Update summarizer.py

summarizer.py

@@ -1,10 +1,24 @@
 from transformers import pipeline
 
-summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
+# Use distilled summarization model
+summarizer = pipeline(
+    "summarization", 
+    model="sshleifer/distilbart-cnn-12-6",
+    tokenizer="sshleifer/distilbart-cnn-12-6"
+)
 
 def summarize_text(text, max_length=100):
-    """Summarize long text into shorter summary."""
-    # BART supports about 1024 tokens. Let's truncate text to ~1500 characters
-    truncated = text[:1500]
-    summary = summarizer(truncated, max_length=max_length, min_length=30, do_sample=False)[0]['summary_text']
-    return summary
+    """Efficient CPU summarization"""
+    if len(text) < 200:
+        return text
+    
+    # Truncate to model's max capacity
+    truncated = text[:1024]
+    
+    return summarizer(
+        truncated,
+        max_length=max_length,
+        min_length=30,
+        do_sample=False,  # Faster without sampling
+        truncation=True
+    )[0]['summary_text']