511 lines
14 KiB
Go
511 lines
14 KiB
Go
package service
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import (
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"context"
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"encoding/json"
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"errors"
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"fmt"
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"strings"
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"time"
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"prompts-core/consts/public"
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"prompts-core/dao"
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"prompts-core/model/dto"
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"prompts-core/model/entity"
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"github.com/gogf/gf/v2/container/gvar"
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"github.com/gogf/gf/v2/frame/g"
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)
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// ============================================
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// 核心业务流程
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// ============================================
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// ComposeMessages 拼接提示词主流程
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func (s *promptService) ComposeMessages(ctx context.Context, req *dto.ComposeMessagesReq) (*dto.ComposeMessagesRes, error) {
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var (
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epicycleId int64
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err error
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historyMessages []Message // 用来存放历史会话
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)
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// 1. 如果不需要构建返回记录id
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if req.IsBuilder == false {
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epicycleId, err = dao.ComposeSession.Insert(ctx, &entity.ComposeSession{
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SessionId: req.SessionId,
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Remark: req.Cause,
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})
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return &dto.ComposeMessagesRes{
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EpicycleId: epicycleId,
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}, nil
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}
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// 2. 获取当前用户模型信息
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sessionModel, err := dao.Model.GetByIsChatModel(ctx) //获取会话模型
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if err != nil {
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return nil, err
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}
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if sessionModel == nil {
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return nil, errors.New("当前没有对话模型，请添加")
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}
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model, err := dao.Model.GetByModelName(ctx, req.ModelName) //获取模型信息
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if err != nil {
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return nil, err
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}
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if model == nil {
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return nil, fmt.Errorf("模型 %s 不存在", sessionModel.ModelName)
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}
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// 3 获取历史会话
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historyMessages, err = Session.GetSessionHistoryForInference(ctx, req.SessionId)
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if err != nil {
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g.Log().Errorf(ctx, "获取历史会话失败: %v，将不使用历史会话", err)
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historyMessages = nil // 出错就用空的，不影响主流程
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}
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// 4. 调用推理模型
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taskID, err := s.callInferenceModel(ctx, req, sessionModel, model, historyMessages)
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if err != nil {
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return nil, err
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}
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// 5. 保存相关记录
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_, err = dao.ComposeTask.Insert(ctx, &entity.ComposeTask{
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TaskId: taskID,
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ModelName: req.ModelName,
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SkillName: req.SkillName,
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RequestPayload: mustMarshal(req),
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Status: public.ComposeStatusPending,
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})
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if err != nil {
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return nil, err
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}
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// 6. 等待结果
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taskRecord, err := s.waitForResult(ctx, taskID)
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if err != nil {
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return nil, err
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}
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// 7. 处理返回结果
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messages := s.processResult(taskRecord)
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//8.1 数据库查询当前会话是否存在
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session, err := dao.ComposeSession.GetBySessionId(ctx, req.SessionId)
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if err != nil {
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return nil, err
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}
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if session == nil {
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//8.2 不存在则创建新会话记录
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epicycleId, err = dao.ComposeSession.Insert(ctx, &entity.ComposeSession{
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SessionId: req.SessionId,
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RequestContent: messages,
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})
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if err != nil {
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return nil, err
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}
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}
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// 9. 更新历史会话
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_, err = dao.ComposeSession.UpdateById(ctx, epicycleId, map[string]any{
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entity.ComposeSessionCol.RequestContent: messages,
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})
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return &dto.ComposeMessagesRes{
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Messages: messages,
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EpicycleId: epicycleId,
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}, nil
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}
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func (s *promptService) Callback(ctx context.Context, req *dto.CallbackReq) error {
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g.Log().Infof(ctx, "[Callback][RECV] taskId=%s state=%d ossFile=%s fileType=%s textLen=%d",
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req.TaskId, req.State, req.OssFile, req.FileType, len(req.Text))
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// ============ 先查任务是否存在 ============
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task, err := dao.ComposeTask.GetByTaskId(ctx, req.TaskId)
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if err != nil {
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return err
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}
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if task == nil {
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return fmt.Errorf("任务不存在: %s", req.TaskId)
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}
