---
title: AGI
description: Section index for AGI — RL animation rigging with a WebGPU tensor library and AGI Studio (overview, architecture, getting started, training guide, API reference).
updated: 2026-06-05
---

# AGI

Reinforcement-learning animation rigging ("parasite rig") with a WebGPU tensor library and AGI Studio. Source: `agi/`.

## In this section

- [Overview](overview.md) — what AGI is and how the RL loop works.
- [Architecture](architecture.md) — tensor → brain → core → scene/rig → studio.
- [Getting Started](getting-started.md) — launch Studio and start training.
- [Training Guide](training-guide.md) — curriculum, tuning, troubleshooting.
- **API Reference** — per-file symbols from `agi/` (browse `agi/reference/`).

## Module map

```text
agi/
  core/      RagdollController, ObservationBuilder, MotorController, RewardFunction,
             CurriculumManager, MotionMatchingTeacher
  brain/     policy/value networks, PPO trainer, optimizers, losses, utils
  tensor/    WebGPU tensors + compute shaders (matmul/activation/reduction) + autodiff
  rig/       parasite visuals (injection, tentacles, brain)
  scene/     training scene, ground, tracking camera, renderer, debug
  studio/    AGI Studio app (core, panels, editors, visualizers, tools)
  runtime/   runtime manager
  api/       Gym-compatible environment API
  adapters/  WebGPU/Python/WASM/Rust/C++
  loader/ config/ data/   model loading, hyperparameters/curriculum/rewards, data
```

## Related

- [GPU Device Sharing](../concepts/gpu-device-sharing.md) — the tensor library runs on the shared device.
- [Engine](../engine/index.md) — AGI is built on Engine v2.