almost there i think

app.py

@@ -1,5 +1,5 @@
 import gradio as gr
-from gradio import components #add for csv?
+from gradio import inputs, outputs  # Import inputs and outputs from gradio
 import torch
 from PIL import Image
 import pandas as pd
@@ -12,6 +12,7 @@ import io
 from sklearn.metrics.pairwise import cosine_similarity
 
 
+
 # Import logging module
 import logging
 
@@ -137,9 +138,9 @@ def process_images_and_statements(image):
     return results_df, csv_results  # <--- Return results_df and csv_results
 
 # Gradio interface
-image_input = gr.inputs.Image()
-output_df = gr.outputs.Dataframe(type="pandas", label="Results")
-output_csv = gr.outputs.File(label="Download CSV")
+image_input = inputs.Image()  # Use inputs instead of gr.inputs
+output_df = outputs.Dataframe(type="pandas", label="Results")  # Use outputs instead of gr.outputs
+output_csv = outputs.File(label="Download CSV")  # Use outputs instead of gr.outputs
 
 iface = gr.Interface(
     fn=process_images_and_statements,