Add: o200k_harmony tokenizer for gpt-oss and update model mapping.

tiktoken-rs/README.md

@@ -105,7 +105,8 @@ println!("max_tokens: {}", max_tokens);
 
 | Encoding name           | OpenAI models                                                             |
 | ----------------------- | ------------------------------------------------------------------------- |
-| `o200k_base`            | GPT-4o models, GPT-4.1, o1, o3, and o4 models                             |
+| `o200k_harmony`         | gpt-oss models, `gpt-oss-20b`, `gpt-oss-120b`                             |
+| `o200k_base`            | GPT-4o models, GPT-4.1, GPT-5, o1, o3, and o4 models                      |
 | `cl100k_base`           | ChatGPT models, `text-embedding-ada-002`                                  |
 | `p50k_base`             | Code models, `text-davinci-002`, `text-davinci-003`                       |
 | `p50k_edit`             | Use for edit models like `text-davinci-edit-001`, `code-davinci-edit-001` |

tiktoken-rs/benches/init.rs

@@ -1,7 +1,12 @@
 #![feature(test)]
 extern crate test;
 
-use tiktoken_rs::{cl100k_base, o200k_base, p50k_base, p50k_edit, r50k_base};
+use tiktoken_rs::{cl100k_base, o200k_base, o200k_harmony, p50k_base, p50k_edit, r50k_base};
+
+#[bench]
+fn bench_init_o200k_harmony(b: &mut test::Bencher) {
+    b.iter(|| o200k_harmony().unwrap());
+}
 
 #[bench]
 fn bench_init_o200k_base(b: &mut test::Bencher) {

tiktoken-rs/src/api.rs

@@ -3,7 +3,7 @@ use anyhow::{anyhow, Result};
 use crate::{
     cl100k_base,
     model::get_context_size,
-    o200k_base, p50k_base, p50k_edit, r50k_base,
+    o200k_base, o200k_harmony, p50k_base, p50k_edit, r50k_base,
     tokenizer::{get_tokenizer, Tokenizer},
     CoreBPE,
 };
@@ -99,7 +99,10 @@ pub fn num_tokens_from_messages(
 ) -> Result<usize> {
     let tokenizer =
         get_tokenizer(model).ok_or_else(|| anyhow!("No tokenizer found for model {}", model))?;
-    if tokenizer != Tokenizer::Cl100kBase && tokenizer != Tokenizer::O200kBase {
+    if tokenizer != Tokenizer::Cl100kBase
+        && tokenizer != Tokenizer::O200kBase
+        && tokenizer != Tokenizer::O200kHarmony
+    {
         anyhow::bail!("Chat completion is only supported chat models")
     }
     let bpe = get_bpe_from_tokenizer(tokenizer)?;
@@ -255,6 +258,7 @@ pub fn get_bpe_from_model(model: &str) -> Result<CoreBPE> {
 /// If successful, the function returns a `Result` containing the `CoreBPE` instance corresponding to the given tokenizer.
 pub fn get_bpe_from_tokenizer(tokenizer: Tokenizer) -> Result<CoreBPE> {
     match tokenizer {
+        Tokenizer::O200kHarmony => o200k_harmony(),
         Tokenizer::O200kBase => o200k_base(),
         Tokenizer::Cl100kBase => cl100k_base(),
         Tokenizer::R50kBase => r50k_base(),

tiktoken-rs/src/model.rs

@@ -36,6 +36,12 @@ pub fn get_context_size(model: &str) -> usize {
         let base = rest.split(':').next().unwrap_or(rest);
         return get_context_size(base);
     }
+    if starts_with_any!(model, "gpt-5") {
+        return 400_000;
+    }
+    if starts_with_any!(model, "gpt-oss") {
+        return 131_072;
+    }
     if starts_with_any!(model, "o1", "o3", "o4") {
         return 200_000;
     }

tiktoken-rs/src/singleton.rs

@@ -2,7 +2,7 @@ use lazy_static::lazy_static;
 
 use crate::vendor_tiktoken::CoreBPE;
 
-use crate::{cl100k_base, o200k_base, p50k_base, p50k_edit, r50k_base};
+use crate::{cl100k_base, o200k_base, o200k_harmony, p50k_base, p50k_edit, r50k_base};
 
 /// Returns a singleton instance of the r50k_base tokenizer. (also known as `gpt2`)
 /// Use for GPT-3 models like `davinci`
@@ -58,3 +58,14 @@ pub fn o200k_base_singleton() -> &'static CoreBPE {
     }
     &O200K_BASE
 }
+
+/// Returns a singleton instance of the o200k_harmony tokenizer.
+/// Use for gpt-oss models like `gpt-oss-20b`, `gpt-oss-120b`.
+///
+/// This function will only initialize the tokenizer once, and then return a reference the tokenizer
+pub fn o200k_harmony_singleton() -> &'static CoreBPE {
+    lazy_static! {
+        static ref O200K_HARMONY: CoreBPE = o200k_harmony().unwrap();
+    }
+    &O200K_HARMONY
+}

