[router] add tokenizer chat template support (#9370)

Co-authored-by: Chang Su <chang.s.su@oracle.com>

sgl-router/Cargo.toml

@@ -5,7 +5,7 @@ edition = "2021"
 
 [features]
 default = ["huggingface", "grpc-client"]
-huggingface = ["tokenizers"]
+huggingface = ["tokenizers", "minijinja"]
 tiktoken = ["tiktoken-rs"]
 grpc-client = []
 grpc-server = []
@@ -52,7 +52,8 @@ url = "2.5.4"
 tokio-stream = { version = "0.1", features = ["sync"] }
 anyhow = "1.0"
 tokenizers = { version = "0.21.4", optional = true }
-tiktoken-rs = { version = "0.5", optional = true }
+tiktoken-rs = { version = "0.7.0", optional = true }
+minijinja = { version = "2.0", optional = true }
 
 # gRPC and Protobuf dependencies
 tonic = { version = "0.12", features = ["tls", "gzip", "transport"] }
@@ -71,6 +72,7 @@ criterion = { version = "0.5", features = ["html_reports"] }
 tower = { version = "0.5", features = ["util"] }
 http-body-util = "0.1"
 portpicker = "0.1"
+tempfile = "3.8"
 
 [[bench]]
 name = "request_processing"

