Tommy ai assistant

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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):
Get full code

Frequently Asked Questions

Domain-specific knowledge integration through the moderation prompt For example, a healthcare company could set strict guidelines for HIPAA compliance, while a marketing agency could configure it for more creative responses. Q3: What is the pricing model and ROI potential for implementing the Tommy AI Assistant?

The Tommy AI Assistant template provides value through: - One-time purchase with no recurring template costs - Pay-as-you-go model for AI API usage - Reduced training costs for new employees - Improved efficiency in customer support - Scalable team management without additional licensing fees

Organizations typically see ROI through reduced support costs and improved employee productivity within 3-6 months of implementation.

Q4: How can I modify the chat interface to add custom styling in the Tommy AI Assistant?

A: You can customize the chat interface by modifying the CSS in styles.css. Here's an example to create a custom chat bubble style:

```css .message-wrapper { margin-bottom: 16px; display: flex; flex-direction: column; }

.user-message .message-content { align-self: flex-end; background-color: #007bff; color: white; border-radius: 20px 20px 0 20px; padding: 12px; max-width: 80%; }

.ai-message .message-content { align-self: flex-start; background-color: #f0f0f0; border-radius: 20px 20px 20px 0; padding: 12px; max-width: 80%; } ```

Q5: How can I add a new API endpoint to handle custom actions in the Tommy AI Assistant?

A: You can add new API endpoints in the routes.py file. Here's an example of adding a custom action endpoint:

```python @app.route("/api/custom_action", methods=["POST"]) def custom_action(): try: # Get the action parameters from the request action_type = request.json.get("action_type") user_id = session['user']['email']

    # Perform the custom action
    if action_type == "analyze":
        # Add your custom analysis logic here
        result = perform_analysis(user_id)
        return jsonify({
            "status": "success",
            "data": result
        })
    else:
        return jsonify({
            "status": "error",
            "message": "Invalid action type"
        }), 400

except Exception as e:
    app.logger.error(f"Error in custom action: {str(e)}")
    return jsonify({
        "status": "error",
        "message": "An error occurred while processing your request"
    }), 500

```

Created: | Last Updated:

Ai assistant

I'll help you use this template code as a starting point for your own AI assistant application. Let me break down how to adapt and use this template.

Introduction

This template provides a complete AI assistant dashboard with user management, chat interface, and customizable AI model settings. It includes authentication, admin controls, and a clean user interface.

Getting Started

  • Click "Start with this Template" to begin working with the code
  • Replace your_logo.png in the static/img directory with your own logo
  • Update the title "AI Agent" in the templates to your preferred name

Test

  • Click the Test button to launch the application
  • The app will start and provide you with a server link

Using the Dashboard

Home Page

  • Customize AI settings:
  • Set custom instructions for the AI
  • Choose from available AI models
  • Adjust response temperature
  • Save changes to update AI behavior

Team Management

  • Manage admin access through:
  • Individual email addresses
  • Domain-wide access
  • Block/unblock admin users
  • First user becomes super admin

AI Chat Interface

  • Test AI responses in real-time
  • View chat history
  • Clear conversation history
  • See which AI model was used for each response

Customization Points

Update AI Models

In home.html, modify the model selection options:

html <select class="form-control custom-select" id="model_selection" name="model_selection"> <option value="your-model-1">Model 1</option> <option value="your-model-2">Model 2</option> </select>

Customize Styling

Modify static/css/styles.css to match your brand:

css :root { --primary-color: #your-color; --secondary-color: #your-color; }

Update Navigation

Edit _nav_items.html to customize menu items:

```html

```

The template provides a solid foundation for building an AI assistant interface with user management capabilities. You can extend it by adding more features or customizing the existing functionality to match your specific needs.



Template Benefits

  1. Customizable AI Chat Interface
  2. Provides a professional, user-friendly interface for interacting with various AI models (GPT-4, Claude, Gemini)
  3. Allows businesses to customize AI responses through temperature settings and custom instructions

  4. Enterprise-Grade Access Management

  5. Robust domain-based access control for managing team permissions
  6. Built-in blocking and unblocking capabilities for user management
  7. Secure authentication system with email domain verification

  8. Multi-Model AI Integration

  9. Supports multiple AI models (GPT-4, Claude 3, Gemini 1.5) in a single interface
  10. Easy switching between models for different use cases and cost optimization
  11. Centralized settings management for all AI models

  12. Team Collaboration Features

  13. Dedicated team management interface for adding/removing team members
  14. Role-based access control for administrators
  15. Domain-wide access management for enterprise deployment

  16. Professional Error Handling & UI

  17. Clean, modern interface with responsive design
  18. Comprehensive error handling with custom error pages
  19. Professional modal notifications and user feedback system
  20. Session management and secure logout functionality

Technologies

Streamline CSS Development with Lazy AI: Automate Styling, Optimize Workflows and More Streamline CSS Development with Lazy AI: Automate Styling, Optimize Workflows and More
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Flask Templates from Lazy AI – Boost Web App Development with Bootstrap, HTML, and Free Python Flask Flask Templates from Lazy AI – Boost Web App Development with Bootstrap, HTML, and Free Python Flask
Enhance HTML Development with Lazy AI: Automate Templates, Optimize Workflows and More Enhance HTML Development with Lazy AI: Automate Templates, Optimize Workflows and More
Streamline JavaScript Workflows with Lazy AI: Automate Development, Debugging, API Integration and More  Streamline JavaScript Workflows with Lazy AI: Automate Development, Debugging, API Integration and More

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Open Source LLM based Web Chat Interface

This app will be a web interface that allows the user to send prompts to open source LLMs. It requires to enter the openrouter API key for it to work. This api key is free to get on openrouter.ai and there are a bunch of free opensource models on openrouter.ai so you can make a free chatbot. The user will be able to choose from a list of models and have a conversation with the chosen model. The conversation history will be displayed in chronological order, with the oldest message on top and the newest message below. The app will indicate who said each message in the conversation. The app will show a loader and block the send button while waiting for the model's response. The chat bar will be displayed as a sticky bar at the bottom of the page, with 10 pixels of padding below it. The input field will be 3 times wider than the default size, but it will not exceed the width of the page. The send button will be on the right side of the input field and will always fit on the page. The user will be able to press enter to send the message in addition to pressing the send button. The send button will have padding on the right side to match the left side. The message will be cleared from the input bar after pressing send. The last message will now be displayed above the sticky input block, and the conversation div will have a height of 80% to leave space for the model selection and input fields. There will be some space between the messages, and the user messages will be colored in green while the model messages will be colored in grey. The input will be blocked when waiting for the model's response, and a spinner will be displayed on the send button during this time.

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