Add context windows, web search, streamed answers, overlay move/resize; overhaul docs

- Context windows (contexts/*.yaml) scope answers to a defined domain
- Optional DuckDuckGo web search behind ai.web_search.enabled (default off)
- Stream partial answers into the overlay at first-token time
- Default Whisper to local base.en (~9x faster); offline model loading
- Priority-ordered loopback detection (BlackHole > Teams device)
- Overlay: drag interior to move, edges to resize
- Stop tracking model binaries (models/ is gitignored)
- README/CLAUDE.md overhaul + tracked config.example.yaml

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

contexts/python_flask_backend.yaml

@@ -0,0 +1,31 @@
+name: Python / Flask — Senior Backend Engineer
+scope: Senior backend engineering interview focused on Python and the Flask web framework
+active: true
+strict: false
+definition: |
+  This is a senior backend engineering interview centered on Python and the
+  Flask web framework. Interpret every question within Python/Flask backend
+  engineering first, even when the question does not say so explicitly, and
+  answer at the depth expected of a senior engineer.
+
+  When a term also has meanings outside this scope (e.g. STOMP, CORS, WSGI,
+  "workers", "streams"), give the Python/Flask-relevant answer first, then
+  briefly note other necessary variations so the answer stays accurate.
+
+  Assume strong familiarity with and expect depth on:
+  - Flask app structure: application factory, blueprints, extensions, config.
+  - Request lifecycle: WSGI, the app/request contexts, g, before/after request.
+  - Concurrency & deployment: the GIL, gunicorn/uwsgi workers, gevent/eventlet,
+    threads vs processes, async (ASGI/Quart) trade-offs.
+  - Data: SQLAlchemy ORM and Core, sessions, migrations (Alembic), connection
+    pooling, N+1 queries, transactions.
+  - APIs: RESTful design, status codes, pagination, versioning, serialization
+    (marshmallow/pydantic), input validation, error handling.
+  - Auth & security: sessions vs JWT, CSRF, CORS, OWASP basics, secrets, rate
+    limiting.
+  - Reliability & performance: caching (Redis), background jobs (Celery/RQ),
+    idempotency, observability (logging, metrics, tracing), profiling.
+  - Testing & quality: pytest, fixtures, test client, mocking, coverage, CI.
+
+  Keep answers interview-appropriate: precise, technically correct, and concise,
+  with concrete Python/Flask examples or trade-offs where helpful.