Recipes and the local runtime.

A recipe is the reproducible local execution contract for a model or a piece of code: where it comes from, what it needs, which inputs it accepts and which outputs it returns. A node is the graph-facing interface that calls that recipe through Runtime.

That separation is the point. The recipe pins how something runs on your machine; the node is how a graph talks to it.

#Running recipes

The runtime runs installed recipes locally. From the CLI:

kaitoi runtime list
kaitoi runtime install <recipe>
kaitoi runtime run <recipe>
kaitoi runtime serve

Or from Kaitoi Code, in plain language:

You > list my available runtime recipes
You > run the gemma recipe with a short test prompt
You > save the runtime output into this workspace

Code actions that execute code, install or uninstall packages, or start or stop the runtime all require confirmation.

#Turning a repository into a node

#1. Generate the recipe

Point the generator at a GitHub repository or a Hugging Face model:

kaitoi runtime generate https://github.com/owner/repository -o my-recipe.yaml

kaitoi runtime generate https://huggingface.co/owner/model -o my-recipe.yaml

This produces a recipe YAML file and a companion Python script.

Generation calls a model, and there are two ways it can be paid for. Generating from the kaitoi dashboard uses your Kaitoi login: the call goes through Kaitoi's managed provider and is billed to your Kaitoi account, so there is no key to configure. You have to be signed in; the dashboard says so if you are not.

Running kaitoi runtime generate straight from the command line does not go through Kaitoi. It calls Anthropic directly and needs your own key, passed as --api-key or set in the runtime config:

kaitoi runtime config set anthropic_api_key sk-ant-...

Review the generated code before running it, exactly as you would review any code downloaded from a repository.

#2. Validate and test locally

kaitoi runtime validate ./my-recipe.yaml
kaitoi runtime info ./my-recipe.yaml

Pass the input flags the generated recipe declares. A text recipe might take:

kaitoi runtime run ./my-recipe.yaml --prompt "A small launch test"

When the result looks right, install it so Runtime and Kaitoi Studio can discover it:

kaitoi runtime install ./my-recipe.yaml
kaitoi runtime packages

#3. Start Runtime and connect it

kaitoi up

kaitoi up starts the Runtime server and its Kaitoi connection together. Check both are healthy with kaitoi status.

#4. Create the node in Kaitoi Studio

1. Open Settings → Integrations → Runtime.
2. Confirm Runtime shows Connected and find the installed recipe.
3. Choose Create Node beside that recipe.
4. Penny reads the recipe schema, creates typed inputs and outputs, wires the call through Runtime, and adds the node to your graph.
5. Run the node once with a small input before using it in a larger graph.

To write the node yourself, declare which recipe it covers and accept the runtime helper as an injected argument:

# @node title="My Local Recipe" category="Local" icon="cpu" preview=true
# @task category="Create" subcategory="Text" filter="Local Runtime"
# @input string prompt label="Prompt" widget=multiLine default=""
# @output string text label="Result"
# @api runtime recipe="my-recipe"

def run(prompt, runtime):
    result = runtime.run_recipe("my-recipe", {"prompt": prompt})
    text_files = result.get("outputs", {}).get("text", [])
    if not text_files:
        return {"@error": "The recipe did not produce text."}
    return {"text": runtime.download_text(text_files[0]).strip()}

The exact input names and output keys come from your recipe. For file inputs use runtime.upload(...); for generated files use runtime.download(...) or one of the bounded text and JSON download helpers. A node created through Create Node handles those mappings for you.

#Connecting local services

Use Connect when you want Kaitoi Studio to reach services running on your computer. Several can be connected at once: starting Blender does not replace your Runtime or Ollama connection.

kaitoi up          # start runtime and tunnel it to Kaitoi
kaitoi status      # check what is connected

Tunnel a specific service:

kaitoi connect runtime
kaitoi connect ollama
kaitoi connect comfyui
kaitoi connect blender

Tunnel any local port:

kaitoi tunnel 3000 --name my-app

Stop local tunnels and runtime processes:

kaitoi stop

#Current limitations

• If the Runtime connection is unavailable, Kaitoi Studio cannot start a new recipe run or receive its result. Check kaitoi status before starting a long graph run.
• Recipe generation from the command line calls Anthropic directly and needs your own key. Only the dashboard path is billed to your Kaitoi account.