Create utils/fallback_suggester.py

utils/fallback_suggester.py

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+# utils/fallback_suggester.py
+
+import json
+from sentence_transformers import SentenceTransformer, util
+
+model = SentenceTransformer("sentence-transformers/paraphrase-mpnet-base-v2")
+
+with open("fallback_clauses.json", "r", encoding="utf-8") as f:
+    clause_bank = json.load(f)
+
+clause_labels = list(clause_bank.keys())
+clause_texts = list(clause_bank.values())
+clause_embeddings = model.encode(clause_texts, convert_to_tensor=True)
+
+def suggest_fallback(input_clause):
+    if not input_clause or len(input_clause.strip()) == 0:
+        return "No input clause provided."
+
+    input_embedding = model.encode(input_clause, convert_to_tensor=True)
+    scores = util.cos_sim(input_embedding, clause_embeddings)[0]
+    best_idx = scores.argmax().item()
+
+    label = clause_labels[best_idx]
+    suggestion = clause_texts[best_idx]
+
+    return f"🔹 {label} → {suggestion}"