Hi! It's usually not so helpful to bump a thread, especially not after such a short period of time – it can often make it harder for us to keep track of new threads and make sure we can answer everyone.
If you see an error message in the UI about the server not running correctly, it typically means that the Python recipe raised an error. In this case, the cause of the error was this:
Which recipe are you running and how are you loading in the data? Are you labelling examples with pre-defined spans?
Basically, what the error means is that Prodigy came across an annotated span referring to a slice from character 1 to 4 – but this slice doesn't map to valid tokens produced by the tokenizer. If you've generated pre-annotated spans yourself, this can sometimes happen if you have leading or trailing whitespace, or an off-by-one error in the offsets. In some cases, it can also mean that your data assumes that a string is split when it isn't – for instance, A-B → ["A", "-", "B"] vs. ["A-B"]. So you can either adjust the tokenization rules, provide your custom "tokens" in the data (if you'll be using the same tokenization during training) or adjust your annotation scheme to ensure that the model will be able to learn from the data. Also see this thread for tips on how to find and resolve mismatched tokenization: