Detect stop tokens during streaming inference

## Problem: Stop-token / stop-sequence detection in streaming generation During LLM inference you receive tokens incrementally (streaming). Implement logic that decides when to stop generation based on one or more **stop sequences**. ### Input - A stream/iterator of generated token IDs (or strings). - A list of stop sequences, where each stop sequence can be: - a single token ID, or - a list of token IDs representing a multi-token sequence (e.g., `[A, B, C]`). ### Output / behavior - As tokens arrive, emit generated tokens **up to but not including** the first occurrence of any stop sequence. - Stop as soon as any stop sequence is detected. ### Requirements - Must work for overlapping matches (e.g., stop sequences `[1,2,1]` and stream `...1,2,1`). - Must handle cases where a partial stop sequence appears at the end of the current buffer and completes with future tokens. - Efficient: do not rescan the entire history per token. ### Clarifications - If multiple stop sequences could match ending at the same position, stopping is immediate regardless of which matched. - If the stream ends without a stop sequence, return all tokens. Describe your approach and complexity; implement in your chosen language.