Upload embedding_utils.py

src/embedding_utils.py

@@ -0,0 +1,15 @@
+import os
+os.environ["SENTENCE_TRANSFORMERS_DISABLE_ONNX"] = "1"
+
+
+from sentence_transformers import SentenceTransformer
+model = SentenceTransformer("sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2")
+
+
+def generate_embedding(text):
+
+    if not text or not isinstance(text, str) or text.strip() == "":
+        raise ValueError("Input text is empty or invalid.")
+    return model.encode(text)
+
+