Add app.py

app.py

@@ -0,0 +1,58 @@
+import json
+import pickle
+import pandas as pd
+import numpy as np
+from datetime import datetime
+from flask import Flask, jsonify, Response
+from model import download_data, format_data, train_model
+from config import model_file_path
+
+app = Flask(__name__)
+
+
+def update_data():
+    """Download price data, format data and train model."""
+    download_data()
+    format_data()
+    train_model()
+
+
+def get_eth_inference():
+    """Load model and predict current price."""
+    with open(model_file_path, "rb") as f:
+        loaded_model = pickle.load(f)
+
+    now_timestamp = pd.Timestamp(datetime.now()).timestamp()
+    X_new = np.array([now_timestamp]).reshape(-1, 1)
+    current_price_pred = loaded_model.predict(X_new)
+
+    return current_price_pred[0]
+
+
+@app.route("/inference/<string:token>")
+def generate_inference(token):
+    """Generate inference for given token."""
+    if not token or token != "ETH":
+        error_msg = "Token is required" if not token else "Token not supported"
+        return Response(json.dumps({"error": error_msg}), status=400, mimetype='application/json')
+
+    try:
+        inference = get_eth_inference()
+        return Response(str(inference), status=200)
+    except Exception as e:
+        return Response(json.dumps({"error": str(e)}), status=500, mimetype='application/json')
+
+
+@app.route("/update")
+def update():
+    """Update data and return status."""
+    try:
+        update_data()
+        return "0"
+    except Exception:
+        return "1"
+
+
+if __name__ == "__main__":
+    update_data()
+    app.run(host="0.0.0.0", port=8000)