tiktoken-rs/src/tiktoken_ext/openai_public.rs

@@ -1,4 +1,19 @@
+pub const STARTOFTEXT: &str = "<|startoftext|>";
 pub const ENDOFTEXT: &str = "<|endoftext|>";
+pub const RESERVED_200000: &str = "<|reserved_200000|>";
+pub const RESERVED_200001: &str = "<|reserved_200001|>";
+pub const RETURN: &str = "<|return|>";
+pub const CONSTRAIN: &str = "<|constrain|>";
+pub const RESERVED_200004: &str = "<|reserved_200004|>";
+pub const CHANNEL: &str = "<|channel|>";
+pub const START: &str = "<|start|>";
+pub const END: &str = "<|end|>";
+pub const MESSAGE: &str = "<|message|>";
+pub const RESERVED_200009: &str = "<|reserved_200009|>";
+pub const RESERVED_200010: &str = "<|reserved_200010|>";
+pub const RESERVED_200011: &str = "<|reserved_200011|>";
+pub const CALL: &str = "<|call|>";
+pub const RESERVED_200013: &str = "<|reserved_200013|>";
 pub const FIM_PREFIX: &str = "<|fim_prefix|>";
 pub const FIM_MIDDLE: &str = "<|fim_middle|>";
 pub const FIM_SUFFIX: &str = "<|fim_suffix|>";
@@ -123,11 +138,7 @@ pub fn cl100k_base() -> Result<CoreBPE> {
 pub fn o200k_base() -> Result<CoreBPE> {
     let o200k_base = include_str!("../../assets/o200k_base.tiktoken");
 
-    let mut encoder: std::collections::HashMap<
-        Vec<u8>,
-        Rank,
-        std::hash::BuildHasherDefault<rustc_hash::FxHasher>,
-    > = HashMap::default();
+    let mut encoder = HashMap::default();
     for line in o200k_base.lines() {
         let mut parts = line.split(' ');
         let raw = parts.next().unwrap();
@@ -155,3 +166,52 @@ pub fn o200k_base() -> Result<CoreBPE> {
     )?;
     Ok(bpe)
 }
+
+/// Use for gpt-oss models like `gpt-oss-20b`, `gpt-oss-120b`.
+/// Initializes and returns a new instance of the o200k_harmony tokenizer.
+pub fn o200k_harmony() -> Result<CoreBPE> {
+    let o200k_harmony = include_str!("../../assets/o200k_base.tiktoken");
+
+    let mut encoder = HashMap::default();
+    for line in o200k_harmony.lines() {
+        let mut parts = line.split(' ');
+        let raw = parts.next().unwrap();
+        let token = &general_purpose::STANDARD.decode(raw)?;
+        let rank: Rank = parts.next().unwrap().parse().unwrap();
+        encoder.insert(token.clone(), rank);
+    }
+
+    let mut special_tokens = HashMap::default();
+
+    special_tokens.insert(String::from(STARTOFTEXT), 199998);
+    special_tokens.insert(String::from(ENDOFTEXT), 199999);
+    special_tokens.insert(String::from(RESERVED_200000), 200000);
+    special_tokens.insert(String::from(RESERVED_200001), 200001);
+    special_tokens.insert(String::from(RETURN), 200002);
+    special_tokens.insert(String::from(CONSTRAIN), 200003);
+    special_tokens.insert(String::from(RESERVED_200004), 200004);
+    special_tokens.insert(String::from(CHANNEL), 200005);
+    special_tokens.insert(String::from(START), 200006);
+    special_tokens.insert(String::from(END), 200007);
+    special_tokens.insert(String::from(MESSAGE), 200008);
+    special_tokens.insert(String::from(RESERVED_200009), 200009);
+    special_tokens.insert(String::from(RESERVED_200010), 200010);
+    special_tokens.insert(String::from(RESERVED_200011), 200011);
+    special_tokens.insert(String::from(CALL), 200012);
+    special_tokens.insert(String::from(RESERVED_200013), 200013);
+
+    let bpe = CoreBPE::new(
+        encoder,
+        special_tokens,
+        &[
+            "[^\\r\\n\\p{L}\\p{N}]?[\\p{Lu}\\p{Lt}\\p{Lm}\\p{Lo}\\p{M}]*[\\p{Ll}\\p{Lm}\\p{Lo}\\p{M}]+(?i:'s|'t|'re|'ve|'m|'ll|'d)?",
+            "[^\\r\\n\\p{L}\\p{N}]?[\\p{Lu}\\p{Lt}\\p{Lm}\\p{Lo}\\p{M}]+[\\p{Ll}\\p{Lm}\\p{Lo}\\p{M}]*(?i:'s|'t|'re|'ve|'m|'ll|'d)?",
+            "\\p{N}{1,3}",
+            " ?[^\\s\\p{L}\\p{N}]+[\\r\\n/]*",
+            "\\s*[\\r\\n]+",
+            "\\s+(?!\\S)",
+            "\\s+",
+        ].join("|"),
+    )?;
+    Ok(bpe)
+}

tiktoken-rs/src/tokenizer.rs

@@ -20,6 +20,7 @@ use lazy_static::lazy_static;
 /// ```
 #[derive(Debug, PartialEq, Eq, Hash, Copy, Clone)]
 pub enum Tokenizer {
+    O200kHarmony,
     O200kBase,
     Cl100kBase,
     P50kBase,
@@ -29,18 +30,21 @@ pub enum Tokenizer {
 }
 
