Machine learning platform for market analysis and forecasting, with a focus on stock volatility prediction, market trend forecasting, and portfolio optimization.
MeridianAlgo/AraAI erreicht einen Gesundheitsindex von 57 von 100 und liegt damit im Bereich Mittel. Am stärksten schneidet es bei Vitality (84/100) ab, am schwächsten bei Security (33/100). Zuletzt vor 12 Tagen aktualisiert. Ein einzelner Mitwirkender trägt den Großteil der jüngsten Arbeit.
57
gesamt / 100
Mittel
Software-Gesundheitsindex
Metriken werden auf einer standardisierten Skala von 1–100 in gewichtete Kategorien gruppiert. Der Gesamtwert beginnt als ihr gewichtetes Mittel, kalibriert auf die Verteilung des öffentlichen Registers, sodass die Stufen Perzentilbedeutung tragen; sobald öffentliche Evidenz die Richtlinie für Hochrisikojurisdiktionen auslöst, wird die Bewertung angepasst und erhält die Obergrenze Gefährdet von 34.
57
Außergewöhnlich93-100Die Spitzengruppe des Registers (≈ obere 5 %); erfüllt im Wesentlichen alle geprüften Kriterien
Gut65-79Gesund; Lücken sind begrenzt und beherrschbar
Mittel50-64Akzeptabel mit deutlichen Lücken; Überprüfung empfohlen
Schwach35-49Wesentliche Schwächen in mehreren Bereichen
Gefährdet20-34Erhebliche Schwächen; eine Übernahme erfordert Vorsicht
Kritisch1-19Schwerwiegende Probleme (aufgegeben, nur ein Maintainer, keine Hygiene)
Bewertungsprofil
Jede Achse ist eine Kategorie. Die Form zählt mehr als der Durchschnitt — ein gesundes Projekt füllt die gesamte Fläche, während ein Profil aus Spitzen und Kratern bedeutet, dass Stärke in einer Dimension Risiken in einer anderen verdeckt.
Der gewichtete Gesamtwert 55 wird auf der veröffentlichten Indexskala auf 57 kalibriert (Register-Kalibrierung 2026-08-02).
Dieses Repository wird von einer Organisation getragen — geteilte, rechenschaftspflichtige Trägerschaft, die jeden einzelnen Maintainer überdauern kann.
Release-Rhythmus — ein Release etwa alle 23,5 Tage
0/10
OpenSSF Scorecard: Signed-Releases — keine Daten
Verwendete Eingangsdaten
releases_count
3
latest_release_tag
v1.2.1
releases_from_tags
nein
days_since_latest_release
12
mean_days_between_releases
23,5
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): OpenSSF Scorecard: Signed-Releases. Die verbleibenden Gewichte wurden renormalisiert.
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): ci_tests, packaging, signed_releases. Die verbleibenden Gewichte wurden renormalisiert.
Wie gut ist das Repository dafür ausgestattet, mit KI-Coding-Agenten entwickelt und gepflegt zu werden? Trägt ein bewusst kleines Gewicht (4 %): Agenten-Tooling ist ein echtes Pflegesignal, doch ein Repository ohne jedes Signal kann weiterhin 100/100 erreichen.
Typprüfbarer Code — Python ohne Typprüfungs-Konfiguration
52.8/55
Handhabbare Dateigrößen — 1/25 Quelldateien über 60 KB
Verwendete Eingangsdaten
primary_language
Python
largest_source_bytes
70.050
source_files_sampled
25
oversized_source_files
1
Eckdaten
15GitHub-Sterne
4Mitwirkende
178Commits, letzte 12 Monate
12Tage seit letztem Push
3Releases
1Bus-Faktor
0offene Issues
PyPIPaket-Ökosysteme
Warnungen zur Datenerhebung
Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
Could not fetch pypi package 'ara-ai' from its registry
GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository
Weitere Details
Stern- und Fork-Verlauf 0 ★ / 4 ⇿
0Sterne
4Forks
2Releases
Wann jeder Stern und Fork hinzugefügt wurde, von GitHub erfasst und nach Tagen gruppiert. Das kumulierte Wachstum steht direkt über den täglichen Zugängen, aus denen es besteht, sodass beide gegeneinander lesbar sind: stetiger organischer Zuwachs sieht ganz anders aus als ein abrupter, kurzlebiger Ausschlag. Wo dieser Unterschied messbar ist, wird er als Wachstumsauthentizität ausgewiesen.
