mirror of
https://github.com/BigBodyCobain/Shadowbroker.git
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Shadowbroker
cfbeabda1e
* 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>
121 lines
3.9 KiB
Python
121 lines
3.9 KiB
Python
"""Micro rolling 3-day average for Strategic Risk Analytics."""
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from __future__ import annotations
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from datetime import date, timedelta
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from pathlib import Path
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import pytest
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from analytics.daily_store import DailyRegionReading, DailySnapshot, date_id, save_daily
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from analytics.gt_early_warning import GT_EarlyWarning
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from analytics.micro_rolling import (
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capture_daily_readings,
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compute_micro_view,
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enrich_heatmap_features,
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micro_rolling_report,
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)
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from analytics.settings import GTAnalyticsSettings
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@pytest.fixture()
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def daily_store(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> Path:
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store = tmp_path / "daily"
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monkeypatch.setenv("GT_DAILY_STORE_DIR", str(store))
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return store
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def _seed_engine() -> GT_EarlyWarning:
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engine = GT_EarlyWarning(GTAnalyticsSettings(enabled=True, base_prior=0.15))
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engine.process_feed_item(
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{
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"text": "Troop movement and military mobilization near border",
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"region": "ukraine",
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"source": "test",
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"source_type": "manual",
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}
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)
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return engine
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def _save_day(day: date, region: str, peak: float) -> None:
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day_key = date_id(day)
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snap = DailySnapshot(date=day_key, regions={})
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snap.regions[region] = DailyRegionReading(
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region=region,
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composite_risk=peak * 0.9,
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financial=0.15,
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unrest=0.15,
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conflict=peak,
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peak_score=peak,
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readings=1,
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last_captured_at=f"{day_key}T12:00:00+00:00",
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)
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save_daily(snap)
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def test_capture_daily_readings(daily_store: Path) -> None:
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engine = _seed_engine()
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result = capture_daily_readings(engine, when=date(2026, 6, 16))
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assert result["regions"] >= 1
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again = capture_daily_readings(engine, when=date(2026, 6, 16))
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assert again["regions"] >= 1
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def test_3day_rolling_average_and_ignition(daily_store: Path) -> None:
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region = "ukraine"
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today = date(2026, 6, 16)
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_save_day(today - timedelta(days=2), region, 0.20)
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_save_day(today - timedelta(days=1), region, 0.22)
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_save_day(today, region, 0.45)
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view = compute_micro_view(region, as_of=today, window_days=3)
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assert view is not None
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assert view.days_in_window == 3
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assert view.risk_3d_avg == pytest.approx(0.29, abs=0.01)
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assert view.spot_risk == 0.45
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assert view.risk_delta == pytest.approx(0.16, abs=0.01)
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assert view.ignition is True
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def test_enrich_heatmap_features(daily_store: Path) -> None:
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engine = _seed_engine()
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today = date(2026, 6, 16)
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capture_daily_readings(engine, when=today)
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heatmap = engine.get_risk_heatmap()
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enriched = enrich_heatmap_features(heatmap, as_of=today, window_days=3)
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feature = enriched["features"][0]
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props = feature["properties"]
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assert "risk_3d_avg" in props
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assert "risk_spot" in props
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assert "micro_ignition" in props
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def test_micro_rolling_report(daily_store: Path) -> None:
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region = "ukraine"
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today = date(2026, 6, 16)
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_save_day(today - timedelta(days=1), region, 0.21)
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_save_day(today, region, 0.40)
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report = micro_rolling_report(as_of=today, window_days=3, limit=5)
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assert report["mode"] == "micro_rolling"
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assert report["window_days"] == 3
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assert report["regions_tracked"] >= 1
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def test_openclaw_micro_command(daily_store: Path, monkeypatch: pytest.MonkeyPatch) -> None:
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from analytics.integration import reset_gt_engine
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from services.openclaw_channel import _dispatch_command
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monkeypatch.setenv("GT_ANALYTICS_ENABLED", "true")
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reset_gt_engine()
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result = _dispatch_command("gt_micro_rolling", {"window_days": 3, "compact": True})
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assert result["ok"] is True
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assert result["data"]["mode"] == "micro_rolling"
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def test_route_query_micro_intent() -> None:
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from services.openclaw_routing import route_query
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plan = route_query("Show GT rolling 3 day average and ignition regions")
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assert plan["recommended"]["cmd"] == "gt_micro_rolling" |