Migration 028: For each recommendation with no evidence rows, finds
the closest matching trend_window (by ticker + time_horizon + timestamp)
and re-inserts evidence from top_supporting/opposing_evidence arrays.
Filters out non-UUID pattern IDs and verifies documents exist.
This fixes 'No evidence linked' on recommendations created before the
UUID filtering fix in persist_recommendation.
- Migration 026 and OllamaConfig now default to qwen3.5:9b instead of
llama3.1:8b. Existing deployments keep their current model (qwen3.5:9b-fast)
since the migration uses WHERE NOT EXISTS on slug.
- Event classifier system prompt expanded with macro-vs-company filtering:
explicitly instructs the model to NOT classify single-company news
(lawsuits, earnings, management changes, debt crises) as macro events.
Sets severity=low and confidence<0.3 for company-specific articles.
Reserves 'critical' severity for multi-country/global market events.
Prevents over-tagging event_types by requiring direct description.
- Updated test_system_prompt_is_concise threshold to accommodate the
expanded prompt (300 → 1000 chars).
New Agents tab in the sidebar (Ops group) for viewing, editing, and
creating AI agent configurations:
Database (migration 026):
- ai_agents table: editable configs for each LLM agent (model, prompts,
temperature, tokens, retries). source='system' for built-in,
source='user' for custom. Seeds 3 system agents (Document Extractor,
Event Classifier, Thesis Rewriter) using WHERE NOT EXISTS to never
overwrite user edits across reinstalls.
- agent_performance_log table: per-invocation metrics (duration,
confidence, retries, tokens, errors) linked to agent config.
API endpoints:
- GET/POST /api/agents — list and create agents
- GET/PUT/DELETE /api/agents/{id} — view, edit, delete (system agents
can be edited but not deleted)
- GET /api/agents/{id}/performance — aggregated metrics (success rate,
avg/p95 latency, confidence, token usage)
- GET /api/agents/{id}/performance/history — hourly time series
Frontend:
- AgentsPage with sidebar list + detail panel
- Agent detail: config display, system prompt viewer, performance
dashboard with metrics cards and time-series chart
- Edit form: all config fields editable including system prompt,
model, temperature, tokens, retries
- Create form: new user-defined agents with auto-slug generation
- System agents show blue badge, user agents show green badge
Migration 023 was deleting all but the latest trend_windows row per
entity before 024 could save them to trend_history. On reinstall,
this wiped the entire history every time.
Fixed by restructuring:
- 023 now creates trend_history FIRST and copies all trend_windows
rows into it before deduplicating trend_windows down to latest-only.
Uses NOT EXISTS to avoid duplicating rows on re-runs.
- 024 is now idempotent: ensures table/indexes exist and backfills
from recommendations (last 7 days, 1 point per ticker/window/hour)
to reconstruct approximate history even if trend_windows was sparse.
Both migrations are safe to re-run on existing databases.
- New 'intraday_bars' endpoint in PolygonMarketAdapter: fetches hourly
bars for today using range_bars URL with timespan=hour, sort=asc
- Scheduler expands intraday_bars global source into per-ticker jobs
for all active companies (every 15 minutes via polling_interval)
- Migration 025 inserts the intraday source with 900s cadence
- Frontend price matching uses closest-timestamp instead of date-string
matching, with 2h tolerance for intraday and 36h for daily windows
- Bumped market price fetch limit to 200 for intraday granularity
Trend charts blank:
- trend_windows uses upsert (1 row per ticker/window), so charts had
at most 1 data point. Added trend_history table (migration 024) that
appends every snapshot. New /api/trends/history endpoint serves the
time series. Frontend now uses useTrendHistory for charts and
useTrends for the latest summary card.
Competitor GUIDs:
- list_competitors query returned raw company_b_id UUIDs without
joining companies table. Added LEFT JOIN with CASE to resolve the
other company's ticker and legal_name. Updated Pydantic model to
include enriched fields. Frontend fallback changed from truncated
UUID to ticker/legal_name/Unknown.
