事件分析优化

src/main/java/com/zzsn/event/controller/yjzx/EventHomeController.java

@@ -174,8 +174,19 @@ public class EventHomeController {
      */
     @GetMapping("/hotWordRecommend")
     public Result<?> hotWordRecommend(@RequestParam String networkName) {
-        String prompt = "请根据提供的百度/新浪热榜中的网络事件，再结合网络上资讯，推荐一些简短的关键词。以json格式输出：[\"关键词1\",\"关键词2\"]";
-        String result = llmService.model(null, prompt, networkName);
+        String prompt = "你是一个专业信息采集助手，根据用户专题描述生成关键词表达式：\n" +
+                "1. 用 + 表示与关系（必须同现），| 表示或关系（任一出现），用()分组\n" +
+                "2. 执行三步操作：\n" +
+                "   (1) 提取核心实体（如企业/产品名）\n" +
+                "   (2) 将抽象词拆解为3-5个具体场景词（如\"动向\"→\"上升|下降|波动|结构调整\"）\n" +
+                "   (3) 扩展同义词/行业关联词\n" +
+                "3. 排除时间词，+号不超过2个，单组|内词不超过5个\n" +
+                "4. 输出仅含表达式\n" +
+                "\n" +
+                "示例： \n" +
+                "描述：苹果新款iPhone发布引发市场反响\n" +
+                "输出：(苹果|iPhone)+(発売|価格|予約状況|市場シェア|消費者反応)";
+        String result = llmService.model(null,null, prompt, networkName);
         if (result.startsWith("```json")) {
             result = result.substring(7, result.length() - 3);
         } else if (result.startsWith("```")) {

src/main/java/com/zzsn/event/llm/LlmService.java

@@ -8,21 +8,11 @@ public interface LlmService {
     /**
      * glm模型调用
      *
-     * @param model   模型类型
-     * @param system  提示词
-     * @param content 引用内容
-     * @return 大模型响应结果
-     */
-    String model(String model, String system, String content);
-
-    /**
-     * 采集词推荐(定制自定义专题)
-     *
+     * @param modelType 模型类型
      * @param modelName 模型名称
-     * @param prompt    提示词
-     * @param content   输入的内容
-     * @author lkg
-     * @date 2025/8/16
+     * @param system    提示词
+     * @param content   引用内容
+     * @return 大模型响应结果
      */
-    String crawlerWord(String modelName, String prompt, String content);
+    String model(String modelType, String modelName, String system, String content);
 }

src/main/java/com/zzsn/event/llm/LlmServiceImpl.java

@@ -45,11 +45,14 @@ public class LlmServiceImpl implements LlmService {
     private LlmProperties llmProperties;
 
     @Override
-    public String model(String modelType, String system, String content) {
+    public String model(String modelType,String modelName, String system, String content) {
         if (StringUtils.isEmpty(modelType)) {
             modelType = llmProperties.getDefaultModelType();
         }
         LlmProperties.ModelConfig modelConfig = llmProperties.getModelConfig(modelType);
+        if (StringUtils.isNotEmpty(modelName)) {
+            modelConfig.setDefaultModel(modelName);
+        }
         if (modelType.equalsIgnoreCase("zhipu")) {
             return glmModel(modelConfig, system, content);
         } else if (modelType.equalsIgnoreCase("qwen")) {
@@ -62,15 +65,6 @@ public class LlmServiceImpl implements LlmService {
         return null;
     }
 
-    @Override
-    public String crawlerWord(String modelName, String prompt, String content) {
-        LlmProperties.ModelConfig modelConfig = llmProperties.getModelConfig("qwen");
-        if (StringUtils.isNotEmpty(modelName)) {
-            modelConfig.setDefaultModel(modelName);
-        }
-        return qwenModel(modelConfig, prompt, content);
-    }
-
     /**
      * glm模型调用
      *

