Create ai_mapper.py

ai_mapper.py

@@ -0,0 +1,30 @@
+# ai_mapper.py
+
+from sentence_transformers import SentenceTransformer, util
+
+# Load model once at module level
+model = SentenceTransformer("sentence-transformers/all-MiniLM-L6-v2")
+
+def ai_map_fields(extracted_keys, object_fields):
+    try:
+        mappings = {}
+        confidence_scores = {}
+
+        field_embeddings = model.encode(object_fields, convert_to_tensor=True)
+
+        for key in extracted_keys:
+            if key.lower() in ["name", "email"]:
+                continue
+
+            key_embedding = model.encode(key, convert_to_tensor=True)
+            cosine_scores = util.pytorch_cos_sim(key_embedding, field_embeddings)[0]
+            best_score_idx = cosine_scores.argmax().item()
+            best_match = object_fields[best_score_idx]
+            confidence = cosine_scores[best_score_idx].item()
+
+            mappings[key] = best_match
+            confidence_scores[key] = round(confidence, 2)
+
+        return mappings, confidence_scores, None
+    except Exception as e:
+        return None, None, str(e)