14 n8n orchestration workflows and 53 GitHub Actions covering CI/CD, content publishing, training pipelines, multi-cloud deployment, and governance scanning. Every workflow is governed.
Self-hosted n8n with a FastAPI bridge for governance scanning, Sacred Tongue encoding, and training data ingestion.
Multi-platform content publishing with governance scanning. Writes to Medium, LinkedIn, Dev.to, X/Twitter, Bluesky, GitHub, and HuggingFace. Every post passes through the governance gate before publishing.
Dispatches autonomous web research tasks to the AetherBrowse agent fleet. Handles URL extraction, content summarization, and training data generation from web sources.
Ingests data from Notion, Dropbox, and local sources. Runs governance checks on every record, syncs to Airtable, and publishes governed datasets to HuggingFace.
Orchestrates multi-model debates where different AI models argue positions on research questions. Generates DPO training pairs from the debate transcripts.
Bidirectional sync between Google Vertex AI and HuggingFace. Trains on Vertex, deploys to HF. Governance gate validates model artifacts before promotion.
Social media growth automation with merchandise operations. Scheduled posts, engagement tracking, and merch inventory sync.
Connects n8n to the SCBE governance engine. Exposes /health, /v1/governance/scan, /v1/tongue/encode, /v1/agent/task, /v1/training/ingest, and /v1/vertex/push-to-hf endpoints.
Main CI pipeline: TypeScript compile, Vitest (5,957 tests), pytest (785 tests), Prettier, flake8, circular dependency check. Runs on every push and PR.
Vulnerability scanning, conflict marker detection, weekly automated security audits. PQC key rotation checks and dependency auditing.
Automated npm and Docker publishing on tagged releases. Dry-run verification, pre-publish safety checks, and changelog generation.
AWS Lambda, EKS, GKE, and Cloud Run deployment workflows. Docker image building and registry pushing included.
Nightly connector health, multicloud training, daily ops, social media updates, and review workflows. Runs on schedule, not on push.
HuggingFace model sync, Notion integration, cloud kernel data pipeline, and Vertex AI training triggers.
Ingests from Notion, Obsidian, Dropbox, GitHub, web research, and game session logs. Deduplicates, labels, and validates before entering the training pool.
254 raw labels consolidated to 24 families. 690,479 "unknown" records dropped. Class imbalance capped at 5,000 samples per label. Minimum 10 samples per label.
Start with scbe_canonical_training_lane_colab.ipynb when you want one Colab surface for upload, normalization, and QLoRA fine-tune. Keep Kaggle aligned to the same contract as a secondary lane, not a CPU-first fallback. Run python scripts/system/kaggle_notebook_smoke.py --micro-train before any long Kaggle job.
Multi-stage Dockerfile: Node 20 (TS compile) → liboqs (PQC) → Python 3.11 → runtime. Ports 8080 (API) + 3000 (gateway). Docker Compose for full stack.
Pre-built manifests for EKS (AWS), GKE (Google), and generic Kubernetes. Includes service accounts, RBAC, and ingress configs.
AWS Lambda and Google Cloud Run deployment configs. Trust policy JSON for IAM roles. Stateless governance evaluation on demand.