添加了通过识别图片导入课表的模块
This commit is contained in:
44
main.go
44
main.go
@@ -3,6 +3,7 @@ package main
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import (
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"context"
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"flag"
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"io"
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"log"
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"net/http"
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"os"
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@@ -16,6 +17,7 @@ import (
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"jwts/config"
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grpcClient "jwts/grpc"
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"jwts/parser"
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"jwts/recognizer"
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"github.com/gin-gonic/gin"
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)
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@@ -93,6 +95,48 @@ func runHTTPServer() {
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})
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})
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// 课表图片识别接口
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r.POST("/recognize", func(c *gin.Context) {
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// 读取上传的图片文件
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file, header, err := c.Request.FormFile("image")
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if err != nil {
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c.JSON(http.StatusBadRequest, gin.H{"error": "请上传图片文件", "details": err.Error()})
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return
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}
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defer file.Close()
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log.Printf("收到图片上传: %s, 大小: %d bytes", header.Filename, header.Size)
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// 读取图片数据
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imageData, err := io.ReadAll(file)
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if err != nil {
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c.JSON(http.StatusInternalServerError, gin.H{"error": "读取图片失败", "details": err.Error()})
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return
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}
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// 调用识别模块
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courses, err := recognizer.RecognizeFromBytes(imageData)
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if err != nil {
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c.JSON(http.StatusInternalServerError, gin.H{"error": "识别失败", "details": err.Error()})
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return
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}
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// 打印识别结果
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recognizer.PrintCourses(courses)
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// 保存到JSON文件
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err = recognizer.SaveToJSON(courses, "schedule_result.json")
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if err != nil {
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log.Printf("保存JSON失败: %v", err)
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}
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c.JSON(http.StatusOK, gin.H{
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"message": "识别成功",
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"courses": courses,
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"count": len(courses),
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})
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})
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// 任务处理接口
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r.POST("/task", func(c *gin.Context) {
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// 这里可以根据请求体参数决定执行什么任务
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297
recognizer/recognizer.go
Normal file
297
recognizer/recognizer.go
Normal file
@@ -0,0 +1,297 @@
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package recognizer
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import (
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"bytes"
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"encoding/base64"
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"encoding/json"
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"fmt"
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"io"
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"log"
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"net/http"
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"os"
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"regexp"
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"strings"
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"time"
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"jwts/models"
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)
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// 配置 - 使用您提供的API配置
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const (
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APIURL = "https://api.littlelan.cn/v1/chat/completions"
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APIKey = "sk-Ll7P7vuiLum3N0pj7XaYfwHhD5UW1rDYlFoQ7F5JmeBfTewZ"
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Model = "qwen3.5-plus" // 使用qwen3.5-plus模型
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)
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// APIRequest API请求结构
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type APIRequest struct {
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Model string `json:"model"`
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Messages []Message `json:"messages"`
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MaxTokens int `json:"max_tokens"`
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EnableThinking *bool `json:"enable_thinking,omitempty"`
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ThinkingBudget *int `json:"thinking_budget,omitempty"`
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}
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// Message 消息结构
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type Message struct {
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Role string `json:"role"`
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Content interface{} `json:"content"`
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}
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// ContentItem 内容项
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type ContentItem struct {
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Type string `json:"type,omitempty"`
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Text string `json:"text,omitempty"`
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ImageURL *ImageURL `json:"image_url,omitempty"`
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}
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// ImageURL 图片URL
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type ImageURL struct {
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URL string `json:"url"`
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}
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// APIResponse API响应结构
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type APIResponse struct {
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Choices []Choice `json:"choices"`
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}
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// Choice 选择
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type Choice struct {
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Message Message `json:"message"`
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}
