如何使用 Go 语言进行智能客服开发？

package main

import "github.com/gin-gonic/gin"

func main() {
    r := gin.Default()
    r.GET("/", func(c *gin.Context) {
        c.JSON(200, gin.H{
            "message": "Welcome to the Smart Customer Service System!",
        })
    })
    r.Run() // listen and serve on 0.0.0.0:8080
}

package main

import (
    "github.com/gin-gonic/gin"
    tf "github.com/galeone/tfgo"
    pb "github.com/galeone/tfgo/image.Tensorflow_inception_v3"
    "github.com/galeone/tfgo/tensorflow/core/framework/tensor_go"
    "github.com/gorilla/websocket"
    "log"
    "net/http"
)

var upgrader = websocket.Upgrader{
    ReadBufferSize:  1024,
    WriteBufferSize: 1024,
    CheckOrigin: func(r *http.Request) bool {
        return true
    },
}

type Message struct {
    Name string      `json:"name"`
    Body interface{} `json:"body"`
}

func main() {
    router := gin.Default()

    ai := NewAI()
    defer ai.Close()

    router.GET("/ws", func(c *gin.Context) {
        conn, err := upgrader.Upgrade(c.Writer, c.Request, nil)
        if err != nil {
            log.Println(err)
            return
        }
        defer conn.Close()

        for {
            var msg Message
            err := conn.ReadJSON(&msg)
            if err != nil {
                log.Println(err)
                break
            }

            response := ai.Query(msg.Body.(string))

            err = conn.WriteJSON(Message{
                Name: "response",
                Body: response,
            })
            if err != nil {
                log.Println(err)
                break
            }
        }
    })

    router.Run(":8080")
}

type AI struct {
    sess   *tf.Session
    graph  *tf.Graph
    labels []string
}

func NewAI() *AI {
    graph := tf.NewGraph()
    model, err := ioutil.ReadFile("model.pb")
    if err != nil {
        log.Fatalf("Unable to read %q: %v", "model.pb", err)
    }
    if err := graph.Import(model, ""); err != nil {
        log.Fatalf("Unable to read model %q: %v", "model.pb", err)
    }

    labels := make([]string, 0)
    file, err := os.Open("labels.txt")
    if err != nil {
        log.Fatalf("Unable to open labels file: %v", err)
    }
    defer file.Close()

    scanner := bufio.NewScanner(file)
    for scanner.Scan() {
        labels = append(labels, scanner.Text())
    }

    sess, err := tf.NewSession(graph, nil)
    if err != nil {
        log.Fatal(err)
    }

    return &AI{
        graph:  graph,
        sess:   sess,
        labels: labels,
    }
}

func (ai *AI) Query(input string) string {
    pb := tf.Output{
        Op:    ai.graph.Operation("input"),
        Index: 0,
    }

    prob := tf.Output{
        Op:    ai.graph.Operation("output"),
        Index: 0,
    }

    tensor, err := tensorflow.NewTensor(input)
    if err != nil {
        log.Fatalln("Cannot construct tensor: ", err)
    }

    result, err := ai.sess.Run(map[tf.Output]*tensorflow.Tensor{
        pb: tensor,
    }, []tf.Output{
        prob,
    }, nil)

    if err != nil {
        log.Fatal(err)
    }

    prob_result := result[0].Value().([][]float32)[0]
    max_prob_index := 0
    max_prob := prob_result[0]

    for i, prob := range prob_result {
        if prob > max_prob {
            max_prob = prob
            max_prob_index = i
        }
    }
    return ai.labels[max_prob_index]
}

func (ai *AI) Close() {
    ai.sess.Close()
}