Update app.py

app.py

@@ -5,18 +5,29 @@ from gtts import gTTS
 from datetime import datetime
 from openpyxl import Workbook, load_workbook
 
-from langchain_google_genai import ChatGoogleGenerativeAI
+# ========== Install dependencies if missing ==========
+try:
+    import google.generativeai as genai
+except ImportError:
+    import subprocess
+    subprocess.run(["pip", "install", "google-generativeai", "langchain", "langchain-community", "tiktoken"], check=True)
+    import google.generativeai as genai
+
+from langchain.chat_models import ChatGoogleGenerativeAI
 from langchain.memory import ConversationBufferMemory
 from langchain.chains import ConversationChain
+from langchain.prompts import PromptTemplate
 
-# ========== SETUP ==========
+# ========== Gemini API Setup ==========
+genai.configure(api_key="AIzaSyBJFmohAmhmqXQlM3fVxj8MLegVb26kyJk") 
 
-# Google Gemini configuration
-os.environ["GOOGLE_API_KEY"] = "AIzaSyBJFmohAmhmqXQlM3fVxj8MLegVb26kyJk"  
-llm = ChatGoogleGenerativeAI(model="gemini-1.5-flash", temperature=0.7)
-memory = ConversationBufferMemory()
-conversation = ConversationChain(llm=llm, memory=memory)
+llm = ChatGoogleGenerativeAI(
+    model="gemini-1.5-flash-latest",
+    temperature=0.7,
+    convert_system_message_to_human=True
+)
 
+# ========== Menu ==========
 MENU = {
     "Cheeseburger": 5.99,
     "Fries": 2.99,
@@ -26,12 +37,9 @@ MENU = {
     "Salad": 6.99
 }
 
-chat_history = []
-order = []
-customer_name = ""
-
 # ========== Excel Setup ==========
 EXCEL_FILE = "orders.xlsx"
+
 def setup_excel():
     if not os.path.exists(EXCEL_FILE):
         wb = Workbook()
@@ -54,8 +62,8 @@ def save_to_excel(name, items):
 
 # ========== TTS ==========
 def clean_text(text):
-    text = re.sub(r"\*\*(.*?)\*\*", r"\1", text)  # remove **bold**
-    text = re.sub(r"Bot\s*:\s*", "", text, flags=re.IGNORECASE)  # remove "Bot:" label
+    text = re.sub(r"\*\*(.*?)\*\*", r"\1", text)
+    text = re.sub(r"Bot\s*:\s*", "", text, flags=re.IGNORECASE)
     return text.strip()
 
 def speak(text, filename="response.mp3"):
@@ -64,44 +72,87 @@ def speak(text, filename="response.mp3"):
     tts.save(filename)
     return filename
 
-# ========== Handler ==========
-def handle_chat(user_input):
-    global customer_name, order
-
-    bot_reply = conversation.predict(input=user_input)
+# ========== LangChain Memory & Prompt ==========
+memory = ConversationBufferMemory()
 
-    # Extract name
-    if "my name is" in user_input.lower():
-        customer_name = user_input.split("my name is")[-1].strip().split()[0].title()
+custom_template = """
+You are a friendly and professional restaurant assistant at 'Systaurant'.
+
+Here is the menu:
+Cheeseburger: $5.99
+Fries: $2.99
+Coke: $1.99
+Pizza: $12.99
+Chicken Wings: $7.99
+Salad: $6.99
+
+Rules:
+- If name not known, ask for it.
+- If menu is requested, show it.
+- Extract item names and quantities.
+- When user is done, say 'Order summary' and ask 'Confirm?'.
+- If confirmed, generate order ID.
+- Keep tone friendly and human.
+- Don't prefix messages with "Bot:".
+
+{history}
+Customer: {input}
+Bot:"""
+
+prompt = PromptTemplate(input_variables=["history", "input"], template=custom_template)
+
+conversation = ConversationChain(
+    llm=llm,
+    memory=memory,
+    prompt=prompt
+)
+
+# ========== Chat Logic ==========
+chat_order = []
+customer_name = ""
 
-    # Extract items
+def extract_order_info(text):
+    items = []
     for item in MENU:
-        if item.lower() in user_input.lower():
+        if item.lower() in text.lower():
             qty = 1
-            for word in user_input.lower().split():
+            for word in text.split():
                 if word.isdigit():
                     qty = int(word)
                     break
-            order.append((item, qty))
+            items.append((item, qty))
+    return items
+
+def handle_chat(user_input):
+    global chat_order, customer_name
+
+    response = conversation.predict(input=user_input)
+
+    # Detect name
+    if "my name is" in user_input.lower():
+        customer_name = user_input.split("my name is")[-1].strip().split()[0].title()
+
+    # Add items
+    chat_order += extract_order_info(user_input)
 
-    # Confirm order
+    # Confirm and save order
     if "confirm" in user_input.lower() or "yes" in user_input.lower():
-        if customer_name and order:
-            order_id = save_to_excel(customer_name, order)
-            bot_reply += f"\n✅ Your order ID is {order_id}. Thank you for ordering from Saad's Restaurant!"
+        if customer_name and chat_order:
+            order_id = save_to_excel(customer_name, chat_order)
+            response += f"\n✅ Your order ID is {order_id}. Thank you for ordering!"
 
-    audio_file = speak(bot_reply)
-    return bot_reply, audio_file
+    audio_path = speak(response)
+    return response, audio_path
 
 # ========== Gradio UI ==========
 gr.Interface(
     fn=handle_chat,
-    inputs=gr.Textbox(label="👤 You", placeholder="Type your order..."),
+    inputs=gr.Textbox(label="👤 You", placeholder="Type your message..."),
     outputs=[
-        gr.Textbox(label="🤖 Bot Response"),
-        gr.Audio(label="🔊 Speaking", autoplay=True)
+        gr.Textbox(label="🤖 Bot"),
+        gr.Audio(label="🔊 Response", autoplay=True)
     ],
     title="🍔 SysTaurant Voice Bot (LangChain + Gemini)",
-    description="Chat with the voice bot to place your order.",
+    description="Smart voice ordering assistant with memory and Excel logging.",
     theme="soft"
 ).launch(share=True)