- Migration 031: change ai_agents/agent_variants max_tokens default
from 32768 to 4096 (32768 exceeds vLLM context window, causing
HTTP 400 on every extraction)
- API: re-enqueue approved orders to broker queue — previously
approved orders sat in DB with nothing to execute them
- values-beta: enable TRADING_ENABLED, update Alpaca paper keys
- Added pipelineEnabled flag to Helm values (default: true)
- Worker services (scheduler, ingestion, parser, extractor, aggregation,
recommendation, broker-adapter, lake-publisher) scale to 0 when disabled
- API services always run regardless of toggle
- Redis-based runtime toggle: POST /api/ops/pipeline/toggle
- Scheduler checks the flag before each cycle
- Frontend: green/red Pipeline ON/OFF button on the pipeline page
- Beta defaults to pipelineEnabled: false
- Base values.yaml: blanked external URLs (Ollama, Polygon, Alpaca)
so stages only connect to what they explicitly configure
Recovery sweeps and the retry endpoint now check a per-document Redis
key (SET NX, 1h TTL) before pushing to the queue. If the marker exists,
the doc is already enqueued and gets skipped. This prevents the
scheduler from re-enqueuing the same parsed docs every 5 minutes.
The pipeline health, SSE stream, and retry endpoints were hardcoding
'stonks:queue:{name}' but services use DEPLOY_STAGE prefix
('stonks:paper:queue:{name}'). Now uses queue_key() from redis_keys.py.
- POST /api/ops/pipeline/retry-failed endpoint resets extraction_failed
docs to parsed, deletes failed intelligence rows, and re-enqueues
them (batch of 200)
- Scheduler now auto-retries extraction_failed docs every ~10 minutes
(100 per cycle, 60-min cooldown per doc)
- Pipeline page shows 'Retry Failed (N)' button when extraction_failed
count > 0, with pending/success/error states
The inline catalyst_type query in GET /api/patterns/{ticker} referenced
dir.document_id which does not exist on document_impact_records. The
table links to documents via intelligence_id -> document_intelligence ->
document_id. Added the missing JOIN to match the pattern used in
_SELF_PATTERN_QUERY.
1. patterns endpoint: fix query referencing non-existent column
di.catalyst_type → dir.catalyst_type (column is on document_impact_records)
2. lockouts seed: use relative timestamps (now + 7d) so active lockout
is always in the future regardless of when tests run
3. create_agent: make slug optional with auto-generation from name
4. create_source: json.dumps(config) + ::jsonb cast for asyncpg JSONB compat
5. approval_expiry: return count as int (len(expired)) not the list itself
6. metrics_consistency: fix test assertion to match API contract
(total >= active + reserve, not total == active + reserve + unrealized)
- Add GET/PUT /api/admin/trading/approval-config endpoints
- Add POST/DELETE /api/admin/trading/lockouts endpoints
- Add useApprovalConfig, useUpdateApprovalConfig, useCreateLockout, useDeleteLockout hooks
- Add Paper Order Approval toggle card with confirmation dialog
- Add lockout creation form and delete button to Active Lockouts card
- Add MSW handlers for all new endpoints
- Add property-based tests for bug condition exploration and preservation
API was returning a flat array but frontend expects CompanyMacroImpacts
wrapper with exposure_profile and impacts fields. Also queries the
exposure_profiles table for the company's active profile.
- Trading page: added conservative/moderate/aggressive selector that
updates the trading engine config via PUT /api/trading/config
- Recommendations page: added risk tier dropdown that defaults to the
engine's current tier and filters recs by the tier's min_confidence
- Backend: added min_confidence query param to GET /api/recommendations
- Risk tier thresholds: conservative ≥0.75, moderate ≥0.55, aggressive ≥0.40
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
- New GET /api/market/prices/{ticker} endpoint serving OHLCV data from
market_snapshots, deduped by bar_timestamp
- New useMarketPrices hook in frontend
- Trend chart now shows price (purple line) on a right Y axis ($)
alongside trend metrics (%) on the left Y axis
- Custom tooltip formats price as dollars, metrics as percentages
- Price line uses connectNulls for days with missing bar data
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.
- Add dedup check in recommendation worker: skip generation when latest
rec for same ticker+window has identical action/mode/confidence
- Widen position sizing range (1-10% portfolio, 0.3-2% max loss) and
factor in trend strength + evidence count for differentiated sizing
- API returns only latest recommendation per ticker by default (DISTINCT ON)
to eliminate duplicate rows in the frontend list view
- Strip SQL comments (-- and /* */) before checking for SELECT,
so queries with leading comments don't get rejected
- Show the actual error detail from the API response instead of
generic 'API error 400' in the SQL Explorer UI
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
Celes Renata