Added a feature to select the emotion analysis model, supporting switching betwe…

…en the basic and improved models.

@@ -167,24 +167,44 @@ def getYuQingCharDataOne():
     biedata = [{'name': x, 'value': y} for x, y in zip(X, Y)]
     return X, Y, biedata
 
-def getYuQingCharDataTwo():
-    # 分析评论和文章的情感
+def getYuQingCharDataTwo(model_type='pro'):
+    """
+    分析评论和文章的情感
+    :param model_type: 使用的模型类型，'basic' 为基础模型，'pro' 为改进模型
+    """
     comment_texts = [comment[4] for comment in commentList]
     article_texts = [article[5] for article in articleList]
     
-    # 预测评论情感
-    comment_predictions = predict_sentiment(comment_texts)
-    if comment_predictions is not None:
-        comment_sentiments = ['良好' if pred == 0 else '不良' for pred in comment_predictions]
-    else:
+    if model_type == 'basic':
+        # 使用基础模型（SnowNLP）
         comment_sentiments = []
-    
-    # 预测文章情感
-    article_predictions = predict_sentiment(article_texts)
-    if article_predictions is not None:
-        article_sentiments = ['良好' if pred == 0 else '不良' for pred in article_predictions]
-    else:
+        for text in comment_texts:
+            value = SnowNLP(text).sentiments
+            if value > 0.6:
+                comment_sentiments.append('良好')
+            else:
+                comment_sentiments.append('不良')
+        
         article_sentiments = []
+        for text in article_texts:
+            value = SnowNLP(text).sentiments
+            if value > 0.6:
+                article_sentiments.append('良好')
+            else:
+                article_sentiments.append('不良')
+    else:
+        # 使用改进模型
+        comment_predictions = predict_sentiment(comment_texts)
+        if comment_predictions is not None:
+            comment_sentiments = ['良好' if pred == 0 else '不良' for pred in comment_predictions]
+        else:
+            comment_sentiments = []
+        
+        article_predictions = predict_sentiment(article_texts)
+        if article_predictions is not None:
+            article_sentiments = ['良好' if pred == 0 else '不良' for pred in article_predictions]
+        else:
+            article_sentiments = []
     
     # 统计结果
     comment_counts = Counter(comment_sentiments)

@@ -199,8 +199,11 @@ def commentChar():
 @pb.route('/yuqingChar')
 def yuqingChar():
     username = session.get('username')
+    # 获取模型选择参数
+    model_type = request.args.get('model', 'pro')  # 默认使用改进模型
+    
     X, Y, biedata = getYuQingCharDataOne()
-    biedata1, biedata2 = getYuQingCharDataTwo()
+    biedata1, biedata2 = getYuQingCharDataTwo(model_type)
     x1Data, y1Data = getYuQingCharDataThree()
     return render_template('yuqingChar.html',
                            username=username,
@@ -210,7 +213,8 @@ def yuqingChar():
                            biedata1=biedata1,
                            biedata2=biedata2,
                            x1Data=x1Data,
-                           y1Data=y1Data)
+                           y1Data=y1Data,
+                           model_type=model_type)
 
 @pb.route('/yuqingpredict')
 def yuqingpredict():
@@ -222,13 +226,26 @@ def yuqingpredict():
     TopicLen = getTopicLen(defaultTopic)
     X, Y = getTopicCreatedAtandpredictData(defaultTopic)
     
-    # 使用改进版模型进行情感预测
-    predicted_label, confidence = predict_sentiment(defaultTopic)
-    if predicted_label is not None:
-        sentences = '良好' if predicted_label == 0 else '不良'
-        sentences = f"{sentences} (置信度: {confidence:.2f})"
+    # 获取模型选择参数
+    model_type = request.args.get('model', 'pro')  # 默认使用改进模型
+    
+    if model_type == 'basic':
+        # 使用基础模型（SnowNLP）
+        value = SnowNLP(defaultTopic).sentiments
+        if value == 0.5:
+            sentences = '中性'
+        elif value > 0.5:
+            sentences = '正面'
+        elif value < 0.5:
+            sentences = '负面'
     else:
-        sentences = '预测失败'
+        # 使用改进模型
+        predicted_label, confidence = predict_sentiment(defaultTopic)
+        if predicted_label is not None:
+            sentences = '良好' if predicted_label == 0 else '不良'
+            sentences = f"{sentences} (置信度: {confidence:.2f})"
+        else:
+            sentences = '预测失败'
     
     comments = getCommentFilterDataTopic(defaultTopic)
     return render_template('yuqingpredict.html',
@@ -239,7 +256,8 @@ def yuqingpredict():
                            sentences=sentences,
                            xData=X,
                            yData=Y,
-                           comments=comments)
+                           comments=comments,
+                           model_type=model_type)
 
 
 @pb.route('/articleCloud')

@@ -155,18 +155,35 @@
                         <select onchange="hotWordChange(event)" class="form-control mb-3">
                             {% for i in hotWordList %}
                                 {% if defaultHotWord == i[0] %}
-                                                                                       <option selected value="{{ i[0] }}">{{ i[0] }}</option>
+                                    <option selected value="{{ i[0] }}">{{ i[0] }}</option>
                                 {% else %}
-                                                                                       <option value="{{ i[0] }}">{{ i[0] }}</option>
+                                    <option value="{{ i[0] }}">{{ i[0] }}</option>
                                 {% endif %}
                             {% endfor %}
                         </select>
+                     </div>
+                     <div class="form-group">
+                        <label>模型选择</label>
+                        <select onchange="modelChange(event)" class="form-control mb-3">
+                            {% if model_type == 'basic' %}
+                                <option selected value="basic">基础模型</option>
+                                <option value="pro">改进模型</option>
+                            {% else %}
+                                <option value="basic">基础模型</option>
+                                <option selected value="pro">改进模型</option>
+                            {% endif %}
+                        </select>
+                     </div>
                          <script>
                              function hotWordChange(e){
-                                 window.location.href = 'http://127.0.0.1:5000/page/yuqingpredict?Topic=' + e.target.value
+                                 const model = document.querySelector('select[onchange="modelChange(event)"]').value;
+                                 window.location.href = 'http://127.0.0.1:5000/page/yuqingpredict?Topic=' + e.target.value + '&model=' + model;
+                             }
+                             function modelChange(e){
+                                 const topic = document.querySelector('select[onchange="hotWordChange(event)"]').value;
+                                 window.location.href = 'http://127.0.0.1:5000/page/yuqingpredict?Topic=' + topic + '&model=' + e.target.value;
                              }
                          </script>
-                     </div>
                   </div>
          </div>