kopitiam-tokenizer 0.2.0

//! [`BpeTokenizer`]: the byte-level BPE [`crate::Tokenizer`] implementation.
//!
//! This ties together the other modules in this crate into the pipeline a
//! GPT-2/Qwen-family tokenizer actually runs:
//!
//! ```text
//! text
//!   -> split off special tokens atomically      (specials::SpecialTokens)
//!   -> pre-tokenize the remaining text spans     (pretokenize::split)
//!   -> map each chunk's raw UTF-8 bytes to base-vocab ids
//!   -> repeatedly apply the highest-priority merge until none apply
//! ```
//!
//! Two design choices are worth calling out because they are easy to get
//! wrong by copying GPT-2's Python reference too literally:
//!
//! * **The byte-to-unicode alphabet never appears here.** [`crate::vocab::Vocab`]
//!   stores every token's *canonical raw bytes*, decoded once at load time
//!   by [`crate::loader`] (or supplied directly by [`BpeTokenizer::from_vocab_and_merges`]).
//!   So encoding a chunk is simply "look up the vocab id for each of its
//!   raw UTF-8 bytes" -- no per-token mapped-character round trip, at
//!   encode or decode time.
//! * **Decoding needs no special-token branch.** A special token's id maps
//!   to the raw UTF-8 bytes of its own content (see [`crate::specials`]),
//!   so plain byte concatenation already reconstructs it.

use crate::Tokenizer;
use crate::merges::MergeTable;
use crate::pretokenize;
use crate::specials::{Segment, SpecialTokens};
use crate::vocab::Vocab;
use kopitiam_core::{Error, Result};

/// A byte-level BPE tokenizer: the scheme used by the GPT-2/GPT-3/GPT-4 and
/// Qwen model families.
///
/// Build one via [`BpeTokenizer::from_vocab_and_merges`] (plain data --
/// what tests and a future GGUF loader use) or
/// [`crate::loader::from_tokenizer_json`] (HuggingFace `tokenizer.json`).
#[derive(Debug, Clone)]
pub struct BpeTokenizer {
    vocab: Vocab,
    /// `byte_ids[b as usize]` is the vocab id of the single-byte token for
    /// raw byte `b`. Precomputed once at construction (rather than doing a
    /// `vocab.id_of(&[b])` hash lookup per input byte) since every encode
    /// call starts by mapping raw bytes to ids.
    byte_ids: [u32; 256],
    merges: MergeTable,
    /// Whether to prepend a single space to the input before
    /// pre-tokenizing, if it does not already start with one. See
    /// [`BpeTokenizer::with_add_prefix_space`] for why this exists and
    /// its (documented) scope limitation.
    add_prefix_space: bool,
    specials: SpecialTokens,
}

impl BpeTokenizer {
    /// Builds a tokenizer directly from a dense, id-ordered vocab and an
    /// ordered merge list -- no JSON, no byte-to-unicode mapping involved.
    ///
    /// `vocab_entries[i]` is the raw-byte token for id `i`. Every one of
    /// the 256 possible single bytes must appear somewhere in
    /// `vocab_entries` as its own one-byte token, or this returns
    /// [`Error::MalformedModel`] -- that completeness is what makes
    /// byte-level BPE total (every input is encodable, no `<UNK>`).
    pub fn from_vocab_and_merges(
        vocab_entries: Vec<Vec<u8>>,
        merge_pairs: Vec<(Vec<u8>, Vec<u8>)>,
    ) -> Result<Self> {
        Self::from_vocab(Vocab::from_entries(vocab_entries)?, merge_pairs)
    }