Major 1Minor 0Patch 1
OpenSSF Scorecard 3.3 / 10
3.3Gesamtwert
Unabhängige, werkzeugneutrale Sicherheitsbewertung durch das quelloffene OpenSSF Scorecard. Jede Prüfung honoriert eine Sicherheits-Praxis, nicht das Werkzeug eines bestimmten Anbieters. Prüfungen, die Scorecard nicht ermitteln konnte, sind mit k. A. markiert und vom Sicherheitswert ausgeschlossen (nie als null gezählt).Scorecard v5.5.0 · 2026-08-02 21:14 UTC
Der aufgelöste Abhängigkeitssatz konnte für diesen Bericht nicht erhoben werden: GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository
JSON-Rohbericht maschinenlesbar
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"body": "… [skip ci]\n\nThe model predicted 'down' ~92% of the time and scored below a coin flip\nlive, despite claiming 74% validation accuracy. Root cause was data\ncontamination in the training pipeline:\n\n- unified_ml: windows + indicators + next-day returns were computed over\n one flat array of ~100 symbols\n[…]\nmixing or\n split-induced fake returns).\n- train_stocks/forex: load filters interval='1d'.\n- large_torch_model: scaler fit on train split only (was leaking val stats);\n stock target clip 1.0 -> 0.25.",
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"body": "0.45 still flags normal market noise. At n=90 samples, 0.40 is ~2 sigma\nbelow chance — it catches genuinely degenerate outputs without tripping\non models that are simply struggling in hard-to-predict markets.",
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"body": "n=40 samples has too much variance — a model at true 50% accuracy\nfails the old threshold ~30% of the time by chance. 90 samples halves\nthat false-failure rate. Floor of 0.45 still catches degenerate outputs.",
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"headline": "fix: raise n_steps to 90 and lower live accuracy floor to 0.45",
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"is_bot": false,
"headline": "fix: patch daily test workflow after first run",
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"oid": "dc5edb3c1891732f2b2e1ecff85758b33de4df99",
"body": "…s actually train (v5.2.2)",
"is_bot": false,
"headline": "feat: step-based LR schedule + raise step budget to 300 so capped run…",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-05-26T17:22:10Z",
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"oid": "1bf0cfbdea86eb4b63f62bb281351316997dbd95",
"body": null,
"is_bot": false,
"headline": "chore: remove stale datasets and deprecated revolutionary_model shim",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-05-26T16:33:38Z",
"body_truncated": false,
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"oid": "c4d519c6b3d76aff2759fafd618f40062eb880d9",
"body": "…HF push (v5.2.1)",
"is_bot": false,
"headline": "fix: batch validation forward pass to stop CI runner OOM-kill before …",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-05-26T16:25:40Z",
"body_truncated": false,
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{
"oid": "4af7b95f73284fa10cb6274bfbf4c63bfc819b3d",
"body": "…ation script",
"is_bot": false,
"headline": "release v5.2.0 — bump version, fix readme badges, drop duplicate migr…",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-05-24T02:59:29Z",
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"headline": "style: auto-format and lint [skip ci]",
"author_name": "GitHub Action",
"author_login": "actions-user",
"committed_at": "2026-05-24T02:54:59Z",
"body_truncated": false,
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{
"oid": "4681bca4a40b0e657135074ee63deab6d54fd28f",
"body": "…migration script + rename scripts",
"is_bot": false,
"headline": "consolidate to single-job workflow + per-step comet logging + legacy …",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-05-24T02:54:41Z",
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"body_truncated": false,
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"oid": "36d744270b979684f94c5621b2600ac70b1e5092",
"body": "Confirmed via Hugging Face that no pushes have landed since 2026-05-15\neven though training loops have been completing 70 steps cleanly. The\ntraining script gets SIGTERMed within ~25 seconds of 'Step limit\nreached' — before the 4096-sample CPU validation, Comet log_model\n(132 MB upload), final 2048-\n[…]\nantees the artifact step\nfinds a valid checkpoint when we don't.\n\nAlso added flush=True to the step/time limit print lines so CI logs\nshow the message immediately, not on Python's stdout buffer flush.",
"is_bot": false,
"headline": "fix(train): safety-save model BEFORE post-train validation/Comet",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-05-24T02:44:34Z",
