Feat/gt analytics openclaw (#392)

* feat(telegram): auto-translate OSINT channel posts to English Cherry-picked from @Bobpick PR #391 (telegram-only slice): server-side translation during fetch, SHOW ORIGINAL toggle in TelegramOsintPopup, and on-demand /api/telegram-feed?lang=. Co-authored-by: Robert Pickett <bobpickettsr@yahoo.com> Co-authored-by: Cursor <cursoragent@cursor.com> * feat(gt): experimental Derived OSINT analytics with lean-node safeguards Cherry-picked from @Bobpick PR #391 (GT + OpenClaw slice): Bayesian strategic-risk engine, map overlay, OpenClaw commands, and telegram_rhetoric watchdog. Off by default (GT_ANALYTICS_ENABLED=false, gt_risk layer false). 1 vCPU nodes get cgroup detection, UI warning on layer toggle, and lean profile that skips scheduled ingest/Louvain unless GT_ANALYTICS_ACK_LOW_CPU=true. Backtest HUD removed from dashboard (OpenClaw/API regression only). Co-authored-by: Robert Pickett <bobpickettsr@yahoo.com> Co-authored-by: Cursor <cursoragent@cursor.com> --------- Co-authored-by: Robert Pickett <bobpickettsr@yahoo.com> Co-authored-by: Cursor <cursoragent@cursor.com>
2026-08-22 18:37:25 +02:00 · 2026-06-16 17:05:46 -06:00
parent 9c5a4054f6
commit cfbeabda1e
69 changed files with 8101 additions and 77 deletions
@@ -0,0 +1,121 @@
+"""Micro rolling 3-day average for Strategic Risk Analytics."""
+
+from __future__ import annotations
+
+from datetime import date, timedelta
+from pathlib import Path
+
+import pytest
+
+from analytics.daily_store import DailyRegionReading, DailySnapshot, date_id, save_daily
+from analytics.gt_early_warning import GT_EarlyWarning
+from analytics.micro_rolling import (
+    capture_daily_readings,
+    compute_micro_view,
+    enrich_heatmap_features,
+    micro_rolling_report,
+)
+from analytics.settings import GTAnalyticsSettings
+
+
+@pytest.fixture()
+def daily_store(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> Path:
+    store = tmp_path / "daily"
+    monkeypatch.setenv("GT_DAILY_STORE_DIR", str(store))
+    return store
+
+
+def _seed_engine() -> GT_EarlyWarning:
+    engine = GT_EarlyWarning(GTAnalyticsSettings(enabled=True, base_prior=0.15))
+    engine.process_feed_item(
+        {
+            "text": "Troop movement and military mobilization near border",
+            "region": "ukraine",
+            "source": "test",
+            "source_type": "manual",
+        }
+    )
+    return engine
+
+
+def _save_day(day: date, region: str, peak: float) -> None:
+    day_key = date_id(day)
+    snap = DailySnapshot(date=day_key, regions={})
+    snap.regions[region] = DailyRegionReading(
+        region=region,
+        composite_risk=peak * 0.9,
+        financial=0.15,
+        unrest=0.15,
+        conflict=peak,
+        peak_score=peak,
+        readings=1,
+        last_captured_at=f"{day_key}T12:00:00+00:00",
+    )
+    save_daily(snap)
+
+
+def test_capture_daily_readings(daily_store: Path) -> None:
+    engine = _seed_engine()
+    result = capture_daily_readings(engine, when=date(2026, 6, 16))
+    assert result["regions"] >= 1
+    again = capture_daily_readings(engine, when=date(2026, 6, 16))
+    assert again["regions"] >= 1
+
+
+def test_3day_rolling_average_and_ignition(daily_store: Path) -> None:
+    region = "ukraine"
+    today = date(2026, 6, 16)
+    _save_day(today - timedelta(days=2), region, 0.20)
+    _save_day(today - timedelta(days=1), region, 0.22)
+    _save_day(today, region, 0.45)
+
+    view = compute_micro_view(region, as_of=today, window_days=3)
+    assert view is not None
+    assert view.days_in_window == 3
+    assert view.risk_3d_avg == pytest.approx(0.29, abs=0.01)
+    assert view.spot_risk == 0.45
+    assert view.risk_delta == pytest.approx(0.16, abs=0.01)
+    assert view.ignition is True
+
+
+def test_enrich_heatmap_features(daily_store: Path) -> None:
+    engine = _seed_engine()
+    today = date(2026, 6, 16)
+    capture_daily_readings(engine, when=today)
+    heatmap = engine.get_risk_heatmap()
+    enriched = enrich_heatmap_features(heatmap, as_of=today, window_days=3)
+    feature = enriched["features"][0]
+    props = feature["properties"]
+    assert "risk_3d_avg" in props
+    assert "risk_spot" in props
+    assert "micro_ignition" in props
+
+
+def test_micro_rolling_report(daily_store: Path) -> None:
+    region = "ukraine"
+    today = date(2026, 6, 16)
+    _save_day(today - timedelta(days=1), region, 0.21)
+    _save_day(today, region, 0.40)
+
+    report = micro_rolling_report(as_of=today, window_days=3, limit=5)
+    assert report["mode"] == "micro_rolling"
+    assert report["window_days"] == 3
+    assert report["regions_tracked"] >= 1
+
+
+def test_openclaw_micro_command(daily_store: Path, monkeypatch: pytest.MonkeyPatch) -> None:
+    from analytics.integration import reset_gt_engine
+    from services.openclaw_channel import _dispatch_command
+
+    monkeypatch.setenv("GT_ANALYTICS_ENABLED", "true")
+    reset_gt_engine()
+    result = _dispatch_command("gt_micro_rolling", {"window_days": 3, "compact": True})
+    assert result["ok"] is True
+    assert result["data"]["mode"] == "micro_rolling"
+
+
+def test_route_query_micro_intent() -> None:
+    from services.openclaw_routing import route_query
+
+    plan = route_query("Show GT rolling 3 day average and ignition regions")
+    assert plan["recommended"]["cmd"] == "gt_micro_rolling"