📅 2024-04-13 — Session: Resolved Flask API and Model Integration Issues
🕒 17:10–18:40
🏷️ Labels: Flask, Javascript, API, Debugging, Model Management
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to troubleshoot and resolve various issues related to the integration of Flask APIs with JavaScript for model prediction and management.
Key Activities
- KeyError Troubleshooting: Addressed a
KeyErrorin the prediction logic by ensuring data consistency and proper preprocessing. - 404 Error Resolution: Resolved multiple
404 Not Founderrors by verifying route definitions, registering blueprints, and correcting AJAX requests in the Flask application. - Model Retrieval Update: Modified the
get_models()function and updated JavaScript code to dynamically populate dropdown menus with model filenames. - Model Metadata Management: Improved the handling of model metadata in both JavaScript and Python.
- Prediction Logic Integration: Integrated data preprocessing and model prediction within the Flask
/predictendpoint. - Git Commit Organization: Structured Git commits for clarity and logical grouping.
Achievements
- Successfully resolved
404errors and improved API endpoint accessibility. - Enhanced the model selection and prediction logic in the web application.
- Improved the management and retrieval of model metadata.
- Organized Git commits to reflect best practices in version control.
Pending Tasks
- Further testing of the
/retrainendpoint to ensure no additional404errors occur. - Continuous monitoring and debugging of the Flask and JavaScript integration to maintain robust data flow.