Adding Client CRUD APIs and Prediction Model Integration#35
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frankluo123 wants to merge 49 commits into
Open
Adding Client CRUD APIs and Prediction Model Integration#35frankluo123 wants to merge 49 commits into
frankluo123 wants to merge 49 commits into
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merge updates from main to my local branch
…r messages when client not found
CRUD and endpoints updates and added testcases
Include database configurations
merge main into local branch.
Add test_crud.py to only include local unit tests for CRUD functions; Reverse test.py to be the original version
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This Pull Request introduces significant enhancements to the CommonAssessmentTool backend application, focusing on CRUD functionality, predictive modeling, and database integration.
Overview of Changes:
Implemented CRUD APIs for managing client data, allowing users to:
Integrated a prediction endpoint to recommend success rates based on chosen factors.
Trained a machine learning model to process client data and return actionable predictions.
Added a lightweight HTML form for user interaction, enabling data input and submission to the prediction API.
Configured the application to use a MySQL database for persistent storage of client information.
Created unit tests for CRUD functions to ensure robustness and reliability.
Developed utility scripts for loading sample data and preprocessing inputs for the machine learning model.
Reason for Changes:
The goal of these changes was to deliver a functional backend for the Client Assessment Tool. This helps facilitate client data management and provides predictive insights to improve case management outcomes.
Impact:
Improves usability by providing core CRUD functionalities for client data.
Enhances decision-making for caseworkers through predictive analytics.
Establishes a scalable and maintainable foundation for future features and integrations.