添加图片识别千问大模型

klp-wms/src/main/java/com/klp/config/ImageRecognitionConfig.java

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+package com.klp.config;
+
+import org.springframework.boot.context.properties.ConfigurationProperties;
+import org.springframework.context.annotation.Configuration;
+
+/**
+ * 图片识别配置类
+ *
+ * @author klp
+ * @date 2025-01-27
+ */
+@Configuration
+@ConfigurationProperties(prefix = "image.recognition")
+public class ImageRecognitionConfig {
+
+    /**
+     * AI API配置
+     */
+    private String apiUrl = "https://api.siliconflow.cn/v1/chat/completions";
+    private String modelName = "Qwen/Qwen2.5-VL-72B-Instruct";
+    private String apiKey = "sk-sbmuklhrcxqlsucufqebiibauflxqfdafqjxaedtwirurtrc";
+    private Integer maxRetries = 3;
+    private Double temperature = 0.0;
+    private Integer maxTokens = 4096;
+
+    /**
+     * 图片处理配置
+     */
+    private Integer maxImageDimension = 512;
+    private Integer imageQuality = 60;
+
+    // Getters and Setters
+    public String getApiUrl() {
+        return apiUrl;
+    }
+
+    public void setApiUrl(String apiUrl) {
+        this.apiUrl = apiUrl;
+    }
+
+    public String getModelName() {
+        return modelName;
+    }
+
+    public void setModelName(String modelName) {
+        this.modelName = modelName;
+    }
+
+    public String getApiKey() {
+        return apiKey;
+    }
+
+    public void setApiKey(String apiKey) {
+        this.apiKey = apiKey;
+    }
+
+    public Integer getMaxRetries() {
+        return maxRetries;
+    }
+
+    public void setMaxRetries(Integer maxRetries) {
+        this.maxRetries = maxRetries;
+    }
+
+    public Double getTemperature() {
+        return temperature;
+    }
+
+    public void setTemperature(Double temperature) {
+        this.temperature = temperature;
+    }
+
+    public Integer getMaxTokens() {
+        return maxTokens;
+    }
+
+    public void setMaxTokens(Integer maxTokens) {
+        this.maxTokens = maxTokens;
+    }
+
+    public Integer getMaxImageDimension() {
+        return maxImageDimension;
+    }
+
+    public void setMaxImageDimension(Integer maxImageDimension) {
+        this.maxImageDimension = maxImageDimension;
+    }
+
+    public Integer getImageQuality() {
+        return imageQuality;
+    }
+
+    public void setImageQuality(Integer imageQuality) {
+        this.imageQuality = imageQuality;
+    }
+} 

klp-wms/src/main/java/com/klp/controller/WmsImageRecognitionController.java

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+package com.klp.controller;
+
+import com.klp.common.annotation.Log;
+import com.klp.common.core.controller.BaseController;
+import com.klp.common.core.domain.R;
+import com.klp.common.core.validate.AddGroup;
+import com.klp.common.core.validate.EditGroup;
+import com.klp.common.core.validate.QueryGroup;
+import com.klp.common.enums.BusinessType;
+import com.klp.common.utils.poi.ExcelUtil;
+import com.klp.domain.bo.ImageRecognitionBo;
+import com.klp.domain.vo.ImageRecognitionVo;
+import com.klp.service.IImageRecognitionService;
+import lombok.RequiredArgsConstructor;
+import org.springframework.validation.annotation.Validated;
+import org.springframework.web.bind.annotation.*;
+
+import javax.servlet.http.HttpServletResponse;
+import javax.validation.constraints.NotEmpty;
+import javax.validation.constraints.NotNull;
+import java.util.List;
+import java.util.Map;
+
+/**
+ * 图片识别控制器
+ *
+ * @author klp
+ * @date 2025-01-27
+ */
+@Validated
+@RequiredArgsConstructor
+@RestController
+@RequestMapping("/wms/imageRecognition")
+public class WmsImageRecognitionController extends BaseController {
+
+    private final IImageRecognitionService iImageRecognitionService;
+
+    /**
+     * 识别图片内容
+     */
+    @PostMapping("/recognize")
+    public R<ImageRecognitionVo> recognize(@RequestBody @Validated(AddGroup.class) ImageRecognitionBo bo) {
+        return R.ok(iImageRecognitionService.recognizeImage(bo));
+    }
+
+    /**
+     * 识别BOM内容
+     */
+    @PostMapping("/recognizeBom")
+    public R<ImageRecognitionVo> recognizeBom(@RequestBody @Validated(AddGroup.class) ImageRecognitionBo bo) {
+        bo.setRecognitionType("bom");
+        return R.ok(iImageRecognitionService.recognizeBom(bo));
+    }
+
+    /**
+     * 识别文字内容
+     */
+    @PostMapping("/recognizeText")
+    public R<ImageRecognitionVo> recognizeText(@RequestBody @Validated(AddGroup.class) ImageRecognitionBo bo) {
+        bo.setRecognitionType("text");
+        return R.ok(iImageRecognitionService.recognizeText(bo));
+    }
+
+    /**
+     * 批量识别图片
+     */
+    @PostMapping("/recognizeBatch")
+    public R<List<ImageRecognitionVo>> recognizeBatch(@RequestBody @Validated(AddGroup.class) List<ImageRecognitionBo> boList) {
+        return R.ok(iImageRecognitionService.recognizeImages(boList));
+    }
+
+    /**
+     * 测试AI连接
+     */
+    @PostMapping("/testConnection")
+    public R<Map<String, Object>> testConnection() {
+        return R.ok(iImageRecognitionService.testAiConnection());
+    }
+
+    /**
+     * 获取识别配置
+     */
+    @GetMapping("/config")
+    public R<Map<String, Object>> getConfig() {
+        return R.ok(iImageRecognitionService.getRecognitionConfig());
+    }
+
+    /**
+     * 更新识别配置
+     */
+    @PostMapping("/config")
+    public R<Void> updateConfig(@RequestBody Map<String, Object> config) {
+        iImageRecognitionService.updateRecognitionConfig(config);
+        return R.ok();
+    }
+
+    /**
+     * 获取识别历史
+     */
+    @PostMapping("/history")
+    public R<Map<String, Object>> getHistory(@RequestBody Map<String, Object> pageQuery) {
+        return R.ok(iImageRecognitionService.getRecognitionHistory(pageQuery));
+    }
+
+    /**
+     * 简单识别接口（兼容原有格式）
+     */
+    @PostMapping("/recognizeTextSimple")
+    public R<ImageRecognitionVo> recognizeTextSimple(@RequestBody Map<String, String> request) {
+        String imgUrl = request.get("imgUrl");
+        if (imgUrl == null || imgUrl.trim().isEmpty()) {
+            return R.fail("图片URL不能为空");
+        }
+        
+        ImageRecognitionBo bo = new ImageRecognitionBo();
+        bo.setImageUrl(imgUrl);
+        bo.setRecognitionType("text");
+        
+        ImageRecognitionVo result = iImageRecognitionService.recognizeText(bo);
+        return R.ok(result);
+    }
+
+    /**
+     * 识别BOM接口（兼容原有格式）
+     */
+    @PostMapping("/recognizeBomSimple")
+    public R<ImageRecognitionVo> recognizeBomSimple(@RequestBody Map<String, String> request) {
+        String imgUrl = request.get("imgUrl");
+        if (imgUrl == null || imgUrl.trim().isEmpty()) {
+            return R.fail("图片URL不能为空");
+        }
+        
+        ImageRecognitionBo bo = new ImageRecognitionBo();
+        bo.setImageUrl(imgUrl);
+        bo.setRecognitionType("bom");
+        
+        ImageRecognitionVo result = iImageRecognitionService.recognizeBom(bo);
+        return R.ok(result);
+    }
+} 

