Update app.py

app.py

@@ -1,11 +1,13 @@
 from sentence_transformers import SentenceTransformer
 import gradio as gr
+import ast
 
 # Load the pre-trained model
 model = SentenceTransformer('all-MiniLM-L6-v2')
 
 def get_embeddings(sentences):
-    embeddings = model.encode(sentences, convert_to_tensor=True)
+    chunks = ast.literal_eval(sentences)
+    embeddings = model.encode(chunks, convert_to_tensor=True)
     return embeddings.tolist()
 
 # Define the Gradio interface