"body_truncated": true,
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{
"oid": "87455e6539c1e7303dd09b28d9c106143d203bf0",
"body": "Every stage now shows what it's doing:\n\nSetup job\n- Run Information: run#, trigger, commit, branch, timestamp, CPU/RAM/disk\n- Install Dependencies: show package versions after install\n- Free Disk Space: before + after disk stats\n- Fetch Data: elapsed time\n- Check if Data was Fetched: full per-symbol\n[…]\n timestamp\n- Model Download Status: confirm artifact arrived + size\n- Upload to HF Hub: show file size, repo, start time, elapsed time\n\nCleanup job\n- Pipeline Summary: all four job results at a glance",
"is_bot": false,
"headline": "feat(ci): add comprehensive logging to stock + forex workflows",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-05-24T01:27:41Z",
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"body": "…ompletion\n\nTraining completes 70 steps in ~31min then needs unbounded time for\npost-training validation, atomic model save, and Comet log_model upload\n(~130 MB .pt to Comet). The 75-min step timeout was killing the process\nafter training finished but before the model was saved, causing:\n - artifac\n[…]\nted\n\nFix:\n- Remove timeout-minutes from Train Model step (both forex + stocks)\n- Raise job timeout 95 -> 360 min (GitHub public-repo maximum)\n- Only --max-steps 70 governs when the training loop exits",
"is_bot": false,
"headline": "fix(ci): remove step timeout -- let 70 steps + post-training run to c…",
"author_name": "MeridianAlgo",
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"committed_at": "2026-05-24T01:20:54Z",
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"headline": "style: auto-format and lint [skip ci]",
"author_name": "GitHub Action",
"author_login": "actions-user",
"committed_at": "2026-05-22T17:28:17Z",
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"oid": "423bd8b072e49cc648f9795be740cf30351bff00",
"body": "…imit)\n\n- Remove --max-time from both training scripts (was firing at step 47,\n before 70 steps could complete, causing the post-training validation\n to run past the step timeout and get canceled)\n- Add --max-steps 70 to both workflows — training stops cleanly at\n exactly step 70 then saves + pus\n[…]\n max_time_minutes=None (unlimited) in both training functions\n- Expand Train Model step timeout 55→75min, job timeout 75→95min to\n accommodate 70 steps (~47min) + validation/save/Comet flush (~15min)",
"is_bot": false,
"headline": "switch CI from time-based to step-based training (70 steps, no time l…",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-05-22T17:27:59Z",
"body_truncated": true,
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"oid": "2ba096a6167312a3615d0304f41edce7caeaf5ca",
"body": "…+ push HF on partial runs\n\nThree coupled changes so a training run that hits the time budget still\nsaves, gets logged, and ends up on Hugging Face:\n\n1. Step timeout 38min -> 55min, script --max-time 35min -> 32min.\n The script stopped training at 33min and then ran final validation\n (forward pa\n[…]\ndel.outcome ==\n 'success' + hashFiles). With the atomic _save_model + SIGTERM handler\n already in place, a partial-but-improved checkpoint reaches HF on\n timeout runs instead of being discarded.",
"is_bot": false,
"headline": "fix(ci): stop exit-143 on training cleanup + register model in Comet …",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-05-22T16:04:33Z",
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"headline": "style: auto-format and lint [skip ci]",
"author_name": "GitHub Action",
"author_login": "actions-user",
"committed_at": "2026-05-22T13:39:21Z",
"body_truncated": false,
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},
{
"oid": "06d11d1c9562170d3a07115fec755bc714c0bbad",
"body": "One-shot maintenance script: cancels all in-progress runs and deletes\nevery run for non-lint workflows in MeridianAlgo/AraAI, so the Actions\ntab shows a clean slate for the v5 release (lint runs are preserved).\n\n- GitHub REST API directly (no gh CLI dependency)\n- --dry-run flag to preview cancel/delete plan\n- Cancels active runs, waits, then deletes; gentle pacing between calls\n- Token from $GITHUB_TOKEN / $GH_TOKEN or --token; needs repo+workflow",
"is_bot": false,
"headline": "chore: add scripts/clean_workflow_runs.py for v5 history wipe",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-05-22T13:39:04Z",
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"body": null,
"is_bot": false,
"headline": "style: auto-format and lint [skip ci]",
