app.py

# python 3.9
# Available backend options are: "jax", "torch", "tensorflow".
import os
os.environ["KERAS_BACKEND"] = "tensorflow"
	
from tensorflow.keras.models import load_model
from sentence_transformers import SentenceTransformer
from huggingface_hub import hf_hub_download


def load_modeler():
    local_model_path = hf_hub_download(
        repo_id="noobpk/web-attack-detection",
        filename="model.h5"
    )
    return load_model(local_model_path)
    
model = load_modeler()

def load_encoder():
    model_name_or_path = os.environ.get("model_name_or_path", "sentence-transformers/all-MiniLM-L6-v2")
    return SentenceTransformer(model_name_or_path)

encoder = load_encoder()

if __name__ == "__main__":
    payload = input("Enter payload: ")
    print("Processing...")

embeddings = encoder.encode(payload).reshape((1, 384))
prediction = model.predict(embeddings)
accuracy = float(prediction[0][0] * 100)
print(f"Accuracy: {accuracy}")