Update app.py

app.py

@@ -60,11 +60,13 @@ def speech_answer(audio_file_path):
 # ------------------------------
 # Summarizer
 # ------------------------------
+from transformers import pipeline
+
+summarizer = pipeline("summarization", model="facebook/bart-large-cnn")
+
 def summarize_text(text):
-    input_text = f"summarize: {text.strip()}"
-    input_ids = tokenizer_qg.encode(input_text, return_tensors="pt", max_length=512, truncation=True)
-    summary_ids = model_qg.generate(input_ids, max_length=150, min_length=30, length_penalty=5.0, num_beams=2)
-    return tokenizer_qg.decode(summary_ids[0], skip_special_tokens=True)
+    summary = summarizer(text, max_length=100, min_length=30, do_sample=False)
+    return summary[0]['summary_text']
 
 # ------------------------------
 # Engagement Predictor (Mock)