    /// Shared construction path for an already-built [`Vocab`]. Used by
    /// [`BpeTokenizer::from_vocab_and_merges`] (dense array input) and by
    /// [`crate::loader`] (sparse, id-keyed JSON input, which cannot go
    /// through `Vocab::from_entries`'s "index is the id" assumption).
    pub(crate) fn from_vocab(vocab: Vocab, merge_pairs: Vec<(Vec<u8>, Vec<u8>)>) -> Result<Self> {
        let merges = MergeTable::build(&merge_pairs, |b| vocab.id_of(b))?;

        let mut byte_ids = [0u32; 256];
        for b in 0u16..=255 {
            let b = b as u8;
            byte_ids[b as usize] = vocab.id_of(&[b]).ok_or_else(|| Error::MalformedModel {
                format: "bpe-vocab",
                reason: format!(
                    "byte-level vocab has no single-byte token for byte {b:#04x}; \
                     byte-level BPE requires all 256 bytes as base tokens"
                ),
            })?;
        }

        Ok(Self {
            vocab,
            byte_ids,
            merges,
            add_prefix_space: false,
            specials: SpecialTokens::new(),
        })
    }

    /// Sets whether a leading space is prepended before pre-tokenizing an
    /// input that does not already start with one.
    ///
    /// GPT-2 treats a word at the very start of a sequence differently
    /// from the same word later on (the pre-tokenization pattern's
    /// `" ?"` prefix means "dog" and " dog" are different tokens), so
    /// most fast tokenizers add this synthetic leading space to make the
    /// first word behave like every other word. Whether it defaults to on
    /// varies by model family; a loaded `tokenizer.json`'s
    /// `pre_tokenizer.add_prefix_space` field (see [`crate::loader`])
    /// takes precedence over this default when present.
    ///
    /// Scope limitation: this crate applies the prefix space to the very
    /// start of the whole input passed to [`BpeTokenizer::encode`], before
    /// special-token splitting. The reference implementation technically
    /// scopes it to the first *non-special* span, which only differs when
    /// a special token is the very first thing in the input -- a rare
    /// enough case that documenting it here beats the added complexity of
    /// tracking it precisely.
    #[must_use]
    pub fn with_add_prefix_space(mut self, add_prefix_space: bool) -> Self {
        self.add_prefix_space = add_prefix_space;
        self
    }

    /// Registers a token that must always be matched atomically, never
    /// split by pre-tokenization or BPE -- e.g. Qwen's `<|endoftext|>`,
    /// `<|im_start|>`, `<|im_end|>`.
    ///
    /// `id` becomes the token's vocab id; if it falls outside the current
    /// vocab it grows the vocab to fit (special tokens are conventionally
    /// appended after the base vocab). Errors if `id` is already assigned
    /// to different content.
    pub fn add_special_token(&mut self, content: impl Into<String>, id: u32) -> Result<()> {
        let content = content.into();
        self.vocab.insert(id, content.clone().into_bytes())?;
        self.specials.register(content, id);
        Ok(())
    }

    /// The id of a registered special token by its exact content, if any.
    pub fn special_token_id(&self, content: &str) -> Option<u32> {
        self.specials.id_of(content)
    }

    /// The id of any exact token (special or ordinary) by its raw bytes.
    pub fn token_id(&self, token: &[u8]) -> Option<u32> {
        self.vocab.id_of(token)
    }

    /// Maps a pre-tokenized chunk's raw UTF-8 bytes to their base
    /// (single-byte) vocab ids.
    fn chunk_to_symbols(&self, chunk: &str) -> Vec<u32> {
        chunk.bytes().map(|b| self.byte_ids[b as usize]).collect()
    }

