Update app.py

app.py

@@ -30,9 +30,14 @@ def load_sentiment_pipeline():
 def load_keybert_model():
     return KeyBERT(model="all-MiniLM-L6-v2")
 
-# ─── FLAN-T5 Generation Pipeline ────────────────────────────────────────────
+# ─── BlenderBot Response Pipeline ───────────────────────────────────────────
 @st.cache_resource
 def load_response_pipeline():
+    # High-level helper using BlenderBot 400M Distill
+    return pipeline(
+        "text2text-generation",
+        model="facebook/blenderbot-400M-distill"
+    ):
     seq_tok = AutoTokenizer.from_pretrained("google/flan-t5-base")
     seq_model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-base")
     return pipeline(
@@ -106,7 +111,7 @@ def main():
     if max_label in ["Positive", "Very Positive"]:
         prompt = (
             f"You are a friendly customer success representative. The customer said: \"{review}\". "
-            "Write two sentences to appreciative reply their positive experience."
+            "Write a warm, appreciative reply celebrating their positive experience."
         )
     else:
         prompt = (