Create app.py

app.py

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+import gradio as gr
+import pandas as pd
+import numpy as np
+
+# Gerekli fonksiyonlar ve modeller buraya import edilmeli
+
+def predict_risk(cvss_score, cwe_id, description):
+    desc_len = len(description)
+    # Simülasyon (yerine gerçek model konmalı)
+    previous_pred = 4.5
+    
+    optimized = dynamic_risk_adjustment(previous_pred, cvss_score, cwe_id, desc_len)
+    confidence = calculate_confidence(0, cvss_score)
+    
+    if optimized <= 3.0:
+        category = "Düşük"
+    elif optimized <= 7.0:
+        category = "Orta"
+    else:
+        category = "Yüksek"
+
+    return {
+        "Risk Skoru": optimized,
+        "Kategori": category,
+        "Güven": f"{confidence:.0%}"
+    }
+
+iface = gr.Interface(
+    fn=predict_risk,
+    inputs=[
+        gr.Number(label="CVSS Skoru"),
+        gr.Text(label="CWE ID (örnek: CWE-89)"),
+        gr.Textbox(label="CVE Açıklaması", lines=5),
+    ],
+    outputs="json",
+    title="Siber Risk Skoru Tahmini",
+    description="CVE/CWE verisinden risk tahmini yapan basit demo"
+)
+
+iface.launch()