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// ============ 根据状态区分处理 ============
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if req.State == 3 {
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// 失败：直接更新状态
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_, err = dao.ComposeTask.UpdateByTaskId(ctx, req.TaskId, map[string]any{
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entity.ComposeTaskCol.Status: public.ComposeStatusFailed,
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entity.ComposeTaskCol.ErrorMessage: req.ErrorMsg,
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})
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return err
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}
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// ======================================
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// 成功：解析模型输出
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result, err := parseModelOutput(req.Text)
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if err != nil {
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_, updateErr := dao.ComposeTask.UpdateByTaskId(ctx, req.TaskId, map[string]any{
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entity.ComposeTaskCol.Status: public.ComposeStatusFailed,
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entity.ComposeTaskCol.ErrorMessage: err.Error(),
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})
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if updateErr != nil {
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g.Log().Warningf(ctx, "[Callback] 更新失败状态出错 taskId=%s err=%v", req.TaskId, updateErr)
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}
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return err
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}
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// ============ result 可能为 nil ============
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var messages any
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if result != nil {
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messages = result
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}
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// =======================================
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_, err = dao.ComposeTask.UpdateByTaskId(ctx, req.TaskId, map[string]any{
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entity.ComposeTaskCol.Status: public.ComposeStatusSuccess,
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entity.ComposeTaskCol.Messages: messages,
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})
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if err != nil {
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g.Log().Errorf(ctx, "[Callback] 更新任务失败 taskId=%s err=%v", req.TaskId, err)
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}
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return err
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}
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// GetComposeTask 查询任务结果
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func (s *promptService) GetComposeTask(ctx context.Context, taskID string) (*dto.GetComposeTaskRes, error) {
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record, err := dao.ComposeTask.GetByTaskId(ctx, taskID)
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if err != nil {
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return nil, err
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}
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if record == nil {
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return nil, fmt.Errorf("未找到任务(taskId=%s)", taskID)
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}
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// 如果 Messages 是字符串，反序列化为 JSON 数组
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messages := record.Messages
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if str, ok := messages.(string); ok && str != "" {
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var parsed any
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if err := json.Unmarshal([]byte(str), &parsed); err == nil {
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messages = parsed
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}
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}
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return &dto.GetComposeTaskRes{
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TaskId: record.TaskId,
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Status: record.Status,
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ErrorMessage: record.ErrorMessage,
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Messages: messages,
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}, nil
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}
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// ============================================
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// 步骤4：调用推理模型
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// ============================================
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func (s *promptService) callInferenceModel(ctx context.Context, req *dto.ComposeMessagesReq, sessionModel *entity.AsynchModel, model *entity.AsynchModel, historyMessages []Message) (string, error) {
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// 构建推理模型请求
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taskReq, err := buildInferenceRequest(ctx, req, sessionModel, model, historyMessages)
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if err != nil {
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return "", fmt.Errorf("构建推理请求失败: %w", err)
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}
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// 创建网关任务
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taskID, err := createGatewayTask(ctx, taskReq)
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if err != nil {
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return "", fmt.Errorf("创建网关任务失败: %w", err)
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}
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if taskID == "" {
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return "", errors.New("网关未返回taskId")
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}
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return taskID, nil
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}
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// ============================================
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// 步骤6：等待结果
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// ============================================
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func (s *promptService) waitForResult(ctx context.Context, taskID string) (*entity.ComposeTask, error) {
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timeout := time.Duration(getIntConfig(ctx, "task.waitTimeoutSeconds", 30)) * time.Second
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pollInterval := time.Duration(getIntConfig(ctx, "task.pollIntervalMillis", 500)) * time.Millisecond
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deadline := time.Now().Add(timeout)
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for {
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// 1. 查数据库
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record, err := dao.ComposeTask.GetByTaskId(ctx, taskID)
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if err != nil {
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return nil, err
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}
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if record != nil {
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switch record.Status {
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case public.ComposeStatusSuccess:
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return record, nil
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case public.ComposeStatusFailed:
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return nil, formatTaskError(taskID, record.ErrorMessage)
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}
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}
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// 2. 查网关状态
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state, err := queryGatewayTaskState(ctx, taskID)
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if err != nil {
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// ============ 网关不可达不终止，继续轮询 ============
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g.Log().Warningf(ctx, "[waitForResult] 查询网关失败 taskId=%s err=%v", taskID, err)