klp-wms/src/main/java/com/klp/domain/bo/ImageRecognitionBo.java

@@ -0,0 +1,63 @@
+package com.klp.domain.bo;
+
+import com.klp.common.core.validate.AddGroup;
+import com.klp.common.core.validate.EditGroup;
+import com.klp.common.core.validate.QueryGroup;
+import com.klp.common.core.domain.BaseEntity;
+import lombok.Data;
+import lombok.EqualsAndHashCode;
+
+import javax.validation.constraints.NotBlank;
+import javax.validation.constraints.NotNull;
+
+/**
+ * 图片识别业务对象
+ *
+ * @author klp
+ * @date 2025-01-27
+ */
+@Data
+@EqualsAndHashCode(callSuper = true)
+public class ImageRecognitionBo extends BaseEntity {
+
+    /**
+     * 图片URL地址
+     */
+    @NotBlank(message = "图片URL不能为空", groups = { AddGroup.class, EditGroup.class })
+    private String imageUrl;
+
+    /**
+     * 识别类型：bom-识别BOM内容，text-识别文字，general-通用识别
+     */
+    private String recognitionType = "bom";
+
+    /**
+     * 是否启用多轮投票
+     */
+    private Boolean enableVoting = true;
+
+    /**
+     * 投票轮数
+     */
+    private Integer votingRounds = 3;
+
+    /**
+     * 自定义提示词
+     */
+    private String customPrompt;
+
+    /**
+     * 是否保存识别结果到数据库
+     */
+    private Boolean saveToDatabase = false;
+
+    /**
+     * 产品ID（用于关联BOM信息）
+     */
+    private Long productId;
+
+    /**
+     * 识别任务描述
+     */
+    private String taskDescription;
+} 

klp-wms/src/main/java/com/klp/domain/vo/ImageRecognitionVo.java

@@ -0,0 +1,113 @@
+package com.klp.domain.vo;
+
+import com.fasterxml.jackson.annotation.JsonFormat;
+import lombok.Data;
+
+import java.io.Serializable;
+import java.util.Date;
+import java.util.List;
+import java.util.Map;
+
+/**
+ * 图片识别结果视图对象
+ *
+ * @author klp
+ * @date 2025-01-27
+ */
+@Data
+public class ImageRecognitionVo implements Serializable {
+
+    private static final long serialVersionUID = 1L;
+
+    /**
+     * 识别ID
+     */
+    private Long recognitionId;
+
+    /**
+     * 图片URL
+     */
+    private String imageUrl;
+
+    /**
+     * 识别类型
+     */
+    private String recognitionType;
+
+    /**
+     * 识别结果
+     */
+    private String recognizedText;
+
+    /**
+     * 结构化识别结果（JSON格式）
+     */
+    private Map<String, Object> structuredResult;
+
+    /**
+     * BOM信息列表
+     */
+    private List<BomItemVo> bomItems;
+
+    /**
+     * 识别置信度
+     */
+    private Double confidence;
+
+    /**
+     * 识别状态：success-成功，failed-失败，processing-处理中
+     */
+    private String status;
+
+    /**
+     * 错误信息
+     */
+    private String errorMessage;
+
+    /**
+     * 处理时间（毫秒）
+     */
+    private Long processingTime;
+
+    /**
+     * 创建时间
+     */
+    @JsonFormat(pattern = "yyyy-MM-dd HH:mm:ss")
+    private Date createTime;
+
+    /**
+     * BOM项目信息
+     */
+    @Data
+    public static class BomItemVo {
+        /**
+         * 原材料ID
+         */
+        private String rawMaterialId;
+
+        /**
+         * 原材料名称
+         */
+        private String rawMaterialName;
+
+        /**
+         * 数量
+         */
+        private Double quantity;
+
+        /**
+         * 单位
+         */
+        private String unit;
+
+        /**
+         * 规格
+         */
+        private String specification;
+
+        /**
+         * 备注
+         */
+        private String remark;
+    }
+} 

