AI agents
Agents are AI assistants you attach to a node, a connection between two nodes, or the whole canvas, to chat about that part of your dataflow. When an agent suggests a change, nothing happens until you apply it.
Choose the provider and model
Agents answer with an LLM configuration: a provider, its key and a model, which you set up in API Settings. It opens from the button at the top of the Projects and catalog pages, or from the Agent Catalog drawer on the canvas.
- Under LLM configurations, click Add configuration.
- Give it a Label, and pick the Provider: OpenAI, Anthropic, Gemini, or Custom for any OpenAI-compatible endpoint, such as a model you run yourself (Custom asks for a Base URL).
- Paste the API key, and choose the Model: Fetch models suggests what the endpoint serves, or type a model name.
- Click Save. Your first configuration is your default.
You can keep several configurations, for different providers or models. Under Agent models, choose which one each agent runs on; an agent left on Default uses your default. If whoever runs the server set a Deployment default, it is offered too. On a server started with --deploy, guest accounts cannot add a configuration and answer with the server's guest configuration. Curio does not bill agent runs: the provider charges whoever's key is used.
new:apisettingsAdd an agent to a dataflow
On the canvas, open Data > Agent Catalog, or open the Agent Catalog dropdown in the Tools panel and click Browse Agent Catalog +. The drawer has two tabs: Browse all, and In project for the agents this dataflow has. In the catalogs, a project is one of your saved dataflows.
Click Add to project and confirm. An agent that relies on others says so on its button, as in Add to project (+1 required), and the agents it needs are added with it. Added agents appear in the Tools panel's Agent Catalog dropdown.
The Agent Catalog tab at the top of the Projects page lists the agents for your whole account. Click one to read about it; Add to all projects adds it to every project you have and to new ones. Import agent adds one you wrote yourself.
Attach it to your work
Adding an agent makes it available; attaching it puts it to work. Drag it from the Agent Catalog dropdown and drop it:
- on a node, to work with that node's code and output (a badge appears under the node)
- on a connection, to work with what flows between two nodes (a badge appears on the connection)
- on empty canvas, to work with the whole dataflow (it joins the bar at the top of the canvas)
An agent only accepts the targets it was made for. Each attachment has its own conversation, and one agent can be attached in several places. Once an agent is attached, the bar at the top also shows a Goal field: say what the dataflow is for, and the agents that read it take it into account. To detach an agent, hover its badge and click ✕, which also deletes its conversation.
Chat and review changes
Click a badge to open the agent's chat. The header says what the agent is attached to, the arrows step through your attached agents, and you can rename or clear the conversation. The first message is the agent's instruction, which the pencil lets you edit. Type in Message this agent… and send.
What an agent does depends on the agent: explain or debug a node, write node code, find datasets (including in the open data portals of the Discovery Catalog), plan or build a whole dataflow, suggest connections and packages, or review your work. Proposed changes, such as new nodes, connections, code or packages, appear as cards in the chat. Nothing changes until you click Apply, and Dismiss drops a proposal.
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