# Import necessary libraries
import hubspot
import langchain
import openai
import streamlit

# Define function to analyze customer data using Langchain
def analyze_customer_data(customer_data):
    langchain.analyze(customer_data)
    # returns analyzed data

# Define function to send personalized appointment reminders via email and text message
def send_appointment_reminder(customer_email, customer_phone, appt_time):
    # Create message using OpenAI language model
    message = openai.generate_message(customer_name, appt_time)
    # Send email using Hubspot API
    hubspot.send_email(customer_email, message)
    # Send text message using Hubspot API
    hubspot.send_text(customer_phone, message)

# Call analyze_customer_data function on customer data
analyzed_data = analyze_customer_data(customer_data)

# Loop through customers in analyzed_data
for customer in analyzed_data:
    # Check if customer has an appointment scheduled
    if customer['appointment_time'] != None:
        # Send personalized appointment reminder to customer via email and text message
        send_appointment_reminder(customer['email'], customer['phone'], customer['appointment_time'])

langchain.analyze
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