- Introduced a new module `curve_client.py` for interacting with the Luxsin curve API, including functions for custom Base64 decoding and parametric EQ validation.
- Implemented error handling for API responses and validation checks for curve data.
- Removed outdated test files to streamline the codebase.
- Updated brand creation and update logic in `brands.py` to ensure brand names are validated and checked for duplicates.
- Enhanced model handling in `models.py` with new validation and push-to-search functionality, integrating curve validation before pushing to Meilisearch.
- Updated frontend components to support new validation and push processes, including user feedback for validation results and progress tracking.
- Changed favicon to SVG format for better scalability and appearance.
- Introduced a new endpoint for uploading OTA packages in backend/routes/ota.py.
- Implemented file handling and MD5 checksum calculation for OTA packages.
- Updated frontend API to support OTA package uploads with a new uploadOtaPackage function.
- Enhanced the OTA management UI to include file upload options and improved layout.
- Updated requirements.txt to include boto3 for S3 interactions.
- Made various UI adjustments for better user experience and consistency.
- Updated main.py to include authentication for brand, model, and OTA routers.
- Added new OTA schemas in schemas.py for version management.
- Enhanced model retrieval with sorting options in models.py.
- Improved model update functionality to support multipart/form-data uploads.
- Updated frontend layout and styles for a more modern look, including new font integration.
- Implemented login route and authentication checks in router/index.js.
- Added sorting capabilities in model table and improved file handling in model view.
- Updated requirements.txt to include PyJWT for token management.
- Updated docker-compose.yml to rename backend and frontend container names for clarity.
- Added volume mappings for frontend and backend services to persist data.
- Removed obsolete files related to frequency response extraction, including Python scripts and output data files.
- Adjusted backend port configuration in main.py to align with new service architecture.
- Enhanced logging for file upload paths in models.py for better traceability.
- Created .env.example for environment variable configuration.
- Added docker-compose.yml for service orchestration.
- Implemented frequency response extraction in extract_frequency_response.py and convert_to_frequency_db.py.
- Generated output files: frequency_response_detailed.json, frequency_response_points.json, frequency_response.csv, and frequency_response_curve.png.
- Included sample measurement data for FiiO FA19 in CSV format.
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