sgl-router/src/tokenizer/chat_template.rs

+//! Chat template support for tokenizers using Jinja2 templates
+//!
+//! This module provides functionality to apply chat templates to messages,
+//! similar to HuggingFace transformers' apply_chat_template method.
+
+use anyhow::{anyhow, Result};
+#[cfg(feature = "huggingface")]
+use minijinja::{context, Environment, Value};
+use serde::{Deserialize, Serialize};
+use serde_json;
+
+/// Represents a chat message with role and content
+#[derive(Debug, Clone, Serialize, Deserialize)]
+pub struct ChatMessage {
+    pub role: String,
+    pub content: String,
+}
+
+impl ChatMessage {
+    pub fn new(role: impl Into<String>, content: impl Into<String>) -> Self {
+        ChatMessage {
+            role: role.into(),
+            content: content.into(),
+        }
+    }
+
+    pub fn system(content: impl Into<String>) -> Self {
+        Self::new("system", content)
+    }
+
+    pub fn user(content: impl Into<String>) -> Self {
+        Self::new("user", content)
+    }
+
+    pub fn assistant(content: impl Into<String>) -> Self {
+        Self::new("assistant", content)
+    }
+}
+
+/// Chat template processor using Jinja2
+#[cfg(feature = "huggingface")]
+pub struct ChatTemplateProcessor {
+    template: String,
+    bos_token: Option<String>,
+    eos_token: Option<String>,
+}
+
+#[cfg(feature = "huggingface")]
+impl ChatTemplateProcessor {
+    /// Create a new chat template processor
+    pub fn new(template: String, bos_token: Option<String>, eos_token: Option<String>) -> Self {
+        ChatTemplateProcessor {
+            template,
+            bos_token,
+            eos_token,
+        }
+    }
+
+    /// Apply the chat template to a list of messages
+    ///
+    /// This mimics the behavior of HuggingFace's apply_chat_template method
+    /// but returns the formatted string instead of token IDs.
+    pub fn apply_chat_template(
+        &self,
+        messages: &[ChatMessage],
+        add_generation_prompt: bool,
+    ) -> Result<String> {
+        let mut env = Environment::new();
+
+        // Register the template
+        env.add_template("chat", &self.template)
+            .map_err(|e| anyhow!("Failed to add template: {}", e))?;
+
+        // Get the template
+        let tmpl = env
+            .get_template("chat")
+            .map_err(|e| anyhow!("Failed to get template: {}", e))?;
+
+        // Convert messages to a format Jinja can work with
+        let messages_value: Vec<Value> = messages
+            .iter()
+            .map(|msg| {
+                context! {
+                    role => msg.role.clone(),
+                    content => msg.content.clone()
+                }
+            })
+            .collect();
+
+        // Render the template
+        let rendered = tmpl
+            .render(context! {
+                messages => messages_value,
+                add_generation_prompt => add_generation_prompt,
+                bos_token => self.bos_token.clone().unwrap_or_default(),
+                eos_token => self.eos_token.clone().unwrap_or_default()
+            })
+            .map_err(|e| anyhow!("Failed to render template: {}", e))?;
+
+        Ok(rendered)
+    }
+}
+
+/// Load chat template from tokenizer config JSON
+#[cfg(feature = "huggingface")]
+pub fn load_chat_template_from_config(config_path: &str) -> Result<Option<String>> {
+    use std::fs;
+
+    let content = fs::read_to_string(config_path)?;
+    let config: serde_json::Value = serde_json::from_str(&content)?;
+
+    // Look for chat_template in the config
+    if let Some(template) = config.get("chat_template") {
+        if let Some(template_str) = template.as_str() {
+            return Ok(Some(template_str.to_string()));
+        }
+    }
+
+    Ok(None)
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    #[test]
+    fn test_chat_message_creation() {
+        let msg = ChatMessage::system("You are a helpful assistant");
+        assert_eq!(msg.role, "system");
+        assert_eq!(msg.content, "You are a helpful assistant");
+
+        let user_msg = ChatMessage::user("Hello!");
+        assert_eq!(user_msg.role, "user");
+
+        let assistant_msg = ChatMessage::assistant("Hi there!");
+        assert_eq!(assistant_msg.role, "assistant");
+    }
+
+    #[cfg(feature = "huggingface")]
+    #[test]
+    fn test_simple_chat_template() {
+        // Simple template that formats messages
+        let template = r#"
+{%- for message in messages -%}
+{{ message.role }}: {{ message.content }}
+{% endfor -%}
+{%- if add_generation_prompt -%}
+assistant:
+{%- endif -%}
+"#;
+
+        let processor = ChatTemplateProcessor::new(template.to_string(), None, None);
+
+        let messages = vec![
+            ChatMessage::system("You are helpful"),
+            ChatMessage::user("Hello"),
+        ];
+
+        let result = processor.apply_chat_template(&messages, true).unwrap();
+        assert!(result.contains("system: You are helpful"));
+        assert!(result.contains("user: Hello"));
+        assert!(result.contains("assistant:"));
+    }
+
+    #[cfg(feature = "huggingface")]
+    #[test]
+    fn test_chat_template_with_tokens() {
+        // Template that uses special tokens
+        let template = r#"
+{{ bos_token }}
+{%- for message in messages -%}
+{{ message.role }}: {{ message.content }}{{ eos_token }}
+{% endfor -%}
+"#;
+
+        let processor = ChatTemplateProcessor::new(
+            template.to_string(),
+            Some("<s>".to_string()),
+            Some("</s>".to_string()),
+        );
+
+        let messages = vec![ChatMessage::user("Test")];
+
+        let result = processor.apply_chat_template(&messages, false).unwrap();
+        assert!(result.contains("<s>"));
+        assert!(result.contains("</s>"));
+    }
+}

sgl-router/src/tokenizer/factory.rs

@@ -26,6 +26,14 @@ pub enum TokenizerType {
 /// - json: HuggingFace tokenizer
 /// - For testing: can return mock tokenizer
 pub fn create_tokenizer_from_file(file_path: &str) -> Result<Arc<dyn traits::Tokenizer>> {
+    create_tokenizer_with_chat_template(file_path, None)
+}
+
+/// Create a tokenizer from a file path with an optional chat template
+pub fn create_tokenizer_with_chat_template(
+    file_path: &str,
+    chat_template_path: Option<&str>,
+) -> Result<Arc<dyn traits::Tokenizer>> {
     let start_time = Instant::now();
 
     // Special case for testing
@@ -51,7 +59,10 @@ pub fn create_tokenizer_from_file(file_path: &str) -> Result<Arc<dyn traits::Tok
         Some("json") => {
             #[cfg(feature = "huggingface")]
             {
-                let tokenizer = HuggingFaceTokenizer::from_file(file_path)?;
+                let tokenizer = HuggingFaceTokenizer::from_file_with_chat_template(
+                    file_path,
+                    chat_template_path,
+                )?;
 
