Shavx AI: Real Estate Chatbot

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import logging

from flask import Flask, render_template, session
from flask_session import Session
from gunicorn.app.base import BaseApplication
from abilities import apply_sqlite_migrations

from app_init import create_initialized_flask_app
from models import db

logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

# Flask app creation should be done by create_initialized_flask_app to avoid circular dependency problems.
app = create_initialized_flask_app()

# Configuring server-side session
app.config["SESSION_PERMANENT"] = False
app.config["SESSION_TYPE"] = "filesystem"
Session(app)

from abilities import llm
from flask import request, jsonify
Get full code

Frequently Asked Questions

How can Shavx AI benefit my real estate agency?

Shavx AI can significantly enhance your real estate agency's customer service and lead generation. By providing an AI-powered chatbot, Shavx AI offers 24/7 availability to answer potential clients' questions about properties, market trends, and general real estate inquiries. This constant availability can improve customer satisfaction, capture more leads, and free up your human agents to focus on high-value tasks. The chatbot's ability to provide tailored property recommendations based on user requirements can also help streamline the property search process for clients.

Can Shavx AI be customized to match my agency's branding?

Yes, Shavx AI is designed with customization in mind. The template uses a sleek, modern design with gradient backgrounds and can be easily adapted to match your agency's branding. You can modify the color scheme, logo, and messaging to align with your brand identity. For example, you can change the gradient colors in the CSS, update the logo and agency name in the header, and customize the chatbot's responses to reflect your agency's tone and style.

How does Shavx AI handle property data and updates?

Shavx AI integrates with a database to store and manage property information. The template includes a Property model in the models.py file, which allows you to easily add, update, or remove properties. The chatbot accesses this data to provide up-to-date information to users. You can implement automated processes to sync your property database with external listing services or your agency's main database to ensure the chatbot always has the most current information.

How can I extend Shavx AI's functionality to include more features?

Shavx AI is built on a Flask backend, making it highly extensible. You can add new features by creating additional routes in the main.py file and implementing corresponding frontend logic in the script.js file. For example, to add a feature that allows users to schedule property viewings, you could implement it like this:

In main.py: python @app.route("/schedule_viewing", methods=['POST']) def schedule_viewing(): property_id = request.json['property_id'] viewing_date = request.json['viewing_date'] # Logic to schedule the viewing # ... return jsonify({"message": "Viewing scheduled successfully"})

In script.js: javascript function scheduleViewing(propertyId, viewingDate) { fetch('/schedule_viewing', { method: 'POST', headers: { 'Content-Type': 'application/json', }, body: JSON.stringify({ property_id: propertyId, viewing_date: viewingDate }), }) .then(response => response.json()) .then(data => { // Handle the response console.log(data.message); }); }

How does Shavx AI ensure data privacy and security?

Shavx AI incorporates several security measures to protect user data and ensure privacy. The template uses Flask-Session for server-side session management, which helps prevent client-side tampering of session data. Additionally, the SQLite database is configured with foreign key constraints enabled for data integrity. To further enhance security, you should implement HTTPS, input validation, and proper authentication mechanisms. Here's an example of how you can add basic authentication to protect sensitive routes:

```python from functools import wraps from flask import request, abort

def require_api_key(view_function): @wraps(view_function) def decorated_function(args, kwargs): if request.headers.get('X-API-KEY') and request.headers.get('X-API-KEY') == 'your_secret_api_key': return view_function(args, kwargs) else: abort(401) return decorated_function

@app.route("/admin/properties", methods=['GET']) @require_api_key def get_all_properties(): properties = Property.query.all() # Return properties data return jsonify([prop.to_dict() for prop in properties]) ```

This example adds an API key check to protect admin routes, ensuring that only authorized users can access sensitive data or perform administrative actions in Shavx AI.

Created: | Last Updated:

AI-powered chatbot for real estate agencies with a user-friendly interface, tailored responses, and enhanced UI featuring gradient backgrounds and branding.

Here's a step-by-step guide for using the Shavx AI: Real Estate Chatbot template:

Introduction

The Shavx AI: Real Estate Chatbot template provides an AI-powered chatbot for real estate agencies. It features a user-friendly interface with gradient backgrounds and branding, tailored responses, and an enhanced UI. This chatbot can assist users with property inquiries, market trends, and general real estate questions.

Getting Started

To begin using this template, follow these steps:

  1. Click "Start with this Template" in the Lazy Builder interface.

  2. Press the "Test" button to deploy the application and launch the Lazy CLI.

Using the Chatbot

Once the application is deployed, you'll receive a dedicated server link to access the chatbot interface. The interface includes:

  • A header with the Shavx AI branding
  • A chat window where conversations are displayed
  • An input field for users to type their questions
  • A "Send" button to submit queries

Users can interact with the chatbot by:

  1. Typing their real estate-related questions into the input field
  2. Clicking the "Send" button or pressing Enter to submit the question
  3. Viewing the chatbot's response in the chat window

The chatbot can provide information about:

  • Available properties
  • Property details (price, location, bedrooms, bathrooms, square footage)
  • Market trends
  • General real estate inquiries

Customizing the Chatbot

To tailor the chatbot to your specific real estate agency:

  1. Modify the Property model in models.py to include any additional fields relevant to your listings.
  2. Update the sample properties in 002_add_sample_properties.sql to reflect your current listings.
  3. Adjust the prompt in the send_message function in main.py to include any specific instructions or information you want the AI to consider when responding to user queries.

Integrating with Your Website

To integrate this chatbot into your existing real estate website:

  1. Use the server link provided by Lazy to access the chatbot interface.
  2. Embed the chatbot interface into your website using an iframe or by creating a dedicated page that links to the chatbot URL.

For example, you could add an iframe to your website with:

```html

```

Replace YOUR_LAZY_APP_URL with the actual URL provided by Lazy after deployment.

By following these steps, you'll have a functional AI-powered real estate chatbot that can assist your clients with property inquiries and general real estate questions.



Here are 5 key business benefits for the Shavx AI Real Estate Chatbot template:

Template Benefits

  1. 24/7 Customer Service: The AI-powered chatbot provides round-the-clock assistance to potential clients, answering property-related queries and offering recommendations at any time, improving customer satisfaction and engagement.

  2. Efficient Lead Qualification: By interacting with users and understanding their preferences, the chatbot can effectively qualify leads, helping real estate agents focus on the most promising prospects and saving time on initial consultations.

  3. Personalized Property Recommendations: The chatbot's ability to filter and suggest properties based on user criteria enables personalized recommendations, increasing the likelihood of successful matches between clients and available listings.

  4. Scalable Client Interaction: As an AI-powered solution, the chatbot can handle multiple client interactions simultaneously, allowing real estate agencies to scale their customer service capabilities without proportionally increasing staff.

  5. Data-Driven Insights: The conversation history stored in the database provides valuable data on client preferences, popular property types, and common inquiries, enabling agencies to refine their marketing strategies and property portfolio based on actual customer interests.

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