第二章：Go语言大模型调用框架 - Eino自定义工具调用

1. 自定义工具

1.1 模拟调用天气API获取数据

packagetoolimport"context"// WeatherRequest 工具的参数typeWeatherRequeststruct{Citystring`json:"city"`}// WeatherResponse 工具的返回集typeWeatherResponsestruct{Citystring`json:"city"`Tempstring`json:"temp"`Weatherstring`json:"weather"`}// GetWeather 工具的执行逻辑funcGetWeather(ctx context.Context,req*WeatherRequest)(*WeatherResponse,error){// 模拟天气的API返回结果mockData:=map[string]WeatherResponse{"北京":{City:"北京",Temp:"22°C",Weather:"晴"},"上海":{City:"上海",Temp:"26°C",Weather:"多云"},"深圳":{City:"深圳",Temp:"30°C",Weather:"阵雨"},}ifdata,ok:=mockData[req.City];ok{return&data,nil}return&WeatherResponse{City:req.City,Temp:"未知",Weather:"未知"},nil}

1.2 集成工具进行回复

packagemainimport("context"myTool"day03/tool""fmt""github.com/cloudwego/eino-ext/components/model/openai""github.com/cloudwego/eino/components/tool""github.com/cloudwego/eino/components/tool/utils""github.com/cloudwego/eino/compose""github.com/cloudwego/eino/flow/agent/react""github.com/cloudwego/eino/schema""log")// 自定义工具funcmain(){ctx:=context.Background()// 调用LLMmodel,err:=openai.NewChatModel(ctx,&openai.ChatModelConfig{BaseURL:"https://api-inference.modelscope.cn/v1/",APIKey:"xxx",Model:"Qwen/Qwen3.5-35B-A3B",})iferr!=nil{log.Fatalf("创建 ChatModel 失败: %v",err)}// 创建工具weatherTool:=utils.NewTool(&schema.ToolInfo{Name:"get_weather",Desc:"查询指定城市的实时天气信息，包括温度和天气状况",ParamsOneOf:schema.NewParamsOneOfByParams(map[string]*schema.ParameterInfo{"city":{Type:schema.String,Desc:"要查询天气的城市名称，如：北京、上海、深圳",Required:true,},}),},myTool.GetWeather,)// 验证工具信息/*info, _ := weatherTool.Info(ctx) fmt.Printf("工具名: %s\n", info.Name) fmt.Printf("工具描述: %s\n", info.Desc)*/// 创建ReAct Agentagent,err:=react.NewAgent(ctx,&react.AgentConfig{ToolCallingModel:model,ToolsConfig:compose.ToolsNodeConfig{Tools:[]tool.BaseTool{weatherTool},},})iferr!=nil{log.Fatalf("创建 Agent 失败: %v",err)}// 模拟参数// args := `{"city": "深圳"}`// 执行工具/*result, err := weatherTool.InvokableRun(ctx, args) if err != nil { log.Fatal(err) } fmt.Printf("执行结果: %s\n", result)*/// 解析结果/* var resp myTool.WeatherResponse json.Unmarshal([]byte(result), &resp) fmt.Printf("城市: %s, 温度: %s, 天气: %s\n", resp.City, resp.Temp, resp.Weather)*/// 向agent 提问answer,err:=agent.Generate(ctx,[]*schema.Message{schema.UserMessage("上海今天天气怎么样？"),})iferr!=nil{log.Fatalf("Agent 执行失败: %v",err)}fmt.Printf("Agent 执行结果: %s\n",answer.Content)}

输出结果：