# Background

In RLHFDataset, we filter out prompts that are too long. This requires
apply_chat_template to the whole dataset, which is not scalable when the
dataset is large.
https://github.com/volcengine/verl/blob/main/verl/utils/dataset/rl_dataset.py#L132

Instead of performing filtering online, we probably want to move this
process offline and add an assertion to avoid truncation or simply
perform truncation

Reference: #502 

# Key Changes

- Add an option `data.filter_overlong_prompts=True \` to enable the
above data filtering. The default value is set to False, but we enable
it for all the example scripts.
- Add an option `data.truncation` to truncate the input_ids or prompt
length if they
exceed max_prompt_length. The default is 'error', which does not allow
the
max_prompt_length to be exceeded. The users should increase the
max_prompt_length if
  throwing the error. You can also set `left` and `right`.

### Suggestion for large-scale dataset.
For large-scale datasets, filtering overlong prompts could be
time-consuming. You should set `data.filtering_overlong_prompts=False`
and set `truncation='left'`. Also, please note that you should increase
`data.max_prompt_length` to avoid over-truncation of the prompts.