update

app.py

@@ -1,24 +1,28 @@
-import gradio as gr
+import streamlit as st
 from transformers import pipeline
 
 # 加载中文垃圾邮件分类器
-classifier = pipeline("text-classification", model="app-x/chinese_spam_classifier")
+@st.cache_resource
+def load_classifier():
+    return pipeline("text-classification", model="app-x/chinese_spam_classifier")
 
-def classify_text(text):
-    result = classifier(text)[0]
-    label = "垃圾邮件" if result["label"] == "LABEL_1" else "正常邮件"
-    confidence = result["score"]
-    return f"{label} (置信度: {confidence:.2f})"
+classifier = load_classifier()
 
-# 创建 Gradio 界面
-iface = gr.Interface(
-    fn=classify_text,
-    inputs=gr.Textbox(lines=5, placeholder="请输入中文文本..."),
-    outputs="text",
-    title="中文垃圾邮件分类器",
-    description="使用 app-x/chinese_spam_classifier 模型进行中文文本的垃圾邮件分类。"
-)
+st.title("中文垃圾信息分类器")
+st.write("使用 app-x/chinese_spam_classifier 模型进行中文文本的垃圾信息分类。")
 
-# 启动应用
-iface.launch()
+# 创建文本输入框
+text_input = st.text_area("请输入中文文本:", height=150)
 
+if st.button("分类"):
+    if text_input:
+        # 进行分类
+        result = classifier(text_input)[0]
+        label = "垃圾信息" if result["label"] == "LABEL_1" else "正常信息"
+        confidence = result["score"]
+        
+        # 显示结果
+        st.write(f"分类结果: {label}")
+        st.write(f"置信度: {confidence:.2f}")
+    else:
+        st.warning("请输入文本后再进行分类。")

requirements.txt

@@ -1,4 +1,5 @@
-gradio
+streamlit
 transformers
 torch
 
+