by UnityAI
AI Web Chatbot
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
Frequently Asked Questions
What is the Mistral AI Web Chatbot, and how can businesses benefit from it?
The Mistral AI Web Chatbot is a public chatbot template that leverages Mistral AI and LangChain technologies to provide user-friendly interactions without requiring login. Businesses can benefit from this template by quickly deploying an AI-powered chatbot on their websites to enhance customer engagement, provide 24/7 support, and gather valuable customer insights. The template's ease of use and lack of login requirements make it ideal for businesses looking to improve their online presence and customer service capabilities.
How customizable is the Mistral AI Web Chatbot for different industries?
The Mistral AI Web Chatbot is highly customizable to suit various industries. Businesses can tailor the chatbot's responses, appearance, and functionality to align with their specific needs. For example, an e-commerce company could customize the chatbot to handle product inquiries and provide recommendations, while a healthcare provider could adapt it to schedule appointments and answer common medical questions. The template's flexibility allows for easy integration of industry-specific knowledge and workflows.
What are the potential cost savings associated with implementing the Mistral AI Web Chatbot?
Implementing the Mistral AI Web Chatbot can lead to significant cost savings for businesses. By automating customer interactions, companies can reduce the workload on human customer service representatives, potentially lowering staffing costs. Additionally, the chatbot's ability to handle multiple conversations simultaneously can improve efficiency and reduce response times, leading to higher customer satisfaction and potentially increased sales. The template's public nature and lack of login requirements also mean reduced development and maintenance costs compared to more complex, authenticated systems.
How can I modify the chat interface of the Mistral AI Web Chatbot?
The chat interface of the Mistral AI Web Chatbot can be easily modified by editing the HTML and CSS in the template.html
file. For example, to change the color scheme of the chat messages, you can update the CSS classes in the script.js
file. Here's an example of how to modify the user and bot message styles:
```javascript // In script.js userMessage.className = 'p-4 my-3 text-right bg-gradient-to-r from-green-600 to-green-800 rounded-lg shadow-md message-fade-in transform hover:scale-[1.02] transition-all duration-300';
botMessage.className = 'p-4 my-3 text-left bg-gradient-to-r from-yellow-600 to-yellow-800 rounded-lg shadow-md message-fade-in transform hover:scale-[1.02] transition-all duration-300'; ```
This change would update the user messages to have a green gradient and the bot messages to have a yellow gradient.
How can I extend the Mistral AI Web Chatbot's functionality to include database interactions?
To extend the Mistral AI Web Chatbot's functionality to include database interactions, you can modify the main.py
file to add new routes and database operations. Here's an example of how you might add a simple function to store user feedback in a database:
```python from models import db, Feedback
@app.route("/store_feedback", methods=['POST']) def store_feedback(): try: feedback_text = request.json['feedback'] new_feedback = Feedback(text=feedback_text) db.session.add(new_feedback) db.session.commit() return jsonify({"message": "Feedback stored successfully"}), 200 except Exception as e: logger.error(f"Error storing feedback: {str(e)}") return jsonify({"message": "Error storing feedback"}), 500 ```
You would also need to create a corresponding Feedback
model in the models.py
file:
python
class Feedback(db.Model):
id = db.Column(db.Integer, primary_key=True)
text = db.Column(db.Text, nullable=False)
created_at = db.Column(db.DateTime, default=db.func.current_timestamp())
This extension allows the Mistral AI Web Chatbot to store user feedback in a database, enabling businesses to collect and analyze user interactions for continuous improvement.
Created: | Last Updated:
Here's a step-by-step guide on how to use the Mistral AI Web Chatbot template:
Introduction
This template provides a web-based chatbot powered by Mistral AI and LangChain. It offers a user-friendly interface for public interactions without requiring login. The chatbot uses advanced language models to provide intelligent responses to user queries.
Getting Started
To begin using this template:
- Click the "Start with this Template" button in the Lazy Builder interface.
Test the Application
Once you've started with the template:
- Click the "Test" button in the Lazy Builder interface.
- This action will initiate the deployment of your app and launch the Lazy CLI.
Using the Chatbot
After the deployment is complete, Lazy will provide you with a dedicated server link to access your chatbot. Here's how to use it:
- Open the provided link in your web browser.
- You'll see a chat interface with a message input box at the bottom.
- Type your message into the input box and press Enter or click the send button.
- The chatbot will process your message and provide a response.
- Continue the conversation by sending more messages as needed.
Features of the Chatbot
The chatbot includes several notable features:
- Persistent conversation history: The chat maintains a history of the last 10 messages (5 user, 5 chatbot) to provide context for responses.
- Animated typing indicator: When the chatbot is processing a response, you'll see a "Thinking" animation.
- Responsive design: The interface is designed to work well on both desktop and mobile devices.
- Gradient background: The chat window features an animated gradient background for visual appeal.
Customization Options
While not required to run the template, you may want to customize certain aspects:
- Update the chatbot's name: You can modify the "AI Chatbot" title in the
template.html
file. - Adjust the styling: The template uses Tailwind CSS for styling. You can modify classes in the HTML to change colors, sizes, or layouts.
- Modify the LLM model: In
main.py
, you can change themodel
parameter in thellm()
function call to use a different language model if desired.
Remember, these customizations are optional and not necessary for the basic functioning of the chatbot.
By following these steps, you'll have a fully functional AI-powered web chatbot up and running, ready to engage with users and provide intelligent responses to their queries.
Here are 5 key business benefits for this Mistral AI Web Chatbot template:
Template Benefits
-
Instant Customer Support: Provide 24/7 automated customer service, reducing response times and improving customer satisfaction without the need for human agents.
-
Cost-Effective Scalability: Handle multiple user inquiries simultaneously without additional staffing costs, allowing businesses to scale their support operations efficiently.
-
Consistent Brand Voice: Maintain a uniform brand personality and messaging across all customer interactions, ensuring a cohesive user experience.
-
Data Collection and Insights: Gather valuable user data and frequently asked questions, which can be analyzed to improve products, services, and marketing strategies.
-
Seamless Integration: Easily integrate this chatbot into existing websites or applications, enhancing user engagement and providing an additional channel for customer interaction without requiring significant development resources.