compliance: flag-gate AI portfolio + cloud sync + Stripe; de-risk prompts; harden reviewer
Implements docs/read-markets-compliance-changes.md as flag-gated changes (no deletions) so paused features stay in the tree for future re-enable. All four flags default False so a fresh deploy is compliance-safe. - New env flags: PORTFOLIO_AI_ENABLED, PORTFOLIO_SYNC_ENABLED, TICKER_UNIVERSE_AGGREGATE_ENABLED, SUBSCRIPTIONS_ENABLED. - Gates: /api/analyze, /api/portfolio/sync*, /api/stripe/*, /pricing, ticker_universe writes, portfolio_analysis.analyse(). is_paid_active() returns True for any auth'd user when subscriptions are paused. - Prompts (PROMPT_VERSION 10): universal _COMPLIANCE_RIDER prepended to every system prompt; watch list removed; price-target / close-above-below / trigger / forward-state-as-description rules added; SPECULATIVE pivoted to regime-only scenarios; daily + weekly digests tightened. - Reviewer: deterministic regex/lexicon pre-check fail-closed under the Haiku call; portfolio rider gated by PORTFOLIO_AI_ENABLED; base prompt sharpened for forward-state and MAR forward-opinion patterns; ReviewerVerdict audit table; generate_with_review retry helper. - Migration 0026: purge portfolio_sync + ticker_universe; create reviewer_verdicts. - Copy: MAR cite fixed to Art 3(1)(35) + Art 20 + Del Reg 2016/958; portfolio reframed as browser-only viewer in disclaimer / privacy / terms / about / pricing / landing (en + it). TODO(legal) marker for lawyer sign-off on disclaimer. - Tests: 13 lexicon + 6 reviewer compliance regressions; conftest enables all flags so existing 402 tests still cover their code paths. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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tests/test_output_review_lexicon.py
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tests/test_output_review_lexicon.py
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"""Tests for the deterministic regex/lexicon pre-check.
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These are pure-function tests for ``app.services.output_review_lexicon.check``
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— no LLM, no DB, no fixtures. They protect both the obvious-rejects and
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the false-positive guards (bare 'should', 'cut', 'hold' must not match in
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benign contexts)."""
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from __future__ import annotations
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import pytest
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from app.services.output_review_lexicon import check
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# ---------------------------------------------------------------------------
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# Obvious rejects — should hit and identify the firing rule
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# ---------------------------------------------------------------------------
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@pytest.mark.parametrize("text,expected_rule", [
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# First-match-wins ordering: action_phrase runs before advice_phrase, so
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# a sentence with both ("you should buy") fires action_phrase. That's
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# fine — the goal is to catch a violation, not to attribute the rule.
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("You should buy the dip.", "action_phrase"),
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("Investors should consider buying defensives.", "advice_phrase"),
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("We recommend trimming this position.", "advice_phrase"),
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("That stock is a buy at these levels.", "action_phrase"),
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("Take profit on the position.", "action_phrase"),
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("Trim your exposure to growth.", "action_phrase"),
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("Rotate into defensives.", "action_phrase"),
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("Overweight the sector into Q1.", "action_phrase"),
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# Forecast / level register
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("Our price target sits at $95.", "forecast_phrase"),
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("Target of $93 looks reasonable.", "forecast_phrase"),
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("There is support at $4,200.", "forecast_phrase"),
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("Resistance near $570 is the level to watch.", "forecast_phrase"),
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# Composed patterns
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("Brent close above $93 would confirm.", "level_trigger"),
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("If SOXX breaks below 570 the bid fades.", "level_trigger"),
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("Watch for a move above 4,600.", "level_trigger"),
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("Floor at $90 looks intact.", "forecast_phrase"),
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# "X as a floor / ceiling" phrasing — not currently a hard rule in the
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# lexicon (LLM layer catches it); see future-tightening note in the
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# module docstring.
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])
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def test_lexicon_catches_obvious_violations(text, expected_rule):
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hit = check(text)
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assert hit is not None, f"should have flagged: {text!r}"
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assert hit.rule == expected_rule, (
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f"expected rule {expected_rule!r}, got {hit.rule!r} for {text!r}"
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)
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assert hit.snippet, "snippet should never be empty"
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# ---------------------------------------------------------------------------
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# False-positive guards from the brief — must NOT match
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# ---------------------------------------------------------------------------
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@pytest.mark.parametrize("text", [
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# The brief specifically calls these out as false-positive risks for
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# bare-word matchers.
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"Saudi price cuts pushed energy lower this week.",
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"The cargo hold story dominated the tape.",
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"OPEC may hold output steady at the next meeting.",
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# State-level commentary the LLM layer should judge, not the lexicon.
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"Valuations are stretched after the rally.",
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"Real yields are restrictive across the curve.",
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"Positioning is crowded in megacap tech.",
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# Plain factual price citation — no trigger framing.
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"Brent is trading at $90, down 12% YTD.",
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"Gold is at $4,600 after a sharp move higher.",
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# Empty / whitespace
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"",
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" ",
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])
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def test_lexicon_lets_clean_text_through(text):
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hit = check(text)
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assert hit is None, f"lexicon false-positive on: {text!r} (rule={hit and hit.rule})"
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