Agent

Warning

Unstable — in active development

The agent is experimental, and that applies to every surface on this page: the docked chat bar, the Agent Window, /loop jobs, and report generation. Behaviour and results change between releases and vary with the connected model provider. Check what it did before relying on it, particularly for actions that modify data or the model — all of which are also available by hand through quick filters, the grid’s context menu, the left panel, and the CLI console.

Weights Studio has a docked agent bar and an expandable, tabbed agent window. Both are backed entirely by a local OpenCode server (opencode.ai) — see Experiment Agent Assistant for the full action list, and for the distinction between this chat-bar agent and the separate /loop/landing-page OpenCode agent.

The docked chat bar sits above the grid and is always available. Ask it in plain language to sort the grid, tag or discard samples, analyse a signal, or freeze or reset part of the model.

Agent Window

Expanding the chat history opens a tabbed window:

• Frontend Agent — the main conversation, carried over from the landing page when the backend connected. Replies to the docked chat bar land in this same transcript, so there is one conversation rather than two.

• One tab per running /loop job, created when the job starts and closable when you’re done with it.

The window also exports the conversation as JSON, and clears it.

Commands

Command	What it does
/init	Connect to the OpenCode server and pick a model.
/model	Switch the active model.
/reset	Clear the current agent runtime connection and status.
/clear	Clear the conversation.
/compact	Compact the conversation so a long session keeps its context.
/loop <minutes> <prompt>	Run a prompt on a repeating interval as a background job — for example /loop 10 check whether train loss has plateaued and tag the worst samples. /loop list shows the running jobs; /loop stop <id> ends one.
@reset	Reset the grid to the full dataset.

/loop jobs run against the local OpenCode server, not the gRPC agent, and survive while you work elsewhere in the studio.

Setting it up

WeightsLab starts (or reuses) a local opencode serve process for you, so there is normally nothing to configure before the agent is available. If the backend is not connected to it yet, the studio shows the agent as unconfigured and the input placeholder tells you to type /init.

Typical setup:

1. Authenticate OpenCode once, if you haven’t already: opencode auth login (or the landing page’s login modal) — OpenRouter, Anthropic, a local Ollama endpoint, anything OpenCode supports.

2. Start WeightsLab (wl.serve(serving_grpc=True)).

3. Start Weights Studio (weightslab start).

4. Ask questions in the agent bar, or type /init first to pick a specific model.

The /init flow itself:

1. Type /init in the agent input.

2. Weights Studio connects to the OpenCode server.

3. Select a model from the available model list.

4. Confirm to initialize the runtime connection.

Tip

On a remote machine, the browser reaches the OpenCode server directly rather than through the studio’s proxy — so its port has to be reachable too. See Bridging to a remote server.

History behavior

• Command entries such as /init, /model, and /reset are shown on the user side of the history.

• Agent lifecycle events (connection setup, model changes, reset) are shown as separate log-style entries.

• A pinned instruction line at the top summarizes the available commands.