User reported that the old prompt could emit 'sell' on backward-looking
capitulation ('Kevin sold after a 20% drop') — exactly the false signal
to avoid. v2 reframes every per-ticker field as forward-looking and
adds an explicit expected_move enum for the trading bot to weight.
Changes:
- New ExpectedMove enum (up_strong/up_mild/sideways/down_mild/
down_strong/unknown) in shared/schemas + shared/models, with
matching kevin_expected_move Postgres enum + column on
kevin_stock_mentions (migration e5f6a7b8c9d0). NOT NULL with
server_default 'unknown' so existing rows backfill cleanly.
- SYSTEM_PROMPT rewritten: action semantics now require a FORWARD
view; reactive sells get downgraded to 'watch' or skipped; the
rationale_quote must contain forward reasoning. Quality
checklist updated.
- _ANALYSIS_TOOL JSON schema gains expected_move (required).
- prompt_version v1 → v2 in config + infra + ad-hoc CLI default.
- pipeline.py persists ticker.expected_move into the new column.
Migration safety: the column is NOT NULL DEFAULT 'unknown' so 96
existing mentions auto-fill with 'unknown' (no forward call known
for backward analyses) without breaking any reads.
Cost to backfill the 27 existing analyses with v2 prompt: ~$3 LLM
spend. A follow-up reanalyze script will replay them after this
ships.
Given a YouTube video ID or URL, runs the same caption-extraction +
LLM-analysis pipeline the watcher uses in prod, then prints the
extracted tickers + actions sorted by action priority and conviction
descending. No DB writes, no Redis publish — strictly observational.
Two entry points:
- scripts/analyze_kevin_video.py — pure Python; needs yt-dlp +
Anthropic OAuth token in env. Local laptop yt-dlp tends to hit
"Sign in to confirm you're not a bot" rate-limits; running inside
a cluster pod avoids this.
- scripts/kevin-analyze.sh — wrapper that finds the running
trading-bot-workers pod and execs the Python script in the
meet-kevin-watcher container. Easiest invocation.
Example:
$ ./scripts/kevin-analyze.sh poUJIZRmFew
=== Meet Kevin analysis — poUJIZRmFew ===
Market outlook: bullish
TICKERS (12):
SYMBOL ACTION CONV HORIZON RATIONALE
APPF buy 85.0% long_term Apploven's looking fantastic ...
SOX buy 80.0% months Semiconductor ETF momentum ...
...
- Point Ollama to local instance via host.docker.internal, use gemma3 model
- Remove Docker Ollama service (using host's Ollama instead)
- Add company-name-to-ticker mapping (Apple→AAPL, Tesla→TSLA, etc.) for RSS articles
- Lower signal thresholds for faster feedback with paper trading:
- FinBERT confidence: 0.6→0.4, signal strength: 0.3→0.15
- News strategy: article_count 2→1, confidence 0.5→0.3, score ±0.3→±0.15
- Fix market data BarSet access bug (BarSet.__contains__ returns False incorrectly)
- Fix market data SIP feed error by switching to IEX feed for free Alpaca accounts
- Fix nginx proxy routing for /api/auth/* to api-gateway /auth/*
- Add seed_sample_data script
- Update tests for new thresholds and alpaca mock modules
Add integration tests for the news pipeline (test_news_pipeline.py) and
trading flow (test_trading_flow.py) using real Redis with mocked FinBERT
and Alpaca. Add seed_strategies.py to insert default strategies (momentum,
mean_reversion, news_driven) with equal weights. Add smoke_test.sh for
end-to-end stack validation. Update pyproject.toml with integration marker
and scripts package discovery.