"author_name": "GitHub Action",
"author_login": "actions-user",
"committed_at": "2026-05-22T13:08:11Z",
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{
"oid": "197873c7d1bbefadf3e57e0c4cf97f95dcdf7cbb",
"body": "Runs were dying at the 50-min job timeout (exit 143 / \"operation was\ncanceled\") because the math under-counted setup time: ~17min for\ninstall + artifact download + HF model fetch, then 33min of training,\nthen validation+save pushed total past 50min.\n\n- meridian-stocks.yml / meridian-forex.yml: timeo\n[…]\nlocal variable 'ema_decay' where it is not associated\nwith a value\": the Comet log_parameters block referenced ema_decay\nbefore it was defined further down. Moved the assignment above the\nComet block.",
"is_bot": false,
"headline": "fix(ci): raise training job timeout to 75min and fix ema_decay NameError",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-05-22T13:07:49Z",
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{
"oid": "89f8e421e505d1f28bef647c3d09ddacd2d9ce48",
"body": "…y migration\n\nFix recurring \"operation was canceled\" CI failure at ~44min by making the\ntraining pipeline signal-safe and tightening the time budget:\n\n- SIGTERM/SIGINT handler in AdvancedMLSystem.train sets a shutdown flag\n the step loop polls; final save always runs before exit\n- _save_model is no\n[…]\n,\n comet_ai_token) via load_dotenv at script start\n- MODEL_CARD refreshed: new layout, hardening notes, Comet links, v5.1.0 metadata\n\nVersion bumps: pyproject.toml + meridianalgo/__init__.py -> 5.1.0",
"is_bot": false,
"headline": "v5.1.0: harden CI training pipeline + full Comet telemetry + HF legac…",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-05-21T16:58:34Z",
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},
{
"oid": "5546666c0f061e66b8dc48c1a731b94ed8a3fc15",
"body": null,
"is_bot": false,
"headline": "fix: extend forex and stock training job timeouts to 120 minutes",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-05-17T23:38:41Z",
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"headline": "style: auto-format and lint [skip ci]",
"author_name": "GitHub Action",
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"committed_at": "2026-05-15T19:08:27Z",
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{
"oid": "f47595c607dd8547941d795814e0f134f4cf3d4a",
"body": "The alias was a leftover compat shim in the try-block; MeridianModel is\nthe only name used in this file. Also fixes ruff I001 import sort in\nrevolutionary_model.py.",
"is_bot": false,
"headline": "fix: remove unused RevolutionaryFinancialModel import alias (ruff F401)",
"author_name": "Ishaan",
"author_login": "ishaanman7898",
"committed_at": "2026-05-15T19:08:09Z",
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{
"oid": "d3e258aececdf98b55fa5da04d5302713ac6681d",
"body": "- CHANGELOG.md: full version history from v1.0.0-Beta to v5.0.0, built\n from all git tags and GitHub releases\n- QUICK_START.md: rewritten with accurate v5.0 specs, correct training\n commands, troubleshooting for known pre-v5 bugs\n- MODEL_CARD.md: updated to v5.0 — MeridianModel, checkpoint format\n\n[…]\nth, class weighting,\n logit scaling rationale, direction metrics table\n- INDEX.md (new): single-page documentation index with source layout\n- LICENSE: fix year (2025→2026) and placeholder GitHub URLs",
"is_bot": false,
"headline": "docs: comprehensive v5.0 documentation overhaul",
"author_name": "Ishaan",
"author_login": "ishaanman7898",
"committed_at": "2026-05-15T19:05:14Z",
"body_truncated": true,
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},
{
"oid": "10c85542c70ce70efc2b27a2a455658590ccb489",
"body": "Documents all 7 training bugs fixed in v5.0, the architecture rename\nfrom RevolutionaryFinancialModel to MeridianModel, hourly CI schedule,\nCPU vs GPU model specs, checkpoint format reference, and updated project\nstructure.",
"is_bot": false,
"headline": "docs: update README for MeridianModel v5.0",
"author_name": "Ishaan",
"author_login": "ishaanman7898",
"committed_at": "2026-05-15T18:55:50Z",
"body_truncated": false,
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},
{
"oid": "404e0ed76343122c86fa1545ea5e31f0dff52683",
"body": "Architecture rename:\n- meridian_model.py: new canonical file — classes MeridianModel, MeridianBlock\n- revolutionary_model.py: backward-compat shim (3-line re-export)\n- Checkpoint string: \"MeridianModel-2026\" (v5.0); _load_model accepts both old\n \"RevolutionaryFinancialModel-2026\" and new string so \n[…]\nremove hardcoded dim=384/num_heads=6/version=\"4.1\"\n so new models (dim=256/4/5.0) and old HF models both pass\n- Accepts architecture strings \"MeridianModel-2026\" or \"RevolutionaryFinancialModel-2026\"",
