returning json for compatibility

app.py

@@ -7,7 +7,7 @@ import torch # For gpu
 device = torch.device("cuda") if torch.cuda.is_available() else torch.device("cpu")
 
 # Load a pretrained Sentence Transformer model and move it to the appropriate device
-model = SentenceTransformer('Alibaba-NLP/gte-large-en-v1.5', trust_remote_code=True)
+model = SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2', trust_remote_code=True)
 model = model.to(device)
 
 # Function that does the embedding
@@ -22,7 +22,7 @@ def predict(input_text):
 gradio_app = gr.Interface(
     predict,
     inputs="text", 
-    outputs="numpy",
+    outputs="json",
     title="Text to Vector Generator",
     description="Input a text and get its vector representation using an embedding model."
 )