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import re
import gradio as gr
import vanna as vn
from groq import Groq
from vanna.remote import VannaDefault
# Set up Vanna.ai and Groq client as before
MY_VANNA_MODEL = "llama3-8b"
vn = VannaDefault(model=MY_VANNA_MODEL, api_key='30efac58cfee46d1967e28b8d6bdf5db')
vn.connect_to_mssql(odbc_conn_str=r'DRIVER={ODBC Driver 17 for SQL Server};SERVER=YISC1100715LT\SQLEXPRESS;DATABASE=master;Trusted_Connection=yes;') # Connect to your database
# Set up Groq client
groq_client = Groq(api_key="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")
def get_order_status(order_number):
sql = f"SELECT know_history.status FROM know_history WHERE know_history.erpordernumber = {order_number};"
result = vn.run_sql(sql)
# if result and len(result) > 0:
# return result['STATUS']
return result['status']
def generate_response(user_input):
# Check for order number in the input
order_match = re.search(r'#?(\d{5})', user_input)
if order_match:
order_number = order_match.group(1)
status = get_order_status(order_number)
# if status:
# Use Groq to generate a conversational response
prompt = f"""Given an order status '{status}' for order number {order_number},
generate a friendly, conversational response to the customer's query: "{user_input}".
The response should be informative and reassuring."""
chat_completion = groq_client.chat.completions.create(
messages=[
{
"role": "system",
"content": "You are a helpful customer service chatbot for an e-commerce company."
},
{
"role": "user",
"content": prompt,
}
],
model="llama3-8b-8192",
max_tokens=150,
temperature=0.7,
)
return chat_completion.choices[0].message.content.strip()
# else:
# return f"I'm sorry, but I couldn't find any information for order #{order_number}. Could you please check if the order number is correct?"
else:
# Handle general queries
prompt = f"""As a customer service chatbot for an e-commerce company,
provide a helpful response to the following customer query: "{user_input}"."""
chat_completion = groq_client.chat.completions.create(
messages=[
{
"role": "system",
"content": "You are a helpful customer service chatbot for an e-commerce company."
},
{
"role": "user",
"content": prompt,
}
],
model="llama3-8b-8192",
max_tokens=150,
temperature=0.7,
)
return chat_completion.choices[0].message.content.strip()
def chat_interface(message, history):
response = generate_response(message)
return response
iface = gr.ChatInterface(
chat_interface,
title="E-Commerce Customer Service Chatbot",
description="Ask about your order status or any other questions!",
examples=[
"Where is my order #12345?",
"What is the status of my order #67890?",
"How can I track my order?",
"Can I change my shipping address?",
"What's your return policy?"
]
)
if __name__ == "__main__":
iface.launch() |