Update app.py

app.py

@@ -1,26 +1,30 @@
 import gradio as gr
-from transformers import pipeline
 from span_marker import SpanMarkerModel
 
 # Define the function
-def function(messages):
+def function(text):
     # Load the pre-trained model from Hugging Face
     model = SpanMarkerModel.from_pretrained("tomaarsen/span-marker-bert-base-acronyms")
     
     # Ensure the input is valid
-    if messages:
-        # Run inference on the input messages
-        out = model.predict(messages)
+    if text:
+        # Run inference on the input text
+        out = model.predict([text])  # Wrap the text in a list as the model expects a list of strings
         return out
     else:
         return "Please provide valid text input."
 
 # Set up the Gradio interface
-demo = gr.ChatInterface(
+demo = gr.Interface(
     fn=function,
-    type="messages",
-    examples=["Hello, I'm curious about abbreviations like NASA.", "Hola, ¿qué significa AI?", "Merhaba, kısaltmalar hakkında bilgi verir misiniz?"],
-    title="Abbreviation Detector"
+    inputs=gr.Textbox(lines=5, placeholder="Enter your text here...", label="Input Text"),
+    outputs="json",
+    title="Abbreviation Detector",
+    examples=[
+        "NASA is an abbreviation for National Aeronautics and Space Administration.",
+        "AI stands for Artificial Intelligence.",
+        "What does HTTP mean?"
+    ]
 )
 
 # Launch the app