Create embedding_handler.py

embedding_handler.py

@@ -0,0 +1,13 @@
+# embedding_handler.py
+
+from sentence_transformers import SentenceTransformer
+import numpy as np
+
+class EmbeddingHandler:
+    def __init__(self, model_name: str = "intfloat/e5-base"):
+        self.model = SentenceTransformer(model_name)
+    
+    def encode(self, text: str) -> np.ndarray:
+        if not text:
+            return np.zeros((768,))
+        return self.model.encode(text, convert_to_numpy=True, normalize_embeddings=True)