Update app.py

app.py

@@ -1,28 +1,52 @@
 import gradio as gr
-import pickle
 import pandas as pd
+import pickle
+from huggingface_hub import hf_hub_download
+
+# Download model from Hugging Face Hub
+model_path = hf_hub_download(
+    repo_id="utsavNagar/cyberids-ml",
+    filename="ids_model.pkl"
+)
 
 # Load model
-with open("ids_model.pkl", "rb") as f:
+with open(model_path, "rb") as f:
     model = pickle.load(f)
 
-def predict(sample):
-    df = pd.DataFrame([sample])
-    
-    # Force numeric conversion
-    df = df.apply(pd.to_numeric, errors='coerce').fillna(0)
+# All NSL-KDD features (41 features)
+columns = [
+    "duration","protocol_type","service","flag","src_bytes","dst_bytes","land",
+    "wrong_fragment","urgent","hot","num_failed_logins","logged_in",
+    "num_compromised","root_shell","su_attempted","num_root",
+    "num_file_creations","num_shells","num_access_files","num_outbound_cmds",
+    "is_host_login","is_guest_login","count","srv_count","serror_rate",
+    "srv_serror_rate","rerror_rate","srv_rerror_rate","same_srv_rate",
+    "diff_srv_rate","srv_diff_host_rate","dst_host_count","dst_host_srv_count",
+    "dst_host_same_srv_rate","dst_host_diff_srv_rate",
+    "dst_host_same_src_port_rate","dst_host_srv_diff_host_rate",
+    "dst_host_serror_rate","dst_host_srv_serror_rate","dst_host_rerror_rate",
+    "dst_host_srv_rerror_rate"
+]
 
-    pred = model.predict(df)[0]
-    return "🔴 Attack Detected" if pred > 0.5 else "🟢 Normal Traffic"
+def predict_intrusion(*inputs):
+    data = pd.DataFrame([inputs], columns=columns)
+    data = data.apply(pd.to_numeric, errors="coerce").fillna(0)
 
-inputs = [
-    gr.Number(label=col) for col in range(41)   # but better replace with real feature names
-]
+    pred = model.predict(data)[0]
+    if pred > 0.5:
+        return "🔴 ATTACK DETECTED"
+    else:
+        return "🟢 NORMAL TRAFFIC"
+
+# Build Gradio UI with 41 numeric inputs
+inputs_ui = [gr.Number(label=col) for col in columns]
 
-gr.Interface(
-    fn=predict,
-    inputs=inputs,
+app = gr.Interface(
+    fn=predict_intrusion,
+    inputs=inputs_ui,
     outputs="text",
-    title="CyberSecurity Intrusion Detection System (IDS)",
-    description="Upload network flow values and detect intrusions using LightGBM."
-).launch()
+    title="CyberSecurity IDS - NSL KDD",
+    description="Enter feature values to detect intrusion using LightGBM model."
+)
+
+app.launch()