from chatterbot import ChatBot

from chatterbot.trainers import ChatterBotCorpusTrainer

# Create a chatbot instance

chatbot = ChatBot('PropertyBot')

# Create a new trainer for the chatbot

trainer = ChatterBotCorpusTrainer(chatbot)

# Train the chatbot on English language data

trainer.train('chatterbot.corpus.english')

# Sample property data

properties = [

{"type": "Apartment", "location": "City Center", "price": 2000},

{"type": "House", "location": "Suburb", "price": 3000},

# Add more property data as needed

]

# Define a function to search for properties based on user preferences

def search_properties(user_preferences):

# Implement your property search logic here

# For simplicity, this example returns all properties

return properties

# Define a function to recommend properties based on user preferences

def recommend_properties(user_preferences):

# Implement your property recommendation logic here

# For simplicity, this example returns a random property

import random

return random.choice(properties)

# Main chat loop

while True:

user_input = input("You: ")

# Exit the loop if the user types 'exit'

if user_input.lower() == 'exit':

print("PropertyBot: Goodbye!")

break

# Get the chatbot's response

response = chatbot.get_response(user_input)

# If the user asks to search for properties

if "search" in user_input.lower():

# Implement property search logic

user_preferences = {} # Placeholder for user preferences

search_results = search_properties(user_preferences)

print("PropertyBot: Here are the search results:")

for prop in search_results:

print(f"{prop['type']} in {prop['location']} for ${prop['price']}/month")

# If the user asks for property recommendations

elif "recommend" in user_input.lower():

# Implement property recommendation logic

user_preferences = {} # Placeholder for user preferences

recommended_property = recommend_properties(user_preferences)

print("PropertyBot: I recommend the following property:")

print(f"{recommended_property['type']} in {recommended_property['location']} for ${recommended_property['price']}/month")

else:

# Default response from the chatbot

print("PropertyBot:", response)