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OmniBioAI Control Center

Local Development, Orchestration & Deployment Plane

This repository defines the OmniBioAI Control Center — the orchestration, deployment, and operational control plane of the OmniBioAI ecosystem.

OmniBioAI is a reproducible scientific execution and reasoning platform designed to run consistently across:

  • Local machines
  • On-prem servers
  • HPC environments
  • Cloud infrastructure

With no mandatory cloud dependencies.

This repository does not embed bioinformatics algorithms or core application logic. Instead, it assembles independently versioned OmniBioAI components into a single runnable, production-grade ecosystem.

Think of this repository as the operational brain and runtime assembly layer of OmniBioAI.


What Is the OmniBioAI Control Center?

The Control Center is responsible for:

  • Service orchestration
  • Environment configuration
  • Runtime boundaries
  • Cross-service wiring
  • Health checks and dependency contracts
  • Persistence management
  • Deployment portability (local ↔ HPC ↔ cloud)

It defines how OmniBioAI runs — not what each component internally implements.

It is the control plane of the ecosystem.


Architectural Positioning

OmniBioAI follows a multi-plane architecture:

1. Control Plane (This Repository)

  • Django Workbench
  • Model Registry
  • Tool Execution Service (TES)
  • ToolServer
  • LIMS
  • Metadata databases
  • Object and artifact governance
  • API boundaries
  • Health contracts

These services are:

  • Long-lived
  • Stateful
  • Restart-safe
  • Governance-aware

2. Compute Plane

  • Workflow runners (WDL, Nextflow, Snakemake, CWL)
  • Tool runtime containers
  • HPC adapters
  • Slurm execution
  • Kubernetes jobs
  • Cloud batch adapters

These services are:

  • Ephemeral
  • Replaceable
  • Execution-only

TES is the strict boundary between control and compute planes.


3. Data Plane

  • OmniObjects
  • Model artifacts
  • Workflow outputs
  • Versioned bundles
  • Datasets

4. AI Plane

  • RAG services
  • LLM reasoning
  • Agent orchestration
  • Scientific interpretation layers

Who This Repository Is For

This repository is intended for:

  • Core OmniBioAI developers
  • Infrastructure engineers
  • HPC administrators
  • Enterprise deployment teams
  • Regulated or air-gapped environments
  • Power users running full stacks locally

It is not required for:

  • Plugin-only development
  • SDK-only usage
  • Users consuming hosted OmniBioAI

Workspace Layout

Desktop/machine/
├── omnibioai/                     # Workbench (Django platform)
├── omnibioai-tes/                 # Tool Execution Service
├── omnibioai-toolserver/          # FastAPI ToolServer
├── omnibioai-model-registry/      # Model registry service
├── omnibioai-lims/                # LIMS
├── omnibioai-rag/                 # RAG & LLM services
├── omnibioai_sdk/                 # Python SDK
├── omnibioai-workflow-bundles/    # Engine-agnostic workflows
│
├── deploy/
│   ├── compose/                   # Canonical Docker Compose
│   ├── scripts/                   # Bootstrap utilities
│   ├── bundle/                    # Offline bundles
│   ├── hpc/                       # Apptainer assets
│   └── k8s/                       # Kubernetes (in progress)
│
├── data/
├── work/
├── tmpdata/
├── out/
├── local_registry/
│
├── db-init/
├── utils/
├── images/
│
├── docker-compose.yml
├── .env.example
└── README.md

Canonical Runtime Services

Service Port Role
OmniBioAI Workbench 8000 UI, plugins, agents
Tool Execution Service (TES) 8081 Workflow orchestration
ToolServer 9090 Tool APIs
Model Registry 8095 Versioned ML artifacts
LIMS 7000 Sample & metadata management
MySQL 3306 Databases
Redis 6379 Celery & caching

All ports are configurable via .env.


Key Capabilities of the Control Center

1. Deterministic Multi-Service Orchestration

  • Ordered startup with health checks
  • Restart-safe dependency management
  • Strict port contracts
  • Environment-based configuration

2. Model Governance Layer

  • Model versioning
  • Alias promotion
  • Artifact verification
  • Reproducibility metadata
  • Strict package validation

3. HPC Compatibility

Supports execution on:

  • Slurm clusters
  • Apptainer / Singularity environments
  • Non-root HPC nodes

Control plane can remain external while compute runs on HPC.


4. Cloud Parity

OCI-compliant images allow deployment to:

  • AWS Batch
  • Azure Batch
  • Kubernetes
  • On-prem Docker

Design goal: parity across environments


5. Offline / Air-Gapped Deployment

This repository supports:

  • Prebuilt Docker image bundles
  • Volume snapshots
  • Seeded databases
  • Fully offline installation

Suitable for:

  • Regulated research labs
  • Secure enterprise networks
  • Hospital environments

Local Deployment

Prerequisites

  • Docker Engine or Docker Desktop
  • Docker Compose v2+

Start Full Stack

cp deploy/compose/.env.example deploy/compose/.env
docker compose \
  --project-directory . \
  --env-file deploy/compose/.env \
  -f deploy/compose/docker-compose.yml \
  up -d

Verify Services

curl http://127.0.0.1:8000
curl http://127.0.0.1:8081/health
curl http://127.0.0.1:8095/health

Operational Modes

Mode Control Plane Compute Plane
Local dev Docker Compose Local Docker
On-prem Docker Compose Docker / TES
HPC External VM Apptainer via TES
Hybrid VM HPC + TES
Cloud Kubernetes Kubernetes

Design Principles

  • Single workspace root
  • No absolute paths
  • Strict service boundaries
  • Control plane ≠ compute plane
  • Restart-safe orchestration
  • Container-native design
  • Environment-driven configuration
  • No forced cloud dependencies

What This Repository Does Not Do

  • Does not contain bioinformatics algorithms
  • Does not vendor component repositories
  • Does not enforce a single workflow engine
  • Does not hide execution behind opaque AI calls
  • Does not require external SaaS services

Strategic Role in the Ecosystem

OmniBioAI components are independently versioned repositories.

This repository:

  • Assembles them
  • Wires them
  • Runs them
  • Governs them
  • Deploys them

It is the operational control boundary of OmniBioAI.


Current Status

  • Multi-service orchestration stable
  • Model Registry integrated
  • TES integrated
  • ToolServer integrated
  • LIMS integrated
  • Offline-ready structure
  • HPC-aware architecture
  • Kubernetes preparation underway

Final Positioning

This repository is:

The OmniBioAI Control Center — the orchestration, deployment, and runtime control plane of the OmniBioAI ecosystem.

It defines how the ecosystem runs, scales, and moves across environments — while preserving strict reproducibility and architectural boundaries.

About

Control plane and orchestration hub for the OmniBioAI ecosystem, coordinating Workbench, TES, ToolServer, Model Registry, LIMS-X, and AI services with reproducible local and on-prem deployment.

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