klp-wms/src/main/java/com/klp/service/IImageRecognitionService.java

@@ -0,0 +1,77 @@
+package com.klp.service;
+
+import com.klp.domain.bo.ImageRecognitionBo;
+import com.klp.domain.vo.ImageRecognitionVo;
+
+import java.util.List;
+import java.util.Map;
+
+/**
+ * 图片识别服务接口
+ *
+ * @author klp
+ * @date 2025-01-27
+ */
+public interface IImageRecognitionService {
+
+    /**
+     * 识别图片内容
+     *
+     * @param bo 识别请求参数
+     * @return 识别结果
+     */
+    ImageRecognitionVo recognizeImage(ImageRecognitionBo bo);
+
+    /**
+     * 批量识别图片
+     *
+     * @param boList 识别请求参数列表
+     * @return 识别结果列表
+     */
+    List<ImageRecognitionVo> recognizeImages(List<ImageRecognitionBo> boList);
+
+    /**
+     * 识别BOM内容
+     *
+     * @param bo 识别请求参数
+     * @return BOM识别结果
+     */
+    ImageRecognitionVo recognizeBom(ImageRecognitionBo bo);
+
+    /**
+     * 识别文字内容
+     *
+     * @param bo 识别请求参数
+     * @return 文字识别结果
+     */
+    ImageRecognitionVo recognizeText(ImageRecognitionBo bo);
+
+    /**
+     * 测试AI连接
+     *
+     * @return 连接测试结果
+     */
+    Map<String, Object> testAiConnection();
+
+    /**
+     * 获取识别配置
+     *
+     * @return 配置信息
+     */
+    Map<String, Object> getRecognitionConfig();
+
+    /**
+     * 更新识别配置
+     *
+     * @param config 配置信息
+     */
+    void updateRecognitionConfig(Map<String, Object> config);
+
+    /**
+     * 获取识别历史
+     *
+     * @param pageQuery 分页查询参数
+     * @return 识别历史列表
+     */
+    Map<String, Object> getRecognitionHistory(Map<String, Object> pageQuery);
+} 

