src/tokenizer.rs

// SPF Smart Gateway - BPE Tokenizer
// Copyright 2026 Joseph Stone - All Rights Reserved
//
// Byte-Pair Encoding tokenizer for SPF Transformer.
// Trains on SPF corpus (brain data, source code, rules).
// Pure Rust. No external tokenizer dependencies.
//
// Depends on: nothing (Layer 0)

use std::collections::HashMap;

// ============================================================================
// SPECIAL TOKENS
// ============================================================================

pub const PAD_TOKEN: &str = "[PAD]";
pub const BOS_TOKEN: &str = "[BOS]";
pub const EOS_TOKEN: &str = "[EOS]";
pub const UNK_TOKEN: &str = "[UNK]";
pub const TOOL_TOKEN: &str = "[TOOL]";
pub const GATE_TOKEN: &str = "[GATE]";
pub const USER_TOKEN: &str = "[USER]";
pub const SPF_TOKEN: &str = "[SPF]";
pub const ALLOWED_TOKEN: &str = "[ALLOWED]";
pub const BLOCKED_TOKEN: &str = "[BLOCKED]";

pub const PAD_ID: u32 = 0;
pub const BOS_ID: u32 = 1;
pub const EOS_ID: u32 = 2;
pub const UNK_ID: u32 = 3;
pub const TOOL_ID: u32 = 4;
pub const GATE_ID: u32 = 5;
pub const USER_ID: u32 = 6;
pub const SPF_ID: u32 = 7;
pub const ALLOWED_ID: u32 = 8;
pub const BLOCKED_ID: u32 = 9;

const NUM_SPECIAL: u32 = 10;

// ============================================================================
// BPE TOKENIZER
// ============================================================================

/// Byte-Pair Encoding tokenizer with SPF-specific special tokens
#[derive(Clone)]
pub struct Tokenizer {
    /// Token string → ID
    token_to_id: HashMap<String, u32>,
    /// ID → token string
    id_to_token: HashMap<u32, String>,
    /// Merge rules: (pair) → merged token, ordered by priority
    merges: Vec<(String, String)>,
    /// Vocabulary size
    pub vocab_size: u32,
}

impl Tokenizer {
    /// Create a new tokenizer with only special tokens (untrained)
    pub fn new() -> Self {
        let mut tok = Self {
            token_to_id: HashMap::new(),
            id_to_token: HashMap::new(),
            merges: Vec::new(),
            vocab_size: NUM_SPECIAL,
        };
        // Register special tokens
        let specials = [
            PAD_TOKEN, BOS_TOKEN, EOS_TOKEN, UNK_TOKEN, TOOL_TOKEN,
            GATE_TOKEN, USER_TOKEN, SPF_TOKEN, ALLOWED_TOKEN, BLOCKED_TOKEN,
        ];
        for (i, &s) in specials.iter().enumerate() {
            tok.token_to_id.insert(s.to_string(), i as u32);
            tok.id_to_token.insert(i as u32, s.to_string());
        }
        tok
    }

    /// Load tokenizer vocabulary from JSON file.
    /// Falls back to untrained tokenizer if file doesn't exist.
    pub fn load(path: &str) -> Result<Self, String> {
        let file_path = std::path::Path::new(path);
        if !file_path.exists() {
            // No trained tokenizer yet — use untrained (special tokens + byte fallback)
            return Ok(Self::new());
        }
        let content = std::fs::read_to_string(file_path)
            .map_err(|e| format!("Read error: {}", e))?;
        Self::from_json(&content)
    }

    /// Save tokenizer vocabulary to JSON file.
    pub fn save(&self, path: &str) -> Result<(), String> {
        let json = self.to_json();
        std::fs::write(path, json)
            .map_err(|e| format!("Write error: {}", e))
    }

    /// Train BPE on a corpus of text. Learns `num_merges` merge rules.
    /// `target_vocab` is the desired vocabulary size (including special tokens).
    pub fn train(&mut self, corpus: &str, target_vocab: u32) {
        let num_merges = target_vocab.saturating_sub(NUM_SPECIAL + 256); // 256 byte-level tokens

