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test
This video demonstrates how to use the test template.
import logging
from gunicorn.app.base import BaseApplication
from app_init import create_initialized_flask_app
# Flask app creation should be done by create_initialized_flask_app to avoid circular dependency problems.
app = create_initialized_flask_app()
# Setup logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
class StandaloneApplication(BaseApplication):
def __init__(self, app, options=None):
self.application = app
self.options = options or {}
super().__init__()
def load_config(self):
# Apply configuration to Gunicorn
for key, value in self.options.items():
if key in self.cfg.settings and value is not None:
self.cfg.set(key.lower(), value)
def load(self):Frequently Asked Questions
What are the main business applications for the AI Agent dashboard?
The AI Agent dashboard is designed for businesses looking to implement AI-powered customer service or support solutions. It allows companies to customize their AI chatbot settings, manage team access, and simulate conversations to test the AI's responses. This makes it ideal for businesses in e-commerce, customer support, or any industry seeking to enhance their customer interaction capabilities with AI technology.
How does the AI Agent dashboard help improve customer service efficiency?
The AI Agent dashboard improves customer service efficiency by allowing businesses to fine-tune their AI chatbot's responses. Through the dashboard, companies can adjust the AI model selection, response temperature, and provide custom instructions. This level of customization ensures that the AI agent can handle a wide range of customer inquiries accurately and efficiently, reducing the workload on human customer service representatives and providing 24/7 support capabilities.
Can the AI Agent dashboard be integrated with existing customer relationship management (CRM) systems?
While the current template doesn't show direct CRM integration, the AI Agent dashboard is built with extensibility in mind. Businesses can potentially integrate it with their existing CRM systems by extending the Flask application. This would involve adding new routes and database models to sync customer data between the AI Agent and the CRM, enabling a more comprehensive view of customer interactions and history.
How can I add a new API endpoint to the AI Agent dashboard for custom functionality?
To add a new API endpoint to the AI Agent dashboard, you would modify the routes.py file. Here's an example of how you might add a new endpoint for retrieving chat statistics:
```python @app.route("/api/chat_stats", methods=["GET"]) def get_chat_stats(): try: user_id = session['user']['email'] total_chats = ChatMessage.query.filter_by(user_id=user_id).count() ai_responses = ChatMessage.query.filter_by(user_id=user_id, is_ai=True).count()
return jsonify({
"status": "success",
"total_chats": total_chats,
"ai_responses": ai_responses
})
except Exception as e:
app.logger.error(f"Error retrieving chat stats: {str(e)}")
return jsonify({"status": "error", "message": "An error occurred while retrieving chat statistics"}), 500
```
This new endpoint would allow users to retrieve statistics about their chat history.
How can I modify the AI Agent dashboard to support multiple languages?
To support multiple languages in the AI Agent dashboard, you would need to implement internationalization (i18n). Here's a basic example of how you might start this process using Flask-Babel:
Created: Thu, Jan 30, 2025, 5:00 AM | Last Updated: Thu, Jan 30, 2025, 5:00 AM
Here's a step-by-step guide for using this template as a starting point for your project:
Introduction to the Template
This template provides a foundation for building a web-based AI chat application with user authentication and admin management features. It includes a Flask backend, SQLite database, and a responsive frontend using Bootstrap and custom CSS.
Getting Started
-
Click "Start with this Template" to begin working with this code in the Lazy Builder interface.
-
Press the "Test" button to initiate the deployment process. This will launch the Lazy CLI and start the application.
Using the App
Once the app is deployed, you can access it through the provided server link. The application includes the following features:
- User authentication with Google Sign-In
- Admin dashboard for managing settings and users
- AI chat simulator for testing chatbot configurations
- Responsive design for desktop and mobile devices
Accessing the Admin Dashboard
- Log in using your Google account.
- If you're the first user, you'll automatically be granted admin access.
- Navigate to the "Team" page to manage admin access and domain restrictions.
Configuring Chatbot Settings
- On the home page, you can adjust the following settings:
- Chatbot Instructions: Customize the AI's behavior
- AI Model Selection: Choose from various AI models
-
AI Response Temperature: Adjust the creativity of responses
-
Click "Save Changes" to update the settings.
Using the AI Chat Simulator
- Navigate to the "AI Chat" page.
- Type your message in the input field and press Enter or click the send button.
- The AI will respond based on your configured settings.
Managing Team Access
- Go to the "Team" page.
- To add individual admin access:
- Click "Add New Admin"
- Enter the admin's email address
- To allow domain-wide access:
- Click "Add New Email Ending"
- Enter the domain (e.g., "example.com")
- Use the "Block" or "Delete" buttons to manage existing admin access.
Integrating the App
This template is designed to be a standalone web application and doesn't require integration with external services beyond the initial Google Sign-In setup. However, you can extend its functionality by:
- Customizing the AI models and prompts
- Adding additional features to the admin dashboard
- Integrating with other services using the Flask backend
Remember to thoroughly test your application after making any modifications to ensure all features are working as expected.
Here are 5 key business benefits of this AI agent dashboard template:
Template Benefits
-
Customizable AI Chat Interface: Provides an interactive chat simulator to test and refine AI responses, allowing businesses to optimize their chatbot's performance before deployment.
-
Flexible Admin Management: Offers robust tools for managing admin access, including domain-level permissions and individual admin controls, enhancing security and access control.
-
Configurable AI Model Settings: Allows easy adjustment of AI model parameters like temperature and model selection, enabling businesses to fine-tune the AI's behavior for different use cases.
-
Secure Authentication System: Implements a comprehensive authentication system with features like allowed email domains and blocklists, ensuring only authorized personnel can access the dashboard.
-
Scalable Flask Architecture: Built on a well-structured Flask application with Gunicorn integration, providing a solid foundation for scaling the application as business needs grow.
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