src/main/java/com/zzsn/event/service/impl/AnalysisServiceImpl.java

@@ -311,8 +311,27 @@ public class AnalysisServiceImpl implements AnalysisService {
         if (llmConfig == null) {
             return null;
         }
-        String result = llmService.model(llmConfig.getLlmName(), llmConfig.getLlmPrompt(), content);
-        result = result.replaceAll("```json","").replaceAll("```","");
+        String result = llmService.model(llmConfig.getLlmName(),null, llmConfig.getLlmPrompt(), content);
+        AnalysisColumnEnum analysisColumnEnum = AnalysisColumnEnum.getByCode(llmConfig.getColumnCode());
+        String startHeader = null;
+        if (analysisColumnEnum != null) {
+            String resType = analysisColumnEnum.getResType();
+            if (resType.equals("array")) {
+                startHeader = "[";
+            } else if (resType.equals("object")) {
+                startHeader = "{";
+            }
+        }
+        if (startHeader != null && !result.startsWith(startHeader)) {
+            if (result.startsWith("```json")) {
+                result = result.substring(7, result.length() - 3);
+            } else if (result.startsWith("```")) {
+                result = result.substring(3, result.length() - 3);
+            } else if (result.contains(startHeader)){
+                result = result.substring(result.indexOf(startHeader));
+            }
+        }
+        result = result.replaceAll("```json", "").replaceAll("```","");
         if (llmConfig.getColumnCode().equals(AnalysisColumnEnum.IMPACT_ASSESSMENT.getCode())) {
             EventLlmConfig detailConfig = eventLlmConfigService.getConfig(event.getId(), AnalysisColumnEnum.IMPACT_ASSESSMENT_DETAIL.getCode());
             List<JSONObject> impactList = JSON.parseArray(result, JSONObject.class);
@@ -321,7 +340,7 @@ public class AnalysisServiceImpl implements AnalysisService {
                 params.put("eventName", event.getEventName());
                 params.put("eventSummary", event.getEventDescribe());
                 params.put("impactOutline", impact);
-                String impactDetail = llmService.model(detailConfig.getLlmName(), detailConfig.getLlmPrompt(), params.toJSONString());
+                String impactDetail = llmService.model(detailConfig.getLlmName(),null, detailConfig.getLlmPrompt(), params.toJSONString());
                 impact.put("impactDetail", impactDetail);
             }
             result = JSON.toJSONString(impactList);

src/main/java/com/zzsn/event/task/NetWorkEventTask.java

@@ -71,7 +71,7 @@ public class NetWorkEventTask {
 
     public void test(Integer type) {
         List<EventNetwork> networkList = getNetWordEventList(type);
-        String response = llmService.model(null, PROMPT, JSONObject.toJSONString(networkList));
+        String response = llmService.model(null,null, PROMPT, JSONObject.toJSONString(networkList));
         if (response.contains("```json")) {
             response = response.substring(response.indexOf("```json") + 7, response.lastIndexOf("```"));
         }
@@ -109,7 +109,7 @@ public class NetWorkEventTask {
         }
         if (CollectionUtils.isNotEmpty(finalList)) {
             finalList.forEach(network -> network.setLatest(1));
-            String response = llmService.model(null, PROMPT, JSONObject.toJSONString(finalList));
+            String response = llmService.model(null,null, PROMPT, JSONObject.toJSONString(finalList));
             if (StringUtils.isNotEmpty(response)) {
                 try {
                     if (response.contains("```json")) {

src/main/resources/application-dev.yml

@@ -183,3 +183,28 @@ caiji:
 data-permit:
   dataPermitGetQueryEntityTest: http://1.95.77.159:10089/permission/
   dataPermitGetQueryEntityProd: http://1.95.14.24:8060/
+
+model:
+  default-modelType: zhipu
+  configs:
+    - modelType: zhipu
+      modelTypeName: 智谱
+      url: https://open.bigmodel.cn/api/paas/v4/chat/completions
+      api-key: c5a53bd5f95a4e37a8997deb5d0c6031.orXyRRPNvZiqRaxF
+      default-model: glm-4-flash    #免费
+      web-search: true
+    - modelType: qwen
+      modelTypeName: 千问
+      url: https://dashscope.aliyuncs.com/compatible-mode/v1/chat/completions
+      api-key: sk-01ee9a6efa394178993a950b768e3753
+      default-model: qwen-plus      #收费
+    - modelType: deepseek
+      modelTypeName: deepseek
+      url: https://api.deepseek.com/v1/chat/completions
+      api-key: sk-656a8ec451dc47aaad3dacf24fe36f20
+      default-model: deepseek-chat  #收费
+    - modelType: doubao
+      modelTypeName: 豆包
+      url: https://ark.cn-beijing.volces.com/api/v3/chat/completions
+      api-key: ab54c534-4f3c-41b9-9b27-132cb7954b6f
+      default-model: doubao-1-5-pro-32k-250115 # Doubao-1.5-pro-32k #收费