TickerScorecardTable: bridge-status badges (WOULD-TRADE/HOLDING/etc),
conviction bar, unrealised P&L, manual-close button.
BacktestRunHistory: sortable run list with return/sharpe/alpha columns,
row click selects a run for detail view.
StrategyVsBenchmarkCurve: dual lightweight-charts line (strategy blue,
SPY dashed grey) with legend.
BacktestRun, BacktestRunDetail, StrategyTicker, StrategyEquityCurve,
StrategyPerformance types added to meetKevin.ts. New meetKevinStrategy.ts
with 8 axios methods covering the backtest run/list/get/latest and
strategy tickers/equity-curve/performance/close endpoints.
Maps the design doc (commit 280f807) to bite-sized tasks. Phase 1 ships
strategy + backtest + bridge in audit-only mode; Phase 2 extends
OrderRequest/AlpacaBroker for BRACKET orders, extends RiskManager, and
flips the kill-switch; Phase 3 ships the paper-account UI page.
Each task has Test → Run-and-fail → Implement → Run-and-pass → Commit
steps with concrete code in every step. Implementer can pick up any
task without prior session context.
Synthesizes work of two parallel architect agents (strategy +
paper-trading rules / backtest + UI surface) and the subsequent
challenger review. Resolves 11 issues the challenger raised:
- KevinStrategy is standalone, not BaseStrategy subclass (signature
mismatch — BaseStrategy.evaluate is bar-driven, Kevin is event-driven)
- backtester/kevin_backtest.py as parallel mention-driven mini-engine,
not a fake adapter onto BacktestEngine
- AlpacaBroker BRACKET support specified (OrderRequest schema + broker
_build_order_request extensions)
- Filtering paper-account trades via strategy_id FK (the actual field;
Trade.strategy_name doesn't exist) — migration seeds a 'kevin' row
- Cursor advance race fixed (XADD success → cursor advance)
- Daily counter mechanics specified (Redis INCR + audit dedupe)
- kevin_signal_bridge_state table added to data model (3 new tables now)
- All PKs UUID for consistency with Trade/Position
- StrategyVsBenchmarkCurve.tsx promoted from contingent to definitely-new
- 'avoid' policy split into AVOID_CLOSES_LONGS + AVOID_BLOCKS_DAYS knobs
- Phasing collapsed A+B into Phase 1 (ticker scorecard needs bridge
audit rows to render WOULD-TRADE badges)
First production run hit Anthropic's per-account rate_limit_error (429) trying
to burn through 16 backfill videos in seconds. The SDK's built-in retry can't
recover because the rate limit window resets slower than the 3 retry attempts.
Added meet_kevin_inter_video_sleep_seconds (default 30s) to PipelineDeps and
main's _process_pending_videos loop. 16 backfill videos now take ~8 min (16 * 30s
sleeps + ~30s per LLM call) instead of bursting into the rate limit.
sentiment-analyzer service is disabled in the K8s revival (removed from
the workers Pod spec). Its torch+transformers dependency adds ~2GB to
the image with no runtime benefit. Tests still install it via the
.[dev] extras for the test step.
Image size: ~3GB -> ~1GB.
Previous refactor (89f01ad) moved to OpenRouter because no sk-ant-api-* key
was found in Vault. Turns out claude-agent-service-spare-{1,2} hold
sk-ant-oat01-* OAuth tokens (108 chars, scope user:inference, 1-year TTL,
minted via 'claude setup-token' — see memory id=832).
These tokens work with the Anthropic SDK via the auth_token= constructor
argument (routes to Authorization: Bearer ... instead of x-api-key: ...).
They consume the Enterprise Claude subscription quota rather than
per-call billing, so the OpenRouter zero-credit problem goes away.
- llm_analyzer.py: revert OpenAI client to AsyncAnthropic; tool-use API
+ cache_control restored
- config.py: openrouter_api_key -> anthropic_oauth_token; model slug
reverted from anthropic/claude-sonnet-4.5 -> claude-sonnet-4-5
- main.py: AsyncOpenAI -> AsyncAnthropic(auth_token=...), drop OpenRouter
attribution headers
- pyproject: openai>=1.50 -> anthropic>=0.40 in meet_kevin extras
- tests: mocks ported back to messages.create + tool_use blocks
yt-dlp requires:
- ffmpeg for sub-conversion (--convert-subs srt) and any format mux
- A JS runtime for YouTube player decryption (deno or node)
Without these, every caption extraction attempt in the meet-kevin-watcher
container fails with 'ffmpeg not found' + 'No supported JavaScript runtime
could be found'. Adding both to the runtime stage of Dockerfile.service.
Size impact: ~50 MB.
User's Vault has openrouter_api_key but no direct sk-ant-* Anthropic key.
OpenRouter passes through Claude Sonnet 4.6 (~3% markup over Anthropic
list pricing) and matches the existing gpt_mini_endpoint pattern used
by recruiter-responder.
- Replace anthropic.AsyncAnthropic with openai.AsyncOpenAI + base_url
- Convert Anthropic tool-use API to OpenAI function-calling
- System prompt unchanged (analyst instructions are model-agnostic)
- Drop cache_control (not in OpenAI API); revisit later if cost matters
- Model slug: anthropic/claude-sonnet-4.5 (OpenRouter's current Claude tier)
- Pricing: $3.10/M input, $15.50/M output (OpenRouter pass-through)
- Config field anthropic_api_key -> openrouter_api_key
- pyproject extras: anthropic>=0.40 -> openai>=1.50
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Three issues caught during end-to-end manual QA against docker-compose:
1. SAEnum field columns serialized to Python enum NAMES ('DISCOVERED')
but the DB enum had VALUES ('discovered'). Added `values_callable`
to all 5 SAEnum() declarations in shared/models/meet_kevin.py so they
emit values, matching the migration's enum literals.
