app.py

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)

# Streamlit 部分
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:")

if st.button("提交"):
    if user_input.strip():
        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}")
            except Exception as 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()