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} else {
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switch state {
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case 2: // 网关成功
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// ============ 网关已成功，主动更新数据库 ============
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if record != nil {
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dao.ComposeTask.UpdateByTaskId(ctx, taskID, map[string]any{
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entity.ComposeTaskCol.Status: public.ComposeStatusSuccess,
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})
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}
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case 3: // 网关失败
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if record != nil {
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dao.ComposeTask.UpdateByTaskId(ctx, taskID, map[string]any{
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entity.ComposeTaskCol.Status: public.ComposeStatusFailed,
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entity.ComposeTaskCol.ErrorMessage: "model-gateway 任务执行失败",
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})
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}
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return nil, fmt.Errorf("model-gateway 任务执行失败(taskId=%s)", taskID)
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}
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}
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// 3. 超时检查
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if time.Now().After(deadline) {
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return nil, fmt.Errorf("等待任务回调超时(taskId=%s)", taskID)
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}
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time.Sleep(pollInterval)
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}
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}
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// ============================================
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// 步骤6：处理结果
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// ============================================
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func (s *promptService) processResult(taskRecord *entity.ComposeTask) map[string]any {
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if taskRecord == nil {
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return nil
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}
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// 1. 解析 Messages 获取 content
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var contentStr string
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switch v := taskRecord.Messages.(type) {
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case *gvar.Var:
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if v != nil {
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var mapped map[string]any
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json.Unmarshal([]byte(v.String()), &mapped)
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if c, ok := mapped["content"].(string); ok {
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contentStr = c
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}
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}
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case string:
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var mapped map[string]any
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json.Unmarshal([]byte(v), &mapped)
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if c, ok := mapped["content"].(string); ok {
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contentStr = c
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}
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case map[string]any:
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if c, ok := v["content"].(string); ok {
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contentStr = c
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}
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}
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// 2. 清理并解析
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contentStr = cleanJSONString(contentStr)
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var innerData map[string]any
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json.Unmarshal([]byte(contentStr), &innerData)
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return innerData
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}
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// ============================================
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// 消息处理管道
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// ============================================
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// parseStoredMessages 从数据库存储的数据中解析消息列表
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// 处理多层 JSON 嵌套的情况
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func parseStoredMessages(data any) []dto.Message {
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if data == nil {
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return nil
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}
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// 统一序列化为 JSON
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jsonBytes, err := json.Marshal(data)
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if err != nil {
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return nil
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}
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// 第一层解析：尝试直接解析为消息数组
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var messages []dto.Message
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if err := json.Unmarshal(jsonBytes, &messages); err == nil {
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// 成功解析，但需要处理 content 可能是 JSON 字符串的情况
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return deepNormalizeMessages(messages)
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}
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// 第二层解析：可能是 JSON 字符串包裹的数组
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var rawStr string
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if err := json.Unmarshal(jsonBytes, &rawStr); err != nil {
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return nil
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}
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// 尝试解析字符串为消息数组
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if err := json.Unmarshal([]byte(rawStr), &messages); err == nil {
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return deepNormalizeMessages(messages)
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}
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return nil
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}
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// deepNormalizeMessages 深度规范化消息，处理 content 为 JSON 字符串的情况
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func deepNormalizeMessages(messages []dto.Message) []dto.Message {
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for i, msg := range messages {
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messages[i].Content = deepNormalizeContent(msg.Content)
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}
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return messages
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}
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// deepNormalizeContent 递归处理 content，支持多层 JSON 嵌套
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func deepNormalizeContent(content any) any {
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switch v := content.(type) {
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case string:
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// 尝试解析 JSON 字符串
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v = strings.TrimSpace(v)
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if v == "" {
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return v
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}
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// 如果看起来像 JSON，尝试解析
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if looksLikeJSON(v) {
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var parsed any
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if err := json.Unmarshal([]byte(v), &parsed); err == nil {
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// 递归处理解析后的内容
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return deepNormalizeContent(parsed)
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}