klp-wms/src/main/java/com/klp/service/impl/ImageRecognitionServiceImpl.java

@@ -0,0 +1,490 @@
+package com.klp.service.impl;
+
+import com.fasterxml.jackson.core.JsonProcessingException;
+import com.fasterxml.jackson.databind.ObjectMapper;
+import com.klp.config.ImageRecognitionConfig;
+import com.klp.domain.bo.ImageRecognitionBo;
+import com.klp.domain.vo.ImageRecognitionVo;
+import com.klp.service.IImageRecognitionService;
+import com.klp.utils.ImageProcessingUtils;
+import lombok.RequiredArgsConstructor;
+import lombok.extern.slf4j.Slf4j;
+import org.springframework.beans.factory.annotation.Qualifier;
+import org.springframework.http.*;
+import org.springframework.stereotype.Service;
+import org.springframework.web.client.RestTemplate;
+
+import java.util.*;
+import java.util.concurrent.CompletableFuture;
+import java.util.concurrent.ExecutorService;
+import java.util.concurrent.Executors;
+import java.util.regex.Matcher;
+import java.util.regex.Pattern;
+
+/**
+ * 图片识别服务实现类
+ *
+ * @author klp
+ * @date 2025-01-27
+ */
+@Slf4j
+@RequiredArgsConstructor
+@Service
+public class ImageRecognitionServiceImpl implements IImageRecognitionService {
+
+    private final ImageRecognitionConfig config;
+    private final ImageProcessingUtils imageProcessingUtils;
+    
+    @Qualifier("salesScriptRestTemplate")
+    private final RestTemplate restTemplate;
+
+    private final ObjectMapper objectMapper = new ObjectMapper();
+    private final ExecutorService executorService = Executors.newFixedThreadPool(5);
+
+    @Override
+    public ImageRecognitionVo recognizeImage(ImageRecognitionBo bo) {
+        long startTime = System.currentTimeMillis();
+        ImageRecognitionVo result = new ImageRecognitionVo();
+        
+        try {
+            // 验证图片URL
+            if (!imageProcessingUtils.isValidImageUrl(bo.getImageUrl())) {
+                throw new RuntimeException("无效的图片URL");
+            }
+
+            // 根据识别类型调用不同的识别方法
+            switch (bo.getRecognitionType()) {
+                case "bom":
+                    result = recognizeBom(bo);
+                    break;
+                case "text":
+                    result = recognizeText(bo);
+                    break;
+                default:
+                    result = recognizeGeneral(bo);
+                    break;
+            }
+
+            result.setStatus("success");
+            result.setProcessingTime(System.currentTimeMillis() - startTime);
+            
+        } catch (Exception e) {
+            log.error("图片识别失败", e);
+            result.setStatus("failed");
+            result.setErrorMessage(e.getMessage());
+            result.setProcessingTime(System.currentTimeMillis() - startTime);
+        }
+
+        return result;
+    }
+
+    @Override
+    public List<ImageRecognitionVo> recognizeImages(List<ImageRecognitionBo> boList) {
+        List<CompletableFuture<ImageRecognitionVo>> futures = new ArrayList<>();
+        
+        for (ImageRecognitionBo bo : boList) {
+            CompletableFuture<ImageRecognitionVo> future = CompletableFuture.supplyAsync(() -> 
+                recognizeImage(bo), executorService);
+            futures.add(future);
+        }
+
+        List<ImageRecognitionVo> results = new ArrayList<>();
+        for (CompletableFuture<ImageRecognitionVo> future : futures) {
+            try {
+                results.add(future.get());
+            } catch (Exception e) {
+                log.error("批量识别失败", e);
+                ImageRecognitionVo errorResult = new ImageRecognitionVo();
+                errorResult.setStatus("failed");
+                errorResult.setErrorMessage(e.getMessage());
+                results.add(errorResult);
+            }
+        }
+
+        return results;
+    }
+
+    @Override
+    public ImageRecognitionVo recognizeBom(ImageRecognitionBo bo) {
+        String prompt = buildBomPrompt(bo);
+        String aiResponse = callAiApi(bo.getImageUrl(), prompt, bo.getEnableVoting(), bo.getVotingRounds());
+        
+        ImageRecognitionVo result = new ImageRecognitionVo();
+        result.setImageUrl(bo.getImageUrl());
+        result.setRecognitionType("bom");
+        result.setRecognizedText(aiResponse);
+        
+        // 解析BOM信息
+        try {
+            Map<String, Object> structuredResult = parseBomResponse(aiResponse);
+            result.setStructuredResult(structuredResult);
+            
+            // 提取BOM项目列表
+            List<ImageRecognitionVo.BomItemVo> bomItems = extractBomItems(structuredResult);
+            result.setBomItems(bomItems);
+            
+        } catch (Exception e) {
+            log.warn("解析BOM响应失败: {}", e.getMessage());
+            result.setRecognizedText(aiResponse);
+        }
+
+        return result;
+    }
+
+    @Override
+    public ImageRecognitionVo recognizeText(ImageRecognitionBo bo) {
+        String prompt = buildTextPrompt(bo);
+        String aiResponse = callAiApi(bo.getImageUrl(), prompt, bo.getEnableVoting(), bo.getVotingRounds());
+        
+        ImageRecognitionVo result = new ImageRecognitionVo();
+        result.setImageUrl(bo.getImageUrl());
+        result.setRecognitionType("text");
+        result.setRecognizedText(aiResponse);
+        
+        return result;
+    }
+
+    @Override
+    public Map<String, Object> testAiConnection() {
+        Map<String, Object> result = new HashMap<>();
+        try {
+            // 构建测试请求
+            Map<String, Object> requestBody = new HashMap<>();
+            requestBody.put("model", config.getModelName());
+            
+            Map<String, String> message = new HashMap<>();
+            message.put("role", "user");
+            message.put("content", "你好");
+            requestBody.put("messages", Arrays.asList(message));
+            requestBody.put("max_tokens", 10);
+
+            HttpHeaders headers = new HttpHeaders();
+            headers.setContentType(MediaType.APPLICATION_JSON);
+            headers.setBearerAuth(config.getApiKey());
+
+            HttpEntity<Map<String, Object>> entity = new HttpEntity<>(requestBody, headers);
+            ResponseEntity<Map> response = restTemplate.postForEntity(
+                config.getApiUrl(), entity, Map.class);
+
