Create app.py

app.py

@@ -0,0 +1,42 @@
+import numpy as np
+from tensorflow.keras.models import load_model
+from huggingface_hub import hf_hub_download
+
+# 🎯 Change to your actual model repo and filename
+REPO_ID = "Sukumar2005/rnn_models"
+FILENAME = "rnn_next_number.h5"  # replace with actual model file name
+
+def download_model(repo_id: str, filename: str, revision: str = None):
+    """Download model from Hugging Face hub."""
+    local_path = hf_hub_download(
+        repo_id=repo_id,
+        filename=filename,
+        revision=revision
+    )
+    return local_path
+
+def load_rnn_model(model_path: str):
+    return load_model(model_path)
+
+def predict_next(model, a: int, b: int, c: int):
+    x = np.array([a, b, c], dtype=float).reshape((1, 3, 1))
+    return float(model.predict(x)[0][0])
+
+def main():
+    # 📦 Download
+    print("Downloading model...")
+    model_path = download_model(REPO_ID, FILENAME)
+    print("Model downloaded to:", model_path)
+
+    # ⚙️ Load
+    model = load_rnn_model(model_path)
+    print("Model loaded!")
+
+    # 🧪 Test prediction
+    test_input = [10, 11, 12]
+    print(f"Input: {test_input}")
+    next_val = predict_next(model, *test_input)
+    print(f"Predicted next value: {next_val:.2f}")
+
+if __name__ == "__main__":
+    main()