    /// Repeatedly merges the highest-priority (lowest-rank) adjacent pair
    /// until no pair in `symbols` has a merge rule.
    ///
    /// This rescans every adjacent pair from scratch on every merge, so it
    /// is O(merges x symbols) per chunk -- quadratic in the chunk length
    /// in the worst case. That is the "naive but correct first"
    /// implementation named in this crate's design brief. The standard
    /// production technique (see e.g. the vendored reference's
    /// `models/bpe/word.rs`) keeps a doubly-linked list of symbols plus a
    /// binary heap of candidate merges keyed by rank, so each merge is
    /// found in O(log symbols) and applying it only re-examines the two
    /// new neighboring pairs instead of rescanning everything. That
    /// optimization is a pure performance change with no effect on the
    /// output and belongs here, behind this same function signature, once
    /// tokenizer throughput actually matters for the runtime.
    fn merge(&self, mut symbols: Vec<u32>) -> Vec<u32> {
        loop {
            let mut best: Option<(usize, u32, u32)> = None; // (position, rank, merged_id)
            for i in 0..symbols.len().saturating_sub(1) {
                if let Some(rule) = self.merges.get(symbols[i], symbols[i + 1])
                    && best.is_none_or(|(_, best_rank, _)| rule.rank < best_rank)
                {
                    best = Some((i, rule.rank, rule.merged_id));
                }
            }
            let Some((i, _, merged_id)) = best else {
                return symbols;
            };
            symbols[i] = merged_id;
            symbols.remove(i + 1);
        }
    }
}

impl Tokenizer for BpeTokenizer {
    fn encode(&self, text: &str) -> Result<Vec<u32>> {
        if text.is_empty() {
            return Ok(Vec::new());
        }

        let prefixed;
        let text = if self.add_prefix_space && !text.starts_with(' ') {
            prefixed = format!(" {text}");
            prefixed.as_str()
        } else {
            text
        };

        let mut ids = Vec::new();
        for segment in self.specials.split(text) {
            match segment {
                Segment::Special(id) => ids.push(id),
                Segment::Text(span) => {
                    for (start, end) in pretokenize::split(span) {
                        let symbols = self.chunk_to_symbols(&span[start..end]);
                        ids.extend(self.merge(symbols));
                    }
                }
            }
        }
        Ok(ids)
    }

    fn decode(&self, ids: &[u32]) -> Result<String> {
        let mut bytes = Vec::new();
        for &id in ids {
            let token_bytes = self.vocab.bytes_of(id).ok_or(Error::IndexOutOfBounds {
                dim: 0,
                index: id as usize,
                len: self.vocab.len(),
            })?;
            bytes.extend_from_slice(token_bytes);
        }
        // Lossy, not `from_utf8`: for any id sequence produced by this
        // tokenizer's own `encode`, the concatenated bytes are always
        // valid UTF-8 (they reconstruct the original valid `&str`), so the
        // lossy path never actually triggers there. But `decode` is also
        // called on model output during generation, where a caller may
        // reasonably decode a prefix of ids that splits a multi-byte
        // character mid-sequence (e.g. streaming token-by-token before a
        // multi-token emoji is complete); erroring on that would make
        // streaming decode unusable, so this matches the universal
        // tokenizer convention of never failing decode on well-formed ids.
        Ok(String::from_utf8_lossy(&bytes).into_owned())
    }

    fn vocab_size(&self) -> usize {
        self.vocab.len()
    }
}

#[cfg(test)]
mod tests {
    use super::*;

    /// A tiny hand-built vocab/merges pair standing in for a trained BPE
    /// model. Base bytes 'a', 'b', 'c' (plus every other byte, since
    /// byte-level BPE requires all 256), and two merges: `("a","b")` ->
    /// `"ab"` (rank 0, highest priority) and `("ab","c")` -> `"abc"`
    /// (rank 1).
    fn tiny_tokenizer() -> BpeTokenizer {
        let mut vocab: Vec<Vec<u8>> = (0u16..=255).map(|b| vec![b as u8]).collect();
        vocab.push(b"ab".to_vec()); // id 256
        vocab.push(b"abc".to_vec()); // id 257
        let merges = vec![
            (b"a".to_vec(), b"b".to_vec()),
            (b"ab".to_vec(), b"c".to_vec()),
        ];
        BpeTokenizer::from_vocab_and_merges(vocab, merges).expect("valid tiny tokenizer")
    }

    fn byte_id(tok: &BpeTokenizer, b: u8) -> u32 {
        tok.token_id(&[b]).unwrap()
    }

