Update app.py

app.py

@@ -1,42 +1,50 @@
-# app.py
 import streamlit as st
 from transformers import pipeline
 
-# Initialize pipelines
+# 加载模型
 @st.cache_resource
 def load_pipelines():
     sentiment_pipeline = pipeline(model="KeviniveK/CustomModel_IMDB")
     translation_pipeline = pipeline(
-        "translation_en_to_zh", 
+        "translation_en_to_zh",
         model="Helsinki-NLP/opus-mt-en-zh"
     )
     return sentiment_pipeline, translation_pipeline
 
 sentiment_pipeline, translation_pipeline = load_pipelines()
 
-# Streamlit App
-st.title("IMDB Review Sentiment & Translation App")
-st.write("Enter an English movie review to analyze its sentiment and translate it into Chinese.")
+# 标签映射
+label_map = {
+    "LABEL_0": "差评 / Negative",
+    "LABEL_1": "好评 / Positive"
+}
+
+# 页面标题
+st.title("影评分析与翻译 | Sentiment Analysis & Translation")
+st.write("请输入一段英文影评，我们将分析其情感并翻译成中文。")
+st.write("Enter an English movie review below. The app will analyze its sentiment and translate it into Chinese.")
+
+# 用户输入
+user_input = st.text_area("英文影评输入 | Enter English Movie Review", height=150)
 
-user_input = st.text_area("English Movie Review", height=150)
 if user_input:
-    # Sentiment Analysis
+    # 情感分析
     result = sentiment_pipeline(user_input)
-    sentiment = result[0]["label"]
+    sentiment_raw = result[0]["label"]
+    sentiment = label_map.get(sentiment_raw, sentiment_raw)
     confidence = result[0]["score"]
 
-    # Translation
+    # 翻译
     translation = translation_pipeline(user_input)
     translated_text = translation[0]["translation_text"]
 
-    # Display Results
-    st.subheader("Sentiment Analysis Result")
-    st.write(f"**Sentiment:** {sentiment}")
-    st.write(f"**Confidence:** {confidence:.2f}")
+    # 显示结果
+    st.subheader("情感分析结果 | Sentiment Analysis Result")
+    st.write(f"**情感 (Sentiment):** {sentiment}")
+    st.write(f"**置信度 (Confidence):** {confidence:.2f}")
 
-    st.subheader("Chinese Translation")
+    st.subheader("中文翻译结果 | Chinese Translation")
     st.write(translated_text)
 
 if __name__ == "__main__":
-    # Run the app with: streamlit run app.py
-    pass
+    pass