                 TokenizerMetrics::record_factory_load("json");
                 TokenizerMetrics::set_vocab_size("huggingface", tokenizer.vocab_size());

sgl-router/src/tokenizer/huggingface.rs

-use super::traits::{Decoder, Encoder, Encoding, SpecialTokens, Tokenizer as TokenizerTrait};
+use super::traits::{
+    Decoder, Encoder, Encoding, SpecialTokens, TokenIdType, Tokenizer as TokenizerTrait,
+};
 use crate::metrics::TokenizerMetrics;
 use anyhow::{Error, Result};
 use std::collections::HashMap;
 use std::time::Instant;
 use tokenizers::tokenizer::Tokenizer as HfTokenizer;
 
+#[cfg(feature = "minijinja")]
+use super::chat_template::{ChatMessage, ChatTemplateProcessor};
+
 /// HuggingFace tokenizer wrapper
 pub struct HuggingFaceTokenizer {
     tokenizer: HfTokenizer,
     special_tokens: SpecialTokens,
-    vocab: HashMap<String, u32>,
-    reverse_vocab: HashMap<u32, String>,
+    vocab: HashMap<String, TokenIdType>,
+    reverse_vocab: HashMap<TokenIdType, String>,
+    #[cfg(feature = "minijinja")]
+    chat_template: Option<String>,
 }
 
 impl HuggingFaceTokenizer {
     /// Create a tokenizer from a HuggingFace tokenizer JSON file
     pub fn from_file(file_path: &str) -> Result<Self> {
+        Self::from_file_with_chat_template(file_path, None)
+    }
+
+    /// Create a tokenizer from a HuggingFace tokenizer JSON file with an optional chat template
+    pub fn from_file_with_chat_template(
+        file_path: &str,
+        chat_template_path: Option<&str>,
+    ) -> Result<Self> {
         let tokenizer = HfTokenizer::from_file(file_path)
             .map_err(|e| Error::msg(format!("Failed to load tokenizer: {}", e)))?;
 
@@ -24,16 +39,28 @@ impl HuggingFaceTokenizer {
 
         // Build vocab mappings
         let vocab = tokenizer.get_vocab(false);
-        let reverse_vocab: HashMap<u32, String> = vocab
+        let reverse_vocab: HashMap<TokenIdType, String> = vocab
             .iter()
             .map(|(token, &id)| (id, token.clone()))
             .collect();
 
+        // Load chat template
+        #[cfg(feature = "minijinja")]
+        let chat_template = if let Some(template_path) = chat_template_path {
+            // Load from specified .jinja file
+            Self::load_chat_template_from_file(template_path)?
+        } else {
+            // Try to load from tokenizer_config.json
+            Self::load_chat_template(file_path)
+        };
+
         Ok(HuggingFaceTokenizer {
             tokenizer,
             special_tokens,
             vocab,
             reverse_vocab,
+            #[cfg(feature = "minijinja")]
+            chat_template,
         })
     }
 
@@ -41,7 +68,7 @@ impl HuggingFaceTokenizer {
     pub fn from_tokenizer(tokenizer: HfTokenizer) -> Self {
         let special_tokens = Self::extract_special_tokens(&tokenizer);
         let vocab = tokenizer.get_vocab(false);
-        let reverse_vocab: HashMap<u32, String> = vocab
+        let reverse_vocab: HashMap<TokenIdType, String> = vocab
             .iter()
             .map(|(token, &id)| (id, token.clone()))
             .collect();
@@ -51,6 +78,8 @@ impl HuggingFaceTokenizer {
             special_tokens,
             vocab,
             reverse_vocab,
+            #[cfg(feature = "minijinja")]
+            chat_template: None,
         }
     }
 