"is_bot": false,
"headline": "feat: rename to MeridianModel v5.0, hourly CI, LR warmup",
"author_name": "Ishaan",
"author_login": "ishaanman7898",
"committed_at": "2026-05-15T18:26:33Z",
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"oid": "ff044c6313eb36169bce3ff2568f25109be20bdd",
"body": "Without this, new models saved with mamba_state_dim=4 would build the wrong\ngraph shape when the directional-accuracy tests reconstruct the model for\ninference, causing a state-dict load mismatch. Defaults to 16 so existing\nHuggingFace checkpoints (which predate this field) continue to load correctly.",
"is_bot": false,
"headline": "fix: pass mamba_state_dim to RevolutionaryFinancialModel in signal tests",
"author_name": "Ishaan",
"author_login": "ishaanman7898",
"committed_at": "2026-05-15T16:36:40Z",
"body_truncated": false,
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"headline": "style: auto-format and lint [skip ci]",
"author_name": "GitHub Action",
"author_login": "actions-user",
"committed_at": "2026-05-15T16:35:48Z",
"body_truncated": false,
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{
"oid": "4902160f30b330654ee6467eab45a20b044168cf",
"body": "Architecture changes (speed):\n- RevolutionaryFinancialModel: thread mamba_state_dim through to MambaBlock\n so state_dim is configurable without rebuilding the graph\n- New CPU training config: dim=256, num_heads=4, use_mamba=False, mamba_state_dim=4\n (~11M params, ~27 min/epoch on 60K samples vs 23\n[…]\n 180s time-limit buffer (from 120s) to guarantee validation always fits\n- Checkpoint: save actual use_mamba from model (was hardcoded True)\n and persist mamba_state_dim for faithful round-trip reload",
"is_bot": false,
"headline": "perf+fix: CPU-optimised architecture + 7 training correctness fixes",
"author_name": "Ishaan",
"author_login": "ishaanman7898",
"committed_at": "2026-05-15T16:32:19Z",
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{
"oid": "a5eeb6b082cc8b60b05d7fac485b684f786725e5",
"body": "* fix: clip target return outliers, remove min-max remap, add model test suite\n\nThe trained checkpoints on HuggingFace shipped with metadata showing\nbest_val_loss=Infinity across all 50 training runs and direction_accuracy=0\nbecause the target distribution was poisoned by single bad price ticks\n(sto\n[…]\nt CI training run uses the fixed code path.\n\n* style: auto-format and lint [skip ci]\n\n---------\n\nCo-authored-by: MeridianAlgo <meridianalgo@gmail.com>\nCo-authored-by: GitHub Action <action@github.com>",
"is_bot": false,
"headline": "fix: clip target return outliers; add rigorous model test suite (#154)",
"author_name": "Ishaan M.",
"author_login": "ishaanman7898",
"committed_at": "2026-05-01T13:05:48Z",
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"body": null,
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"headline": "style: auto-format and lint [skip ci]",
"author_name": "GitHub Action",
"author_login": "actions-user",
"committed_at": "2026-04-07T23:57:18Z",
"body_truncated": false,
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{
"oid": "ff417e840bde00ec372eeb959e66f9de549c1730",
"body": null,
"is_bot": false,
"headline": "fix: remove unused mem_model_mb variable (ruff F841)",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-04-07T23:56:46Z",
"body_truncated": false,
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{
"oid": "22e2a896a86590de24d13632091edce221e5c9ba",
"body": "X was deleted (line 557) to free numpy memory but still referenced in\n_update_metadata. Save n_samples before del and pass that instead.\n\nAlso update MODEL_CARD.md with correct v4.1 specs (45M params, not 388M).",
"is_bot": false,
"headline": "fix: resolve UnboundLocalError on X after del in training loop",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-04-07T23:54:08Z",
"body_truncated": false,
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},
{
"oid": "2caf5092a82a9433bfcddb8814bcdf0a63fef74b",
"body": "- --max-time 45 (45min training from script start)\n- timeout-minutes: 60 (15min buffer for CI overhead)\n- cancel-in-progress: false (queued runs wait, never kill running ones)\n- Stocks every 6h at :00, Forex every 6h at :30",
"is_bot": false,
"headline": "fix: simple 45min training / 60min timeout, no cancel-in-progress",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-04-07T01:28:42Z",
"body_truncated": false,
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},
{
"oid": "716fcdd880ea5a7d9e560f1a7a19e977eaf768fd",
