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Implemented the requested architectural blueprint for Yogimass.

Key features:

  • Configuration-Driven: All major parameters (paths, filters, models) are controlled via config/settings.yaml.
  • Modularity: Code is split into logical modules (dataloader, filters, engine).
  • Caching: LibraryLoader caches parsed spectra to pickle files to speed up subsequent runs. Filters are applied after loading (raw or cached) to allow dynamic reconfiguration.
  • Pipeline Pattern: Filters are applied sequentially based on the YAML list.
  • Search Engine: Supports switching between Cosine Greedy (matchms) and Spec2Vec algorithms.

PR created automatically by Jules for task 1427371836429214696 started by @janusson

- Created directory structure (config, data, src).
- Implemented core modules:
    - `src/dataloader.py`: LibraryLoader with pickle-based caching.
    - `src/filters.py`: Dynamic filter pipeline driven by config.
    - `src/engine.py`: Searcher class supporting Cosine and Spec2Vec.
    - `src/utils.py`: Logger configuration.
- Created `config/settings.yaml` template.
- Created `main.py` entry point.
- Created `environment.yml`.
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👋 Jules, reporting for duty! I'm here to lend a hand with this pull request.

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I'll push a commit with your requested changes shortly after. Please note there might be a delay between these steps, but rest assured I'm on the job!

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