package llm_service import ( "ai_scheduler/internal/config" "ai_scheduler/internal/data/impl" "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" "xorm.io/builder" ) type OllamaService struct { client *utils_ollama.Client config *config.Config chatHis *impl.ChatImpl } func NewOllamaGenerate( client *utils_ollama.Client, config *config.Config, chatHis *impl.ChatImpl, ) *OllamaService { return &OllamaService{ client: client, config: config, chatHis: chatHis, } } func (r *OllamaService) IntentRecognize(ctx context.Context, req *entitys.ToolSelect) (msg string, err error) { if err != nil { return } toolDefinitions := r.registerToolsOllama(req.Tools) match, err := r.client.ToolSelect(ctx, rec.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) RecognizeWithImg(ctx context.Context, imgByte []api.ImageData, ch chan entitys.Response) (desc api.GenerateResponse, err error) { if imgByte == nil { return } entitys.ResLog(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: imgByte, KeepAlive: &api.Duration{Duration: 3600 * time.Second}, //Think: &api.ThinkValue{Value: false}, }) if err != nil { return } entitys.ResLog(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 }