Update mylab/personalized_chat_w_viz.py

mylab/personalized_chat_w_viz.py

@@ -152,16 +152,24 @@ with gr.Blocks() as demo:
         )
         chart_path = visualize_bmi_and_calories(bmi, calories)
 
-        # Append metrics to response
+        # Append metrics to response with actionable advice
         personalized_metrics = (
             f"Based on your metrics:\n"
             f"- BMI: {bmi:.2f} ({status})\n"
             f"- Daily Caloric Needs: {calories:.2f} kcal\n"
-            f"Visualized metrics are displayed alongside."
+            f"\nAdvice: "
         )
-
-        response = run_graph(f"{message}\n\n{personalized_metrics}", history, user_details)
-        history.append((f"{user_details['name']}", message))
+        if status == "underweight":
+            personalized_metrics += "Your BMI indicates you are underweight. Focus on consuming more calories from nutrient-dense foods, including lean proteins, healthy fats, and whole grains. Consider strength training exercises to build muscle mass."
+        elif status == "normal weight":
+            personalized_metrics += "Your BMI is in the normal range. Maintain your weight by balancing calorie intake with regular physical activity. Incorporate a mix of cardio and strength training for overall fitness."
+        elif status == "overweight":
+            personalized_metrics += "Your BMI indicates you are overweight. Aim for a calorie deficit by reducing portion sizes and increasing physical activity. Focus on a diet rich in vegetables, lean protein, and healthy fats."
+        else:
+            personalized_metrics += "Your BMI indicates you are obese. Consult a healthcare provider for a personalized weight loss plan. Start with small, sustainable changes, such as reducing sugary foods and increasing daily physical activity."
+
+        response = personalized_metrics
+        history.append((f"User", message))
         history.append(("FIT.AI", response))
         return history, chart_path
 
@@ -183,4 +191,4 @@ with gr.Blocks() as demo:
         outputs=[bmi_output, calorie_output, bmi_chart]
     )
 
-demo.launch(share=True)
+demo.launch(share=True)