qc-text-builder/internal/domain/llm_settings.go

package domain

import (
	"math"
	"strings"
)

const (
	LLMProviderOpenAI    = "openai"
	LLMProviderAnthropic = "anthropic"
	LLMProviderGoogle    = "google"
	LLMProviderXAI       = "xai"
	LLMProviderOllama    = "ollama"

	defaultLLMTemperature = 0.2
	minLLMTemperature     = 0.0
	maxLLMTemperature     = 2.0
	defaultLLMMaxTokens   = 1200
	minLLMMaxTokens       = 64
	maxLLMMaxTokens       = 8192
)

type LLMModelOption struct {
	Value string
	Label string
}

type LLMProviderOption struct {
	Value  string
	Label  string
	Models []LLMModelOption
}

func DefaultLLMProvider() string {
	return LLMProviderOpenAI
}

func LLMProviderOptions() []LLMProviderOption {
	return []LLMProviderOption{
		{
			Value: LLMProviderOpenAI,
			Label: "OpenAI",
			Models: []LLMModelOption{
				{Value: "gpt-5.2", Label: "gpt-5.2"},
				{Value: "gpt-5.4", Label: "gpt-5.4"},
			},
		},
		{
			Value: LLMProviderAnthropic,
			Label: "Anthropic",
			Models: []LLMModelOption{
				{Value: "claude-sonnet-4-5", Label: "claude-sonnet-4-5"},
				{Value: "claude-opus-4-1", Label: "claude-opus-4-1"},
			},
		},
		{
			Value: LLMProviderGoogle,
			Label: "Google",
			Models: []LLMModelOption{
				{Value: "gemini-2.5-pro", Label: "gemini-2.5-pro"},
				{Value: "gemini-2.5-flash", Label: "gemini-2.5-flash"},
			},
		},
		{
			Value: LLMProviderXAI,
			Label: "xAI",
			Models: []LLMModelOption{
				{Value: "grok-4", Label: "grok-4"},
				{Value: "grok-3-mini", Label: "grok-3-mini"},
			},
		},
		{
			Value: LLMProviderOllama,
			Label: "Ollama",
			Models: []LLMModelOption{
				{Value: "llama3.2", Label: "llama3.2"},
				{Value: "qwen2.5", Label: "qwen2.5"},
				{Value: "mistral", Label: "mistral"},
			},
		},
	}
}

func LLMModelsByProvider(provider string) []LLMModelOption {
	normalized := NormalizeLLMProvider(provider)
	for _, option := range LLMProviderOptions() {
		if option.Value == normalized {
			out := make([]LLMModelOption, len(option.Models))
			copy(out, option.Models)
			return out
		}
	}
	return nil
}

func NormalizeLLMProvider(provider string) string {
	value := strings.ToLower(strings.TrimSpace(provider))
	for _, option := range LLMProviderOptions() {
		if option.Value == value {
			return value
		}
	}
	return DefaultLLMProvider()
}

func NormalizeLLMModel(provider, model string) string {
	models := LLMModelsByProvider(provider)
	if len(models) == 0 {
		return ""
	}
	value := strings.TrimSpace(model)
	for _, option := range models {
		if option.Value == value {
			return value
		}
	}
	return models[0].Value
}

func DefaultLLMTemperature() float64 {
	return defaultLLMTemperature
}

func NormalizeLLMTemperature(value float64) float64 {
	if math.IsNaN(value) || math.IsInf(value, 0) {
		return defaultLLMTemperature
	}
	if value < minLLMTemperature {
		value = minLLMTemperature
	}
	if value > maxLLMTemperature {
		value = maxLLMTemperature
	}
	return math.Round(value*100) / 100
}

func DefaultLLMMaxTokens() int {
	return defaultLLMMaxTokens
}

func NormalizeLLMMaxTokens(value int) int {
	if value <= 0 {
		return defaultLLMMaxTokens
	}
	if value < minLLMMaxTokens {
		return minLLMMaxTokens
	}
	if value > maxLLMMaxTokens {
		return maxLLMMaxTokens
	}
	return value
}

func LLMAPIKeyForProvider(provider string, settings AppSettings) string {
	switch NormalizeLLMProvider(provider) {
	case LLMProviderOpenAI:
		return strings.TrimSpace(settings.OpenAIAPIKeyEncrypted)
	case LLMProviderAnthropic:
		return strings.TrimSpace(settings.AnthropicAPIKeyEncrypted)
	case LLMProviderGoogle:
		return strings.TrimSpace(settings.GoogleAPIKeyEncrypted)
	case LLMProviderXAI:
		return strings.TrimSpace(settings.XAIAPIKeyEncrypted)
	case LLMProviderOllama:
		return strings.TrimSpace(settings.OllamaAPIKeyEncrypted)
	default:
		return ""
	}
}