结束评分结果逻辑修改
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@@ -382,7 +382,7 @@ public class ChatWebSocketHandler {
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Map<String, String> mapEntity = list.get(0);
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//更新问题记录
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mapEntity.put("role", "system");
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mapEntity.put("content", "You are a construction industry interview expert. Rate candidate responses on a 1-5 scale and analyze key signals.");
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mapEntity.put("content", "You are a construction industry interview expert. Evaluate candidate responses and provide scores (1-5) and follow-up questions when needed. Always respond in JSON format.");
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//每个回答的内容前面要加上候选人的职位
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if (StrUtil.isNotEmpty(position)) {
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for (Map map : list) {
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@@ -399,8 +399,14 @@ public class ChatWebSocketHandler {
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log.info("结束AI提示词为:{}", promptJson);
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ChatGPTClient gptClient = SpringUtils.getBean(ChatGPTClient.class);
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String resultMsg = gptClient.handleAiChat(promptJson, "QA");
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//开始解析返回结果
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Map mapResultData = JSONUtil.toBean(resultMsg,Map.class);
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//获取评分
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Object scoreStr = mapResultData.get("score");
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Object assessment = mapResultData.get("assessment");
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Map<String, String> resultEntity = new HashMap<>();
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resultEntity.put("content", resultMsg);
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resultEntity.put("content", scoreStr +"\n"+assessment);
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resultEntity.put("type", "score");
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try{
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//返回最终的评分结构
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