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// 全局HTTP客户端
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var client *http.Client
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// 初始化HTTP客户端
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func init() {
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client = &http.Client{
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Timeout: 120 * time.Second,
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}
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log.Println("recognizer模块已初始化")
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}
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// RecognizeFromFile 从图片文件识别课表
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func RecognizeFromFile(imagePath string) ([]models.Course, error) {
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fmt.Printf("[识别] 正在读取图片: %s\n", imagePath)
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// 读取图片文件
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imageData, err := os.ReadFile(imagePath)
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if err != nil {
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return nil, fmt.Errorf("读取图片失败: %v", err)
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}
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// 将图片转为base64
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imageBase64 := base64.StdEncoding.EncodeToString(imageData)
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fmt.Printf("[识别] 图片大小: %d bytes\n", len(imageData))
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return callAPI(imageBase64)
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}
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// RecognizeFromBytes 从图片数据识别课表
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func RecognizeFromBytes(imageData []byte) ([]models.Course, error) {
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fmt.Printf("[识别] 正在处理图片数据, 大小: %d bytes\n", len(imageData))
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// 将图片转为base64
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imageBase64 := base64.StdEncoding.EncodeToString(imageData)
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return callAPI(imageBase64)
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}
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// RecognizeFromBase64 从base64数据识别课表
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func RecognizeFromBase64(imageBase64 string) ([]models.Course, error) {
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fmt.Printf("[识别] 正在处理base64图片数据, 长度: %d\n", len(imageBase64))
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return callAPI(imageBase64)
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}
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// callAPI 调用API识别课表(带重试机制)
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func callAPI(imageBase64 string) ([]models.Course, error) {
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// 重试机制
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maxRetries := 3
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for retry := 0; retry < maxRetries; retry++ {
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if retry > 0 {
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fmt.Printf("[识别] 第 %d 次重试...\n", retry+1)
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time.Sleep(5 * time.Second) // 等待5秒后重试
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}
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courses, err := callAPISingle(imageBase64)
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if err == nil {
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return courses, nil
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}
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fmt.Printf("[识别] 尝试 %d/%d 失败: %v\n", retry+1, maxRetries, err)
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// 如果是504超时,继续重试;否则直接返回错误
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if !strings.Contains(err.Error(), "504") {
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return nil, err
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}
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}
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return nil, fmt.Errorf("已达到最大重试次数")
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}
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// callAPISingle 单次API调用
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func callAPISingle(imageBase64 string) ([]models.Course, error) {
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// 构建请求 - 发送图片给AI识别
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// 禁用qwen3.5的思考模式,避免产生大量不必要的token消耗
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falseVal := false
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zero := 0
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apiReq := APIRequest{
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Model: Model,
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MaxTokens: 4000,
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EnableThinking: &falseVal,
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ThinkingBudget: &zero,
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Messages: []Message{
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{
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Role: "user",
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Content: []ContentItem{
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{
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Type: "text",
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Text: `请解析以下课表图片,提取所有课程信息并以JSON数组格式返回。
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JSON格式要求:
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[{"name":"课程名","teacher":"老师名","room":"教室","schedule":[{"day":"星期X","section":[节次数组],"weeks":[周数数组]}]}]
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注意事项:
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1. day使用"星期一"到"星期日"
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2. section节次:上午1-2节为[1,2],上午3-4节为[3,4],下午5-6节为[5,6],下午7-8节为[7,8],晚上9-10节为[9,10],晚上11-12节为[11,12]
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3. weeks周数:格式如[1,2,3,4,5,6,7,8]或[9,10,11,12,13,14,15,16]
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4. 只返回JSON数组,不要任何其他文字。`,
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},
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{
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Type: "image_url",
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ImageURL: &ImageURL{
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URL: "data:image/png;base64," + imageBase64,
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},
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},
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},
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},
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},
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}
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jsonData, err := json.Marshal(apiReq)
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if err != nil {
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return nil, err
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}
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httpReq, err := http.NewRequest("POST", APIURL, bytes.NewBuffer(jsonData))
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if err != nil {
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return nil, err
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}
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httpReq.Header = http.Header{
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"Content-Type": []string{"application/json"},
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"Authorization": []string{"Bearer " + APIKey},
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}
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fmt.Println("[识别] 正在调用API进行识别...")
