Update app.py

app.py

@@ -3,9 +3,8 @@ from transformers import pipeline
 import torch
 from diffusers import DiffusionPipeline
 
-
-
 def main():
+    # Prepare pipeline
     classifier = pipeline("text-classification", model="lori0330/BART_FineTuned_ZeroShotClassification")
     summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
     painter = DiffusionPipeline.from_pretrained(
@@ -15,10 +14,12 @@ def main():
         )
     painter.to('cuda')
 
+    # Edit the space
     st.title("Brief Report Generator")
     st.write("Copy the text here:")
     user_input = st.text_input("")
-    
+
+    # Check input
     if user_input:
         result_1 = classifier(user_input)
         label = result_1[0]['label']
@@ -26,6 +27,7 @@ def main():
 
         result_2 = summarizer(user_input, max_length=100, min_length=30, do_sample=False)
         summary = result_2[0]['summary_text']
+        st.write(f"The summary of this text:\n{summary}")
         
         description = f"This is mainly about {label}: {summary}"
         negative_prompt = "nsfw, lowres, (bad), text, error, fewer, extra, missing, worst quality, jpeg artifacts, low quality, watermark, unfinished, displeasing, oldest, early, chromatic aberration, signature, extra digits, artistic error, username, scan, [abstract]"
@@ -39,6 +41,7 @@ def main():
             num_inference_steps=28
             ).images[0]
 
+        st.write(f"The attached image:\n")
         st.image(image)
 
 if __name__ == "__main__":