Update app.py

app.py

@@ -15,14 +15,14 @@ def predict(input_text):
     
     # Calculate embeddings by calling model.encode(), specifying the device
     embeddings = model.encode(input_text, device=device)
-    embeddings_str = np.array2string(embeddings, separator=',', threshold=np.inf)
-    return embeddings_str
+    
+    return embeddings
 
 # Gradio app interface
 gradio_app = gr.Interface(
     predict,
     inputs="text", 
-    outputs="text",
+    outputs=gr.Textbox(lines=30, placeholder="Scrollable array output")),
     title="Text to Vector Generator",
     description="Input a text and get its vector representation using an embedding model (mixedbread-ai/mxbai-embed-large-v1)."
 )