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resp, err := client.Do(httpReq)
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if err != nil {
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return nil, fmt.Errorf("API调用失败: %v", err)
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}
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defer resp.Body.Close()
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if resp.StatusCode != 200 {
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respBody, _ := io.ReadAll(resp.Body)
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return nil, fmt.Errorf("API调用失败: %d, %s", resp.StatusCode, string(respBody))
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}
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var apiResp APIResponse
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err = json.NewDecoder(resp.Body).Decode(&apiResp)
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if err != nil {
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return nil, fmt.Errorf("API响应解析失败: %v", err)
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}
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if len(apiResp.Choices) == 0 {
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return nil, fmt.Errorf("API返回为空")
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}
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// 处理Content,可能是string或[]ContentItem
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var resultText string
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switch c := apiResp.Choices[0].Message.Content.(type) {
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case string:
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resultText = c
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case []interface{}:
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for _, item := range c {
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if itemMap, ok := item.(map[string]interface{}); ok {
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if text, ok := itemMap["text"].(string); ok {
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resultText = text
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break
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}
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}
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}
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}
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fmt.Println("[识别] API响应已接收,正在解析...")
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fmt.Printf("[识别] 原始响应: %s\n", resultText)
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// 提取JSON部分
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var jsonMatch string
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// 1. 先尝试匹配 ```json ... ``` 代码块
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jsonBlockMatch := regexp.MustCompile("(?s)```json\\s*(\\[[\\s\\S]*?\\])\\s*```").FindStringSubmatch(resultText)
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if len(jsonBlockMatch) > 1 {
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jsonMatch = jsonBlockMatch[1]
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fmt.Println("[识别] 从json代码块中提取JSON")
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} else {
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// 2. 尝试匹配 ``` ... ``` 代码块中的数组
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jsonBlockMatch = regexp.MustCompile("(?s)```\\s*(\\[[\\s\\S]*?\\])\\s*```").FindStringSubmatch(resultText)
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if len(jsonBlockMatch) > 1 {
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jsonMatch = jsonBlockMatch[1]
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fmt.Println("[识别] 从代码块中提取JSON")
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} else {
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// 3. 查找最外层的JSON数组(匹配第一个 [ 到最后一个 ])
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// 使用非贪婪匹配找到完整的JSON数组
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jsonMatch = regexp.MustCompile(`(\[[\s\S]*\])`).FindString(resultText)
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if jsonMatch == "" {
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return nil, fmt.Errorf("未找到JSON数据,原始响应: %s", resultText)
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}
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fmt.Println("[识别] 从文本中提取JSON")
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}
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}
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// 解析JSON
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var courses []models.Course
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err = json.Unmarshal([]byte(jsonMatch), &courses)
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if err != nil {
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return nil, fmt.Errorf("JSON解析失败: %v, 数据: %s", err, jsonMatch)
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}
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fmt.Printf("[识别] 成功解析 %d 门课程\n", len(courses))
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return courses, nil
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}
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// SaveToJSON 保存课程数据到JSON文件
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func SaveToJSON(courses []models.Course, filename string) error {
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jsonData, err := json.MarshalIndent(courses, "", " ")
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if err != nil {
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return err
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}
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err = os.WriteFile(filename, jsonData, 0644)
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if err != nil {
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return err
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}
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fmt.Printf("[输出] JSON结果已保存到: %s\n", filename)
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return nil
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}
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// PrintCourses 打印课程信息
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func PrintCourses(courses []models.Course) {
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fmt.Println("\n==================================================")
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fmt.Println("识别结果:")
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fmt.Println("==================================================")
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for i, course := range courses {
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fmt.Printf("\n课程 %d: %s\n", i+1, course.Name)
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fmt.Printf(" 教师: %s\n", course.Teacher)
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fmt.Printf(" 教室: %s\n", course.Room)
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fmt.Printf(" 时间:")
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for _, sch := range course.Schedule {
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fmt.Printf(" %s %v 周%v", sch.Day, sch.Section, sch.Weeks)
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}
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fmt.Println()
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}
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fmt.Println("\n==================================================")
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}
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