Update sentiment.py

sentiment.py

@@ -5,50 +5,28 @@ from config import HEADERS
 CURRENT_MODEL = "cardiffnlp/twitter-xlm-roberta-base-sentiment"
 API_URL = f"https://api-inference.huggingface.co/models/{CURRENT_MODEL}"
 
-# 轉換英文分類為中文
-def translate_sentiment(label):
-    if "positive" in label.lower():
-        return "😃 **正向**"
-    elif "neutral" in label.lower():
-        return "😐 **中立**"
-    else:
-        return "😡 **負向**"
-
-# 轉換信心度
-def convert_confidence(score):
-    percentage = round(score * 100)
-    if score >= 0.90:
-        return f"🌟 **極高信心** ({percentage}%)"
-    elif score >= 0.75:
-        return f"✅ **高信心** ({percentage}%)"
-    elif score >= 0.50:
-        return f"⚠️ **中等信心** ({percentage}%)"
-    elif score >= 0.30:
-        return f"❓ **低信心** ({percentage}%)"
-    else:
-        return f"❌ **極低信心（建議忽略）** ({percentage}%)"
-
-# 📌 調用 Hugging Face API 進行情緒分析
 def analyze_sentiment(text, model_id=None):
     global CURRENT_MODEL, API_URL
 
-    # **只在模型變更時更新 API URL**
+    # 📌 **只在模型變更時更新 API URL**
     if model_id and model_id != CURRENT_MODEL:
         CURRENT_MODEL = model_id
         API_URL = f"https://api-inference.huggingface.co/models/{CURRENT_MODEL}"
+        print(f"🔄 重新載入模型: {CURRENT_MODEL}")
 
     try:
+        print("🚀 發送 API 請求...")
         response = requests.post(API_URL, headers=HEADERS, json={"inputs": text})
         result = response.json()
+        print(f"✅ API 回應: {result}")
 
         if isinstance(result, list) and len(result) > 0:
-            sentiment = translate_sentiment(result[0]["label"])
+            sentiment = result[0]["label"]
             confidence = result[0]["score"]
-            confidence_label = convert_confidence(confidence)
-
-            return f"**情緒分類**: {sentiment}\n**AI 判斷的信心度**: {confidence_label}", confidence
+            return f"**情緒分類**: {sentiment}\n**AI 信心度**: {confidence*100:.2f}%", confidence
         else:
             return "⚠️ **無法分析文本，請稍後再試**", 0.0
     
     except Exception as e:
+        print(f"❌ API 錯誤: {e}")
         return f"❌ **錯誤**: {str(e)}", 0.0