random button

app.py

@@ -1,24 +1,37 @@
 import gradio as gr
-
+import random
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+from datasets import load_dataset
 
 tokenizer = AutoTokenizer.from_pretrained("liamvbetts/bart-large-cnn-v4")
 model = AutoModelForSeq2SeqLM.from_pretrained("liamvbetts/bart-large-cnn-v4")
 
+dataset = load_dataset("cnn_dailymail", "3.0.0")
+
 def summarize(article):
     inputs = tokenizer(article, return_tensors="pt").input_ids
     outputs = model.generate(inputs, max_new_tokens=128, do_sample=False)
     summary = tokenizer.decode(outputs[0], skip_special_tokens=True)
     return summary
 
+def get_random_article():
+    random.seed()
+    val_example = dataset["validation"].shuffle().select(range(1))
+    val_article = val_example['article'][0][:512]
+    return val_article
+
 # Create Gradio interface
 input_text = gr.Textbox(lines=10, label="Input Text")
 output_text = gr.Textbox(label="Summary")
+random_article_button = gr.Button("Load Random Article")
+
+def update_input_text():
+    return get_random_article()
 
 gr.Interface(
     fn=summarize,
-    inputs=input_text,
+    inputs=[input_text, gr.components.Button("Load Random Article").click(update_input_text, [], input_text)],
     outputs=output_text,
     title="News Summary App",
-    description="Enter a news text and get its summary."
+    description="Enter a news text and get its summary, or load a random article from the validation set."
 ).launch()