modified app.py

app.py

@@ -32,14 +32,14 @@ model = PeftModel.from_pretrained(model, "McGill-NLP/LLM2Vec-Sheared-LLaMA-mntp-
 # Wrapper for encoding and pooling operations
 l2v = LLM2Vec(model, tokenizer, pooling_mode="mean", max_length=512)
 
-def encode_text(input_text):
-    encoding = l2v.encode(input_text)
-    return encoding
+def encode_texts(input_texts):
+    encodings = [l2v.encode(text) for text in input_texts]
+    return encodings
 
 # Define Gradio interface
 iface = gr.Interface(
-    fn=encode_text,
-    inputs=gr.Textbox(lines=2, placeholder="Enter text here..."),
+    fn=encode_texts,
+    inputs=gr.Textbox(lines=5, placeholder="Enter texts separated by newlines..."),
     outputs=gr.JSON()
 )