> ## Documentation Index
> Fetch the complete documentation index at: https://docs.reactor.inc/llms.txt
> Use this file to discover all available pages before exploring further.

> ## Agent Instructions
> To build and serve your own model, start at /deploy/development/quickstart and /deploy/development/overview. Deploying is the default path: reactor init scaffolds a workspace, reactor auth login authenticates, and reactor model deploy registers the model, publishes the release with the weights/ folder, and activates it on Reactor's GPUs, in one command from that workspace. Docker must be running, because the publish step builds the image locally. Bump model.version in reactor.yaml before redeploying a change, because a release that already has an image is reactivated as it is. Deployment access is granted per account, so contact team@reactor.inc if a deploy is refused. Every key in reactor.yaml is documented at /deploy/platform/reactor-yaml. Model code imports reactor_runtime; Python client code imports reactor_sdk. The runtime overview explains the model interface. Running the model on your own machine with reactor run is optional and needs a GPU you attach with --gpus; /deploy/development/local-testing covers that loop and pairs a complete brightness model with a Python client test in a separate brightness-test workspace.
> Reactor hosts multiple models, each with its own connect slug (modelName) and command/event schema. The video model catalog — slug, typed SDK package, and links to its schema — is at /model-api-reference/overview. Robotics policy documentation starts at /robotics/overview; X-WAM observations, actions, and client integration are under /robotics/xwam/; Cosmos3 Nano Policy DROID is under /robotics/cosmos/nano-policy-droid/. Some models expose one slug per experience (e.g. HappyOyster); always take the slug from the model's own pages, never guess it.
> Fastest path to a working app: `npx create-reactor-app my-app --model=<slug>` scaffolds a complete app with secure auth wired up. Typed TypeScript SDKs are published as @reactor-models/<model>; Python uses the base reactor-sdk package.
> Auth: exchange an API key (rk_...) for a JWT via POST https://api.reactor.inc/tokens from your server. Never put the API key in client-side code.
> Append .md to any docs URL for clean Markdown. Search these docs via the MCP server at https://docs.reactor.inc/mcp.

# DreamZero

> Choose a DreamZero embodiment and its observation/action contract.

DreamZero jointly predicts future video and robot actions from camera observations, measured state,
and a language task. Reactor runs inference and maintains the episode's temporal context; your
client captures observations and controls the robot.

## Choose an embodiment

| Variant | Reactor model | Cameras | Action chunk | Simulation path |
| - | - | - | - | - |
| [DROID / Franka](/robotics/dreamzero/droid/overview) | `reactor/dreamzero` | Two exterior, one wrist | `(24, 8)`: seven joints and gripper | RoboLab gateway |
| [Bimanual YAM](/robotics/dreamzero/yam/overview) | `reactor/dreamzero-yam-molmoact2` | Top, left, right | `(24, 14)`: six joints and gripper per arm | Custom adapter required |

The variants share a streaming lifecycle, but their checkpoints, camera names, joint order, and
state commands differ. Select an embodiment before adapting a client. Matching an action width alone
does not establish compatibility with another robot.

Both variants emit `action_chunk` messages once a prompt and all camera streams are available. They
do not wait for an explicit predict command or execution acknowledgement. Your application decides
how to replace the pending plan, which validated targets to execute, and when to replan. Optional
predicted video is diagnostic output, not a sensed observation or a safety check.

The [upstream DreamZero project](https://github.com/dreamzero0/dreamzero) supplies the model family.
The YAM endpoint uses Robocurve's MolmoAct2 BimanualYAM fine-tune; it is a separate checkpoint from
the DROID endpoint.


This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.