Update app.py

app.py

@@ -120,96 +120,214 @@ def calculate_metrics(status, pre_weight, current_weight, height,
     return "Select pregnancy status"
 
 def chat_function(user_input, image, chat_history):
-    """Handle chat interactions"""
+    """Generate responses based on user input and chat history."""
     history_str = format_history(chat_history)
-    
-    # Crisis detection
-    crisis_terms = {
-        "suicide", "self-harm", "kill myself", "hopeless",
-        "panic attack", "worthless", "end it all"
-    }
-    if any(term in user_input.lower() for term in crisis_terms):
-        return chat_history + [(user_input, crisis_response)]
-    
-    # Process image or text input
+    crisis_keywords = [
+        "suicide", "self-harm", "kill myself", "cutting", "hurt myself", "end my life",
+        "hopeless", "worthless", "can’t go on", "panic attack", "feel like dying"
+    ]
+    newborn_keywords = ["newborn", "baby", "infant", "feeding", "sleep", "colic"]
+
     if image:
-        food_label, confidence = classify_food(image)
-        if food_label:
-            context = f"User uploaded {food_label} image. {user_input}"
+        food_name, confidence = classify_food(image)
+        if food_name:
+            if user_input:
+                prompt = f"""
+Previous conversation:
+{history_str}
+
+The user uploaded an image of {food_name} and asked: '{user_input}'.
+
+Provide a response tailored to pregnancy or postpartum needs.
+"""
+            else:
+                prompt = f"""
+Previous conversation:
+{history_str}
+
+The user uploaded an image of {food_name}.
+
+Provide pregnancy-specific nutritional advice.
+"""
+            response = llm.invoke(prompt).content
         else:
-            return chat_history + [(user_input, "Couldn't identify food in image")]
+            response = "I couldn’t identify a food item in the image. Please upload a clearer picture."
     else:
-        context = user_input
-    
-    # Retrieve relevant documents
-    docs = retriever.get_relevant_documents(context)
-    context_str = "\n".join(d.page_content for d in docs[:3])
-    
-    # Generate response
-    prompt = f"""Context from documents:
-{context_str}
+        if not user_input.strip():
+            response = "Please type a message or upload an image."
+        elif any(keyword in user_input.lower() for keyword in crisis_keywords):
+            response = """
+I'm really sorry you're feeling this way. You’re not alone, and help is available.
+Please reach out to someone you trust or contact a helpline:
+
+- 🇮🇳 India: Vandrevala Foundation - 1860 266 2345
+- 🇺🇸 USA: National Suicide Prevention Lifeline - 988
+- 🇬🇧 UK: Samaritans - 116 123
+- 🌍 International: https://findahelpline.com/
 
-Recent conversation:
+If you’re in immediate danger, call emergency services (911/112).
+"""
+        elif any(keyword in user_input.lower() for keyword in newborn_keywords):
+            prompt = f"""
+Previous conversation:
 {history_str}
 