2. /dashboard's "last 7 days" / "last 14 days" filters used
`func.cast("7 days", type_=None)` which produced NullType DDL.
Replaced with `text("now() - interval '7 days'")`.
3. /dashboard's outlook trend query repeated `func.date_trunc("day", col)`
in SELECT, GROUP BY and ORDER BY — Postgres treats each as a separate
parameterized expression. Hoisted into a single `day_trunc` variable
so all three clauses reference the same SQL fragment.
All 11 /api/meet-kevin/* endpoints now return valid JSON against a
docker-compose Postgres seeded with one analyzed video + NVDA mention.
- Implement CaptionResult frozen dataclass for structured caption data
- Add parse_srt() to parse SubRip format with flexible timestamp handling
- Add extract_captions() async function using yt-dlp subprocess wrapper
- Prefer manual captions over auto-generated; clean up SRT files after parsing
- Add 16 comprehensive tests covering edge cases (empty input, malformed SRT,
timestamp variations, language extraction, manual vs auto selection)
- Type-safe implementation with full mypy --strict compliance
- Add sample.srt fixture with 3 segments mentioning NVDA for test reference
- Replace all Literal[...] type annotations with corresponding enum classes
(TickerAction, TimeHorizon, MarketOutlook, VideoStatus, TranscriptSource)
for MeetKevinTickerMention, MeetKevinAnalysis, and API response models
(VideoSummary, VideoDetail, StockMention, StockSummary, TimelineBucket)
- Add min_length=1, max_length=10 validation to MeetKevinTickerMention.symbol
- Split test_conviction_edge_cases into two separate boundary tests
- Strengthen test_valid_ticker_mention with assertions for all 6 fields
- Trim no-information docstrings from TranscriptSegment, StockTimeline
- All 60 schema tests pass
22-task plan across 6 phases (data layer, watcher service stages,
API gateway, dashboard, container/deps, K8s revival). Each task
includes TDD checkboxes, file paths, acceptance criteria, and
commit commands. References the design doc (ab382af) for schemas,
prompts, and the Terraform diff.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Design for reviving the trading-bot K8s stack with a new Meet Kevin
YouTube watcher pipeline. v1 scope: poll RSS every 3h, extract
captions via yt-dlp, run transcript through Claude Sonnet 4.6 for
structured per-ticker recommendations and market outlook, surface
in a new ticker-centric UI under /meet-kevin/*. Bot integration
(signal_generator) and auto-trading deferred to v2.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
- TradeLog: use created_at (from API) instead of timestamp for date display
- EquityCurve: deduplicate data by day before passing to lightweight-charts,
preventing "data must be asc ordered by time" assertion failure when
multiple snapshots exist on the same day
Made-with: Cursor
The buildx plugin was not passing NGINX_CONF build arg correctly,
causing the docker-compose nginx config (with hostname api-gateway)
to be used instead of the K8s one (with localhost).
- Replace pip with uv in Dockerfile.service builder stage (~5-10x faster)
- Replace pip with uv in CI test step
- Separate pyproject.toml copy from source copy in Dockerfile for better
Docker layer caching (deps only reinstalled when pyproject.toml changes)
- Add cache_from for buildx to reuse layers from previous builds
- Remove pip cache workaround from test step (not persisted in K8s)
The woodpeckerci/plugin-docker-buildx was not passing the EXTRAS build
arg correctly (commas in the value were likely being parsed as list
separators), causing the image to only install dev dependencies instead
of all service extras (api, news, sentiment, trading, backtester).
Hardcode the pip install extras directly in the Dockerfile rather than
relying on the build arg.
- Learning engine: expand default weights from 3 to all 9 strategies
- Learning engine: resolve placeholder strategy_id with DB lookup
- Learning engine: pass strategy_sources from trade execution
- Trade executor: respect trading:paused Redis flag in RiskManager
- Portfolio sync: compute actual daily P&L from day-start snapshot
- Portfolio API: cumulative P&L from first snapshot, read pause flag
- Portfolio metrics: compute max drawdown and avg hold duration
- Add strategy_sources field to TradeExecution schema
- Add dev_mode config (TRADING_DEV_MODE) to bypass auth for local dev
- Dashboard: VITE_DEV_MODE bypasses ProtectedRoute and 401 redirects
- Vite proxy target configurable via VITE_API_TARGET
- Add top-level README.md and remaining-work-plan.md
- Update CLAUDE.md with correct counts and remove stale TODOs
- 404 tests passing
Made-with: Cursor
The publish-images step used an alpine container to run skopeo for
re-tagging, but intermittent DNS failures prevent apk from installing
packages. Instead, have the buildx plugin push with both the pipeline
number tag and latest tag directly, eliminating the extra step.
The alembic migration unconditionally called create_hypertable() which
fails if TimescaleDB isn't installed on the PostgreSQL instance. Wrap
in a DO block that checks for the extension first.
Woodpecker pre-processes ${VAR} syntax as CI variables, replacing
undefined ones with empty strings. Use $$ escaping for shell variables
to prevent Woodpecker from consuming them. The ${REPO} variable in
the skopeo publish step was being replaced with empty string.
plugins/docker does not get privileged: true in K8s pods despite being
in WOODPECKER_PLUGINS_PRIVILEGED. woodpeckerci/plugin-docker-buildx
correctly receives privileged mode. Previous build failure with buildx
was a transient network timeout reaching registry-1.docker.io.
