).
    Execute()

GenerateResult

The Execute() method returns a *GenerateResult:

Field	Type	Description
`Text`	`string`	The generated text
`Usage`	`Usage`	Token usage statistics
`ToolCalls`	`[]ToolCall`	Tool invocations requested by the model
`FinishReason`	`string`	Why generation stopped (`stop`, `length`, `tool_calls`)
`Duration`	`time.Duration`	Total execution time

Text Generation

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