        // Step 1: Initialize vocabulary with all byte values
        for b in 0u8..=255 {
            let token = format!("{}", b as char);
            let id = NUM_SPECIAL + b as u32;
            self.token_to_id.insert(token.clone(), id);
            self.id_to_token.insert(id, token);
        }
        self.vocab_size = NUM_SPECIAL + 256;

        // Step 2: Tokenize corpus into byte-level tokens
        let mut words: Vec<Vec<String>> = corpus
            .split_whitespace()
            .map(|w| w.chars().map(|c| c.to_string()).collect())
            .collect();

        // Step 3: Iteratively merge most frequent pairs
        for _ in 0..num_merges {
            // Count all adjacent pairs
            let mut pair_counts: HashMap<(String, String), u64> = HashMap::new();
            for word in &words {
                for pair in word.windows(2) {
                    *pair_counts
                        .entry((pair[0].clone(), pair[1].clone()))
                        .or_insert(0) += 1;
                }
            }

            if pair_counts.is_empty() {
                break;
            }

            // Find most frequent pair
            let best_pair = pair_counts
                .iter()
                .max_by_key(|(_, &count)| count)
                .map(|(pair, _)| pair.clone());

            let (left, right) = match best_pair {
                Some(p) => p,
                None => break,
            };

            // Create merged token
            let merged = format!("{}{}", left, right);

            // Register in vocabulary
            let id = self.vocab_size;
            self.token_to_id.insert(merged.clone(), id);
            self.id_to_token.insert(id, merged.clone());
            self.merges.push((left.clone(), right.clone()));
            self.vocab_size += 1;

            // Apply merge to all words
            for word in &mut words {
                let mut i = 0;
                while i + 1 < word.len() {
                    if word[i] == left && word[i + 1] == right {
                        word[i] = merged.clone();
                        word.remove(i + 1);
                    } else {
                        i += 1;
                    }
                }
            }
        }
    }

    /// Encode text to token IDs
    pub fn encode(&self, text: &str) -> Vec<u32> {
        let mut tokens = Vec::new();

        for word in text.split_whitespace() {
            // Check if it's a special token
            if let Some(&id) = self.token_to_id.get(word) {
                tokens.push(id);
                continue;
            }

            // Byte-level tokenization
            let mut chars: Vec<String> = word.chars().map(|c| c.to_string()).collect();

            // Apply merges in order
            for (left, right) in &self.merges {
                let merged = format!("{}{}", left, right);
                let mut i = 0;
                while i + 1 < chars.len() {
                    if chars[i] == *left && chars[i + 1] == *right {
                        chars[i] = merged.clone();
                        chars.remove(i + 1);
                    } else {
                        i += 1;
                    }
                }
            }

            // Convert to IDs
            for ch in &chars {
                match self.token_to_id.get(ch) {
                    Some(&id) => tokens.push(id),
                    None => tokens.push(UNK_ID),
                }
            }
        }

        tokens
    }

    /// Decode token IDs back to text
    pub fn decode(&self, ids: &[u32]) -> String {
        let mut parts = Vec::new();
        for &id in ids {
            match self.id_to_token.get(&id) {
                Some(token) => {
                    // Skip special tokens in output (except content ones)
                    match id {
                        PAD_ID | BOS_ID | EOS_ID => continue,
                        _ => parts.push(token.clone()),
                    }
                }
                None => parts.push(UNK_TOKEN.to_string()),
            }
        }
        parts.join("")
    }

    /// Encode with BOS/EOS wrapping
    pub fn encode_with_special(&self, text: &str) -> Vec<u32> {
        let mut ids = vec![BOS_ID];
        ids.extend(self.encode(text));
        ids.push(EOS_ID);
        ids
    }

    /// Get token string for an ID
    pub fn get_token(&self, id: u32) -> Option<&str> {
        self.id_to_token.get(&id).map(|s| s.as_str())
    }

    /// Get ID for a token string
    pub fn get_id(&self, token: &str) -> Option<u32> {
        self.token_to_id.get(token).copied()
    }

