app.py

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 = "/content/drive/MyDrive/model.keras"  # 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()