-User: {context}
-Assistant:"""
-    
-    response = llm.invoke(prompt).content
-    return chat_history + [(user_input, response)]
-
-# Crisis response template
-crisis_response = """🚨 Immediate Help Resources:
-- India: Vandrevala Foundation - 1860 266 2345
-- US: 988 Suicide & Crisis Lifeline
-- UK: Samaritans - 116 123
-- Worldwide: https://findahelpline.com"""
-
-# Gradio Interface
-with gr.Blocks(css=custom_css, theme=gr.themes.Soft()) as demo:
-    gr.Markdown("# 🤰 Maternal Wellness Companion")
-    
+The user asked: '{user_input}'.
+
+Provide basic guidance on newborn care.
+"""
+            response = llm.invoke(prompt).content
+        else:
+            docs = retriever.get_relevant_documents(user_input)
+            context = "\n".join([doc.page_content for doc in docs])
+            prompt = f"""
+Previous conversation:
+{history_str}
+
+Context: {context}
+
+Current question: {user_input}
+
+Assistant:
+"""
+            response = llm.invoke(prompt).content
+
+    chat_history.append((user_input or "[Image Uploaded]", response))
+    return chat_history
+
+# Custom CSS with specified colors
+custom_css = """
+@import url('https://fonts.googleapis.com/css2?family=Roboto:wght@400;500&display=swap');
+
+/* General layout */
+.gradio-container {
+    background: #F1D3B2; /* Light peach background */
+    font-family: 'Roboto', sans-serif; /* Modern, readable font */
+    padding: 20px; /* Add breathing room */
+}
+
+/* Chatbot bubble styling */
+.chatbot .bubble {
+    border-radius: 15px;
+    padding: 10px 15px;
+    margin: 8px;
+    box-shadow: 0 2px 5px rgba(0,0,0,0.1); /* Subtle shadow */
+}
+.chatbot .bubble:nth-child(odd) {
+    background: #F1D3B2; /* Light peach for assistant */
+    color: #46211A; /* Dark brown text for contrast */
+}
+.chatbot .bubble:nth-child(even) {
+    background: #D9B08C; /* Slightly darker peach for user */
+    color: #46211A;
+}
+
+/* Buttons */
+button {
+    border-radius: 10px !important;
+    padding: 10px 20px !important;
+    font-size: 16px !important;
+    transition: all 0.3s ease !important;
+}
+button.primary {
+    background: #A43820 !important; /* Rusty orange for primary actions */
+    color: #F1D3B2 !important; /* Light peach text */
+}
+button.primary:hover {
+    background: #8B2E18 !important; /* Darker orange on hover */
+}
+button.secondary {
+    background: #46211A !important; /* Dark brown for secondary actions */
+    color: #F1D3B2 !important;
+}
+button.secondary:hover {
+    background: #301510 !important; /* Darker brown on hover */
+}
+
+/* Textbox */
+textarea {
+    border-radius: 10px !important;
+    border: 1px solid #46211A !important; /* Dark brown border */
+    padding: 10px !important;
+    background: #FFFFFF !important; /* White background for clarity */
+    color: #46211A !important;
+}
+
+/* Input fields */
+.number-input, .radio {
+    background: #FFFFFF !important;
+    border-radius: 10px !important;
+    border: 1px solid #46211A !important;
+    padding: 10px !important;
+    color: #46211A !important;
+}
+
+/* Disclaimer styling */
+.disclaimer {
+    font-size: 12px;
+    color: #46211A; /* Dark brown for readability */
+    text-align: center;
+}
+"""
+
+# Gradio interface
+with gr.Blocks(css=custom_css) as demo:
+    gr.Markdown("# 🌸 Maternal Wellness Companion 🌸")
+    gr.Markdown("""Welcome! I'm here to support you through pregnancy and postpartum with advice on mental health, nutrition, fitness, and newborn care. Ask me anything or upload a food image!""")
+
+    chatbot = gr.Chatbot(
+        height=600,
+        label="Conversation",
+        value=[[None, "Welcome! I'm here to support you through pregnancy and postpartum. Ask me anything or upload a food image for nutritional advice."]]
+    )
+
     with gr.Row():
-        with gr.Column(scale=2):
-            chatbot = gr.Chatbot(height=500)
-            input_txt = gr.Textbox(placeholder="Ask about pregnancy health...")
-            input_img = gr.Image(type="pil", label="Upload Food Image")
-            btn_send = gr.Button("Send", variant="primary")
-            
         with gr.Column(scale=1):
-            gr.Markdown("## Health Metrics")
-            status = gr.Radio(["Pregnant", "Postpartum"], label="Status")
+            gr.Markdown("## Chat with Me")
+            msg = gr.Textbox(label="Your Message", placeholder="Type your question here...")
+            img = gr.Image(label="Upload Food Image", type="pil")
+            send_btn = gr.Button("Send")
+
+        with gr.Column(scale=1):
+            gr.Markdown("## Pregnancy Metrics")
+            status = gr.Radio(["Pregnant", "Postpartum"], label="Your Status")
             pre_weight = gr.Number(label="Pre-pregnancy Weight (kg)")
             current_weight = gr.Number(label="Current Weight (kg)")
             height = gr.Number(label="Height (cm)")
-            gest_age = gr.Number(visible=False)
-            postpartum_time = gr.Number(visible=False)
-            breastfeeding = gr.Radio(["Yes", "No"], visible=False)
-            btn_calculate = gr.Button("Calculate", variant="secondary")
-            
-    # Event handling
-    status.change(
-        lambda s: (
-            gr.update(visible=s=="Pregnant"),
-            gr.update(visible=s=="Postpartum"),
-            gr.update(visible=s=="Postpartum")
-        ),
-        inputs=status,
-        outputs=[gest_age, postpartum_time, breastfeeding]
-    )
-    
-    btn_send.click(
-        chat_function,
-        [input_txt, input_img, chatbot],
-        [chatbot],
-        queue=False
-    )
-    
-    btn_calculate.click(
-        calculate_metrics,
-        [status, pre_weight, current_weight, height, 
-         gest_age, postpartum_time, breastfeeding],
-        chatbot
-    )
+            gest_age = gr.Number(label="Gestational Age (weeks)", visible=False)
+            time_since_delivery = gr.Number(label="Time Since Delivery (weeks)", visible=False)
+            breastfeeding = gr.Radio(["Yes", "No"], label="Breastfeeding?", visible=False)
+            calc_btn = gr.Button("Calculate Metrics")
+
+    with gr.Row():
+        clear_btn = gr.Button("Clear Chat")
+
+    def update_visibility(status):
+        if status == "Pregnant":
+            return gr.update(visible=True), gr.update(visible=False), gr.update(visible=False)
+        elif status == "Postpartum":
+            return gr.update(visible=False), gr.update(visible=True), gr.update(visible=True)
+        return gr.update(visible=False), gr.update(visible=False), gr.update(visible=False)
+
+    status.change(update_visibility, inputs=status, outputs=[gest_age, time_since_delivery, breastfeeding])
+
+    def handle_send(msg, img, chat_history):
+        chat_history = chat_function(msg, img, chat_history)
+        return "", None, chat_history
+
+    send_btn.click(handle_send, inputs=[msg, img, chatbot], outputs=[msg, img, chatbot])
+
+    def handle_calc(status, pre_weight, current_weight, height, gest_age, time_since_delivery, breastfeeding, chat_history):
+        metrics_response = calculate_metrics(status, pre_weight, current_weight, height, gest_age, time_since_delivery, breastfeeding)
+        chat_history.append(("Pregnancy Metrics Calculation", metrics_response))
+        return chat_history
+
+    calc_btn.click(handle_calc,
+                   inputs=[status, pre_weight, current_weight, height, gest_age, time_since_delivery, breastfeeding, chatbot],
+                   outputs=chatbot)
+
+    clear_btn.click(lambda: [], outputs=chatbot)
+
+    gr.HTML('<div class="disclaimer">**Disclaimer**: This app offers general guidance and is not a substitute for professional medical advice. Consult your healthcare provider for personalized recommendations.</div>')
 
 demo.launch(debug=False)