- Updated the Dockerfile to rename the built binary from `mf-fitter` to `fit_model` for clarity.
- Introduced a new `fit_model_args.rs` file to define command-line arguments for the fit model process, including parameters for matrix factorization.
- Added `pg_types.rs` and `pgvector.rs` files to handle PostgreSQL type interactions and vector serialization/deserialization.
- Implemented the main logic for the fit model in `fit_model.rs`, including data loading, model training, and embedding saving.
- Enhanced `visualize_embeddings.rs` to load embeddings and clusters more efficiently.
These changes improve the organization and functionality of the model fitting process, making it more intuitive and maintainable.
- Introduced a new `args.rs` file to define command-line arguments for data loading parameters, including source and target table details, matrix factorization settings, and optional interaction limits.
- Refactored `main.rs` to utilize the new argument structure, enhancing code organization and readability.
- Removed the previous inline argument definitions, streamlining the main application logic.
These changes improve the configurability and maintainability of the data loading process.
- Updated `.cargo/config.toml` to optimize compilation flags for performance.
- Enhanced `main.rs` by:
- Renaming user and item ID columns for clarity.
- Adding validation functions to ensure the existence of tables and columns in the database schema.
- Implementing immediate exit handling during data loading.
- Modifying the `save_embeddings` function to accept item IDs for processing.
- Improving error handling with context messages for database operations.
These changes improve code readability, robustness, and performance during data processing.
