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junaidahmed361/tendos

Tendos

Plug-and-play AI cartridge hub — package, distribute, and run composable AI harness configurations locally, then deploy the same cartridges to hosted Tendos Cloud.

Tendos is building toward "Docker for AI agents and harnesses": portable, signed cartridges with reproducible execution across local machines and managed cloud.

The name and product metaphor come from Nintendo cartridges (plug in and play) combined with Docker-style portability and reproducibility.

CI License Python


Vision

Small and open language models are making local AI practical. Tendos exists so builders and teams do not have to re-create agent harnesses from scratch for every use case.

A Tendos cartridge is a reusable, swappable unit that can bundle:

  • model configuration (base model + optional adapters)
  • agent configuration (prompt, nodes, graph, tools)
  • security and trust data (checksums, signatures)
  • licensing and usage metadata

Long-term direction:

  • local-first execution by default (privacy and ownership)
  • hosted deployment option via Tendos Cloud (pay to host)
  • community ecosystem where creators publish cartridges and users install/compose them quickly

What is Tendos today?

Tendos currently provides the v0.1 foundation for cartridge packaging and trust:

  • Cartridge specification and manifest schema validation
  • Cartridge loader for validate/pack/unpack workflows
  • Ed25519 signing and signature verification
  • AES-256-GCM encryption helpers for protected artifacts
  • JWT token utilities for pay-per-use licensing primitives
  • Harness YAML declarations for security guardrails, PII redaction, and update/sync policies
  • Manual/custom harness declarations via harness.declarations.custom_config for user-defined launcher/runtime keys
  • tendos run launcher execution supports both host command launchers and self-contained Docker launchers

Quick Start

# Install
pip install tendos
# or
uv add tendos

# Initialize a new cartridge project
tendos init my-cartridge

# Validate the cartridge manifest
tendos validate my-cartridge/cartridge.json

# Pack into a distributable .cartridge archive
tendos pack my-cartridge/

# Sign the cartridge for integrity verification
tendos sign my-cartridge.cartridge --key ~/.tendos/signing.key

# Verify signature
tendos verify my-cartridge.cartridge --pub ~/.tendos/signing.pub --sig my-cartridge.cartridge.sig

# Run harness launcher (if declared)
tendos run my-cartridge/

Core Principles

  • Local-first: run on your hardware first, with cloud as an option
  • Portable artifacts: one cartridge format for reuse and sharing
  • Trust by default: signing, verification, and integrity checks
  • Composability: stack cartridges for domain-specific workflows

Development

# Clone and install
git clone https://github.com/junaidahmed361/tendos.git
cd tendos
uv sync --all-extras

# Run tests
make test

# Run full quality suite
make all

# Run pre-commit hooks
make pre-commit

Project Structure

src/tendos/
  cartridge/    # Cartridge schema, loader, validator
  runtime/      # Runtime execution engine (expanding)
  hub/          # Marketplace and registry client (expanding)
  security/     # Signing, encryption, JWT tokens
  cli/          # Command-line interface
tests/
  unit/
  integration/

Quality Gates

All pull requests are expected to pass:

  • ruff lint + formatting checks
  • mypy strict type checks
  • bandit static security scan
  • pytest with coverage threshold
  • pre-commit hooks

Roadmap (high level)

  1. Local execution runtime for cartridges
  2. Lockfile + compatibility checks for reproducibility
  3. Community hub for publish/discover/install workflows
  4. Tendos Cloud hosted deployment for managed agent execution

Contributing

Contributions are welcome. See CONTRIBUTING.md for guidelines.

License

Apache License 2.0 — see LICENSE.

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Plug-and-play AI cartridge hub — package, distribute, and run composable AI harness configurations locally.

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