Update ui.py

ui.py

@@ -1,5 +1,4 @@
 import gradio as gr
-import matplotlib.pyplot as plt
 from sentiment import analyze_sentiment
 
 # 📌 可選擇的模型
@@ -9,15 +8,6 @@ MODEL_OPTIONS = {
     "🇬🇧 英語情緒分析 (DistilBERT)": "distilbert-base-uncased-finetuned-sst-2-english"
 }
 
-# 📌 生成信心度條狀圖
-def plot_confidence(score):
-    fig, ax = plt.subplots(figsize=(4, 1))
-    ax.barh(["信心度"], [score], color="blue")
-    ax.set_xlim([0, 1])
-    ax.set_xticks([0, 0.25, 0.5, 0.75, 1])
-    ax.set_xlabel("信心度（百分比）")
-    return fig
-
 # 📌 Gradio 介面說明
 intro_text = """
 # 🎯 多語言情緒分析 AI
@@ -52,7 +42,6 @@ def create_ui():
         progress_bar = gr.Textbox(visible=False, label="模型載入進度")
 
         result_output = gr.Markdown(label="分析結果")
-        plot_output = gr.Plot(label="信心度")
 
         # 📌 綁定按鈕功能
         def process_analysis(text, model_name):
@@ -62,13 +51,12 @@ def create_ui():
             if model_id != analyze_sentiment.CURRENT_MODEL:
                 progress_bar.update("🔄 AI 模型載入中，請稍後...", visible=True)
             
-            result, confidence_score = analyze_sentiment(text, model_id)
-
-            plot = plot_confidence(confidence_score)
+            result, _ = analyze_sentiment(text, model_id)  # 只返回文字結果
+            
             progress_bar.update("", visible=False)  # 隱藏進度條
-            return result, plot
+            return result
 
-        analyze_button.click(process_analysis, inputs=[text_input, model_selector], outputs=[result_output, plot_output, progress_bar])
+        analyze_button.click(process_analysis, inputs=[text_input, model_selector], outputs=[result_output, progress_bar])
 
         gr.Markdown(developer_info)