invoke-ai/InvokeAI · error · HTTPException

Error setting recall parameter {param_key}

Error message

Error setting recall parameter {param_key}

What it means

HTTP 500 raised when persisting an individual recall parameter via client_state_persistence.set_by_key throws (storage backend failure, serialization problem, etc.). The failure is logged with the underlying exception and the endpoint aborts with a generic detail naming the offending parameter key.

Source

Thrown at invokeai/app/api/routers/recall_parameters.py:493

        else:
            provided_params = {k: v for k, v in parameters.model_dump().items() if v is not None}

        if not provided_params:
            return {"status": "no_parameters_provided", "updated_count": 0}

        # Store each parameter in client state scoped to the current user
        updated_count = 0
        for param_key, param_value in provided_params.items():
            # Convert parameter values to JSON strings for storage
            value_str = json.dumps(param_value)
            try:
                ApiDependencies.invoker.services.client_state_persistence.set_by_key(
                    current_user.user_id, f"recall_{param_key}", value_str
                )
                updated_count += 1
            except Exception as e:
                logger.error(f"Error setting recall parameter {param_key}: {e}")
                raise HTTPException(
                    status_code=500,
                    detail=f"Error setting recall parameter {param_key}",
                )

        logger.info(f"Updated {updated_count} recall parameters for queue {queue_id}")

        # Resolve model name to key if a model was provided
        if "model" in provided_params and isinstance(provided_params["model"], str):
            model_name = provided_params["model"]
            model_key = resolve_model_name_to_key(model_name, ModelType.Main)

            if model_key:
                logger.info(f"Resolved model name '{model_name}' to key '{model_key}'")
                provided_params["model"] = model_key
            else:
                logger.warning(f"Could not resolve model name '{model_name}' to a model key")
                # Remove model from parameters if we couldn't resolve it
                del provided_params["model"]

View on GitHub (pinned to 0b6a024f2f)

Solutions

1. Check the server log — the underlying exception is logged as 'Error setting recall parameter {param_key}: {e}'
2. Verify the client-state persistence backend (e.g. SQLite file) is writable and not locked
3. Retry the request — the error is per-parameter and may be transient
4. Reduce/sanitize the value being recalled if it is unusually large or malformed
5. Confirm no recent schema migration left the state store incompatible

// pre-flight: ensure the state store backend is reachable/writable
// (server-side check example)
if not os.access(state_db_path, os.W_OK):
    raise RuntimeError('client state store not writable')

try {
  await api.recallParameters(queueId, params);
} catch (e) {
  if (e.status === 500 && /Error setting recall parameter/.test(e.body?.detail ?? '')) {
    await sleep(1000);
    await api.recallParameters(queueId, params); // retry transient storage failure
  } else throw e;
}

When it happens

Trigger: POST /api/v1/recall_parameters/{queue_id} where client state storage (persistence service/database) fails for a given recall_{param_key}: storage down, DB locked/misconfigured, oversized or unserializable value_str, or a state-store schema issue.

Common situations: SQLite file locked by another process; disk full or permissions issue on the state store; very large recall values exceeding storage limits; degraded database after an upgrade.

Related errors

• Error getting client state
• Error setting client state
• Error getting client state keys
• Error deleting client state key
• Failed to add image to board

AI-assisted analysis of invoke-ai/InvokeAI@0b6a024f2f (2026-08-29). Data as JSON: /api/errors/af810ab2f902b0dc. Report an issue: GitHub.