111

app.py

@@ -15,8 +15,8 @@ from app.authors import AUTHORS
 from app.app_utils import preprocess_image_and_predict, preprocess_video_and_predict
 
 def text_emo_analysize(text):
-    text_outcome = my_uie.text_emo_analysize(text)
-    return text_outcome
+    text_outcome1,text_outcome2 = my_uie.text_emo_analysize(text)
+    return text_outcome1,text_outcome2
 
 def clear_static_info():
     return (
@@ -65,8 +65,14 @@ with gr.Blocks(css="app.css") as demo:
             gr.Markdown("文本情感分析")
             text_input = gr.Textbox(lines=2, placeholder='在这里输入文本')
             text_submit_button = gr.Button("提交文本情感分析")
-        text_output = gr.Textbox(label="文本情感分析结果")
-    text_submit_button.click(text_emo_analysize, inputs=text_input, outputs=text_output)
+    
+        # 增加两个输出框
+        text_output_1 = gr.Textbox(label="文本情感")
+        text_output_2 = gr.Textbox(label="情感概率")
+
+    # 让按钮处理两个输出
+    text_submit_button.click(text_emo_analysize, inputs=text_input, outputs=[text_output_1, text_output_2])
+
 
 
 

my_uie.py

@@ -1,7 +1,16 @@
 from paddlenlp import Taskflow
+
 def text_emo_analysize(text):
     senta = Taskflow("sentiment_analysis", model="skep_ernie_1.0_large_ch")
-    result=senta(text)
-    print(result)
-    return result
-text_emo_analysize("你好")
+    result = senta(text)[0]  # 获取第一个结果
+    # 创建两个输出框
+    output_1 = {"文本": result['text'], "情感": "积极" if result['label'] == "positive" else "消极"}
+    output_2 = {"概率": result['score']}
+    
+    # 打印两个输出框
+    print(output_1)
+    print(output_2)
+    
+    return output_1, output_2
+
+text_emo_analysize("不开心")