App: Gradio/CLI wired to settings; requirements and README

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Summary

Wires app.py, run_training.py, and test_system.py to load_settings() so the Gradio dashboard and CLI share the same YAML-driven hyperparameters and paths. Refreshes requirements.txt (FastAPI/Starlette pins, Python 3.13 audioop-lts marker) and replaces README.md with goal-oriented documentation (what the project does, what it is trying to achieve, config overview, quick start).

Base branch: pr/03-training-pipeline (stacked — merge last or retarget after #3).

What changed

• Dashboard / scripts — Single config entrypoint; Bloom seeds path, DNABERT id, training defaults, Gradio host/port range from YAML/env.
• run_app.sh — Prefers Python 3.12 venv when available; installs from requirements.txt.
• requirements.txt — Full dependency set aligned with current app stack.
• README.md — Mission, outcomes, configuration keys for biological consistency, structure, limitations, disclaimer.

Why this PR exists

Users should not fork parallel configuration between UI and training scripts. One profile should drive demo, training, and smoke tests.

Dependencies

• PR Training: DataLoader, feature cache, AMP, lazy package exports #3 (Training: DataLoader, feature cache, AMP, lazy package exports #3): settings-aware pipelines.

How to verify

./run_app.sh
# or: .venv/bin/python run_training.py

Stacked merge order

1. Config + assets (Config layer: Pydantic settings, default YAML, reference assets #1)
2. Data loader (Data: config-driven ClinVarDataLoader and reference-validated windows #2)
3. Training pipeline (Training: DataLoader, feature cache, AMP, lazy package exports #3)
4. App + docs (this PR)

After earlier PRs merge into main, edit the base branch of the remaining PRs to main and rebase if GitHub shows extra commits.

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Final integration PR\n\nWhen #1–#3 are merged into main, edit this PR: set base to main, rebase pr/04-app-and-docs onto main, and confirm the diff only contains app/scripts/requirements/README changes relative to main.