Create embedder.py

embedder.py

@@ -0,0 +1,8 @@
+# embedder.py
+from sentence_transformers import SentenceTransformer
+
+# Load transformer model once
+tf_model = SentenceTransformer("all-MiniLM-L6-v2")
+
+def get_embeddings(text_list):
+    return tf_model.encode(text_list, convert_to_numpy=True)