BerriAI/litellm · error · ValueError

image variation provider has no known model info config - re

Error message

image variation provider has no known model info config - required for getting api keys, etc.: {custom_llm_provider}. Supported providers are: {LITELLM_IMAGE_VARIATION_PROVIDERS}

What it means

The provider was accepted into LITELLM_IMAGE_VARIATION_PROVIDERS, but ProviderConfigManager.get_provider_model_info() returned None, meaning litellm has no model-info config from which to resolve API keys and base URLs for variations (litellm/images/main.py:645-653). This is an internal-coverage gap: the enum knows the provider, the config registry does not.

Source

Thrown at litellm/images/main.py:651

    # route to the correct provider w/ the params
    try:
        llm_provider: Final = LlmProviders(custom_llm_provider)
        image_variation_provider: Final = LITELLM_IMAGE_VARIATION_PROVIDERS(llm_provider)
    except ValueError:
        raise ValueError(
            f"Invalid image variation provider: {custom_llm_provider}. Supported providers are: {LITELLM_IMAGE_VARIATION_PROVIDERS}"
        )
    model_response: Final = ImageResponse()

    response: ImageResponse | None = None

    provider_config: Final = ProviderConfigManager.get_provider_model_info(
        model=model or "",  # openai defaults to dall-e-2
        provider=llm_provider,
    )

    if provider_config is None:
        raise ValueError(
            f"image variation provider has no known model info config - required for getting api keys, etc.: {custom_llm_provider}. Supported providers are: {LITELLM_IMAGE_VARIATION_PROVIDERS}"
        )

    api_key: Final = provider_config.get_api_key(litellm_params.get("api_key", None))
    api_base = provider_config.get_api_base(litellm_params.get("api_base", None))

    if image_variation_provider == LITELLM_IMAGE_VARIATION_PROVIDERS.OPENAI:
        if api_key is None:
            raise ValueError("API key is required for OpenAI image variations")
        if api_base is None:
            raise ValueError("API base is required for OpenAI image variations")

        response = openai_image_variations.image_variations(
            model_response=model_response,
            api_key=api_key,
            api_base=api_base,
            model=model,
            image=image,

View on GitHub (pinned to 6c2dcb801b)

Solutions

Upgrade litellm to a release where the variation provider's model info config is registered
Pin to a known-good litellm version if a recent release introduced the regression
If unresolved, fall back to OpenAI/Topaz variation endpoints which have complete configs
Report the provider/model pair to litellm's GitHub issues

Defensive patterns

Strategy: validation

Validate before calling

def variation_model_info_available(model: str, provider: str) -> bool:
    from litellm.provider_config_manager import ProviderConfigManager  # adjust import
    try:
        return ProviderConfigManager.get_provider_model_info(model=model, provider=provider) is not None
    except Exception:
        return False

Try / catch

try:
    r = litellm.image_variations(model=m, image=img)
except ValueError as e:
    if "no known model info config" in str(e):
        raise RuntimeError(f"litellm version lacks variation config for {m}; upgrade litellm") from e
    raise

Prevention

Pin litellm and test image-variation smoke calls in CI to catch coverage gaps
Upgrade litellm when adopting a new variation provider
Report missing configs upstream with the exact model string

When it happens

Trigger: Hitting a variation provider whose enum entry exists but whose model-info registration is missing in the installed litellm version; typically after adding a new provider enum member without the accompanying config, or version skew between enum and registry.

Common situations: Using a fork/patched litellm where the enum was extended; or a bug in a specific litellm release.

Related errors

AI-assisted analysis of BerriAI/litellm@6c2dcb801b (2026-08-15). Data as JSON: /api/errors/df7cc84f28e078d6. Report an issue: GitHub.