@@ -81,13 +110,86 @@ impl HuggingFaceTokenizer {
         }
     }
 
+    /// Try to load chat template from tokenizer_config.json
+    #[cfg(feature = "minijinja")]
+    fn load_chat_template(tokenizer_path: &str) -> Option<String> {
+        // Try to find tokenizer_config.json in the same directory
+        let path = std::path::Path::new(tokenizer_path);
+        let dir = path.parent()?;
+        let config_path = dir.join("tokenizer_config.json");
+
+        if config_path.exists() {
+            if let Ok(template) =
+                super::chat_template::load_chat_template_from_config(config_path.to_str()?)
+            {
+                return template;
+            }
+        }
+        None
+    }
+
+    /// Load chat template from a .jinja file
+    #[cfg(feature = "minijinja")]
+    fn load_chat_template_from_file(template_path: &str) -> Result<Option<String>> {
+        use std::fs;
+
+        let content = fs::read_to_string(template_path)
+            .map_err(|e| Error::msg(format!("Failed to read chat template file: {}", e)))?;
+
+        // Clean up the template (similar to Python implementation)
+        let template = content.trim().replace("\\n", "\n");
+
+        Ok(Some(template))
+    }
+
+    /// Set or override the chat template
+    #[cfg(feature = "minijinja")]
+    pub fn set_chat_template(&mut self, template: String) {
+        self.chat_template = Some(template);
+    }
+
     /// Apply chat template if available
-    pub fn apply_chat_template(&self, messages: &[ChatMessage]) -> Result<String> {
-        // This is a placeholder - actual implementation would handle templates
+    #[cfg(feature = "minijinja")]
+    pub fn apply_chat_template(
+        &self,
+        messages: &[ChatMessage],
+        add_generation_prompt: bool,
+    ) -> Result<String> {
+        if let Some(ref template) = self.chat_template {
+            let processor = ChatTemplateProcessor::new(
+                template.clone(),
+                self.special_tokens.bos_token.clone(),
+                self.special_tokens.eos_token.clone(),
+            );
+            processor.apply_chat_template(messages, add_generation_prompt)
+        } else {
+            // Fallback to simple formatting if no template is available
+            let mut result = String::new();
+            for msg in messages {
+                result.push_str(&format!("{}: {}\n", msg.role, msg.content));
+            }
+            if add_generation_prompt {
+                result.push_str("assistant: ");
+            }
+            Ok(result)
+        }
+    }
+
+    /// Apply chat template if available (without minijinja feature)
+    #[cfg(not(feature = "minijinja"))]
+    pub fn apply_chat_template(
+        &self,
+        messages: &[ChatMessage],
+        add_generation_prompt: bool,
+    ) -> Result<String> {
+        // Fallback to simple formatting
         let mut result = String::new();
         for msg in messages {
             result.push_str(&format!("{}: {}\n", msg.role, msg.content));
         }
+        if add_generation_prompt {
+            result.push_str("assistant: ");
+        }
         Ok(result)
     }
 }
@@ -133,7 +235,7 @@ impl Encoder for HuggingFaceTokenizer {
 }
 
 impl Decoder for HuggingFaceTokenizer {
-    fn decode(&self, token_ids: &[u32], skip_special_tokens: bool) -> Result<String> {
+    fn decode(&self, token_ids: &[TokenIdType], skip_special_tokens: bool) -> Result<String> {
         let start = Instant::now();
 
         TokenizerMetrics::record_decode_request("huggingface");
@@ -160,47 +262,21 @@ impl TokenizerTrait for HuggingFaceTokenizer {
         &self.special_tokens
     }
 
-    fn token_to_id(&self, token: &str) -> Option<u32> {
+    fn token_to_id(&self, token: &str) -> Option<TokenIdType> {
         self.vocab.get(token).copied()
     }
 
-    fn id_to_token(&self, id: u32) -> Option<String> {
+    fn id_to_token(&self, id: TokenIdType) -> Option<String> {
         self.reverse_vocab.get(&id).cloned()
     }
 }
 
-/// Represents a chat message for template application
-#[derive(Debug, Clone)]
-pub struct ChatMessage {
-    pub role: String,
-    pub content: String,
-}
-
-impl ChatMessage {
-    pub fn new(role: impl Into<String>, content: impl Into<String>) -> Self {
-        ChatMessage {
-            role: role.into(),
-            content: content.into(),
-        }
-    }
-
-    pub fn system(content: impl Into<String>) -> Self {
-        Self::new("system", content)
-    }
-
-    pub fn user(content: impl Into<String>) -> Self {
-        Self::new("user", content)
-    }
-
-    pub fn assistant(content: impl Into<String>) -> Self {
-        Self::new("assistant", content)
-    }
-}
-
 #[cfg(test)]
 mod tests {
-    use super::*;
+    #[cfg(feature = "minijinja")]
+    use super::ChatMessage;
 
