Create summarizer.py

summarizer.py

@@ -0,0 +1,22 @@
+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) -> str:
+    text = text.strip()
+
+    if len(text) < 50:
+        return "Text is too short to summarize."
+
+    inputs = tokenizer([text], max_length=1024, truncation=True, return_tensors="pt")
+
+    summary_ids = model.generate(
+        inputs["input_ids"],
+        num_beams=4,
+        max_length=200,
+        min_length=40,
+        early_stopping=True
+    )
+
+    return tokenizer.decode(summary_ids[0], skip_special_tokens=True)