Update app.py

app.py

@@ -7,7 +7,7 @@ from workflow import create_workflow
 
 graph = create_workflow()
 
-def run_graph(input_message, history):
+def run_graph(input_message, history, user_details):
     try:
         # Relevant fitness-related keywords to handle irrelevant user prompts
         relevant_keywords = [
@@ -34,29 +34,58 @@ def run_graph(input_message, history):
         ]
 
         greetings = ["hello", "hi", "how are you doing"]
-        
-        # Check if the input message contains any relevant keywords
+
         if any(keyword in input_message.lower() for keyword in relevant_keywords):
             response = graph.invoke({
-                "messages": [HumanMessage(content=input_message)]
+                "messages": [HumanMessage(content=input_message)],
+                "user_details": user_details  # Pass user-specific data for customization
             })
             return response['messages'][1].content
-        
+
         elif any(keyword in input_message.lower() for keyword in greetings):
-            return "Hi there, I am FIT bot, your personal wellbeing coach!"
-        
+            return "Hi there, I am FIT bot, your personal wellbeing coach! Let me know your fitness goals or questions."
+
         else:
             return "I'm here to assist with fitness, nutrition, mental health, and related topics. Please ask questions related to these areas."
     except Exception as e:
         return f"An error occurred while processing your request: {e}"
 
+
+# Advanced Functionalities
+def calculate_bmi(height, weight):
+    try:
+        height_m = height / 100
+        bmi = weight / (height_m ** 2)
+        if bmi < 18.5:
+            status = "underweight"
+        elif 18.5 <= bmi < 24.9:
+            status = "normal weight"
+        elif 25 <= bmi < 29.9:
+            status = "overweight"
+        else:
+            status = "obese"
+        return f"Your BMI is {bmi:.2f}, which is considered {status}."
+    except:
+        return "Please provide valid height and weight values."
+
+
 # Interface Components
 with gr.Blocks() as demo:
     gr.Markdown("<strong>FIT.AI - Your Personal Wellbeing Coach</strong>")
+
+    # User Details Form
+    with gr.Row():
+        user_name = gr.Textbox(placeholder="Enter your name", label="Name")
+        user_age = gr.Number(label="Age", value=25, precision=0)
+        user_weight = gr.Number(label="Weight (kg)", value=70, precision=1)
+        user_height = gr.Number(label="Height (cm)", value=170, precision=1)
+
     chatbot = gr.Chatbot(label="Chat with FIT.AI")
     text_input = gr.Textbox(placeholder="Type your question here...", label="Your Question")
     submit_button = gr.Button("Submit")
     clear_button = gr.Button("Clear")
+
+    # Examples
     examples = gr.Examples(
         examples=[
             "Create a personalized workout plan for me",
@@ -77,15 +106,35 @@ with gr.Blocks() as demo:
         ],
         inputs=text_input,
     )
-    
-    # Chatbot logic
-    def submit_message(message, history=[]):
-        response = run_graph(message, history)
+
+    # Chatbot Logic
+    def submit_message(message, history=[], user_details=None):
+        user_details = {
+            "name": user_name.value,
+            "age": user_age.value,
+            "weight": user_weight.value,
+            "height": user_height.value
+        }
+        response = run_graph(message, history, user_details)
         history.append(("User", message))
         history.append(("FIT.AI", response))
         return history, ""
 
-    submit_button.click(submit_message, inputs=[text_input, chatbot], outputs=[chatbot, text_input])
+    submit_button.click(
+        submit_message,
+        inputs=[text_input, chatbot],
+        outputs=[chatbot, text_input]
+    )
     clear_button.click(lambda: ([], ""), inputs=None, outputs=[chatbot, text_input])
 
+    # BMI Calculator Button
+    with gr.Row():
+        calculate_bmi_button = gr.Button("Calculate BMI")
+        bmi_result = gr.Textbox(label="BMI Result", interactive=False)
+        calculate_bmi_button.click(
+            calculate_bmi,
+            inputs=[user_height, user_weight],
+            outputs=[bmi_result]
+        )
+
 demo.launch(share=True)