    #[test]
    fn a_plus_b_then_ab_plus_c_merges_produce_the_single_token_abc() {
        let tok = tiny_tokenizer();
        let ids = tok.encode("abc").unwrap();
        assert_eq!(ids, vec![tok.token_id(b"abc").unwrap()]);
    }

    /// The property that actually needs the rank comparison, not just the
    /// existence check: build a vocab where the *leftmost* adjacent pair
    /// has the *lower priority* (higher rank number) merge, and a
    /// non-leftmost pair has the higher-priority (rank 0) merge. A
    /// tokenizer that greedily merges "the first pair it happens to find"
    /// while scanning left to right -- instead of comparing ranks across
    /// every candidate pair before merging any of them -- would merge
    /// `(a, b)` first because it is encountered first, producing `["ab",
    /// "c"]` with no further merges possible. The correct, rank-ordered
    /// result instead prefers `(b, c)` (rank 0, taught first during BPE
    /// training) even though it is not the leftmost pair, producing `["a",
    /// "bc"]`.
    #[test]
    fn merges_apply_in_rank_order_not_leftmost_scan_order() {
        let mut vocab: Vec<Vec<u8>> = (0u16..=255).map(|b| vec![b as u8]).collect();
        vocab.push(b"bc".to_vec()); // id 256
        vocab.push(b"ab".to_vec()); // id 257
        let merges = vec![
            (b"b".to_vec(), b"c".to_vec()), // rank 0: highest priority
            (b"a".to_vec(), b"b".to_vec()), // rank 1: lower priority
        ];
        let tok = BpeTokenizer::from_vocab_and_merges(vocab, merges).unwrap();

        let ids = tok.encode("abc").unwrap();
        let expected = vec![tok.token_id(b"a").unwrap(), tok.token_id(b"bc").unwrap()];
        assert_eq!(
            ids, expected,
            "expected rank-0 (b,c) to win over the leftmost-but-lower-priority (a,b) pair"
        );

        // Pin down exactly what the *wrong* leftmost-greedy answer would
        // have been, so this test fails loudly (not just "doesn't match
        // expected") if the implementation regresses to scan order.
        let wrong_leftmost_greedy_answer =
            vec![tok.token_id(b"ab").unwrap(), tok.token_id(b"c").unwrap()];
        assert_ne!(ids, wrong_leftmost_greedy_answer);
    }

    #[test]
    fn vocab_size_counts_every_registered_id() {
        let tok = tiny_tokenizer();
        assert_eq!(tok.vocab_size(), 258);
    }

    #[test]
    fn empty_string_encodes_to_empty() {
        let tok = tiny_tokenizer();
        assert_eq!(tok.encode("").unwrap(), Vec::<u32>::new());
    }

    #[test]
    fn decode_of_empty_is_empty() {
        let tok = tiny_tokenizer();
        assert_eq!(tok.decode(&[]).unwrap(), "");
    }

    #[test]
    fn decode_rejects_unknown_id_gracefully() {
        let tok = tiny_tokenizer();
        let err = tok.decode(&[99_999]).unwrap_err();
        assert!(matches!(err, Error::IndexOutOfBounds { .. }));
    }

    #[test]
    fn special_tokens_are_never_split_by_bpe() {
        let mut tok = tiny_tokenizer();
        tok.add_special_token("<|endoftext|>", 300).unwrap();
        let ids = tok.encode("ab<|endoftext|>c").unwrap();
        assert_eq!(ids.last().copied(), Some(byte_id(&tok, b'c')));
        assert!(ids.contains(&300));
        // The special token contributes exactly one id, not one id per
        // byte of "<|endoftext|>".
        assert_eq!(ids.iter().filter(|&&id| id == 300).count(), 1);
    }

    #[test]
    fn decode_of_encode_is_byte_exact_for_ascii() {
        let tok = tiny_tokenizer();
        let s = "abcabc hello world";
        assert_eq!(tok.decode(&tok.encode(s).unwrap()).unwrap(), s);
    }
}