invoke-ai/InvokeAI · error · ValueError

Unknown lora: {lora_key}!

Error message

Unknown lora: {lora_key}!

What it means

The Anima LoRA loader requires the referenced LoRA key to exist in the model manager. If context.models.exists(lora_key) is False, the loader raises this ValueError. It also raises a related error if the LoRA is already applied to the transformer or Qwen3 encoder.

Source

Thrown at invokeai/app/invocations/anima_lora_loader.py:63

    weight: float = InputField(default=0.75, description=FieldDescriptions.lora_weight)
    transformer: TransformerField | None = InputField(
        default=None,
        description=FieldDescriptions.transformer,
        input=Input.Connection,
        title="Anima Transformer",
    )
    qwen3_encoder: Qwen3EncoderField | None = InputField(
        default=None,
        title="Qwen3 Encoder",
        description=FieldDescriptions.qwen3_encoder,
        input=Input.Connection,
    )

    def invoke(self, context: InvocationContext) -> AnimaLoRALoaderOutput:
        lora_key = self.lora.key

        if not context.models.exists(lora_key):
            raise ValueError(f"Unknown lora: {lora_key}!")

        if self.transformer and any(lora.lora.key == lora_key for lora in self.transformer.loras):
            raise ValueError(f'LoRA "{lora_key}" already applied to transformer.')
        if self.qwen3_encoder and any(lora.lora.key == lora_key for lora in self.qwen3_encoder.loras):
            raise ValueError(f'LoRA "{lora_key}" already applied to Qwen3 encoder.')

        output = AnimaLoRALoaderOutput()

        if self.transformer is not None:
            output.transformer = self.transformer.model_copy(deep=True)
            output.transformer.loras.append(
                LoRAField(
                    lora=self.lora,
                    weight=self.weight,
                )
            )
        if self.qwen3_encoder is not None:
            output.qwen3_encoder = self.qwen3_encoder.model_copy(deep=True)

View on GitHub (pinned to 0b6a024f2f)

Solutions

1. Install the missing LoRA via the model manager so its key exists, or update the workflow to reference the installed LoRA's key.
2. Check context.models.exists(key) / the Models tab for the exact key and fix the reference.
3. Re-link the LoRA loader node's model field in the workflow UI after re-import.

Example fix

// before
lora_field = LoRAModelField(key="char_lora_old_key")  // deleted/never installed
// after
if (context.models.exists("char_lora_new_key")) {
  lora_field = LoRAModelField(key="char_lora_new_key")
}

if not context.models.exists(lora_key):
    raise LookupError(f"LoRA {lora_key} not installed; install it or fix the workflow reference")

try:
    output = lora_loader.invoke(context)
except ValueError as e:
    if str(e).startswith("Unknown lora:"):
        missing = str(e).split(":", 1)[1].strip().rstrip("!")
        install_or_relink_lora(missing)  # import the model, then update the node key
    else:
        raise

When it happens

Trigger: Referencing a LoRA by key that was deleted, renamed, or never installed; running a saved workflow whose LoRA key no longer matches any model in the manager.

Common situations: Moving workflows between machines with different model libraries; deleting or re-importing a LoRA which changes its key; typos in keys when scripting workflows via the API.

Related errors

• Unknown lora: {lora_key}!
• Unknown lora: {lora.lora.key}!
• Unknown lora: {self.lora.key}!
• Unknown lora: {lora_key}!
• Unknown lora: {lora_key}!

AI-assisted analysis of invoke-ai/InvokeAI@0b6a024f2f (2026-08-29). Data as JSON: /api/errors/36369ec30b49e3bf. Report an issue: GitHub.