Update summarizer.py

summarizer.py

@@ -3,13 +3,15 @@ from transformers import BartTokenizer, BartForConditionalGeneration
 tokenizer = BartTokenizer.from_pretrained("facebook/bart-large-cnn")
 model = BartForConditionalGeneration.from_pretrained("facebook/bart-large-cnn")
 
-def generate_summary(text: str, max_length=200, min_length=50) -> str:
+def generate_summary(text: str) -> str:
     inputs = tokenizer([text], max_length=1024, truncation=True, return_tensors="pt")
+
     summary_ids = model.generate(
         inputs["input_ids"],
         num_beams=4,
-        max_length=max_length,
-        min_length=min_length,
+        min_length=40,
+        max_length=200,
         early_stopping=True
     )
+
     return tokenizer.decode(summary_ids[0], skip_special_tokens=True)