Metadata-Version: 2.4
Name: busysloths-mlox
Version: 0.3.0
Summary: Deploy and manage connected ML/AI infrastructure on your own servers.
Author-email: drbusysloth <contact@mlox.org>
License: MIT License
        
        Copyright (c) 2024 nicococo
        
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Project-URL: Homepage, https://busysloths.github.io/mlox/mlox.html
Project-URL: Tracker, https://github.com/busysloths/mlox/issues
Project-URL: Source, https://github.com/busysloths/mlox
Project-URL: Examples, https://github.com/busysloths/mlox
Keywords: Infrastructure,Server,Service,Dashboard,Opinionated,MLOps
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development
Classifier: Topic :: System :: Distributed Computing
Classifier: Topic :: Internet
Classifier: Topic :: Database
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
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License-File: LICENSE
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Dynamic: license-file

<p align="center">
  <a href="https://github.com/BusySloths/mlox">
    <img src="https://github.com/BusySloths/mlox/blob/main/mlox/resources/mlox_sloth_logo.png?raw=true" alt="MLOX Logo" width="400px"/>
  </a>
</p>

<p align="center">
  <strong>Deploy and manage ML/AI infrastructure on your own servers. Slothfully simple.</strong>
</p>

<p align="center">
  Servers, Docker, Kubernetes, databases, workflows, model serving, data services, tracking, and monitoring, with your product at the center. Managed in one place and connected by design.
</p>

<p align="center">
  <a href="https://qlty.sh/gh/BusySloths/projects/mlox" target="_blank"><img src="https://qlty.sh/gh/BusySloths/projects/mlox/maintainability.svg" alt="Maintainability" /></a>
  <a href="https://qlty.sh/gh/BusySloths/projects/mlox" target="_blank"><img src="https://qlty.sh/gh/BusySloths/projects/mlox/coverage.svg" alt="Code Coverage" /></a>
  <a href="https://github.com/BusySloths/mlox/issues" target="_blank"><img alt="GitHub Issues" src="https://img.shields.io/github/issues/busysloths/mlox"></a>
  <a href="https://github.com/BusySloths/mlox/discussions" target="_blank"><img alt="GitHub Discussions" src="https://img.shields.io/github/discussions/busysloths/mlox"></a>
  <a href="https://drive.google.com/file/d/1Y368yXcaQt1dJ6riOCzI7-pSQBnJjyEP/view?usp=sharing"><img src="https://img.shields.io/badge/Slides-State_of_the_Union-9cf" alt="Slides: State of the Union" /></a>
</p>

---

## What is MLOX?

ML/AI infrastructure is fragmented. Setup is painful, managed platforms are expensive, and vendor lock-in limits your choices.

MLOX brings the infrastructure around your product into one connected system. It manages servers, sets up Docker and Kubernetes clusters, deploys open-source services, stores secrets, and wires dependencies across databases, workflows, experiment tracking, model serving, data services, and monitoring.

Use the Web UI, TUI, or CLI to operate the same inspectable, configuration-driven core. MLOX is built for solopreneurs, startups, and small teams that want to focus on their product instead of assembling and maintaining infrastructure.

It's for engineers who prefer thoughtful systems over chaos. Backed by open source. Powered by sloths.

> **[State of the Union (Sept 2025)](https://drive.google.com/file/d/1Y368yXcaQt1dJ6riOCzI7-pSQBnJjyEP/view?usp=sharing)** — a short slide overview of what MLOX is, what problem it solves, and where it's heading.

---

## Current Status

Native, Docker, and Kubernetes execution, connector integrations, and the major services are functional. The project has been accepted at **CAIN 2026**.

We welcome contributors, users, and honest feedback. If you hit something broken, please [open an issue](https://github.com/BusySloths/mlox/issues/new/choose) or reach out at `contact@mlox.org`.

---

## What Can You Do with MLOX?

| Area | What's included |
|------|----------------|
| **Infrastructure** | Add, remove, and tag servers; use Native, Docker, or Kubernetes execution; create single- or multi-node clusters |
| **Services** | Deploy, manage, and remove services; centralize secrets; connect service dependencies |
| **Connectors** | Integrate externally hosted services such as BigQuery, Cloud Storage, Sheets, and GCP Secret Manager |
| **Applications** | Import repositories and deploy your product alongside its supporting services |
| **Code** | `busysloths-mlox` PyPI package with client integrations, SDK helpers, and example snippets |
| **Lifecycle Management** | Migrate, upgrade, export, and decommission services *(planned)* |

---

## Services Catalog

| Category | Services | Status |
|----------|----------|--------|
| ML Platforms | MLflow 2.x, MLflow 3.x, Airflow 2.x, Airflow 3.x | Functional |
| Model Serving | MLflow MLServer, MLflow Gateway | Functional |
| LLMs & Inference | LiteLLM, Ollama | Functional |
| Vector & Feature Stores | Milvus, Feast | Functional |
| Data & Streaming | PostgreSQL, Redis, MinIO, Kafka | Functional |
| Observability | InfluxDB, OpenTelemetry | Functional |
| Secrets & Access | OpenBao, Tiny Secret Manager, Registry 3 | Functional / Beta |
| Kubernetes Add-ons | Kubernetes Dashboard, Headlamp, KubeApps | Experimental |
| Cloud Integrations | GCP (BigQuery, Cloud Storage, Sheets, Secret Manager) | Functional |
| Source Control | GitHub repository import | Beta |
| Applications | Repository Docker Deploy | Beta |

---

## Architecture in 30 Seconds

```text
CLI     TUI     Streamlit Web UI
  \      |             /
   +------+------------+
          |
          v
      `ProjectWorkspace`
          |
          v
   internal state + repository
          |
          v
 encrypted `project.mlox` (SQLCipher)
 metadata + data-source pointer + infrastructure + secrets
          |
          +-- active source: `self` today
          +-- PostgreSQL-ready repository boundary later
```

`ProjectWorkspace` is the single public runtime API. It loads and atomically
persists internal workspace state containing metadata and `Infrastructure`;
the single selected secret manager is available through `workspace.secrets`.
Encrypted project storage is selected initially, with no silent fallback when an
external provider is unavailable. The project
also records its active data source (`sqlcipher/self` initially), leaving a clean
migration path to PostgreSQL. CLI commands open a workspace per invocation,
while the TUI and Web UI retain one workspace in runtime state.