The migration ran on every deploy, inserting duplicate queries each
time (96 instead of 12). Added UNIQUE constraint on name and changed
ON CONFLICT to reference it. Cleaned up 84 duplicates in DB.
The trading engine network policy only allowed egress on ports 443
(HTTPS) and 53 (DNS). Gmail SMTP uses port 587 (STARTTLS), causing
'Network is unreachable' when sending notifications.
Replaced the Gmail API (OAuth2) notification delivery with plain
SMTP using a Gmail app password. Much simpler setup — no Google
Cloud project, no OAuth2 flow, no extra dependencies.
- Rewrote _send_gmail() to use smtplib with smtp.gmail.com:587 TLS
- Added stonks-gmail-secrets to Helm chart (GMAIL_SENDER,
GMAIL_RECIPIENT, GMAIL_APP_PASSWORD)
- Added gmail secret to trading-engine deployment
- Updated runmefirst.sh to read gmail.app from kube dir
- Sender/recipient: celes@celestium.life
The ingestion worker creates an AlpacaBrokerAdapter but the pod
didn't have BROKER_API_KEY/BROKER_API_SECRET env vars, causing
401 Unauthorized on every broker source fetch. Added
stonks-broker-secrets to the ingestion service's secrets list.
The SQL Explorer was querying Trino which has zero tables. Rewrote to
use PostgreSQL directly:
Backend:
- GET /api/analytics/pg-schema: returns all public tables with column
names, types, and nullability from information_schema
- POST /api/analytics/pg-query: read-only SQL execution against
PostgreSQL with SELECT-only enforcement, auto LIMIT, and descriptive
error messages for syntax/table/query errors
Frontend:
- Schema browser shows all PostgreSQL tables with columns and types
- Click a table name → generates SELECT * FROM table LIMIT 100
- Pre-built Queries section with 12 seeded queries covering companies,
recommendations, trends, market prices, documents, global events,
trading decisions, ingestion health, reserve pool, sector exposure
- User-saved queries shown separately with delete buttons
- Chart builder, Monaco editor, and save functionality preserved
Migration 021: seeds 12 pre-built saved queries
Two tiers of market data:
1. Per-ticker prev bars (existing 50 sources, 15-min cadence) for
watchlist detail — trading decisions, stop-loss, position sizing
2. Grouped daily (new single source, once per day) for broad market
context — correlation analysis, sector rotation, competitive intel
Changes:
- Add grouped_daily endpoint to PolygonMarketAdapter with auto date
calculation (previous trading day, skip weekends)
- Add fetch_global_market_sources() to scheduler for sources without
company_id, scheduled once daily (86400s cadence)
- Update _persist_market_items to use item-level ticker from T field
and look up company_id dynamically for grouped daily bars
- Migration 020: make company_id nullable on sources and
market_snapshots tables, add grouped daily source row
- Fix backtest replay to query market_snapshots data->>'c' for prices
Phase 2 of the autonomous trading engine:
- Replace start()/stop() stubs with real async implementations
- Decision loop: polls recommendations from PostgreSQL, deduplicates
via Redis, evaluates through the full pipeline, submits orders to
stonks:queue:broker_orders
- Stop-loss monitor: fetches prices from Polygon API, checks crossings,
submits immediate sell orders, safety sell after 15 min without data
- Performance loop: computes metrics every 5 min during market hours,
persists daily snapshots at market close
- Risk tier scheduler: evaluates daily at 16:00 ET, persists tier changes
- Rebalance scheduler: evaluates Monday 09:45 ET, respects circuit breaker
- Notification dispatch: SNS + Gmail with rate limiting and retry
- Backtest replay: fetches historical data, simulates decisions, persists
- Real asyncpg/redis connections in FastAPI lifespan (graceful degradation)
- Migration 019: enable paper trading with conservative tier, 5 cap
- Added max_open_positions to TradingConfig with env var loading
- Phase 2 tasks added to autonomous-trading-engine spec
Celes Renata