Update src/streamlit_app.py

src/streamlit_app.py

@@ -53,7 +53,7 @@ def main():
     st.sidebar.header("Models Used")
     st.sidebar.markdown("""
     - 🖼️ **Image Classifier**: `shingguy1/fine_tuned_vit`
-    - 💬 **Paraphraser**: `google/flan-t5-small`
+    - 💬 **Paraphraser**: `google/flan-t5-small` (beam search mode)
     """)
 
     transform = transforms.Compose([
@@ -97,7 +97,8 @@ def main():
                 f"Try {data['substitute']} as a healthier swap."
             )
             prompt = (
-                f"Paraphrase this nutritional description into a friendly, conversational tone without changing any facts:\n\n"
+                f"Rewrite the following nutritional information in a clear and friendly tone. "
+                f"Do not add or change any facts. Keep the sentence structure simple:\n\n"
                 f"{base_description}"
             )
         else:
@@ -107,14 +108,15 @@ def main():
         output_ids = model_t5.generate(
             inputs["input_ids"],
             max_new_tokens=100,
-            do_sample=True,
-            temperature=1.0,
-            top_p=0.95,
-            top_k=40,
-            repetition_penalty=1.1
+            num_beams=4,
+            early_stopping=True
         )
         response = tokenizer_t5.decode(output_ids[0], skip_special_tokens=True)
 
+        # Fallback if the output seems too short or misses key phrases
+        if "calories" not in response.lower() or len(response.split()) < 10:
+            response = base_description
+
         st.subheader("🧾 Nutrition Overview")
         st.info(response)