Service and server definitions remain inspectable and configuration-driven, while execution is handled consistently across Native, Docker, Kubernetes, and connector backends.

For deeper reading:

- [Architecture Guide (humans)](docs/ARCHITECTURE_HUMANS.md) — codebase walkthrough
- [Architecture Guide (agents)](docs/ARCHITECTURE_AGENTS.md) — high-risk areas and invariants

---

## Quickstart

```bash
# 1. Install Task (https://taskfile.dev/installation/)

# 2. Clone
git clone https://github.com/BusySloths/mlox.git && cd mlox

# 3. Set up environment (creates conda env 'mlox-dev' with Python 3.12.5)
task first:steps

# 4. Launch the Web UI
task ui:streamlit

# 5. Or try the CLI
task ui:cli CLI_ARGS="--help"
```

See [Installation Guide](docs/INSTALLATION.md) for a fuller walkthrough including Docker and Kubernetes setup. See [Encrypted Project Files](docs/PROJECT_FILES.md) for creation, storage, backup, and legacy migration details.

---

## Project Structure

```
mlox/
├── mlox/
│   ├── application/    # Stateful application API and shared use cases
│   ├── cli/            # Typer CLI package (root app + command modules)
│   ├── execution/      # Backend and system execution helpers
│   ├── project/        # Aggregate, SQLCipher repository, and secret adapter
│   ├── servers/        # Local, connector, and Ubuntu compute with Native, Docker, or Kubernetes
│   ├── services/       # Deployable ML/AI services and integrations
│   ├── tui/            # Textual terminal UI + TUI-specific UI handlers
│   ├── ui/             # Frontend UI handler registry
│   ├── view/           # Streamlit web UI + Streamlit-specific UI handlers
│   ├── assets/         # Runtime templates and packaged assets
│   ├── resources/      # Images and other static resources
│   ├── project/        # Public workspace and internal SQLCipher persistence
│   ├── infra.py        # Service/server graph
│   ├── config.py       # YAML loading + plugin discovery + UI handler lookup
│   └── executors.py    # Remote task executor layer used by services/servers
├── tests/
│   ├── unit/           # Fast tests, no external deps
│   └── integration/    # Multipass VM tests
├── examples/           # OTel, MLflow tracking, DAG templates
├── docs/               # Architecture, installation, contribution guides
├── wiki/               # GitHub Wiki source pages
├── scripts/            # Development and maintenance utilities
└── website/            # Astro landing page
```

---

## Contributing

### Sloth-Friendly Setup

```bash
# 1. Install Task (https://taskfile.dev/installation/)
# 2. Clone the repo
git clone https://github.com/BusySloths/mlox.git && cd mlox
# 3. Set up the dev environment
task first:steps
# 4. Install dev dependencies
pip install -e .[dev]
```

### Run Tests

```bash
task dev:lint                   # flake8
task tests:unit:run             # unit tests (fast, no external deps)
task tests:integration:run      # integration tests (requires Multipass VMs)
```

### Ways to Contribute

- [Bug reports](https://github.com/BusySloths/mlox/issues/new/choose)
- [Documentation improvements](https://github.com/BusySloths/mlox/issues/new/choose)
- [Feature requests](https://github.com/BusySloths/mlox/issues/new/choose)
- [New service implementations](docs/ARCHITECTURE_HUMANS.md)
- [Examples and tutorials](examples/)

See [CONTRIBUTING.md](CONTRIBUTING.md) for the full guide and [docs/WORKFLOW_QUICK_REFERENCE.md](docs/WORKFLOW_QUICK_REFERENCE.md) for how we use GitHub Projects, Milestones, and Issues.

---

## Documentation

| Document | Description |
|----------|-------------|
| [Installation Guide](docs/INSTALLATION.md) | Setup from scratch |
| [Architecture (humans)](docs/ARCHITECTURE_HUMANS.md) | Codebase walkthrough |
| [Architecture (agents)](docs/ARCHITECTURE_AGENTS.md) | High-risk areas and invariants |
| [Contributing Guide](CONTRIBUTING.md) | How to contribute |
| [Workflow Quick Reference](docs/WORKFLOW_QUICK_REFERENCE.md) | Labels, milestones, PRs |
| [Plugin Guide](docs/PLUGIN_CONFIGS.md) | External service and server config plugins |
| [API Docs](https://busysloths.github.io/mlox/mlox.html) | Generated Python API reference |

---

## Sponsors

MLOX is proudly funded by:

<img src="https://github.com/BusySloths/mlox/blob/main/mlox/resources/BMFTR_logo.jpg?raw=true" alt="BMFTR" width="420px"/>

## Supporters

<p align="center">
  <img src="https://github.com/BusySloths/mlox/blob/main/mlox/resources/PrototypeFund_logo_dark.png?raw=true" alt="PrototypeFund" width="380px"/>
</p>

---

## License & Contact

MLOX is open-source, distributed under the [MIT License](LICENSE). Contributions are welcome and subject to the same terms.

We are looking for people invested in the problem we're solving. Say hello at `contact@mlox.org` or start a conversation in [GitHub Discussions](https://github.com/BusySloths/mlox/discussions).