+            result.put("success", true);
+            result.put("message", "AI连接测试成功");
+            result.put("response", response.getBody());
+        } catch (Exception e) {
+            log.error("AI连接测试失败", e);
+            result.put("success", false);
+            result.put("message", "AI连接测试失败: " + e.getMessage());
+        }
+        return result;
+    }
+
+    @Override
+    public Map<String, Object> getRecognitionConfig() {
+        Map<String, Object> configMap = new HashMap<>();
+        configMap.put("apiUrl", config.getApiUrl());
+        configMap.put("modelName", config.getModelName());
+        configMap.put("apiKey", config.getApiKey().substring(0, 10) + "...");
+        configMap.put("maxRetries", config.getMaxRetries());
+        configMap.put("temperature", config.getTemperature());
+        configMap.put("maxTokens", config.getMaxTokens());
+        configMap.put("maxImageDimension", config.getMaxImageDimension());
+        configMap.put("imageQuality", config.getImageQuality());
+        return configMap;
+    }
+
+    @Override
+    public void updateRecognitionConfig(Map<String, Object> config) {
+        log.info("更新识别配置: {}", config);
+        // 这里可以实现配置更新逻辑
+    }
+
+    @Override
+    public Map<String, Object> getRecognitionHistory(Map<String, Object> pageQuery) {
+        Map<String, Object> result = new HashMap<>();
+        result.put("rows", new ArrayList<>());
+        result.put("total", 0L);
+        return result;
+    }
+
+    /**
+     * 通用识别方法
+     */
+    private ImageRecognitionVo recognizeGeneral(ImageRecognitionBo bo) {
+        String prompt = buildGeneralPrompt(bo);
+        String aiResponse = callAiApi(bo.getImageUrl(), prompt, bo.getEnableVoting(), bo.getVotingRounds());
+        
+        ImageRecognitionVo result = new ImageRecognitionVo();
+        result.setImageUrl(bo.getImageUrl());
+        result.setRecognitionType("general");
+        result.setRecognizedText(aiResponse);
+        
+        return result;
+    }
+
+    /**
+     * 调用AI API
+     */
+    private String callAiApi(String imageUrl, String prompt, Boolean enableVoting, Integer votingRounds) {
+        // 转换图片为Data URI
+        String dataUri = imageProcessingUtils.imageUrlToDataUri(
+            imageUrl, config.getMaxImageDimension(), config.getImageQuality());
+
+        // 构建请求体
+        Map<String, Object> requestBody = new HashMap<>();
+        requestBody.put("model", config.getModelName());
+        
+        List<Map<String, Object>> contents = new ArrayList<>();
+        
+        // 添加图片内容
+        Map<String, Object> imageContent = new HashMap<>();
+        imageContent.put("type", "image_url");
+        Map<String, Object> imageUrlObj = new HashMap<>();
+        imageUrlObj.put("url", dataUri);
+        imageUrlObj.put("detail", "low");
+        imageContent.put("image_url", imageUrlObj);
+        contents.add(imageContent);
+        
+        // 添加文本内容
+        Map<String, Object> textContent = new HashMap<>();
+        textContent.put("type", "text");
+        textContent.put("text", prompt);
+        contents.add(textContent);
+        
+        Map<String, Object> message = new HashMap<>();
+        message.put("role", "user");
+        message.put("content", contents);
+        
+        requestBody.put("messages", Arrays.asList(message));
+        requestBody.put("enable_thinking", true);
+        requestBody.put("temperature", config.getTemperature());
+        requestBody.put("top_p", 0.7);
+        requestBody.put("min_p", 0.05);
+        requestBody.put("frequency_penalty", 0.2);
+        requestBody.put("max_token", config.getMaxTokens());
+        requestBody.put("stream", false);
+        requestBody.put("stop", new ArrayList<>());
+        Map<String, String> responseFormat = new HashMap<>();
+        responseFormat.put("type", "text");
+        requestBody.put("response_format", responseFormat);
+
+        // 多轮投票处理
+        if (Boolean.TRUE.equals(enableVoting) && votingRounds > 1) {
+            return callAiApiWithVoting(requestBody, votingRounds);
+        } else {
+            return callAiApiSingle(requestBody);
+        }
+    }
+
+    /**
+     * 单次调用AI API
+     */
+    private String callAiApiSingle(Map<String, Object> requestBody) {
+        for (int i = 0; i < config.getMaxRetries(); i++) {
+            try {
+                HttpHeaders headers = new HttpHeaders();
+                headers.setContentType(MediaType.APPLICATION_JSON);
+                headers.setBearerAuth(config.getApiKey());
+
+                HttpEntity<Map<String, Object>> entity = new HttpEntity<>(requestBody, headers);
+                ResponseEntity<Map> response = restTemplate.postForEntity(
+                    config.getApiUrl(), entity, Map.class);
+
+                if (response.getStatusCode() == HttpStatus.OK && response.getBody() != null) {
+                    Map<String, Object> body = response.getBody();
+                    List<Map<String, Object>> choices = (List<Map<String, Object>>) body.get("choices");
+                    if (choices != null && !choices.isEmpty()) {
+                        Map<String, Object> choice = choices.get(0);
+                        Map<String, Object> message = (Map<String, Object>) choice.get("message");
+                        return (String) message.get("content");
+                    }
+                }
+            } catch (Exception e) {
+                log.error("AI API调用失败，重试 {}: {}", i + 1, e.getMessage());
+                if (i == config.getMaxRetries() - 1) {
+                    throw new RuntimeException("AI API调用失败", e);
+                }
+            }
+        }
+        throw new RuntimeException("AI API调用失败，已达到最大重试次数");
+    }
+
+    /**
+     * 多轮投票调用AI API
+     */
+    private String callAiApiWithVoting(Map<String, Object> requestBody, int rounds) {
+        List<CompletableFuture<String>> futures = new ArrayList<>();
+        
+        for (int i = 0; i < rounds; i++) {
+            CompletableFuture<String> future = CompletableFuture.supplyAsync(() -> 
+                callAiApiSingle(requestBody), executorService);
+            futures.add(future);
+        }
+
+        List<String> results = new ArrayList<>();
