vercel/ai · error · TooManyEmbeddingValuesForCallError

AI_TooManyEmbeddingValuesForCallError

AI_TooManyEmbeddingValuesForCallError

Error message

Too many values for a single embedding call. The ${provider} model "${modelId}" can only embed up to ${maxEmbeddingsPerCall} values per call, but ${values.length} values were provided.

What it means

Error "Too many values for a single embedding call. The ${provider} model "${modelId}" can only embed up to ${maxEmbeddingsPerCall} values per call, but ${values.length} values were provided." thrown in vercel/ai.

Source

Thrown at packages/alibaba/src/alibaba-embedding-model.ts:73

  constructor(modelId: AlibabaEmbeddingModelId, config: AlibabaConfig) {
    this.modelId = modelId;
    this.config = config;
  }

  get provider(): string {
    return this.config.provider;
  }

  async doEmbed({
    values,
    headers,
    abortSignal,
    providerOptions,
  }: Parameters<EmbeddingModelV4['doEmbed']>[0]): Promise<
    Awaited<ReturnType<EmbeddingModelV4['doEmbed']>>
  > {
    if (values.length > this.maxEmbeddingsPerCall) {
      throw new TooManyEmbeddingValuesForCallError({
        provider: this.provider,
        modelId: this.modelId,
        maxEmbeddingsPerCall: this.maxEmbeddingsPerCall,
        values,
      });
    }

    const alibabaOptions = await parseProviderOptions({
      provider: 'alibaba',
      providerOptions,
      schema: alibabaEmbeddingModelOptions,
    });

    // TODO: Explore first-class sparse embedding support in AI SDK core.
    if (alibabaOptions?.outputType === 'sparse') {
      throw new UnsupportedFunctionalityError({
        functionality: "Alibaba embedding outputType 'sparse'",
        message:

View on GitHub (pinned to 69428b1f8b)

When it happens

Trigger: Thrown at packages/alibaba/src/alibaba-embedding-model.ts:73 when the library encounters an invalid state.

Common situations: See trigger scenarios.

AI-assisted analysis of vercel/ai@69428b1f8b (2026-08-30). Data as JSON: /api/errors/d97c39ab5e2f8578. Report an issue: GitHub.