Chat Analytics Dashboard

A Django application that creates an analytics dashboard for chat session data. The application allows different companies to have their own dashboards and view their own data.

Features

• Multi-company support with user authentication
• CSV file upload and processing
• Interactive dashboard with charts and visualizations
• Detailed data views for chat sessions
• Search functionality to find specific chat sessions
• Admin interface for managing users and companies
• Responsive design using Bootstrap 5

Requirements

• Python 3.13+
• Django 5.0+
• PostgreSQL (optional, SQLite is fine for development)
• Other dependencies listed in pyproject.toml

Setup

Local Development

1. Clone the repository:

   git clone <repository-url>
   cd dashboard_project
   

2. Create a virtual environment and activate it:

   uv venv
   source .venv/bin/activate  # On Windows: .venv\Scripts\activate
   

3. Install dependencies:

   uv pip install -r requirements.txt
   

4. Run migrations:

   uv run python manage.py makemigrations
   uv run python manage.py migrate
   

5. Create a superuser:

   uv run python manage.py createsuperuser
   

6. Run the development server:

   uv run python manage.py runserver
   

7. Access the application at http://127.0.0.1:8000/

Using Docker

1. Clone the repository:

   git clone <repository-url>
   cd dashboard_project
   

2. Build and run with Docker Compose:

   docker-compose up -d --build
   

3. Create a superuser:

   docker-compose exec web python manage.py createsuperuser
   

4. Access the application at http://localhost/

Usage

1. Login as the superuser you created.
2. Go to the admin interface (http://localhost/admin/) and create companies and users.
3. Assign users to companies.
4. Upload CSV files for each company.
5. View the analytics dashboard.

CSV File Format

The CSV file should contain the following columns:

• session_id: Unique identifier for the chat session
• start_time: When the session started (datetime)
• end_time: When the session ended (datetime)
• ip_address: IP address of the user
• country: Country of the user
• language: Language used in the conversation
• messages_sent: Number of messages in the conversation (integer)
• sentiment: Sentiment analysis of the conversation (string)
• escalated: Whether the conversation was escalated (boolean)
• forwarded_hr: Whether the conversation was forwarded to HR (boolean)
• full_transcript: Full transcript of the conversation (text)
• avg_response_time: Average response time in seconds (float)
• tokens: Total number of tokens used (integer)
• tokens_eur: Cost of tokens in EUR (float)
• category: Category of the conversation (string)
• initial_msg: First message from the user (text)
• user_rating: User rating of the conversation (string)

Future Enhancements

• API integration for real-time data
• More advanced visualizations
• Custom reports
• Export functionality
• Theme customization
• User access control with more granular permissions

License

This project is licensed under the MIT License - see the LICENSE file for details.