Budibase/budibase · error · HTTPError

Unsupported AI config type: ${model.configType}

Error message

Unsupported AI config type: ${model.configType}

What it means

validateConfig is the gatekeeper for AI config creation/update against LiteLLM. It only supports configs whose configType is AIConfigType.COMPLETIONS; any other (unknown or future) config type is rejected with HTTP 400 before delegating to validateCompletionsModel. The enum (packages/types/src/documents/global/ai.ts) currently only contains COMPLETIONS, so this fires when a caller supplies a mistyped, stale, or invented configType string.

Source

Thrown at packages/server/src/sdk/workspace/ai/configs/litellm.ts:373

    const message = [
      "Error validating configuration",
      sanitizeLiteLLMErrorMessage(json.error?.message || json.result?.error),
    ]
      .filter(Boolean)
      .join(": ")

    throw new HTTPError(message, 400)
  }
}

export async function validateConfig(model: {
  provider: string
  name: string
  credentialFields: Record<string, string>
  configType: AIConfigType
}) {
  if (model.configType !== AIConfigType.COMPLETIONS) {
    throw new HTTPError(`Unsupported AI config type: ${model.configType}`, 400)
  }
  return validateCompletionsModel(model)
}

export async function getKeySettings(): Promise<{
  keyId: string
  secretKey: string
  teamId: string
}> {
  const db = context.getWorkspaceDB()
  const keyDocId = docIds.getLiteLLMKeyID()

  let keyConfig = await db.tryGet<LiteLLMKeyConfig>(keyDocId)
  if (!keyConfig || !keyConfig.teamId) {
    const workspaceId = context.getProdWorkspaceId()
    if (!workspaceId) {
      throw new HTTPError("Workspace ID is required to configure LiteLLM", 400)
    }

View on GitHub (pinned to a81a902e9a)

Solutions

1. Set configType to "completions" in the request body (or omit it where the controller defaults it to AIConfigType.COMPLETIONS).
2. Check the exact enum value in @budibase/types (AIConfigType) rather than guessing the string.
3. If a genuinely new config type is needed, extend AIConfigType and add a matching validator in validateConfig.

Example fix

// before
await api.post("/ai/configs", { name: "gpt4o", configType: "chat", ... })
// after
await api.post("/ai/configs", { name: "gpt4o", configType: "completions", ... })

const ALLOWED = ["completions"]
if (!ALLOWED.includes(config.configType)) {
  throw new Error(`configType must be one of ${ALLOWED.join(", ")}, got ${config.configType}`)
}

function isCompletionsConfig(c: { configType: string }): c is { configType: "completions" } {
  return c.configType === "completions"
}

try {
  await createConfig(cfg)
} catch (e) {
  if (e.status === 400 && e.message.startsWith("Unsupported AI config type")) {
    cfg.configType = "completions"
    await createConfig(cfg)
  } else throw e
}

When it happens

Trigger: POST/PUT to the AI config endpoints (create/update in sdk/workspace/ai/configs/index.ts) with body.configType set to anything other than "completions" — e.g. "completion" (typo), "chat", "embedding", or a value from an older client.

Common situations: Hand-rolled API calls to the configs endpoint with a wrong configType; a client SDK or script written against an older/preview enum; copying config JSON between environments where the type drifted.

Related errors

• Invalid status query
• Invalid bookmark query
• Invalid limit query
• Limit query must be between 1 and 100
• Invalid ${queryName} query

AI-assisted analysis of Budibase/budibase@a81a902e9a (2026-08-29). Data as JSON: /api/errors/bfb2661f9245d3f9. Report an issue: GitHub.