by meow_18838

WebChatify

Test this app for free
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Test this app for free
66 
import logging

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

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

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

from abilities import llm_prompt
from flask import request, jsonify

@app.route("/")
def root_route():
    return render_template("template.html")

@app.route("/send_message", methods=['POST'])
def send_message():
Get full code

Frequently Asked Questions

How can WebChatify benefit my business?

WebChatify can significantly enhance your business's customer engagement and support capabilities. By integrating this chat application into your website, you can provide instant, AI-powered assistance to your visitors. This can help in analyzing website content, answering customer queries, and even guiding potential clients through your products or services. The ability to discuss and analyze any website content makes WebChatify a versatile tool for market research, competitor analysis, and customer education.

Can WebChatify be customized to match my brand's look and feel?

Absolutely! WebChatify is built with customization in mind. The template uses Tailwind CSS, which makes it incredibly easy to adjust the styling to match your brand. You can modify colors, fonts, and layout elements in the template.html file. For instance, to change the primary color of the send button, you could update the following line:

html <button id="sendButton" class="w-full mt-2 bg-blue-500 hover:bg-blue-700 text-white font-bold py-2 px-4 rounded">

to:

html <button id="sendButton" class="w-full mt-2 bg-brand-500 hover:bg-brand-700 text-white font-bold py-2 px-4 rounded">

Just make sure to define your brand colors in your Tailwind configuration.

How can I integrate WebChatify with my existing customer relationship management (CRM) system?

WebChatify can be integrated with your CRM system to provide a seamless customer support experience. You can modify the send_message route in main.py to log conversations or important interactions to your CRM. This could involve making API calls to your CRM system whenever a significant interaction occurs. By doing so, you can track customer inquiries, analyze common questions, and improve your overall customer service strategy based on the data collected through WebChatify.

How does WebChatify handle user sessions and maintain context during conversations?

WebChatify uses Flask-Session to manage user sessions server-side. This allows the application to maintain context throughout a conversation. In the main.py file, you'll see the following code:

python app.config["SESSION_PERMANENT"] = False app.config["SESSION_TYPE"] = "filesystem" Session(app)

This sets up session handling. Throughout the conversation, the application stores and retrieves context using the session object:

python session['history'].append({"user": user_message, "bot": response})

This approach allows WebChatify to provide coherent, context-aware responses even in long conversations.

What security measures does WebChatify implement to protect user data?

WebChatify incorporates several security measures to protect user data. Firstly, it uses server-side sessions, which are more secure than client-side storage for sensitive information. The application also uses HTTPS (assuming you set it up on your server) to encrypt data in transit. To further enhance security, you should implement additional measures such as input validation, output encoding, and regular security audits. It's also crucial to keep all dependencies updated, as specified in the requirements.txt file. Remember, while WebChatify provides a solid foundation, it's important to conduct a thorough security review before deploying it in a production environment.

Created: | Last Updated:

WebChatify: A web-based chat application that allows users to discuss and analyze website content using the llm system and a user-friendly interface powered by tailwind.

Introduction to the WebChatify Template

Welcome to the WebChatify template guide! This template provides you with a fully functional web-based chat application that allows users to discuss and analyze website content. The chatbot is powered by an llm system, and the user interface is designed with Tailwind CSS for a sleek and modern look. This template is perfect for builders who want to create a chat service without worrying about the complexities of deployment and environment setup.

Getting Started

To begin using the WebChatify template, simply click on "Start with this Template" in the Lazy Builder interface. This will pre-populate the code in the Lazy Builder, so you won't need to copy or paste any code manually.

Test: Deploying the App

Once you have the template loaded, press the "Test" button to start the deployment process. The Lazy CLI will handle the deployment, and you won't need to install any libraries or set up your environment. The deployment process is managed entirely by Lazy.

Using the WebChatify App

After deployment, you will be provided with a dedicated server link to access the chat application. The interface includes a chat window where users can type messages and receive responses from the chatbot. The chat history is displayed in the window, allowing for a seamless conversation experience.

To interact with the chatbot:

  • Type your message into the input field labeled "Type your message...".
  • Click the "Send" button or press "Enter" to submit your message.
  • The chatbot will process your message and respond accordingly.

If your message contains a URL, the chatbot will fetch content from the website and provide an analysis or summary as part of its response.

Integrating the WebChatify App

If you wish to integrate the WebChatify chat service into another service or frontend, you can use the server link provided by Lazy after deployment. This link can be added to external tools or platforms where you want the chat functionality to be accessible.

For example, if you want to embed the chatbot into a website, you can create an iframe or a web component that points to the server link. This will allow users to interact with the chatbot directly from your website.

Here is a sample code snippet that you can use to embed the chatbot into an HTML page:

<iframe src="YOUR_SERVER_LINK" width="350" height="500"></iframe> Replace "YOUR_SERVER_LINK" with the actual link provided by Lazy.

Remember, all the steps listed above are mandatory to run and integrate the WebChatify template. Follow these instructions carefully to ensure a smooth setup and integration process.

If you encounter any issues or have questions, refer to the documentation provided in the code or reach out for support through the Lazy platform.



Here are 5 key business benefits for the WebChatify template:

Template Benefits

  1. Enhanced Customer Support: Businesses can integrate this chatbot into their websites to provide instant, AI-powered support for customer inquiries about their products or services, reducing the load on human customer service representatives.

  2. Improved Content Analysis: Marketing teams can use this tool to quickly analyze competitor websites or industry news, getting AI-generated insights and summaries without manually reading through entire web pages.

  3. Efficient Research and Development: R&D teams can leverage this chatbot to rapidly gather and process information from multiple web sources, accelerating their research process and idea generation.

  4. Interactive Learning Platform: Educational institutions can adapt this template to create an AI-powered study assistant, helping students analyze and understand complex web content more effectively.

  5. SEO and Digital Marketing Aid: Digital marketers can use this tool to analyze website content, generate keyword ideas, and get AI-assisted suggestions for improving their own web content and SEO strategies.

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