Translate for any user with lang='it' regardless of paid/free status.
Italian + UK are the first markets, so IT availability is part of the
public-facing experience — a free-tier visitor needs to see the AI in
Italian to convert. At ~$0.005/day total cost the gating isn't worth
the savings.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Hybrid model: per-user surfaces (analyse, digest, chat) generated
directly in the target language via a "Respond in Italian" clause
appended to the system prompt. Shared content (strategic log)
generated in English as today, then post-translated and cached per
language in a new strategic_log_translations table. Translation calls
fan out in parallel with asyncio.gather so total job latency stays
bounded by max(single call).
No separate translation-model setting — DeepSeek-4-flash at $0.28/M
output is cheap enough that the routine cost is noise (~$0.005/day
with Italian only at 24 logs/day).
Users.lang VARCHAR(8) DEFAULT 'en'. Settings dropdown lists all four
options but ES/FR/DE are disabled UI-side and rejected server-side
against an ACTIVE_LANGUAGES allowlist — flipping them on later is a
one-line constant change.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Dashboard-native edit mode: EDIT button toggles in-place editing; the
add-position form has on-blur ticker validation against a new paid
endpoint, qty input, and an avg-cost / bought-on-date toggle. Only
avg_cost + qty are persisted to localStorage (no acquisition date,
no server-side holdings). Empty state replaces "Import a CSV" with
the inline form so brand-new users can act without leaving the page.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
- Drop first_seen_user_id; sample is anonymous by construction
- Rename sample_dummy → sample_row, store the upload's first real data
row verbatim (one row, no totals, no other positions, no link to a
user). Narrow, deliberate exception to the "no holdings persisted"
invariant — gives the operator material for hand-writing future
native parsers.
- Drop the cache self-heal behaviour; operator owns eviction. Reinforce
the non-goal of auto-promoting learned formats to code.
Transparent fallback after parse_t212_csv: LLM extracts a column-mapping
(not the data), result is cached globally by header fingerprint, replay
is deterministic Python. Stored dummy contains headers + synthetic row
only — no user holdings ever persisted.
Design doc for three coordinated closed-beta changes: a BETA chip in
the app header, a 6h news-window cap on the free tier, and email
digests (daily for paid Mon-Sat, Sunday weekly for everyone). Draft;
awaits implementation plan.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
