Overview

CompletionsDataset.process() crashes when mask_prompt=True because a single message dict is passed to apply_chat_template instead of a list.

Problem

When training with the completions format and mask_prompt enabled, the process method builds a two-element messages list, then passes messages[0] (a bare dict) to tokenizer.apply_chat_template(). This method expects a list of message dicts, causing a crash.

The analogous code path in ChatDataset.process() correctly passes a list slice (messages[:-1]), so this appears to be an oversight specific to the completions path.

Requirements

• The mask-prompt code path in CompletionsDataset.process() must pass a properly-typed argument (list of message dicts) to apply_chat_template
• The prompt masking offset calculation must match the behavior of ChatDataset.process() (i.e., tokenize only the user prompt portion with add_generation_prompt=True)
• Existing non-mask-prompt behavior must remain unchanged

Acceptance Criteria

• Training with completions format and mask_prompt=True no longer crashes
• The prompt mask offset correctly covers only the prompt tokens (not the completion)
• Training with completions format and mask_prompt=False is unaffected
• ChatDataset with mask_prompt=True continues to work correctly

Constraints

• Fix should be minimal and not change any unrelated behavior
• Must be backwards-compatible with existing training configs

Reference

• ChatDataset.process() handles the same pattern correctly and serves as the reference implementation