Update app.py

app.py

@@ -24,7 +24,6 @@ def proc_submission(
     num_beams,
     token_batch_length,
     length_penalty,
-    #no_repeat_ngram_size: int = 3,
     max_input_length: int = 768,
 ):
     """
@@ -61,7 +60,7 @@ def proc_submission(
         "encoder_no_repeat_ngram_size": 4,
         "num_beams": int(num_beams),
         "min_length": 100,
-        "max_length": int(token_batch_length // 4) if (token_batch_length <500) else 512,
+        "max_length": 512#int(token_batch_length // 4) if (token_batch_length <500) else 512,
         "early_stopping": True,
     }
     st = time.perf_counter()
@@ -72,7 +71,7 @@ def proc_submission(
 
     if processed["was_truncated"]:
         tr_in = processed["truncated_text"]
-        msg = f"Input text was truncated to {max_input_length} words (based on whitespace)"
+        msg = f"Input text was truncated to {max_input_length} words to fit within computational constraints"
         logging.warning(msg)
         history["WARNING"] = msg
     else:
@@ -96,10 +95,8 @@ def proc_submission(
             #batch_length=token_batch_length,
             #**settings_det,
         #)
-    if summary_type == 'TLDR':
-        settings = settings_tldr
-    else:# summary_type == 'Detailed':
-        settings = settings_det
+        
+    settings = settings_tldr if summary_type == 'TLDR' else settings_det
            
     _summaries = summarize_via_tokenbatches(
         tr_in,