 // Keep this in sync with:
-// https://github.com/openai/tiktoken/blob/63527649963def8c759b0f91f2eb69a40934e468/tiktoken/model.py#L7
+// https://github.com/openai/tiktoken/blob/eedc856364506a9d4651645a0290eb0ba81e6935/tiktoken/model.py#L7-L27
 const MODEL_PREFIX_TO_TOKENIZER: &[(&str, Tokenizer)] = &[
     ("o1-", Tokenizer::O200kBase),
     ("o3-", Tokenizer::O200kBase),
     ("o4-", Tokenizer::O200kBase),
     // chat
+    ("gpt-5-", Tokenizer::O200kBase),
+    ("gpt-4.5-", Tokenizer::O200kBase),
     ("gpt-4.1-", Tokenizer::O200kBase),
     ("chatgpt-4o-", Tokenizer::O200kBase),
-    ("gpt-4o-", Tokenizer::O200kBase),
-    ("gpt-4-", Tokenizer::Cl100kBase),
-    ("gpt-3.5-turbo-", Tokenizer::Cl100kBase),
-    ("gpt-35-turbo-", Tokenizer::Cl100kBase),
+    ("gpt-4o-", Tokenizer::O200kBase), // e.g., gpt-4o-2024-05-13
+    ("gpt-4-", Tokenizer::Cl100kBase), // e.g., gpt-4-0314, etc., plus gpt-4-32k
+    ("gpt-3.5-turbo-", Tokenizer::Cl100kBase), // e.g, gpt-3.5-turbo-0301, -0401, etc.
+    ("gpt-35-turbo-", Tokenizer::Cl100kBase), // Azure deployment name
+    ("gpt-oss-", Tokenizer::O200kHarmony),
     // fine-tuned
     ("ft:gpt-4o", Tokenizer::O200kBase),
     ("ft:gpt-4", Tokenizer::Cl100kBase),
@@ -50,13 +54,14 @@ const MODEL_PREFIX_TO_TOKENIZER: &[(&str, Tokenizer)] = &[
 ];
 
 // Keep this in sync with:
-// https://github.com/openai/tiktoken/blob/63527649963def8c759b0f91f2eb69a40934e468/tiktoken/model.py#L22
+// https://github.com/openai/tiktoken/blob/eedc856364506a9d4651645a0290eb0ba81e6935/tiktoken/model.py#L29-L84
 const MODEL_TO_TOKENIZER: &[(&str, Tokenizer)] = &[
     // reasoning
     ("o1", Tokenizer::O200kBase),
     ("o3", Tokenizer::O200kBase),
     ("o4", Tokenizer::O200kBase),
     // chat
+    ("gpt-5", Tokenizer::O200kBase),
     ("gpt-4.1", Tokenizer::O200kBase),
     ("chatgpt-4o-latest", Tokenizer::O200kBase),
     ("gpt-4o", Tokenizer::O200kBase),
@@ -162,6 +167,9 @@ mod tests {
 
     #[test]
     fn test_get_tokenizer() {
+        assert_eq!(get_tokenizer("gpt-5"), Some(Tokenizer::O200kBase));
+        assert_eq!(get_tokenizer("gpt-oss-20b"), Some(Tokenizer::O200kHarmony));
+        assert_eq!(get_tokenizer("gpt-oss-120b"), Some(Tokenizer::O200kHarmony));
         assert_eq!(
             get_tokenizer("chatgpt-4o-latest"),
             Some(Tokenizer::O200kBase)

tiktoken-rs/tests/model.rs

@@ -16,4 +16,5 @@ fn test_finetuned_context_size() {
 fn test_o_series_context_size() {
     assert_eq!(get_context_size("o3-small"), 200_000);
     assert_eq!(get_context_size("o4"), 200_000);
+    assert_eq!(get_context_size("gpt-5"), 400_000);
 }

tiktoken-rs/tests/tiktoken.rs

@@ -1,8 +1,8 @@
 use rustc_hash::FxHashMap as HashMap;
 
 use tiktoken_rs::{
-    byte_pair_split, cl100k_base, o200k_base, p50k_base, p50k_base_singleton, r50k_base, CoreBPE,
-    Rank,
+    byte_pair_split, cl100k_base, o200k_base, o200k_harmony, p50k_base, p50k_base_singleton,
+    r50k_base, CoreBPE, Rank,
 };
 
 #[test]
@@ -166,4 +166,5 @@ fn test_unicode_roundtrip() {
     test_roundtrip(&r50k_base().unwrap(), "我想借几本汉语书");
     test_roundtrip(&cl100k_base().unwrap(), "你会说中文吗？");
     test_roundtrip(&o200k_base().unwrap(), "ひらがなカタカナ漢字");
+    test_roundtrip(&o200k_harmony().unwrap(), "ひらがなカタカナ漢字");
 }