修改bom接口的提示词

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

@@ -116,16 +116,19 @@ public class ImageRecognitionServiceImpl implements IImageRecognitionService {
         
         // 解析识别结果
         try {
-            Map<String, Object> structuredResult = parseBomResponse(aiResponse);
+            // 直接解析属性数组
+            List<ImageRecognitionVo.AttributeVo> attributes = parseAttributesResponse(aiResponse);
+            result.setAttributes(attributes);
+            
+            // 构建结构化结果
+            Map<String, Object> structuredResult = new HashMap<>();
+            structuredResult.put("attributes", attributes);
+            structuredResult.put("summary", "材料质保单识别结果");
+            structuredResult.put("totalItems", attributes.size());
             result.setStructuredResult(structuredResult);
             
-            // 提取BOM项目列表
-            List<ImageRecognitionVo.BomItemVo> bomItems = extractBomItems(structuredResult);
-            result.setBomItems(bomItems);
-            
-            // 提取属性列表
-            List<ImageRecognitionVo.AttributeVo> attributes = extractAttributes(structuredResult);
-            result.setAttributes(attributes);
+            // BOM项目为空，因为这是质保单识别
+            result.setBomItems(new ArrayList<>());
             
         } catch (Exception e) {
             log.warn("解析识别响应失败: {}", e.getMessage());
@@ -345,13 +348,19 @@ public class ImageRecognitionServiceImpl implements IImageRecognitionService {
      */
     private String buildBomPrompt(ImageRecognitionBo bo) {
         StringBuilder prompt = new StringBuilder();
-        prompt.append("请仔细分析这张图片中的内容，并提取所有相关信息：\n\n");
-        prompt.append("【识别要求】\n");
-        prompt.append("1. 如果图片包含BOM（物料清单）信息，请提取原材料ID、名称、数量、单位等\n");
-        prompt.append("2. 如果图片包含其他类型的信息（如检验报告、产品信息等），请提取所有相关属性\n");
-        prompt.append("3. 识别图片中的所有文字信息，包括标题、内容、表格数据等\n");
-        prompt.append("4. 提取关键信息点，如产品名称、规格参数、检验结果等\n");
-        prompt.append("5. 确保信息的准确性和完整性\n\n");
+        prompt.append("这是一张材料质保单的图片。请从表格、文字排布中提取有用的信息，返回其中所有可以被识别为字段名 + 字段值的键值对。\n\n");
+        prompt.append("要求如下：\n\n");
+        prompt.append("1. 忽略标题、编号、日期等通用信息，不要作为键值对输出；\n");
+        prompt.append("2. 仅提取\"字段名 + 字段值\"形式的内容，且字段名可以是如\"钢卷号\"、\"规格\"、\"净重\"、\"材质\"、\"下工序\"、\"生产班组\"、\"生产日期\"等；\n");
+        prompt.append("3. 字段不固定，根据图像内容自行判断，但要尽量提取所有；\n");
+        prompt.append("4. 返回格式统一为 JSON 数组，格式如下：\n");
+        prompt.append("[\n");
+        prompt.append("  { \"attrKey\": \"字段名\", \"attrValue\": \"字段值\" },\n");
+        prompt.append("  ...\n");
+        prompt.append("]\n");
+        prompt.append("5. 如有值缺失或为空的字段，仍保留字段，value 留空字符串；\n");
+        prompt.append("6. 严格按照图像中文字布局顺序返回；\n");
+        prompt.append("7. 只输出 JSON 结果，不需要解释或说明；\n\n");
         
         if (bo.getProductId() != null) {
             prompt.append("【产品信息】\n");
@@ -362,30 +371,6 @@ public class ImageRecognitionServiceImpl implements IImageRecognitionService {
             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("  \"attributes\": [\n");
-        prompt.append("    {\n");
-        prompt.append("      \"attrKey\": \"属性名称\",\n");
-        prompt.append("      \"attrValue\": \"属性值\"\n");
-        prompt.append("    }\n");
-        prompt.append("  ],\n");
-        prompt.append("  \"summary\": \"内容总结\",\n");
-        prompt.append("  \"totalItems\": 总项目数\n");
-        prompt.append("}\n\n");
-        prompt.append("请将识别到的所有信息整理成属性数组，每个属性包含attrKey（属性名称）和attrValue（属性值）。");
 
         return prompt.toString();
     }
@@ -439,7 +424,53 @@ public class ImageRecognitionServiceImpl implements IImageRecognitionService {
     }
 
     /**
-     * 解析BOM响应
+     * 解析属性数组响应
+     */
+    private List<ImageRecognitionVo.AttributeVo> parseAttributesResponse(String response) {
+        try {
+            // 尝试直接解析JSON数组
+            List<Map<String, Object>> attrList = objectMapper.readValue(response, 
+                objectMapper.getTypeFactory().constructCollectionType(List.class, Map.class));
+            
+            List<ImageRecognitionVo.AttributeVo> attributes = new ArrayList<>();
+            for (Map<String, Object> attr : attrList) {
+                ImageRecognitionVo.AttributeVo attribute = new ImageRecognitionVo.AttributeVo();
+                attribute.setAttrKey((String) attr.get("attrKey"));
+                attribute.setAttrValue((String) attr.get("attrValue"));
+                attributes.add(attribute);
+            }
+            return attributes;
+            
+        } catch (JsonProcessingException e) {
+            // 如果直接解析失败，尝试提取JSON数组部分
+            Pattern jsonArrayPattern = Pattern.compile("\\[[\\s\\S]*\\]");
+            Matcher matcher = jsonArrayPattern.matcher(response);
+            if (matcher.find()) {
+                try {
+                    List<Map<String, Object>> attrList = objectMapper.readValue(matcher.group(), 
+                        objectMapper.getTypeFactory().constructCollectionType(List.class, Map.class));
+                    
+                    List<ImageRecognitionVo.AttributeVo> attributes = new ArrayList<>();
+                    for (Map<String, Object> attr : attrList) {
+                        ImageRecognitionVo.AttributeVo attribute = new ImageRecognitionVo.AttributeVo();
+                        attribute.setAttrKey((String) attr.get("attrKey"));
+                        attribute.setAttrValue((String) attr.get("attrValue"));
+                        attributes.add(attribute);
+                    }
+                    return attributes;
+                    
+                } catch (JsonProcessingException ex) {
+                    log.warn("无法解析属性响应为JSON数组: {}", response);
+                    return new ArrayList<>();
+                }
+            }
+            log.warn("无法解析属性响应: {}", response);
+            return new ArrayList<>();
+        }
+    }
+
+    /**
+     * 解析BOM响应（保留用于兼容性）
      */
     private Map<String, Object> parseBomResponse(String response) {
         try {

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

@@ -1,118 +0,0 @@
-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());
-                }
-            }
-            
-            if (result.getAttributes() != null) {
-                log.info("属性数量: {}", result.getAttributes().size());
-                for (ImageRecognitionVo.AttributeVo attr : result.getAttributes()) {
-                    log.info("属性: {} = {}", attr.getAttrKey(), attr.getAttrValue());
-                }
-            }
-        } catch (Exception e) {
-            log.error("BOM识别测试异常", e);
-        }
-    }
-}