Create app.py

app.py

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+import streamlit as st
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from pyngrok import ngrok
+import random
+import re
+
+# ✅ Set up ngrok
+ngrok.set_auth_token("xai-RrirCeSYWUT21ipAY6BjWr3jSEDmK8sA16S3EbGGUC4oWH1cyn3pfI0vIJg1D1ym3NfFkhUbDOeFmf3s")
+public_url = ngrok.connect(8501).public_url
+
+# ✅ Load AI Model
+model_name = "deepseek-ai/deepseek-llm-7b-chat"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(
+    model_name, torch_dtype=torch.float16, device_map="auto", offload_folder="offload_weights"
+)
+
+# 📌 Menu for chatbot
+menu = {
+    "meals": ["Grilled Chicken with Rice", "Beef Steak", "Salmon with Lemon Butter Sauce", "Vegetable Stir-Fry"],
+    "fast_foods": ["Cheeseburger", "Pepperoni Pizza", "Fried Chicken", "Hot Dog", "Tacos", "French Fries"],
+    "drinks": ["Coke", "Pepsi", "Lemonade", "Orange Juice", "Iced Coffee", "Milkshake"],
+    "sweets": ["Chocolate Cake", "Ice Cream", "Apple Pie", "Cheesecake", "Brownies", "Donuts"]
+}
+
+system_prompt = f"""
+You are OrderBot, a virtual restaurant assistant.
+You help customers order food from the following menu:
+
+🍽️ **Meals**: {', '.join(menu['meals'])}
+🍔 **Fast Foods**: {', '.join(menu['fast_foods'])}
+🥤 **Drinks**: {', '.join(menu['drinks'])}
+🍰 **Sweets**: {', '.join(menu['sweets'])}
+
+Rules:
+1️⃣ Always confirm the customer's order.
+2️⃣ Ask if they need anything else.
+3️⃣ Respond in a friendly and professional manner.
+"""
+
+def process_order(user_input):
+    """
+    Handles chatbot conversation and order processing.
+    """
+    responses = {
+        "greetings": ["Hello! How can I assist you today?", "Hey there! What would you like to order?", "Hi! Ready to place an order? 😊"],
+        "farewell": ["Goodbye! Have a great day! 👋", "See you next time!", "Take care!"],
+        "thanks": ["You're welcome! 😊", "Happy to help!", "Anytime!"],
+        "default": ["I'm not sure how to respond to that. Can I take your order?", "Interesting! Tell me more.", "I'm here to assist with your order."]
+    }
+
+    user_input = user_input.lower()
+
+    if any(word in user_input for word in ["hello", "hi", "hey"]):
+        return random.choice(responses["greetings"])
+    elif any(word in user_input for word in ["bye", "goodbye", "see you"]):
+        return random.choice(responses["farewell"])
+    elif any(word in user_input for word in ["thank you", "thanks"]):
+        return random.choice(responses["thanks"])
+
+    # AI-generated response
+    prompt = f"{system_prompt}\nUser: {user_input}\nOrderBot:"
+    inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
+    output = model.generate(**inputs, max_new_tokens=150)
+    raw_response = tokenizer.decode(output[0], skip_special_tokens=True)
+    
+    response = raw_response.split("OrderBot:")[-1].strip()
+    response = re.sub(r"Setting `pad_token_id`.*\n", "", response)
+
+    return response
+
+# 🎨 Streamlit UI
+st.title("🛒 OrderBot: AI Restaurant Assistant")
+st.write(f"🌍 **Public URL:** [{public_url}]({public_url}) (via ngrok)")
+
+# ℹ️ Display OrderBot Description
+st.markdown("""
+### 👋 Hey there, I am OrderBot!
+I am an **AI-driven assistant** powered by the **DeepSeek-7B Chat** model, designed for seamless natural language interaction.  
+I leverage **advanced machine learning** to process and respond to human input with **precision and efficiency**.  
+Let me take your order! 🍔🥤🍰
+""")
+
+# Chat History
+if "messages" not in st.session_state:
+    st.session_state.messages = []
+
+# Display previous chat messages
+for message in st.session_state.messages:
+    with st.chat_message(message["role"]):
+        st.write(message["content"])
+
+# User Input
+user_input = st.chat_input("Type your message here...")
+
+if user_input:
+    st.session_state.messages.append({"role": "user", "content": user_input})
+    with st.chat_message("user"):
+        st.write(user_input)
+
+    response = process_order(user_input)
+
+    st.session_state.messages.append({"role": "assistant", "content": response})
+    with st.chat_message("assistant"):
+        st.write(response)