Update app.py

app.py

@@ -1,32 +1,56 @@
-import streamlit as st
+# app.py
+import gradio as gr
 from transformers import pipeline
 
-def main():
-    # 1. 建立情感分析 pipeline
-    sentiment_pipeline = pipeline(
-        task="sentiment-analysis",
-        model="distilbert/distilbert-base-uncased-finetuned-sst-2-english"
-    )
+# 初始化模型pipeline
+# 情感分析模型（假设输出格式为 {'label': 'POSITIVE/NEGATIVE', 'score': float}）
+sentiment_pipeline = pipeline(
+    "text-classification",
+    model="KeviniveK/CustomModel_IMDB"
+)
 
-    st.title("Sentiment Analysis with HuggingFace Spaces")
-    st.write("Enter a sentence to analyze its sentiment:")
+# 翻译模型（英文->中文）
+translation_pipeline = pipeline(
+    "translation",
+    model="Helsinki-NLP/opus-mt-en-zh"
+)
 
-    user_input = st.text_input("")
-    if user_input:
-        result = sentiment_pipeline(user_input)[0]
-        label = result["label"]       # e.g. "LABEL_0" or "LABEL_1"
-        score = result["score"]
+def analyze_and_translate(text):
+    # 情感分析
+    sentiment_result = sentiment_pipeline(text)[0]
+    
+    # 翻译处理
+    translation_result = translation_pipeline(text)[0]['translation_text']
+    
+    # 格式化置信度为百分比
+    confidence = f"{sentiment_result['score']*100:.2f}%"
+    
+    return {
+        "情感分类": sentiment_result['label'],
+        "置信度": confidence,
+        "中文翻译": translation_result
+    }
 
-        # 2. 映射成更友好的文本
-        label_map = {
-            "LABEL_0": "Negative",
-            "LABEL_1": "Positive"
-        }
-        friendly_label = label_map.get(label, label)
-
-        # 3. 输出
-        st.write(f"Sentiment: **{friendly_label}**")
-        st.write(f"Confidence: **{score:.2f}**")
+# 创建Gradio界面
+demo = gr.Interface(
+    fn=analyze_and_translate,
+    inputs=gr.Textbox(
+        label="英文评价输入",
+        placeholder="Enter your English review here...",
+        lines=3
+    ),
+    outputs=[
+        gr.Textbox(label="情感分类"),
+        gr.Textbox(label="置信度"), 
+        gr.Textbox(label="中文翻译")
+    ],
+    title="🎬 IMDB评价情感分析+翻译系统",
+    description="输入英文影评，获取情感分析结果（分类+置信度）和中文翻译",
+    examples=[
+        ["This movie is absolutely fantastic! The acting was superb and the plot kept me engaged throughout."],
+        ["A terrible waste of time. The storyline was confusing and the acting felt forced."]
+    ]
+)
 
 if __name__ == "__main__":
-    main()
+    demo.launch()