> ## 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 catalog of every model — slug, typed SDK package, and links to its schema — is at /model-api-reference/overview. 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.

# SharedSlotAllocationFailed

> A shared-memory block could not be created or grown.

A shared-memory block could not be created or grown. A subclass of `MemoryError` raised by
[DistributedRunner](/deploy/runtime-reference/distributedrunner).

<Note>
  Development preview. See [availability](/deploy/development/distributed-workers#availability).
</Note>

```python theme={"theme":{"light":"github-light","dark":"github-dark-high-contrast"}}
from reactor_runtime.distributed import SharedSlotAllocationFailed
```

The error reports the requested size. Where available, it also reports free space in `/dev/shm`.
Both a single worker and multiple workers use this transport.

For local containers, follow the shared-memory instructions in
[Test locally](/deploy/development/local-testing#put-your-own-model-in). For deployed models, check
the deployment's shared-memory capacity and memory limit. A local `--shm-size` setting does not
change a deployed container.

An input allocation can fail before any worker receives the request. A result allocation can fail
inside a worker. Do not assume the call left model state unchanged. Check runner health and the
model's recovery policy before another call.