fix: issues

back_end/models/embedding_model.py

@@ -5,5 +5,6 @@ model = SentenceTransformer('Alibaba-NLP/gte-base-en-v1.5', trust_remote_code=Tr
 
 def generate_embedding(text: str):
     """Generate a 768-dimensional embedding for the input text."""
-    embedding = model.encode(text).tolist()  # Convert NumPy array to list
-    return embedding
+    embedding = model.encode(text).tolist()
+    embedding_result = len(embedding)# Convert NumPy array to list
+    return embedding_result