First Commit for test Hugging face platform

app/__init__.py

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+from flask import Flask
+
+def create_app():
+    app = Flask(__name__)
+    from .routes import api
+    app.register_blueprint(api)
+    return app

app/model.py

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+from transformers import pipeline
+
+# 加载模型
+#model = pipeline('text-classification')
+
+def predict(text):
+    try:
+        result = text + ' is a good movie'
+        return result
+    except Exception as e:
+        return {'error': str(e)}

app/routes.py

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+from flask import Blueprint, request, jsonify
+from .model import predict
+
+api = Blueprint('api', __name__)
+
+@api.route('/predict', methods=['POST'])
+def predict_route():
+    data = request.get_json()
+    if not data or 'input' not in data:
+        return jsonify({'error': 'Invalid input'}), 400
+    prediction = predict(data['input'])
+    return jsonify({'prediction': prediction})

config.py

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+class Config:
+    DEBUG = True
+    SECRET_KEY = 'your-secret-key'

requirements.txt

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+flask
+streamlit
+transformers

streamlit_app.py

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+import streamlit as st
+import requests
+
+# 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:')
+
+if st.button('提交'):
+    if user_input.strip():
+        with st.spinner('正在预测...'):
+            try:
+                response = requests.post(
+                    'http://127.0.0.1:5000/predict',
+                    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！')