Update app.py

app.py

@@ -0,0 +1,63 @@
+from flask import Flask, request, jsonify
+import pymongo
+import requests
+import json
+
+app = Flask(__name__)
+
+# MongoDB bağlantısı
+mongo_client = pymongo.MongoClient('mongodb://localhost:27017/')
+db = mongo_client['EgitimDatabase']
+collection = db['test']
+
+# Model API Endpoint
+MODEL_API_URL = "https://api.example.com/model"  # Hugging Face API URL veya başka bir model URL'si
+MODEL_API_KEY = "YOUR_API_KEY"  # API anahtarınız
+
+def get_model_prediction(title, keywords, subheadings):
+    headers = {
+        'Authorization': f'Bearer {MODEL_API_KEY}',
+        'Content-Type': 'application/json'
+    }
+    payload = {
+        'title': title,
+        'keywords': keywords,
+        'subheadings': subheadings
+    }
+    response = requests.post(MODEL_API_URL, headers=headers, json=payload)
+    return response.json()
+
+@app.route('/predict', methods=['POST'])
+def predict():
+    data = request.json
+    title = data.get('title')
+    keywords = data.get('keywords')
+    subheadings = data.get('subheadings')
+    
+    # MongoDB'den ilgili verileri çekme
+    query = {
+        'title': title,
+        'keywords': {'$in': keywords.split(',')},
+        'subheadings': {'$in': subheadings.split(',')}
+    }
+    documents = list(collection.find(query))
+    
+    
+    predictions = []
+    for doc in documents:
+        result = get_model_prediction(doc['title'], doc['keywords'], doc['subheadings'])
+        predictions.append(result)
+
+    # Sonuçları döndürme
+    response = {
+        'title': title,
+        'keywords': keywords,
+        'subheadings': subheadings,
+        'predictions': predictions
+    }
+    
+    return jsonify(response)
+
+if __name__ == "__main__":
+    app.run(host='0.0.0.0', port=8080)
+