The home server's Ollama doesn't have gpt-oss:20b pulled; qwen3:14b is
already there and is what mammon's chat agent uses. Switching the default
now so the first deploy passes the /healthz ollama probe without an extra
`ollama pull` step. The spec lists gpt-oss:20b as a concrete example;
qwen3:14b is equally on-prem and Ollama-structured-output-compatible.
Touched: AppConfig default, BankStatementHeader Request.default_model,
.env.example, setup_server.sh ollama-list check, AGENTS.md, deployment.md,
live tests. Unit tests that hard-coded the old model string but don't
assert the default were left alone.
Also: ASCII en-dash in e2e_smoke.py Paperless-style text (ruff RUF001).
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
First use case lands. The schema is intentionally flat — nine scalar fields,
no nested arrays — because Ollama's structured-output guidance stays most
reliable when the top level has only scalars, and every field we care about
(bank_name, IBAN, period, opening/closing balance) can be rendered as one.
Registration is explicit in `use_cases/__init__.py`, not a side effect of
importing the use-case module. That keeps load order obvious and lets tests
patch the registry without having to reload modules.
`get_use_case(name)` is the one-liner adapters use; it raises
`IX_001_001` with the offending name in `detail` when the lookup misses,
which keeps log-scrape simple.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
