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Implement data integration tasks with Celery, including periodic fetching and manual refresh of chat data; add utility functions for data processing and transcript handling; create views and URLs for manual data refresh; establish Redis and Celery configuration; enhance error handling and logging; introduce scripts for data cleanup and fixing dashboard data; update documentation for Redis and Celery setup and troubleshooting.
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48
README.md
48
README.md
@ -74,13 +74,57 @@ A Django application that creates an analytics dashboard for chat session data.
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python manage.py createsuperuser
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```
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7. Run the development server:
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7. Set up environment variables:
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```sh
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# Copy the sample .env file
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cp .env.sample .env
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# Edit the .env file with your credentials
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nano .env
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```
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Be sure to update:
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- `EXTERNAL_API_USERNAME` and `EXTERNAL_API_PASSWORD` for the data integration API
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- `DJANGO_SECRET_KEY` for production environments
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- Redis URL if using a different configuration for Celery
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8. Start Celery for background tasks:
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```sh
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# In a separate terminal
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cd dashboard_project
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celery -A dashboard_project worker --loglevel=info
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# Start the Celery Beat scheduler in another terminal
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cd dashboard_project
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celery -A dashboard_project beat --scheduler django_celery_beat.schedulers:DatabaseScheduler
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```
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Alternative without Redis (using SQLite):
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```sh
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# Set environment variables to use SQLite instead of Redis
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export CELERY_BROKER_URL=sqla+sqlite:///celery.sqlite
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export CELERY_RESULT_BACKEND=db+sqlite:///results.sqlite
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# In a separate terminal
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cd dashboard_project
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celery -A dashboard_project worker --loglevel=info
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# Start the Celery Beat scheduler in another terminal with the same env vars
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cd dashboard_project
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celery -A dashboard_project beat --scheduler django_celery_beat.schedulers:DatabaseScheduler
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```
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9. Run the development server:
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```sh
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python manage.py runserver
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```
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8. Access the application at <http://127.0.0.1:8000/>
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10. Access the application at <http://127.0.0.1:8000/>
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### Development Workflow with UV
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