Browser-use AI Agent Prompt Manager

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import logging
from gunicorn.app.base import BaseApplication
from app_init import create_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):
        return self.application

if __name__ == "__main__":
Get full code

Created: | Last Updated:

Setup instructions here: https://docs.google.com/document/d/1dB8JCJA6wecU5VbtVZ417V2gkKFFTHO5wav_XPLgUeQ/edit?tab=t.0#heading=h.1m6ups7md5vv Web application for managing prompts to AI Agents that work in the browser by integrating user-specific details into a formatted output.

To use this code template for a Browser-use AI Agent Prompt Manager, here's a step-by-step guide:

  1. First, ensure you have the required directory structure: your_project/ ├── static/ │ ├── css/ │ │ └── styles.css │ └── js/ │ ├── home.js │ ├── settings.js │ └── task_generator.js ├── templates/ │ ├── partials/ │ │ └── _header.html │ ├── 404.html │ ├── 500.html │ ├── home.html │ ├── settings.html │ └── task_generator.html ├── migrations/ │ ├── 000_example.sql │ ├── 001_create_settings_table.sql │ └── 002_add_continuous_run_column.sql ├── abilities.py ├── app_init.py ├── main.py ├── models.py ├── routes.py └── requirements.txt

  2. Create the abilities.py file with a basic LLM function and migration handler:

```python import os import logging

def llm(prompt, response_schema, image_url=None, model="gpt-4", temperature=0.7): # Add your LLM implementation here pass

def apply_sqlite_migrations(engine, model, migrations_dir): # Add your migration implementation here pass ```

  1. Install dependencies: bash pip install -r requirements.txt

  2. Run the application: bash python main.py

The template provides:

  • A modern UI with Bootstrap styling
  • Settings management for AI agent configuration
  • Task generation interface
  • Database migrations for SQLite
  • RESTful API endpoints
  • Error handling pages

Key features:

  • Settings persistence
  • Task prompt generation
  • Version history
  • Dynamic prompt templating
  • Browser configuration
  • LLM integration

To customize:

  1. Modify the HTML templates to match your branding
  2. Update the CSS in styles.css
  3. Implement the LLM function in abilities.py
  4. Add your own database migrations as needed
  5. Extend the Settings model for additional fields
  6. Add new routes as required

The application will run on http://localhost:8080 by default.



Template Benefits

  1. Streamlined AI Agent Management
  2. Centralizes configuration and management of AI agents that operate in web browsers
  3. Reduces setup time and eliminates manual prompt engineering for each new use case
  4. Enables consistent prompt formatting across multiple Twitter automation tasks

  5. Enhanced Social Media Automation

  6. Facilitates intelligent Twitter engagement through customized AI responses
  7. Maintains brand voice consistency while allowing personalized interactions
  8. Scales social media presence without compromising authenticity

  9. Flexible Configuration System

  10. Provides granular control over AI agent behavior, browser settings, and LLM parameters
  11. Supports multiple agent configurations with version history tracking
  12. Allows quick restoration of previous successful settings

  13. Business Process Integration

  14. Seamlessly incorporates business-specific details and customer profiles into AI interactions
  15. Generates task descriptions tailored to company objectives and target audience
  16. Maintains audit trails of AI agent activities and performance

  17. Risk Management & Compliance

  18. Implements structured error handling and monitoring capabilities
  19. Maintains detailed logs of AI agent actions for compliance purposes
  20. Provides controls to ensure AI responses align with business guidelines and tone

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