Create utils/risk_detector.py

utils/risk_detector.py

@@ -0,0 +1,15 @@
+# utils/risk_detector.py
+
+from transformers import pipeline
+
+classifier = pipeline("zero-shot-classification", model="typeform/distilbert-base-uncased-mnli")
+labels = ["Indemnity", "Exclusivity", "Termination", "Jurisdiction", "Confidentiality"]
+
+def detect_risks(text):
+    if not text:
+        return []
+
+    result = classifier(text[:1000], candidate_labels=labels, multi_label=True)
+
+    # Package into list of [label, score] for Gradio dataframe
+    return list(zip(result["labels"], result["scores"]))