mirror of https://github.com/kjanat/livegraphs-django.git synced 2026-01-16 10:12:09 +01:00

Files

Kaj Kowalski 482bea1ba5 Enhance AJAX navigation and pagination across dashboard templates

- Implemented AJAX-based navigation for links and forms to improve user experience.
- Added loading indicators during AJAX requests to enhance feedback.
- Refactored data tables and search results to load content dynamically via AJAX.
- Created partial templates for data tables and search results to streamline rendering.
- Updated pagination links to work with AJAX, maintaining browser history.
- Added JavaScript files for handling AJAX navigation and pagination.
- Improved session detail view with conditional rendering for action buttons.
- Updated Docker Compose file for consistency in version formatting.
- Created a TODO list for future enhancements and features.

2025-05-17 02:31:16 +02:00

3.9 KiB

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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

Clone the repository:

git clone <repository-url>
cd dashboard_project

Create a virtual environment and activate it:

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

Install dependencies:
```
uv pip install -r requirements.txt
```

Run migrations:

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

Create a superuser:

uv run python manage.py createsuperuser

Run the development server:
```
uv run python manage.py runserver
```
Access the application at http://127.0.0.1:8000/

Using Docker

Clone the repository:

git clone <repository-url>
cd dashboard_project

Build and run with Docker Compose:
```
docker-compose up -d --build
```

Create a superuser:

docker-compose exec web python manage.py createsuperuser

Access the application at http://localhost/

Usage

Login as the superuser you created.
Go to the admin interface (http://localhost/admin/) and create companies and users.
Assign users to companies.
Upload CSV files for each company.
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.

3.9 KiB Raw Blame History