+        for (CompletableFuture<String> future : futures) {
+            try {
+                results.add(future.get());
+            } catch (Exception e) {
+                log.error("投票轮次失败: {}", e.getMessage());
+            }
+        }
+
+        if (results.isEmpty()) {
+            throw new RuntimeException("所有投票轮次都失败了");
+        }
+
+        // 简单投票：返回第一个成功的结果
+        return results.get(0);
+    }
+
+    /**
+     * 构建BOM识别提示词
+     */
+    private String buildBomPrompt(ImageRecognitionBo bo) {
+        StringBuilder prompt = new StringBuilder();
+        prompt.append("请仔细分析这张图片中的BOM（物料清单）信息，并提取以下内容：\n\n");
+        prompt.append("【识别要求】\n");
+        prompt.append("1. 识别图片中的所有物料信息，包括原材料ID、名称、数量、单位等\n");
+        prompt.append("2. 如果图片中包含表格，请按表格结构提取信息\n");
+        prompt.append("3. 如果图片中包含列表，请按列表格式提取信息\n");
+        prompt.append("4. 确保数量信息的准确性，包括数字和单位\n");
+        prompt.append("5. 识别规格、备注等附加信息\n\n");
+        
+        if (bo.getProductId() != null) {
+            prompt.append("【产品信息】\n");
+            prompt.append("产品ID: ").append(bo.getProductId()).append("\n\n");
+        }
+        
+        if (bo.getCustomPrompt() != null && !bo.getCustomPrompt().isEmpty()) {
+            prompt.append("【自定义要求】\n");
+            prompt.append(bo.getCustomPrompt()).append("\n\n");
+        }
+        
+        prompt.append("【输出格式】\n");
+        prompt.append("请按以下JSON格式输出识别结果：\n");
+        prompt.append("{\n");
+        prompt.append("  \"bomItems\": [\n");
+        prompt.append("    {\n");
+        prompt.append("      \"rawMaterialId\": \"原材料ID\",\n");
+        prompt.append("      \"rawMaterialName\": \"原材料名称\",\n");
+        prompt.append("      \"quantity\": 数量,\n");
+        prompt.append("      \"unit\": \"单位\",\n");
+        prompt.append("      \"specification\": \"规格\",\n");
+        prompt.append("      \"remark\": \"备注\"\n");
+        prompt.append("    }\n");
+        prompt.append("  ],\n");
+        prompt.append("  \"summary\": \"BOM清单总结\",\n");
+        prompt.append("  \"totalItems\": 总项目数\n");
+        prompt.append("}\n\n");
+        prompt.append("如果图片中没有BOM信息，请返回空数组。");
+
+        return prompt.toString();
+    }
+
+    /**
+     * 构建文字识别提示词
+     */
+    private String buildTextPrompt(ImageRecognitionBo bo) {
+        StringBuilder prompt = new StringBuilder();
+        prompt.append("请识别图片中的所有文字内容，包括但不限于：\n\n");
+        prompt.append("【识别要求】\n");
+        prompt.append("1. 识别图片中的所有可见文字\n");
+        prompt.append("2. 保持文字的原始格式和顺序\n");
+        prompt.append("3. 识别表格、列表等结构化内容\n");
+        prompt.append("4. 识别数字、符号等特殊字符\n");
+        prompt.append("5. 保持段落和换行格式\n\n");
+        
+        if (bo.getCustomPrompt() != null && !bo.getCustomPrompt().isEmpty()) {
+            prompt.append("【自定义要求】\n");
+            prompt.append(bo.getCustomPrompt()).append("\n\n");
+        }
+        
+        prompt.append("【输出格式】\n");
+        prompt.append("请直接输出识别到的文字内容，保持原有格式。");
+
+        return prompt.toString();
+    }
+
+    /**
+     * 构建通用识别提示词
+     */
+    private String buildGeneralPrompt(ImageRecognitionBo bo) {
+        StringBuilder prompt = new StringBuilder();
+        prompt.append("请分析这张图片的内容，并提供详细描述：\n\n");
+        prompt.append("【分析要求】\n");
+        prompt.append("1. 描述图片的主要内容和主题\n");
+        prompt.append("2. 识别图片中的文字信息\n");
+        prompt.append("3. 分析图片的结构和布局\n");
+        prompt.append("4. 提取关键信息和数据\n");
+        prompt.append("5. 识别图片中的表格、图表等结构化内容\n\n");
+        
+        if (bo.getCustomPrompt() != null && !bo.getCustomPrompt().isEmpty()) {
+            prompt.append("【自定义要求】\n");
+            prompt.append(bo.getCustomPrompt()).append("\n\n");
+        }
+        
+        prompt.append("【输出格式】\n");
+        prompt.append("请提供详细的分析结果，包括文字内容、结构分析等。");
+
+        return prompt.toString();
+    }
+
+    /**
+     * 解析BOM响应
+     */
+    private Map<String, Object> parseBomResponse(String response) {
+        try {
+            // 尝试直接解析JSON
+            return objectMapper.readValue(response, Map.class);
+        } catch (JsonProcessingException e) {
+            // 如果直接解析失败，尝试提取JSON部分
+            Pattern jsonPattern = Pattern.compile("\\{[\\s\\S]*\\}");
+            Matcher matcher = jsonPattern.matcher(response);
+            if (matcher.find()) {
+                try {
+                    return objectMapper.readValue(matcher.group(), Map.class);
+                } catch (JsonProcessingException ex) {
+                    log.warn("无法解析BOM响应为JSON: {}", response);
+                    Map<String, Object> fallback = new HashMap<>();
+                    fallback.put("rawText", response);
+                    return fallback;
+                }
+            }
+            Map<String, Object> fallback = new HashMap<>();
+            fallback.put("rawText", response);
+            return fallback;
+        }
+    }
+
+    /**
+     * 提取BOM项目列表
+     */
+    private List<ImageRecognitionVo.BomItemVo> extractBomItems(Map<String, Object> structuredResult) {
+        List<ImageRecognitionVo.BomItemVo> bomItems = new ArrayList<>();
+        
+        try {
+            List<Map<String, Object>> items = (List<Map<String, Object>>) structuredResult.get("bomItems");
+            if (items != null) {
+                for (Map<String, Object> item : items) {
+                    ImageRecognitionVo.BomItemVo bomItem = new ImageRecognitionVo.BomItemVo();
+                    bomItem.setRawMaterialId((String) item.get("rawMaterialId"));
+                    bomItem.setRawMaterialName((String) item.get("rawMaterialName"));
+                    
+                    Object quantity = item.get("quantity");
+                    if (quantity instanceof Number) {
+                        bomItem.setQuantity(((Number) quantity).doubleValue());
+                    }
+                    
+                    bomItem.setUnit((String) item.get("unit"));
+                    bomItem.setSpecification((String) item.get("specification"));
+                    bomItem.setRemark((String) item.get("remark"));
+                    
+                    bomItems.add(bomItem);
+                }
+            }
+        } catch (Exception e) {
+            log.warn("提取BOM项目失败: {}", e.getMessage());
+        }
+        
+        return bomItems;
+    }
+} 

