First Commit for test Hugging face platform

app.py

@@ -1,47 +1,20 @@
-import requests
 import streamlit as st
-from flask import Flask, request, jsonify
-import threading
-
-# Flask 部分
-flask_app = Flask(__name__)
-
-@flask_app.route('/predict', methods=['POST'])
-def predict():
-    data = request.get_json()
-    if not data or 'input' not in data:
-        return jsonify({'error': 'Invalid input'}), 400
-    input_text = data['input']
-    # 模拟模型预测
-    result = {"prediction": f"Predicted for: {input_text}"}
-    return jsonify(result)
-
-def run_flask():
-    flask_app.run(port=5000, debug=False)
+import requests
 
-# Streamlit 部分
-st.title("AI Model API Interface")
-st.write("输入文本，获取模型预测结果。")
+# Streamlit 页面设置
+st.title('AI Model API Interface')
+st.write('输入文本，获取模型预测结果。')
 
 # 用户输入
-user_input = st.text_area("请输入文本:")
+user_input = st.text_area('请输入文本:')
 
-if st.button("提交"):
+if st.button('提交'):
     if user_input.strip():
-        with st.spinner("正在预测..."):
+        with st.spinner('正在预测...'):
             try:
-                api_url = "http://127.0.0.1:5000/predict"  # 内部调用 Flask
-                response = requests.post(api_url, json={"input": user_input})
-                if response.status_code == 200:
-                    prediction = response.json()
-                    st.success(f"预测结果: {prediction}")
-                else:
-                    st.error(f"错误: {response.text}")
+                prediction = user_input + '123'
+                st.success(f'预测结果: {prediction}')
             except Exception as e:
-                st.error(f"请求失败: {e}")
+                st.error(f'请求失败: {e}')
     else:
-        st.warning("请输入文本！")
-
-# 使用线程运行 Flask
-if __name__ == "__main__":
-    threading.Thread(target=run_flask).start()
+        st.warning('请输入文本！')