package llm

import (
	"context"
	"errors"
	"github.com/sashabaranov/go-openai"
	"log/slog"
)

var (
	ErrLlmBackendRequestFailed = errors.New("llm back-end request failed")
	ErrNoChoices               = errors.New("no choices in LLM response")
)

type LlmConnector struct {
	client *openai.Client
}

func NewConnector(baseUrl string, token string) *LlmConnector {
	config := openai.DefaultConfig(token)
	config.BaseURL = baseUrl

	client := openai.NewClientWithConfig(config)

	return &LlmConnector{
		client: client,
	}
}

func (l *LlmConnector) HandleSingleRequest(text string, model string, requestContext RequestContext) (string, error) {
	systemPrompt := "You're a bot in the Telegram chat. " +
		"You're using a free model called \"" + model + "\". " +
		"You see only messages addressed to you using commands due to privacy settings."

	if !requestContext.Empty {
		systemPrompt += " " + requestContext.Prompt()
	}

	req := openai.ChatCompletionRequest{
		Model: model,
		Messages: []openai.ChatCompletionMessage{
			{
				Role:    openai.ChatMessageRoleSystem,
				Content: systemPrompt,
			},
		},
	}

	req.Messages = append(req.Messages, openai.ChatCompletionMessage{
		Role:    openai.ChatMessageRoleUser,
		Content: text,
	})

	resp, err := l.client.CreateChatCompletion(context.Background(), req)
	if err != nil {
		slog.Error("llm: LLM back-end request failed", "error", err)

		return "", ErrLlmBackendRequestFailed
	}

	slog.Debug("llm: Received LLM back-end response", "response", resp)

	if len(resp.Choices) < 1 {
		slog.Error("llm: LLM back-end reply has no choices")

		return "", ErrNoChoices
	}

	return resp.Choices[0].Message.Content, nil
}

func (l *LlmConnector) Summarize(text string, model string) (string, error) {
	req := openai.ChatCompletionRequest{
		Model: model,
		Messages: []openai.ChatCompletionMessage{
			{
				Role: openai.ChatMessageRoleSystem,
				Content: "You're a text shortener. Give a very brief summary of the main facts " +
					"point by point.  Format them as a list of bullet points each starting with \"-\". " +
					"Avoid any commentaries and value judgement on the matter. " +
					"If possible, respond in the same language as the original text." +
					"Do not use any non-ASCII characters.",
			},
		},
	}

	req.Messages = append(req.Messages, openai.ChatCompletionMessage{
		Role:    openai.ChatMessageRoleUser,
		Content: text,
	})

	resp, err := l.client.CreateChatCompletion(context.Background(), req)
	if err != nil {
		slog.Error("llm: LLM back-end request failed", "error", err)

		return "", ErrLlmBackendRequestFailed
	}

	slog.Debug("llm: Received LLM back-end response", resp)

	if len(resp.Choices) < 1 {
		slog.Error("llm: LLM back-end reply has no choices")

		return "", ErrNoChoices
	}

	return resp.Choices[0].Message.Content, nil
}

func (l *LlmConnector) GetModels() []string {
	var result []string

	models, err := l.client.ListModels(context.Background())
	if err != nil {
		slog.Error("llm: Model list request failed", "error", err)

		return result
	}

	slog.Info("Model list retrieved", "models", models)

	for _, model := range models.Models {
		result = append(result, model.ID)
	}

	return result
}

func (l *LlmConnector) HasModel(id string) bool {
	model, err := l.client.GetModel(context.Background(), id)
	if err != nil {
		slog.Error("llm: Model request failed", "error", err)
	}

	slog.Debug("llm: Returned model", "model", model)

	if model.ID != "" {
		return true
	}

	return false
}