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:

Column	Description
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 unlicensed. Usage is restricted to personal and educational purposes only. For commercial use, please contact the author.