Update app.py

app.py

@@ -49,6 +49,7 @@ if __name__ == "__main__":
 
 # New codes to be tested
 
+'''
 import streamlit as st
 from transformers import pipeline
 from langdetect import detect
@@ -132,6 +133,103 @@ def main():
 
 if __name__ == "__main__":
     main()
+'''
+
+
+# V3
+# Improve speed and user experience 
+
+import streamlit as st
+from transformers import pipeline
+from langdetect import detect
+
+# 加载翻译pipeline
+@st.cache_resource
+def load_translation_pipeline():
+    return pipeline("translation", model="facebook/m2m100_418M")
+
+# 加载情感分析pipeline
+@st.cache_resource
+def load_sentiment_pipeline():
+    return pipeline("sentiment-analysis", model="Rocky080808/finetuned-roberta-base")
+
+# 定义语言映射
+language_name_map = {
+    'zh-cn': "Chinese (Simplified)",
+    'zh-tw': "Chinese (Traditional)",
+    'ja': "Japanese",
+    'de': "German",
+    'es': "Spanish",
+    'fr': "French"
+}
+
+def translate_to_english(text, translation_pipeline):
+    # 检测语言
+    detected_language = detect(text)
+    
+    # 语言映射
+    language_map = {
+        'zh-cn': "zh", 
+        'zh-tw': "zh", 
+        'ja': "ja",     
+        'de': "de",     
+        'es': "es",     
+        'fr': "fr"      
+    }
+    
+    if detected_language not in language_map:
+        return None, "Unsupported language"
+    
+    # 翻译到英语
+    translated_text = translation_pipeline(text, src_lang=language_map[detected_language], tgt_lang="en")
+    
+    return translated_text[0]['translation_text'], language_name_map.get(detected_language, detected_language)
+
+# 主程序逻辑
+def main():
+    # 加载模型
+    translation_pipeline = load_translation_pipeline()
+    sentiment_pipeline = load_sentiment_pipeline()
+
+    st.title("Global Customer Sentiment Analyzer")
+    st.write("Analyze customer sentiment in multiple languages including Chinese, Japanese, German, Spanish, and French.")
+
+    user_input = st.text_input("Enter customer comments in supported languages:")
+
+    # 用户点击分析按钮后触发
+    if st.button("Analyze"):
+        if user_input:
+            # 翻译
+            translated_text, detected_language = translate_to_english(user_input, translation_pipeline)
+            
+            if detected_language == "Unsupported language":
+                st.write("The input language is not supported. Please use Chinese, Japanese, German, Spanish, or French.")
+            else:
+                # 显示检测语言和翻译结果
+                st.write(f"Detected language: {detected_language}")
+                st.write(f"Translated Text: {translated_text}")
+
+                # 情感分析
+                result = sentiment_pipeline(translated_text)
+                label_str = result[0]["label"]  
+                label = int(label_str.split("_")[-1])  
+                confidence = result[0]["score"]
+
+                # 情感结果映射
+                label_to_text = {
+                    0: "Very dissatisfied, immediate follow-up is required.",
+                    1: "Dissatisfied, please arrange follow-up.",
+                    2: "Neutral sentiment, further case analysis is needed.",
+                    3: "Satisfied, the customer may return for a purchase.",
+                    4: "Very satisfied, the customer is very likely to return and recommend."
+                }
+                sentiment_text = label_to_text.get(label, "Unrecognized sentiment")
+
+                st.write(f"Sentiment Analysis Result: {sentiment_text}")
+                st.write(f"Confidence Score: {confidence:.2f}")
+
+if __name__ == "__main__":
+    main()