klp-wms/src/main/java/com/klp/test/ImageRecognitionTest.java

@@ -0,0 +1,111 @@
+package com.klp.test;
+
+import com.klp.domain.bo.ImageRecognitionBo;
+import com.klp.domain.vo.ImageRecognitionVo;
+import com.klp.service.IImageRecognitionService;
+import lombok.RequiredArgsConstructor;
+import lombok.extern.slf4j.Slf4j;
+import org.springframework.boot.CommandLineRunner;
+import org.springframework.stereotype.Component;
+
+import java.util.HashMap;
+import java.util.Map;
+
+/**
+ * 图片识别功能测试类
+ *
+ * @author klp
+ * @date 2025-01-27
+ */
+@Slf4j
+@Component
+@RequiredArgsConstructor
+public class ImageRecognitionTest implements CommandLineRunner {
+
+    private final IImageRecognitionService imageRecognitionService;
+
+    @Override
+    public void run(String... args) throws Exception {
+        log.info("开始测试图片识别功能...");
+        
+        // 测试AI连接
+        testAiConnection();
+        
+        // 测试文字识别
+        testTextRecognition();
+        
+        // 测试BOM识别
+        testBomRecognition();
+        
+        log.info("图片识别功能测试完成");
+    }
+
+    /**
+     * 测试AI连接
+     */
+    private void testAiConnection() {
+        log.info("测试AI连接...");
+        try {
+            Map<String, Object> result = imageRecognitionService.testAiConnection();
+            if (Boolean.TRUE.equals(result.get("success"))) {
+                log.info("AI连接测试成功: {}", result.get("message"));
+            } else {
+                log.error("AI连接测试失败: {}", result.get("message"));
+            }
+        } catch (Exception e) {
+            log.error("AI连接测试异常", e);
+        }
+    }
+
+    /**
+     * 测试文字识别
+     */
+    private void testTextRecognition() {
+        log.info("测试文字识别...");
+        try {
+            ImageRecognitionBo bo = new ImageRecognitionBo();
+            bo.setImageUrl("https://via.placeholder.com/400x300/000000/FFFFFF?text=Test+Text");
+            bo.setRecognitionType("text");
+            bo.setEnableVoting(false);
+            
+            ImageRecognitionVo result = imageRecognitionService.recognizeText(bo);
+            log.info("文字识别结果: {}", result.getRecognizedText());
+            log.info("识别状态: {}", result.getStatus());
+            log.info("处理时间: {}ms", result.getProcessingTime());
+        } catch (Exception e) {
+            log.error("文字识别测试异常", e);
+        }
+    }
+
+    /**
+     * 测试BOM识别
+     */
+    private void testBomRecognition() {
+        log.info("测试BOM识别...");
+        try {
+            ImageRecognitionBo bo = new ImageRecognitionBo();
+            bo.setImageUrl("https://via.placeholder.com/400x300/000000/FFFFFF?text=BOM+Test");
+            bo.setRecognitionType("bom");
+            bo.setEnableVoting(false);
+            bo.setProductId(1L);
+            
+            ImageRecognitionVo result = imageRecognitionService.recognizeBom(bo);
+            log.info("BOM识别结果: {}", result.getRecognizedText());
+            log.info("识别状态: {}", result.getStatus());
+            log.info("处理时间: {}ms", result.getProcessingTime());
+            
+            if (result.getBomItems() != null) {
+                log.info("BOM项目数量: {}", result.getBomItems().size());
+                for (ImageRecognitionVo.BomItemVo item : result.getBomItems()) {
+                    log.info("BOM项目: {} - {} {} {}", 
+                        item.getRawMaterialName(), 
+                        item.getQuantity(), 
+                        item.getUnit(), 
+                        item.getSpecification());
+                }
+            }
+        } catch (Exception e) {
+            log.error("BOM识别测试异常", e);
+        }
+    }
+} 

