formatting

app.py

@@ -77,17 +77,17 @@ def proc_submission(
     clean_text = clean(input_text, lower=False)
     processed = truncate_word_count(clean_text, max_input_length)
     if processed["was_truncated"]:
-        history["input_text"] = processed["truncated_text"]
+        tr_in = processed["truncated_text"]
         history["was_truncated"] = True
         msg = f"Input text was truncated to {max_input_length} characters."
         logging.warning(msg)
         history["WARNING"] = msg
     else:
-        history["input_text"] = input_text
+        tr_in = input_text
         history["was_truncated"] = False
 
     _summaries = summarize_via_tokenbatches(
-        history["input_text"],
+        tr_in,
         model,
         tokenizer,
         batch_length=token_batch_length,
@@ -96,9 +96,9 @@ def proc_submission(
     sum_text = [s["summary"][0] for s in _summaries]
     sum_scores = [f"\n - {round(s['summary_score'],4)}" for s in _summaries]
 
-    history["Input"] = input_text
     history["Summary Text"] = "\n\t".join(sum_text)
     history["Summary Scores"] = "\n".join(sum_scores)
+    history["Input"] = tr_in
     html = ""
     for name, item in history.items():
         html += (
@@ -139,7 +139,7 @@ if __name__ == "__main__":
         inputs=[
             gr.inputs.Textbox(lines=10, label="input text"),
             gr.inputs.Slider(
-                minimum=1, maximum=6, label="num_beams", default=2, step=1
+                minimum=1, maximum=6, label="num_beams", default=4, step=1
             ),
             gr.inputs.Slider(
                 minimum=512, maximum=2048, label="token_batch_length", default=1024, step=512,