"body": "- float32 everywhere (was float64) — halves dataset memory\n- Delete numpy arrays after torch conversion (del X, y)\n- In-place normalization (X_tensor.sub_().div_()) — no copy\n- Cap dataset at 300K samples (~1.5GB) with warning\n- Free feature_matrix after building X windows\n- Log memory usage for diagnostics\n\nPeak memory estimate with 50 stocks:\n Before: ~10.5GB (float64 + copies) → OOM\n After: ~3.5GB (float32 + in-place) → fits in 7GB",
"is_bot": false,
"headline": "fix: fit training within 7GB GitHub Actions RAM limit",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-04-07T01:25:07Z",
"body_truncated": false,
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{
"oid": "931ff50b6eb24a9118b312dc54901f60e17ec004",
"body": null,
"is_bot": false,
"headline": "style: auto-format and lint [skip ci]",
"author_name": "GitHub Action",
"author_login": "actions-user",
"committed_at": "2026-04-07T01:19:35Z",
"body_truncated": false,
"is_coding_agent": false
},
{
"oid": "35fef6b1c3b01d9fd73d9cd95f2564f9b1a2a2f1",
"body": "Workflows:\n- timeout-minutes: 350, --max-time 320 (5h20m training budget)\n- Concurrency groups: new scheduled runs cancel stale in-progress ones\n- Staggered crons: stocks at 0/6/12/18h, forex at 3/9/15/21h\n- Workflow dispatch now accepts epochs and max_time inputs\n- Smart issue handling: no duplicat\n[…]\ning time\n- _update_metadata() extracted for checkpoint + final save reuse\n- Training history capped at 50 entries to prevent unbounded growth\n- Patience increased to 20 epochs for longer training runs",
"is_bot": false,
"headline": "feat: robust training pipeline with smart scheduling and issue handling",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-04-07T01:19:23Z",
"body_truncated": true,
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},
{
"oid": "eb9cf3c7dbcb3b44a53c8c6e2d1935a03b52d314",
"body": "- timeout-minutes: 60 was too tight — CI overhead (checkout, install,\n download model) takes ~15min before script starts, leaving no room\n- Now: timeout-minutes: 340, --max-time 320 (5h20m training budget)\n- Cron reduced to every 6h to match longer training runs\n- Final validation capped at 2048 samples and skipped if time is tight\n- global_start_time ensures Python never overshoots its own budget",
"is_bot": false,
"headline": "fix: increase job timeout to 340min, train for 5h+ per run",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-04-07T01:12:07Z",
"body_truncated": false,
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},
{
"oid": "8784faabd00deeb92f8860dedb910677b557407b",
"body": "The MeridianAlgo account token didn't have write access.\nSwitched all model download/upload references to meridianal/ARA.AI\nwhere the write token works.",
"is_bot": false,
"headline": "fix: switch HuggingFace repo to meridianal/ARA.AI",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-04-06T13:30:15Z",
"body_truncated": false,
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{
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"headline": "style: auto-format and lint [skip ci]",
"author_name": "GitHub Action",
"author_login": "actions-user",
"committed_at": "2026-04-05T23:30:29Z",
"body_truncated": false,
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{
"oid": "0a688b926a0414994d43c17335f1d78842af42d3",
"body": "step_limit_reached flag is also set by time-based mid-epoch stops,\nbut the print statement assumed max_steps was always set — caused\nTypeError dividing by None.",
"is_bot": false,
"headline": "fix: prevent crash when time limit stops training before step limit",
"author_name": "MeridianAlgo",
"author_login": "MeridianAlgo-Developer",
"committed_at": "2026-04-05T23:30:09Z",
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{
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{
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"documentation_url": "https://github.com/ossf/scorecard/blob/c395761df6afe1a69e476bc60a013a94bcbc153f/docs/checks.md#sast"
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{
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{
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{
"key": "issue_template",
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],
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{
"key": "governance",
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"name": "Sustainability & Governance",
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{
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{
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{
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{
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"points": 0,
