Update app.py

app.py

@@ -1,103 +1,42 @@
 import gradio as gr
+import time
 
-# Step 1: Greeting the user and asking if they'd like to customize food
-def start_conversation(user_input):
-    # Checking if the input is a positive response
-    if user_input.lower() in ["yes", "yeah"]:
-        return "Great! Please select a food category:"
-    else:
-        return "Okay, let me know if you change your mind!"
+# Function to simulate typing and provide chatbot response
+def chatbot_response(user_input, history):
+    bot_message = ""
+    response = "Here is the response from the bot based on your input: " + user_input  # Replace with your AI response logic
 
-# Step 2: Show categories based on the user's interest
-def select_category(selected_category):
-    categories = {
-        "Veg": "Great! You selected Veg. Now, please select your nutrition preference.",
-        "Non-Veg": "Great! You selected Non-Veg. Now, please select your nutrition preference.",
-        "Vegan": "Great! You selected Vegan. Now, please select your nutrition preference.",
-        "Pasta & Noodles": "Great! You selected Pasta & Noodles. Now, please select your nutrition preference.",
-        "Breads & Baked Goods": "Great! You selected Breads & Baked Goods. Now, please select your nutrition preference."
-    }
-    return categories.get(selected_category, "Please select a valid category.")
+    # Simulate typing by adding characters one by one with a slight delay
+    for char in response:
+        bot_message += char
+        history.append((user_input, bot_message))
+        time.sleep(0.05)  # Delay to simulate typing speed
+        yield gr.update(value=bot_message)  # Yield updated message
 
-
-# Step 3: Show nutrition options based on the selected category
-def select_nutrition(selected_nutrition):
-    nutrition_options = {
-        "Protein Rich": "Now, please select ingredients from the list below.",
-        "Low Carbs": "Now, please select ingredients from the list below.",
-        "Gluten-Free": "Now, please select ingredients from the list below."
-    }
-    return nutrition_options.get(selected_nutrition, "Please select a valid nutrition option.")
-
-
-# Step 4: Show ingredients based on the category and nutrition selection
-def show_ingredients(selected_category, selected_nutrition):
-    # Ingredients based on category and nutrition preference
-    ingredients = {
-        "Veg": ["Paneer", "Potato", "Cabbage", "Gobi"],
-        "Non-Veg": ["Chicken", "Fish", "Mutton"],
-        "Vegan": ["Tofu", "Tempeh", "Seitan"],
-        "Pasta & Noodles": ["Whole Wheat Pasta", "Rice Noodles"],
-        "Breads & Baked Goods": ["Whole Grain Bread", "Gluten-Free Bread"]
-    }
-
-    return f"Here are the ingredients available for {selected_category} with {selected_nutrition} option: " + ", ".join(ingredients.get(selected_category, []))
-
-
-# Step 5: Show dishes based on the selected ingredient
-def show_dishes(selected_ingredient):
-    dishes = {
-        "Paneer": ["Paneer Tikka", "Paneer Curry", "Paneer Manchurian", "Paneer Butter Masala"],
-        "Potato": ["Aloo Dal", "Potato and Chickpea Salad", "Paneer-Stuffed Potatoes", "Potato and Black Bean Tacos"],
-        "Cabbage": ["Cabbage and Chickpea Curry", "Cabbage Stir-Fry with Tofu", "Cabbage and Lentil Soup"],
-        "Chicken": ["Grilled Chicken Breast", "Chicken Tikka Masala", "Chicken Stir-Fry", "Chicken Biryani"],
-        "Fish": ["Grilled Salmon", "Fish Curry", "Baked Fish with Herbs", "Fish Tacos"],
-        "Mutton": ["Mutton Curry", "Mutton Biryani", "Grilled Lamb Chops", "Mutton Rogan Josh"],
-        "Tofu": ["Tofu Stir-Fry", "Crispy Tofu Nuggets", "Tofu Scramble", "Tofu Curry"],
-        "Tempeh": ["Tempeh Bacon", "BBQ Tempeh", "Tempeh Stir-Fry", "Marinated Tempeh"],
-        "Seitan": ["Seitan Steak", "Seitan Wings", "Seitan Stir-Fry", "Seitan Curry"]
-    }
-    return f"Based on your selection, here are the food items you can make: " + ", ".join(dishes.get(selected_ingredient, []))
-
-
-# Gradio interface setup
+# Gradio Interface Setup
 def create_gradio_interface():
-    # Step-by-step interaction using Gradio components
     with gr.Blocks() as demo:
         gr.Markdown("# Food Customization Assistant")
-        gr.Markdown("Talk to the bot and customize your food preferences based on category.")
-
-        # Greeting Step
-        user_input = gr.Textbox(label="Your Message", placeholder="Type 'yes' or 'yeah' to begin.", lines=1)
-        bot_response = gr.Textbox(label="Bot Response", lines=2)
-        
-        # First interaction: Ask user if they want to customize food
-        user_input.submit(start_conversation, user_input, bot_response)
+        gr.Markdown("Talk to the bot and customize your food preferences.")
 
-        # Category Selection
-        category_dropdown = gr.Dropdown(
-            choices=["Veg", "Non-Veg", "Vegan", "Pasta & Noodles", "Breads & Baked Goods"], 
-            label="Select Food Category"
-        )
-        category_dropdown.change(select_category, category_dropdown, bot_response)
+        # Conversation Box
+        with gr.Chatbot() as chatbox:
+            pass
 
-        # Nutrition Preferences
-        nutrition_dropdown = gr.Dropdown(
-            choices=["Protein Rich", "Low Carbs", "Gluten-Free"], 
-            label="Select Nutrition Preference"
-        )
-        nutrition_dropdown.change(select_nutrition, nutrition_dropdown, bot_response)
+        # User input field
+        user_input = gr.Textbox(placeholder="Type your message here...", lines=1)
 
-        # Show Ingredients based on category & nutrition
-        ingredients_output = gr.Textbox(label="Ingredients List", lines=2)
-        ingredients_output.change(show_ingredients, [category_dropdown, nutrition_dropdown], ingredients_output)
+        # Submit button
+        submit_btn = gr.Button("Submit")
 
-        # Ingredient Selection
-        ingredient_dropdown = gr.Dropdown(label="Select Ingredient")
-        ingredient_dropdown.change(show_dishes, ingredient_dropdown, bot_response)
+        # Function for handling message submission
+        submit_btn.click(
+            chatbot_response,
+            inputs=[user_input, chatbox],
+            outputs=chatbox
+        )
 
-        # Start Gradio Interface
-        demo.launch()
+    demo.launch()
 
 if __name__ == "__main__":
     create_gradio_interface()