Fix WorkerLostError

✅ Solution

WorkerLostError in graphrag often signifies that a worker process executing a Ray task died unexpectedly, potentially due to exceeding memory limits, encountering a fatal error (like a ValueError due to unexpected data), or being preempted. To fix it, thoroughly examine the logs of the failed worker to pinpoint the root cause exception (e.g., memory error, specific ValueError), address the underlying issue in your code (e.g., optimize memory usage, handle malformed data gracefully), and ensure your Ray cluster has sufficient resources. Retrying the failed task with `ray.wait` might also help in cases of transient failures.