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}
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return v
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case []any:
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// 递归处理数组中的每个元素
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result := make([]any, len(v))
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for i, item := range v {
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result[i] = deepNormalizeContent(item)
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}
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return result
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case map[string]any:
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// 递归处理 map 中的每个值
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result := make(map[string]any, len(v))
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for k, val := range v {
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result[k] = deepNormalizeContent(val)
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}
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return result
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default:
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return content
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}
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}
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func NormalizeToTwoPart(messages []dto.Message, req *dto.ComposeMessagesReq) []dto.Message {
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var result []dto.Message
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// 1. 提取 system
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sysContent := extractByRole(messages, "system")
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if sysContent == nil {
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sysContent = renderFormText(req.Form, false)
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}
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result = append(result, dto.Message{Role: "system", Content: sysContent})
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// 2. 提取 form
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formContent := extractByRole(messages, "form")
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if formContent != nil {
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result = append(result, dto.Message{Role: "form", Content: formContent})
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} else if req != nil {
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result = append(result, dto.Message{Role: "form", Content: renderFormJSON(req.Form)})
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}
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// 3. 提取 skill
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skillContent := extractByRole(messages, "skill")
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if skillContent != nil {
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result = append(result, dto.Message{Role: "skill", Content: skillContent})
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} else if req != nil && req.SkillName != "" {
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result = append(result, dto.Message{Role: "skill", Content: req.SkillName})
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}
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// 4. 提取 history（如果模型返回了压缩后的历史）
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historyContent := extractByRole(messages, "history")
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if historyContent != nil {
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result = append(result, dto.Message{Role: "history", Content: historyContent})
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}
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// 5. 提取 user
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usrContent := extractByRole(messages, "user")
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if usrContent == nil {
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usrContent = renderUserText(req.UserForm, req.Form)
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}
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result = append(result, dto.Message{Role: "user", Content: usrContent})
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return result
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}
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// ============================================
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// 辅助函数：按 role 提取第一个非空 content
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// ============================================
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func extractByRole(messages []dto.Message, role string) any {
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for _, msg := range messages {
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if msg.Role == role && !isEmptyValue(msg.Content) {
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return msg.Content
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}
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}
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return nil
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}
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// ============================================
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// 辅助函数：将 form 渲染为 JSON 对象
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// ============================================
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func renderFormJSON(form map[string]any) map[string]any {
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if form == nil {
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return nil
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}
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result := make(map[string]any)
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for k, v := range form {
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result[k] = v
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}
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return result
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}
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func enrichSystemMessages(messages []dto.Message, req *dto.ComposeMessagesReq) []dto.Message {
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if len(messages) == 0 {
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return messages
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}
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// 获取系统字段的值映射
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systemValues := extractSystemValues(req)
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for i, msg := range messages {
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if msg.Role != "system" {
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continue
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}
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// 为 schema 数组补充 value
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switch content := msg.Content.(type) {
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case []any:
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messages[i].Content = enrichSchemaWithValues(content, systemValues)
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case []map[string]any:
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arr := make([]any, len(content))
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for j, item := range content {
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arr[j] = item
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}
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messages[i].Content = enrichSchemaWithValues(arr, systemValues)
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case map[string]any:
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// 合并但不覆盖已有值
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for k, v := range systemValues {
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if _, exists := content[k]; !exists {
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content[k] = v
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}
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}
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messages[i].Content = content
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}
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}
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return messages
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}
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