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"key": "stewardship",
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{
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],
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{
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},
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"status": "partial",
"details": [],
"max_points": 7.5
},
{
"key": "ci_tests",
"name": "CI-Tests",
"detail": "no pull request found",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 2.5
},
{
"key": "cii_best_practices",
"name": "CII-Best-Practices",
"detail": "no effort to earn an OpenSSF best practices badge detected",
"points": 0,
"status": "missed",
"details": [],
"max_points": 2.5
},
{
"key": "code_review",
"name": "Code-Review",
"detail": "Found 0/30 approved changesets -- score normalized to 0",
"points": 0,
"status": "missed",
"details": [],
"max_points": 7.5
},
{
"key": "contributors",
"name": "Contributors",
"detail": "project has 2 contributing companies or organizations -- score normalized to 6",
"points": 1.5,
"status": "partial",
"details": [],
"max_points": 2.5
},
{
"key": "dangerous_workflow",
"name": "Dangerous-Workflow",
"detail": "no dangerous workflow patterns detected",
"points": 10,
"status": "met",
"details": [],
"max_points": 10
},
{
"key": "dependency_update_tool",
"name": "Dependency-Update-Tool",
"detail": "no update tool detected",
"points": 0,
"status": "missed",
"details": [],
"max_points": 7.5
},
{
"key": "fuzzing",
"name": "Fuzzing",
"detail": "project is not fuzzed",
"points": 0,
"status": "missed",
"details": [],
"max_points": 5
},
{
"key": "license",
"name": "License",
"detail": "license file detected",
"points": 2.2,
"status": "partial",
"details": [],
"max_points": 2.5
},
{
"key": "maintained",
"name": "Maintained",
"detail": "30 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 10",
"points": 7.5,
"status": "met",
"details": [],
"max_points": 7.5
},
{
"key": "packaging",
"name": "Packaging",
"detail": "packaging workflow not detected",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 5
},
{
"key": "pinned_dependencies",
"name": "Pinned-Dependencies",
"detail": "dependency not pinned by hash detected -- score normalized to 0",
"points": 0,
"status": "missed",
"details": [],
"max_points": 5
},
{
"key": "sast",
"name": "SAST",
"detail": "no SAST tool detected",
"points": 0,
"status": "missed",
"details": [],
"max_points": 5
},
{
"key": "security_policy",
"name": "Security-Policy",
"detail": "security policy file not detected",
"points": 0,
"status": "missed",
"details": [],
"max_points": 5
},
{
"key": "signed_releases",
"name": "Signed-Releases",
"detail": "no releases found",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 7.5
},
{
"key": "token_permissions",
"name": "Token-Permissions",
"detail": "detected GitHub workflow tokens with excessive permissions",
"points": 0,
"status": "missed",
"details": [],
"max_points": 7.5
},
{
"key": "vulnerabilities",
"name": "Vulnerabilities",
"detail": "36 existing vulnerabilities detected",
"points": 0,
"status": "missed",
"details": [],
"max_points": 7.5
}
]
},
{
"key": "high_risk_jurisdiction_exposure",
"band": "exceptional",
"name": "High-Risk Jurisdiction Exposure",
"note": "Only high-confidence self-published location evidence affects this multiplier. Ambiguous matches are review-only; country evidence is not proof of nationality, citizenship, legal registration, malicious intent, or sanctions status.",
"notes": [
{
"code": "jurisdiction_evidence_limits",
"params": {}
}
],
"value": 100,
"inputs": {
"meaning": "self-published location evidence; not nationality or citizenship",
"red_flag": false,
"exposures": [],
"policy_countries": [
"Russia",
"Iran",
"North Korea"
],
"commit_weight_rule": {
"min_commits": 50,
"min_commit_share": 0.1
},
"review_only_matches": 0,
"below_threshold_exposures": [],
"assessed_self_published_locations": 2
},
"components": [
{
"key": "policy_exposure_multiplier",
"name": "Policy exposure multiplier",
"detail": "no confirmed policy-scope location match",
"points": 100,
"status": "met",
"details": [
{
"code": "jurisdiction_no_match",
"params": {}
}
],
"max_points": 100
}
]
}
],
"description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
},
{
"key": "ai_readiness",
"band": "at_risk",
"name": "AI Readiness",
"value": 34,
"weight": 0.04,
"metrics": [
{
"key": "ai_agent_context",
"band": "weak",
"name": "Agent context & guidance",
"note": null,
"notes": [],
"value": 40,
"inputs": {
"has_llms_txt": false,
"legible_history_share": 0.845,
"agent_instruction_files": [],
