package llm_service

import (
	"ai_scheduler/internal/config"
	"ai_scheduler/internal/data/model"
	"ai_scheduler/internal/entitys"
	"ai_scheduler/internal/pkg"
	"ai_scheduler/internal/pkg/utils_ollama"
	"context"
	"encoding/json"
	"errors"
	"strings"
	"time"

	"github.com/ollama/ollama/api"
)

type OllamaService struct {
	client *utils_ollama.Client
	config *config.Config
}

func NewOllamaGenerate(
	client *utils_ollama.Client,
	config *config.Config,
) *OllamaService {
	return &OllamaService{
		client: client,
		config: config,
	}
}

func (r *OllamaService) IntentRecognize(ctx context.Context, requireData *entitys.RequireData) (msg string, err error) {
	prompt, err := r.getPrompt(ctx, requireData)
	if err != nil {
		return
	}
	toolDefinitions := r.registerToolsOllama(requireData.Tasks)

	match, err := r.client.ToolSelect(ctx, prompt, toolDefinitions)
	if err != nil {
		return
	}

	if len(match.Message.Content) == 0 {
		if match.Message.ToolCalls != nil {
			var matchFromTools = &entitys.Match{
				Confidence: 1,
				Index:      match.Message.ToolCalls[0].Function.Name,
				Parameters: pkg.JsonStringIgonErr(match.Message.ToolCalls[0].Function.Arguments),
				IsMatch:    true,
			}
			match.Message.Content = pkg.JsonStringIgonErr(matchFromTools)
		} else {
			err = errors.New("不太明白你想表达的意思呢，可以在仔细描述一下您所需要的内容吗，感谢感谢")
			return
		}
	}

	msg = match.Message.Content
	return
}

func (r *OllamaService) getPrompt(ctx context.Context, requireData *entitys.RequireData) ([]api.Message, error) {

	var (
		prompt = make([]api.Message, 0)
	)
	prompt = append(prompt, api.Message{
		Role:    "system",
		Content: buildSystemPrompt(requireData.Sys.SysPrompt),
	}, api.Message{
		Role:    "assistant",
		Content: "### 聊天记录:" + pkg.JsonStringIgonErr(buildAssistant(requireData.Histories)),
	}, api.Message{
		Role:    "user",
		Content: r.getUserContent(requireData),
		//Images:  requireData.ImgByte,
	})

	if len(requireData.ImgByte) > 0 {
		desc, err := r.RecognizeWithImg(ctx, requireData)
		if err != nil {
			return nil, err
		}
		var imgs strings.Builder
		imgs.WriteString("### 用户上传图片解析内容:\n")

		prompt = append(prompt, api.Message{
			Role:    "image_desc",
			Content: "" + desc.Response,
		})
	}
	return prompt, nil
}

func (r *OllamaService) getUserContent(requireData *entitys.RequireData) string {
	var content strings.Builder
	content.WriteString(requireData.Req.Text)
	if len(requireData.ImgByte) > 0 {
		content.WriteString("\n")
		content.WriteString("### 图片内容已经解析到image_desc里")
	}

	if len(requireData.Req.Tags) > 0 {
		content.WriteString("\n")
		content.WriteString("### 工具必须使用：")
		content.WriteString(requireData.Req.Tags)
	}
	return content.String()
}

func (r *OllamaService) RecognizeWithImg(ctx context.Context, requireData *entitys.RequireData) (desc api.GenerateResponse, err error) {
	if requireData.ImgByte == nil {
		return
	}
	entitys.ResLog(requireData.Ch, "recognize_img_start", "图片识别中...")

	desc, err = r.client.Generation(ctx, &api.GenerateRequest{
		Model:     r.config.Ollama.VlModel,
		Stream:    new(bool),
		System:    r.config.DefaultPrompt.ImgRecognize.SystemPrompt,
		Prompt:    r.config.DefaultPrompt.ImgRecognize.UserPrompt,
		Images:    requireData.ImgByte,
		KeepAlive: &api.Duration{Duration: 3600 * time.Second},
	})
	if err != nil {
		return
	}
	entitys.ResLog(requireData.Ch, "recognize_img_end", "图片识别完成，识别内容："+desc.Response)
	return
}

func (r *OllamaService) registerToolsOllama(tasks []model.AiTask) []api.Tool {
	taskPrompt := make([]api.Tool, 0)
	for _, task := range tasks {
		var taskConfig entitys.TaskConfigDetail
		err := json.Unmarshal([]byte(task.Config), &taskConfig)
		if err != nil {
			continue
		}

		taskPrompt = append(taskPrompt, api.Tool{
			Type: "function",
			Function: api.ToolFunction{
				Name:        task.Index,
				Description: task.Desc,
				Parameters: api.ToolFunctionParameters{
					Type:       taskConfig.Param.Type,
					Required:   taskConfig.Param.Required,
					Properties: taskConfig.Param.Properties,
				},
			},
		})

	}
	return taskPrompt
}