mirror of
https://github.com/kjanat/livegraphs-django.git
synced 2026-01-16 12:32:10 +01:00
Kaj Kowalski
482bea1ba5
- 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.
134 lines
3.9 KiB
Markdown
134 lines
3.9 KiB
Markdown
# Chat Analytics Dashboard
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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.
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## Features
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- Multi-company support with user authentication
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- CSV file upload and processing
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- Interactive dashboard with charts and visualizations
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- Detailed data views for chat sessions
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- Search functionality to find specific chat sessions
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- Admin interface for managing users and companies
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- Responsive design using Bootstrap 5
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## Requirements
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- Python 3.13+
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- Django 5.0+
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- PostgreSQL (optional, SQLite is fine for development)
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- Other dependencies listed in [`pyproject.toml`](pyproject.toml)
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## Setup
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### Local Development
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1. Clone the repository:
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```sh
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git clone <repository-url>
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cd dashboard_project
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```
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2. Create a virtual environment and activate it:
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```sh
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uv venv
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source .venv/bin/activate # On Windows: .venv\Scripts\activate
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```
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3. Install dependencies:
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```sh
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uv pip install -r requirements.txt
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```
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4. Run migrations:
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```sh
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uv run python manage.py makemigrations
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uv run python manage.py migrate
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```
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5. Create a superuser:
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```sh
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uv run python manage.py createsuperuser
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```
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6. Run the development server:
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```sh
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uv run python manage.py runserver
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```
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7. Access the application at <http://127.0.0.1:8000/>
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### Using Docker
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1. Clone the repository:
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```sh
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git clone <repository-url>
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cd dashboard_project
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```
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2. Build and run with Docker Compose:
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```sh
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docker-compose up -d --build
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```
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3. Create a superuser:
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```sh
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docker-compose exec web python manage.py createsuperuser
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```
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4. Access the application at <http://localhost/>
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## Usage
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1. Login as the superuser you created.
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2. Go to the admin interface (<http://localhost/admin/>) and create companies and users.
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3. Assign users to companies.
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4. Upload CSV files for each company.
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5. View the analytics dashboard.
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## CSV File Format
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The CSV file should contain the following columns:
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| Column | Description |
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| ------------------- | ------------------------------------------------------ |
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| `session_id` | Unique identifier for the chat session |
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| `start_time` | When the session started (datetime) |
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| `end_time` | When the session ended (datetime) |
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| `ip_address` | IP address of the user |
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| `country` | Country of the user |
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| `language` | Language used in the conversation |
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| `messages_sent` | Number of messages in the conversation (integer) |
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| `sentiment` | Sentiment analysis of the conversation (string) |
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| `escalated` | Whether the conversation was escalated (boolean) |
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| `forwarded_hr` | Whether the conversation was forwarded to HR (boolean) |
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| `full_transcript` | Full transcript of the conversation (text) |
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| `avg_response_time` | Average response time in seconds (float) |
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| `tokens` | Total number of tokens used (integer) |
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| `tokens_eur` | Cost of tokens in EUR (float) |
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| `category` | Category of the conversation (string) |
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| `initial_msg` | First message from the user (text) |
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| `user_rating` | User rating of the conversation (string) |
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## Future Enhancements
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- API integration for real-time data
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- More advanced visualizations
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- Custom reports
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- Export functionality
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- Theme customization
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- User access control with more granular permissions
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## License
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This project is unlicensed. Usage is restricted to personal and educational purposes only. For commercial use, please contact the author.
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