Function fetchGeminiModels

core/llm/fetchModels.ts:176–216

(
  apiKey?: string,
  apiBase?: string,
)

}

async function fetchGeminiModels(
  apiKey?: string,
  apiBase?: string,
): Promise<FetchedModel[]> {
  const base = apiBase || "https://generativelanguage.googleapis.com/v1beta/";
  const url = new URL("models", base);
  url.searchParams.set("key", apiKey ?? "");
  const response = await fetch(url);
  if (!response.ok) {
    throw new Error(`Failed to fetch Gemini models: ${response.status}`);
  }
  const data = await response.json();
  return (data.models ?? [])
    .filter((m: any) => {
      const id: string = m.name?.replace("models/", "") ?? "";
      const methods: string[] = m.supportedGenerationMethods ?? [];
      return (
        !id.startsWith("gemini-2.0") &&
        !id.startsWith("gemma-") && // Gemma models are supported through Ollama, not the Gemini API
        !id.startsWith("nano-banana") &&
        !id.startsWith("lyria") &&
        methods.includes("generateContent") &&
        !methods.includes("embedContent") &&
        !methods.includes("predict") &&
        !methods.includes("predictLongRunning") &&
        !methods.includes("bidiGenerateContent") &&
        !id.includes("tts") &&
        !id.includes("image") &&
        !id.includes("robotics") &&
        !id.includes("computer-use")
      );
    })
    .map((m: any) => ({
      name: m.displayName ?? m.name?.replace("models/", ""),
      modelId: m.name?.replace("models/", ""),
      icon: "gemini.png",
      contextLength: m.inputTokenLimit,
      maxTokens: m.outputTokenLimit,
      supportsTools: true,
    }));
}

async function fetchProviderModelsViaListModels(
  provider: string,