    /// Serialize tokenizer state to JSON
    pub fn to_json(&self) -> String {
        let merges_json: Vec<String> = self.merges
            .iter()
            .map(|(l, r)| format!("[\"{}\",\"{}\"]", l.replace('"', "\\\""), r.replace('"', "\\\"")))
            .collect();

        let vocab_json: Vec<String> = self.token_to_id
            .iter()
            .map(|(k, v)| format!("\"{}\":{}", k.replace('"', "\\\""), v))
            .collect();

        format!(
            "{{\"vocab_size\":{},\"merges\":[{}],\"vocab\":{{{}}}}}",
            self.vocab_size,
            merges_json.join(","),
            vocab_json.join(",")
        )
    }

    /// Deserialize tokenizer from JSON string
    pub fn from_json(json: &str) -> Result<Self, String> {
        let parsed: serde_json::Value = serde_json::from_str(json)
            .map_err(|e| format!("Tokenizer JSON parse error: {}", e))?;

        let mut tok = Self::new();

        // Load vocab
        if let Some(vocab) = parsed.get("vocab").and_then(|v| v.as_object()) {
            for (token, id) in vocab {
                if let Some(id_num) = id.as_u64() {
                    let id32 = id_num as u32;
                    tok.token_to_id.insert(token.clone(), id32);
                    tok.id_to_token.insert(id32, token.clone());
                }
            }
        }

        // Load merges
        if let Some(merges) = parsed.get("merges").and_then(|m| m.as_array()) {
            for pair in merges {
                if let Some(arr) = pair.as_array() {
                    if arr.len() == 2 {
                        if let (Some(l), Some(r)) = (arr[0].as_str(), arr[1].as_str()) {
                            tok.merges.push((l.to_string(), r.to_string()));
                        }
                    }
                }
            }
        }

        // Load vocab size
        if let Some(vs) = parsed.get("vocab_size").and_then(|v| v.as_u64()) {
            tok.vocab_size = vs as u32;
        } else {
            tok.vocab_size = tok.token_to_id.len() as u32;
        }

        Ok(tok)
    }
}

// ============================================================================
// TESTS
// ============================================================================

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

    #[test]
    fn test_special_tokens() {
        let tok = Tokenizer::new();
        assert_eq!(tok.get_id(PAD_TOKEN), Some(PAD_ID));
        assert_eq!(tok.get_id(BOS_TOKEN), Some(BOS_ID));
        assert_eq!(tok.get_id(TOOL_TOKEN), Some(TOOL_ID));
        assert_eq!(tok.get_id(GATE_TOKEN), Some(GATE_ID));
        assert_eq!(tok.get_token(SPF_ID), Some(SPF_TOKEN));
    }

    #[test]
    fn test_train_and_encode() {
        let mut tok = Tokenizer::new();
        let corpus = "the cat sat on the mat the cat the mat";
        tok.train(corpus, 300);

        let ids = tok.encode("the cat");
        assert!(!ids.is_empty());
        assert!(ids.iter().all(|&id| id != UNK_ID));
    }

    #[test]
    fn test_roundtrip() {
        let mut tok = Tokenizer::new();
        tok.train("hello world hello world", 300);

        let text = "hello";
        let ids = tok.encode(text);
        let decoded = tok.decode(&ids);
        assert_eq!(decoded, text);
    }

    #[test]
    fn test_encode_with_special() {
        let mut tok = Tokenizer::new();
        tok.train("test data", 300);

        let ids = tok.encode_with_special("test");
        assert_eq!(ids[0], BOS_ID);
        assert_eq!(*ids.last().unwrap(), EOS_ID);
    }

    #[test]
    fn test_unknown_token() {
        let tok = Tokenizer::new(); // untrained — only specials + no bytes
        // With an untrained tokenizer, byte-level chars might not exist
        // This tests the UNK fallback path
        assert_eq!(tok.vocab_size, NUM_SPECIAL);
    }

    #[test]
    fn test_json_roundtrip() {
        let mut tok = Tokenizer::new();
        tok.train("the cat sat on the mat", 300);

        let json = tok.to_json();
        let tok2 = Tokenizer::from_json(&json).unwrap();

        assert_eq!(tok.vocab_size, tok2.vocab_size);
        assert_eq!(tok.merges.len(), tok2.merges.len());

        let ids1 = tok.encode("the cat");
        let ids2 = tok2.encode("the cat");
        assert_eq!(ids1, ids2);
    }
}