_parse_classification_response receives raw model output (with thinking
tags, markdown fences, etc.) but was calling json.loads directly.
Now uses _strip_markdown_fences + _repair_json from the client module
before parsing, matching what _call_ollama does for extractions.
_call_ollama validates against the document extraction schema, which
doesn't match event classification output. The event classifier was
checking 'if attempt.error is None' before trying its own parsing,
so it never got to parse the valid event JSON — 956 consecutive
failures.
Now tries _parse_classification_response whenever raw_output exists,
regardless of the extraction validation error.
Redis uses separate env vars, not a single REDIS_URL. Script now
builds the connection string from REDIS_HOST, REDIS_PORT, REDIS_DB,
and REDIS_PASSWORD — matching how services/shared/config.py does it.
No more hardcoded passwords — pulls POSTGRES_HOST, POSTGRES_USER,
POSTGRES_PASSWORD, POSTGRES_DB, and REDIS_URL from the pod's
environment (injected by k8s secrets).
The repo is now private (BSL license), so pods need valid GHCR
credentials to pull images. runmefirst.sh now:
- Verifies the token can authenticate with GHCR
- Force-recreates the ghcr-credentials secret before Helm deploy
- Warns if the token is expired or missing scopes
- scripts/test_saved_queries.py: tests all 24 saved SQL explorer queries
against the live Trino API (all 24 pass)
- scripts/run_reclassify_and_reaggregate.sh: self-contained script to
re-classify macro events with updated prompts and re-aggregate all
tickers. Scales aggregation to 16 pods, monitors queues, scales back.
Licensed under Business Source License 1.1.
Copyright (c) 2025-2026 Celes Hillyerd. All rights reserved.
Production use requires written approval from the author.
Change Date: 2030-04-17 (converts to GPL v2+ after that).
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.
Backend: assemble_trend_with_evidence now deduplicates document IDs
via dict.fromkeys() (the rollup code already did this, but the base
assembly didn't — same doc could appear multiple times from different
intelligence extractions).
Frontend: Trends.tsx deduplicates via Set before rendering as a safety
net for existing data already stored with duplicates.
- EvidenceRef component now fetches document details via useDocument()
hook and displays the title instead of 'doc:43156423…'
- TanStack Query deduplicates and caches lookups for repeated doc IDs
- Pattern IDs still render as before (e.g. 'pattern META other (1d)')
- Override Trade button changed from brand-600 to red-600
The handler for /api/macro/impacts/:ticker was returning the impacts
array directly instead of { exposure_profile, impacts }. The frontend
destructures macroData.impacts which was undefined, falling back to
an empty array — so the Macro tab always showed 'No active macro impacts'
even with mock data present.
- recommendation worker: filter out non-UUID document IDs (synthetic
pattern:* IDs from competitive signals) before inserting into
recommendation_evidence table — the uuid cast was failing and
silently dropping all evidence rows
- wrap executemany in try/except so partial failures don't lose all evidence
- SqlExplorer: wrap Lucide icons in <span title=...> instead of passing
title prop directly (not supported by lucide-react, broke CI build)
- 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
- Pattern IDs (pattern:META:other:1d) shown as 'pattern META other (1d)'
- Document UUIDs shown as clickable 'doc:43156423…' links to document detail
- Unknown formats shown truncated as fallback
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
- Removed PUT /api/trading/capital (set capital) — only touched in-memory state
- Removed POST /api/trading/capital/adjust (add/withdraw) — same problem
- Reset endpoint now: liquidates Alpaca positions, cancels orders, clears DB,
then queries Alpaca for real portfolio_value to set engine capital
- Frontend: replaced CapitalCard with simple ResetCard (one button)
- Removed useSetTradingCapital and useAdjustCapital hooks
- Added cancel_all_orders() and close_all_positions() to AlpacaBrokerAdapter
- Reset endpoint creates a temporary adapter to call Alpaca DELETE /v2/orders
and DELETE /v2/positions before clearing DB and engine state
- Also clears positions table and processed_recommendation_ids on reset
- Broker reset is best-effort — DB/engine reset proceeds even if Alpaca fails
Agreement of 1-2 signals was inflating confidence to paper-eligible
levels (0.575) even with low credibility sources. Added log2-based
dampener that scales agreement contribution by unique source count,
saturating at n=7. Single signals now cap at 0.39 confidence,
2 signals at 0.49 — both correctly below paper threshold (0.50).
- Recommendation worker now resolves thesis-rewriter config from DB
and passes ollama_config to generate_recommendation. Thesis rewriting
is now active when the thesis-rewriter agent exists in ai_agents.
Refreshes config every 50 jobs.
- Event classifier now resolves its own config separately from the
document extractor via 'event-classifier' slug. Uses a separate
OllamaClient when the model differs from the extractor. Refreshes
alongside the extractor every 100 jobs.
- Document extractor was already wired (existing code).
- Added 8 unit tests for AgentConfigResolver covering: DB resolution,
variant override, not-found, DB errors, TTL caching, cache refresh,
and invalidation.
- 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).
Three distinct capital operations on the Trading Controls page:
- Set Capital: overwrites pool balances to a new amount (existing)
- Add/Withdraw: adjusts active pool by a delta without touching
positions, orders, or history. Validates sufficient balance for
withdrawals. Logged to reserve_pool_ledger as manual_adjustment.
- Reset Everything: nuclear option — deletes all positions, orders,
trading decisions, stop levels, snapshots, backtests, notifications,
and circuit breaker events, then resets capital fresh. Red button
with double-confirmation dialog.
Backend: POST /api/trading/capital/adjust and POST /api/trading/reset
Frontend: CapitalCard rebuilt with three sections and confirmation UIs
Celes Renata