"agent_instruction_max_bytes": null
},
"components": [
{
"key": "agent_instructions",
"name": "Agent instructions",
"detail": "no CLAUDE.md / AGENTS.md / editor rules",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_agent_instructions",
"params": {}
}
],
"max_points": 45
},
{
"key": "machine_readable_docs_llms_txt",
"name": "Machine-readable docs (llms.txt)",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 15
},
{
"key": "legible_commit_history",
"name": "Legible commit history",
"detail": "82 of 97 human commits state their intent (structured subject or explanatory body)",
"points": 40,
"status": "met",
"details": [
{
"code": "legible_history",
"params": {
"legible": 82,
"sampled": 97
}
}
],
"max_points": 40
}
]
},
{
"key": "ai_verify_loop",
"band": "at_risk",
"name": "Verify loop (build / test / typecheck)",
"note": null,
"notes": [],
"value": 22,
"inputs": {
"has_nix": false,
"has_tests": true,
"lockfiles": [],
"has_dockerfile": false,
"typed_language": false,
"bootstrap_files": [],
"has_devcontainer": false,
"has_linter_config": false,
"typecheck_configs": [],
"agent_commit_share": 0,
"toolchain_manifests": [],
"dependency_bot_commit_share": 0
},
"components": [
{
"key": "one_command_bootstrap",
"name": "One-command bootstrap",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 18
},
{
"key": "automated_tests",
"name": "Automated tests",
"detail": null,
"points": 22,
"status": "met",
"details": [],
"max_points": 22
},
{
"key": "lint_format_config",
"name": "Lint / format config",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 11
},
{
"key": "static_type_checking",
"name": "Static type checking",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 11
},
{
"key": "reproducible_environment",
"name": "Reproducible environment",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 10
},
{
"key": "demonstrated_agent_practice",
"name": "Demonstrated agent practice",
"detail": "no agent-authored commits among the last 100",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_agent_authored_commits",
"params": {
"sampled": 100
}
}
],
"max_points": 10
},
{
"key": "automated_maintenance",
"name": "Automated maintenance",
"detail": "no automated dependency updates observed",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_dependency_automation",
"params": {}
}
],
"max_points": 8
},
{
"key": "openssf_scorecard_pinned_dependencies",
"name": "OpenSSF Scorecard: Pinned-Dependencies",
"detail": "dependency not pinned by hash detected -- score normalized to 0",
"points": 0,
"status": "missed",
"details": [],
"max_points": 10
}
]
},
{
"key": "ai_code_legibility",
"band": "moderate",
"name": "Code legibility for models",
"note": null,
"notes": [],
"value": 53,
"inputs": {
"primary_language": "Python",
"largest_source_bytes": 70050,
"source_files_sampled": 25,
"oversized_source_files": 1
},
"components": [
{
"key": "type_checkable_code",
"name": "Type-checkable code",
"detail": "Python without a type-check config",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_typecheck_config_language",
"params": {
"language": "Python"
}
}
],
"max_points": 45
},
{
"key": "manageable_file_sizes",
"name": "Manageable file sizes",
"detail": "1/25 source files over 60KB",
"points": 52.8,
"status": "partial",
"details": [
{
"code": "oversized_source_files",
"params": {
"kb": 60,
"sampled": 25,
"oversized": 1
}
}
],
"max_points": 55
}
]
}
],
"description": "How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight: agent tooling is a real maintenance signal, but its absence must never gate the top of the scale (calibration saturates at raw 91, so 100/100 remains reachable with AI Readiness at zero)."
}
],
"classification": {
"labels": [],
"scores": {},
"primary": null,
"evidence": [],
"artifacts": [],
"confidence": "none",
"host_extension": false,
"runs_as_process": false,
"consumed_by_code": false
},
"metrics_version": "2.3.1"
},
"warnings": [
"Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token",
"Could not fetch pypi package 'ara-ai' from its registry",
"GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository"
],
"report_type": "repository",
"generated_at": "2026-08-02T21:14:42.479219Z",
"schema_version": "0.29.0",
"badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/m/MeridianAlgo/AraAI.svg",
"full_name": "MeridianAlgo/AraAI",
"license_state": "custom",
"license_spdx": null
}
Verwandte Einträge
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Fehlende Daten werden ausgeschlossen und die Gewichte neu normiert, nie als null bewertet. Die Methodik ist versioniert und offen: Metriken v2.3.1, Schema v0.29.0 — vollständige Methodik · Metriken-Wiki.
