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Manifest: the Bots Tab

The manifest editor's Bots tab - import and check AI models, declare scripted and AI bots, wire their handlers and difficulties, and open the training page.

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Mod ▸ Mod Details… ▸ Bots is where a game declares its opponents (bots) and the models its AI bots run (aiModels). The tab exists only on a game pack — the host loads models and seats bots for the room's game, and nothing else. Its badge counts the problems publish would refuse. Game bots explains the feature; this page is the reference for the controls.

AI models#

The totals line shows how many models you have of the 4 allowed and their combined size against the 128 MiB cap. Each model is a row: id, path, size, node count, opset, min tier and a status — not checked, checking…, valid, file missing, could not check, or the refusal codes the scanner would report, each listed underneath with its message verbatim (ai-model-op-not-allowed: Operator "Erf" is not one a model may use.). The checks are the publish scanner's own code, run here, so a model that shows valid passes publish.

  • Import model… — pick an .onnx file. See The Import model dialog.
  • Re-check files — validate every model file in the draft again (after replacing one outside the editor, say).
  • Label and Min tier per model; Remove deletes the declaration and the file.
  • Difficulty presets per model — Difficulty (id), Label, Sims (1–4096, 0 for unset) and Temp (0–2). ⚠ These are recorded with the model, not applied: your script decides its own simulations. The one value the table reads is a preset's params.turnBudgetMs, which this tab does not edit.

A model over 45 MiB gets a note: the in-app Publish cannot send a file that large, so push it to the game's GitHub repository with git (git add <path>, commit, push), then publish.

An .onnx file in the project that no model declares is listed with ai-model-undeclared: publish refuses it. Import it as a model or delete it on the Files tab.

Trained models ready to import. When the training page has exported a checkpoint for this project on this device, it is listed here with its size and generation. Import… opens the import dialog on it — the same checks as a picked file, so a file that changed since the export is refused — and Discard deletes the export without importing it. Following the training page's Open the editor to add it link opens this dialog directly.

The Import model dialog#

  1. Model file (.onnx) — the file is checked at once, in a background worker, exactly as publish will check it. A format that is not ONNX (.pt, .h5, .safetensors, …) is refused as ai-model-format. A refused model shows every issue code and message; fix them in the tool that exported it and pick the new file.
  2. The card shows what the model is: size, opset, IR version, inputs and outputs, an operator histogram, the parameter count, and an estimated tier — measured on this device when it can be, otherwise the estimate for a fast processor. Above about 12 MB, or 50 ms per position, it suggests gpu.
  3. Label, Id (lowercase, digits, hyphens) and Min tier. Picking a tier below the estimate is allowed with a warning — choose it only if you have measured it. Importing over an existing id replaces that model: its file and hash are overwritten and the bots using it keep pointing at it.
  4. For a model that looks like a policy/value network, Difficulties offers the presets Easy 16, Normal 64 and Hard 256 simulations per move.
  5. Add to project (or Replace model). The import credit gate asks where the file came from first; then the file is written to ai/<id>.onnx and the manifest entry — with the file's exact size and SHA-256 — is added, and assets updated.

Bots#

Add bot (up to 8) adds a row; Remove deletes one (an AI bot that named it as its fallback loses the fallback, and the tab says so). Each row:

Control Field Notes
Label label The name in the lobby and at the table.
Id id Rooms remember a seated bot by it.
Kind kind Scripted or AI.
Model modelId AI only — one of the models above: the bot's default model.
Fallback bot fallbackBotId AI only — a scripted bot of this game offered to a new host that cannot run the model.
Handler handler The id the scene script passes to bots.register({ id, onTurn }).
Registered — The handler ids your scene scripts actually register; picking one fills in Handler.
Default difficulty defaultDifficulty Which difficulty a room starts on; "the first" when unset.
Seats (most) seats.max The most of this bot one table may seat; 0 leaves it unset (as many as the game has seats).
Description description One line, shown where the bot is offered.
Difficulty / Label / About difficulties[] Named strengths players pick; Add difficulty (up to 8).
Difficulty ▸ Model difficulties[].modelId AI only — the model this difficulty plays with, for a separate network per Easy / Medium / Hard. Bot's default model leaves it unset and uses Model above. The table loads, gates the host's device on, ranks and reports (ctx.modelId) the model picked here for that difficulty.

Handler warnings. The Registered list is read from each scene script's compiled body — what publish reads. A handler no script registers is flagged (publish refuses it as bot-handler-missing). A handler that is in a script's source but not in its compiled body gets its own warning: the script was edited but not saved; open it and save it so it compiles. Only bots.register({ id: "…", … }) with the id written as a plain string inside the call is seen.

Train a model… opens the training page for this project in the same tab.

See also#

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