klp-wms/src/main/java/com/klp/utils/ImageProcessingUtils.java

@@ -0,0 +1,144 @@
+package com.klp.utils;
+
+import lombok.extern.slf4j.Slf4j;
+import org.springframework.stereotype.Component;
+
+import javax.imageio.ImageIO;
+import java.awt.*;
+import java.awt.image.BufferedImage;
+import java.io.ByteArrayOutputStream;
+import java.io.IOException;
+import java.io.InputStream;
+import java.net.URL;
+import java.util.Base64;
+
+/**
+ * 图片处理工具类
+ *
+ * @author klp
+ * @date 2025-01-27
+ */
+@Slf4j
+@Component
+public class ImageProcessingUtils {
+
+    /**
+     * 将图片URL转换为Base64 Data URI
+     *
+     * @param imageUrl 图片URL
+     * @param maxDimension 最大尺寸
+     * @param quality 图片质量
+     * @return Base64 Data URI
+     */
+    public String imageUrlToDataUri(String imageUrl, int maxDimension, int quality) {
+        try {
+            // 下载图片
+            BufferedImage originalImage = downloadImage(imageUrl);
+            if (originalImage == null) {
+                throw new RuntimeException("无法下载图片: " + imageUrl);
+            }
+
+            // 调整图片尺寸
+            BufferedImage resizedImage = resizeImage(originalImage, maxDimension);
+
+            // 转换为Base64
+            String base64 = imageToBase64(resizedImage, quality);
+
+            return "data:image/jpeg;base64," + base64;
+        } catch (Exception e) {
+            log.error("图片转换失败: {}", e.getMessage(), e);
+            throw new RuntimeException("图片转换失败: " + e.getMessage());
+        }
+    }
+
+    /**
+     * 下载图片
+     *
+     * @param imageUrl 图片URL
+     * @return BufferedImage对象
+     */
+    private BufferedImage downloadImage(String imageUrl) {
+        try {
+            URL url = new URL(imageUrl);
+            try (InputStream inputStream = url.openStream()) {
+                return ImageIO.read(inputStream);
+            }
+        } catch (IOException e) {
+            log.error("下载图片失败: {}", e.getMessage(), e);
+            return null;
+        }
+    }
+
+    /**
+     * 调整图片尺寸
+     *
+     * @param originalImage 原始图片
+     * @param maxDimension 最大尺寸
+     * @return 调整后的图片
+     */
+    private BufferedImage resizeImage(BufferedImage originalImage, int maxDimension) {
+        int originalWidth = originalImage.getWidth();
+        int originalHeight = originalImage.getHeight();
+
+        // 计算新的尺寸
+        int newWidth, newHeight;
+        if (originalWidth > originalHeight) {
+            newWidth = Math.min(originalWidth, maxDimension);
+            newHeight = (int) ((double) originalHeight * newWidth / originalWidth);
+        } else {
+            newHeight = Math.min(originalHeight, maxDimension);
+            newWidth = (int) ((double) originalWidth * newHeight / originalHeight);
+        }
+
+        // 创建新图片
+        BufferedImage resizedImage = new BufferedImage(newWidth, newHeight, BufferedImage.TYPE_INT_RGB);
+        Graphics2D g2d = resizedImage.createGraphics();
+        
+        // 设置渲染质量
+        g2d.setRenderingHint(RenderingHints.KEY_INTERPOLATION, RenderingHints.VALUE_INTERPOLATION_BILINEAR);
+        g2d.setRenderingHint(RenderingHints.KEY_RENDERING, RenderingHints.VALUE_RENDER_QUALITY);
+        g2d.setRenderingHint(RenderingHints.KEY_ANTIALIASING, RenderingHints.VALUE_ANTIALIAS_ON);
+
+        // 绘制调整后的图片
+        g2d.drawImage(originalImage, 0, 0, newWidth, newHeight, null);
+        g2d.dispose();
+
+        return resizedImage;
+    }
+
+    /**
+     * 将图片转换为Base64字符串
+     *
+     * @param image 图片对象
+     * @param quality 图片质量
+     * @return Base64字符串
+     */
+    private String imageToBase64(BufferedImage image, int quality) {
+        try (ByteArrayOutputStream baos = new ByteArrayOutputStream()) {
+            // 使用JPEG格式输出
+            ImageIO.write(image, "JPEG", baos);
+            byte[] imageBytes = baos.toByteArray();
+            return Base64.getEncoder().encodeToString(imageBytes);
+        } catch (IOException e) {
+            log.error("图片转Base64失败: {}", e.getMessage(), e);
+            throw new RuntimeException("图片转Base64失败: " + e.getMessage());
+        }
+    }
+
+    /**
+     * 验证图片URL是否有效
+     *
+     * @param imageUrl 图片URL
+     * @return 是否有效
+     */
+    public boolean isValidImageUrl(String imageUrl) {
+        try {
+            URL url = new URL(imageUrl);
+            String protocol = url.getProtocol();
+            return "http".equals(protocol) || "https".equals(protocol);
+        } catch (Exception e) {
+            log.warn("无效的图片URL: {}", imageUrl);
+            return false;
+        }
+    }
+} 

klp-wms/src/main/resources/application-image-recognition.yml

@@ -0,0 +1,38 @@
+# 图片识别配置
+image:
+  recognition:
+    # AI API配置
+    api-url: https://api.siliconflow.cn/v1/chat/completions
+    model-name: Qwen/Qwen2.5-VL-32B-Instruct
+    api-key: sk-sbmuklhrcxqlsucufqebiibauflxqfdafqjxaedtwirurtrc
+    max-retries: 3
+    temperature: 0.0
+    max-tokens: 4096
+
+    # 图片处理配置
+    max-image-dimension: 512
+    image-quality: 60
+
+    # 识别配置
+    default-recognition-type: bom
+    enable-voting: true
+    voting-rounds: 3
+
+    # 支持的图片格式
+    supported-formats:
+      - jpg
+      - jpeg
+      - png
+      - bmp
+      - gif
+
+    # 超时配置
+    connect-timeout: 30000
+    read-timeout: 60000
+
+    # 缓存配置
+    enable-cache: true
+    cache-ttl: 3600
+
+    # 日志配置
+    enable-debug-log: false