converts long chain paragraphs into short and precise summary Text summarisation file flow

1. Make all the required file using python by utilising os path and logging modules
2. Fill the requirement .txt
3. Fill the setup.py
4. If the software is needed I will install on spot
5. Fill logging/init.py for custom logging
6. 1. Update config.yaml
7. Params.yaml
8. Entity
9. Update configuration manager in src config
10. Update components
11. Update pipeline
12. Update main.py
13. Update app.py
14. Note—> after I updated the config file with data ingestion I skipped the updation of params because I do not have any params yet
15. After importing constant fill the constant/init.py
16. After defiing the configuration master fill params.yaml with dummy value so that it doesn’t return any error
17. After expermenting in the trails.ipynb in research folder copy paste the codes according the workflow mentioned above
18. In components you have to create a data_ingestion.ipynb file to paste the component code
19. In the model trainer stage the params.yaml should be filled with the trainable parameters The CI/CD deployment on AWS is yet to be updated