+    #[cfg(feature = "minijinja")]
     #[test]
     fn test_chat_message_creation() {
         let msg = ChatMessage::system("You are a helpful assistant");

sgl-router/src/tokenizer/mod.rs

@@ -10,6 +10,9 @@ pub mod stream;
 pub mod traits;
 
 // Feature-gated modules
+#[cfg(feature = "huggingface")]
+pub mod chat_template;
+
 #[cfg(feature = "huggingface")]
 pub mod huggingface;
 
@@ -20,14 +23,20 @@ pub mod tiktoken;
 mod tests;
 
 // Re-exports
-pub use factory::{create_tokenizer, create_tokenizer_from_file, TokenizerType};
+pub use factory::{
+    create_tokenizer, create_tokenizer_from_file, create_tokenizer_with_chat_template,
+    TokenizerType,
+};
 pub use sequence::Sequence;
 pub use stop::{SequenceDecoderOutput, StopSequenceConfig, StopSequenceDecoder};
 pub use stream::DecodeStream;
 pub use traits::{Decoder, Encoder, Encoding, SpecialTokens, Tokenizer as TokenizerTrait};
 
 #[cfg(feature = "huggingface")]
-pub use huggingface::{ChatMessage, HuggingFaceTokenizer};
+pub use huggingface::HuggingFaceTokenizer;
+
+#[cfg(feature = "huggingface")]
+pub use chat_template::ChatMessage;
 
 #[cfg(feature = "tiktoken")]
 pub use tiktoken::{TiktokenModel, TiktokenTokenizer};
@@ -42,6 +51,17 @@ impl Tokenizer {
         Ok(Tokenizer(factory::create_tokenizer_from_file(file_path)?))
     }
 
+    /// Create a tokenizer from a file path with an optional chat template
+    pub fn from_file_with_chat_template(
+        file_path: &str,
+        chat_template_path: Option<&str>,
+    ) -> Result<Tokenizer> {
+        Ok(Tokenizer(factory::create_tokenizer_with_chat_template(
+            file_path,
+            chat_template_path,
+        )?))
+    }
+
     /// Create a tokenizer from an Arc<dyn Tokenizer>
     pub fn from_arc(tokenizer: Arc<dyn traits::Tokenizer>) -> Self {
         Tokenizer(tokenizer)

sgl-router/src/tokenizer/sequence.rs

-use super::traits::Tokenizer as TokenizerTrait;
+use super::traits::{TokenIdType, Tokenizer as TokenizerTrait};
 use anyhow::Result;
 use std::sync::Arc;
 
@@ -9,7 +9,7 @@ pub struct Sequence {
     tokenizer: Arc<dyn TokenizerTrait>,
 
     /// The current sequence of token ids
-    token_ids: Vec<u32>,
+    token_ids: Vec<TokenIdType>,
 
     /// The position in the current sequence the last decoded token completed
     prefix_offset: usize,
@@ -54,7 +54,7 @@ impl Sequence {
     }
 
     /// Create a sequence with initial tokens
-    pub fn with_tokens(tokenizer: Arc<dyn TokenizerTrait>, token_ids: Vec<u32>) -> Self {
+    pub fn with_tokens(tokenizer: Arc<dyn TokenizerTrait>, token_ids: Vec<TokenIdType>) -> Self {
         let len = token_ids.len();
         Self {
             tokenizer,
@@ -90,7 +90,7 @@ impl Sequence {
 
     /// Append a single token to the sequence and return newly decoded text
     /// Based on HuggingFace TGI incremental decoding
-    pub fn append_token(&mut self, token_id: u32) -> Result<String> {
+    pub fn append_token(&mut self, token_id: TokenIdType) -> Result<String> {
         // Store the old read offset before adding the new token
         let old_read_offset = self.read_offset;
 
@@ -145,7 +145,7 @@ impl Sequence {
     }
 
     /// Get the current token ids
-    pub fn token_ids(&self) -> &[u32] {
+    pub fn token_ids(&self) -> &[TokenIdType] {
         &self.token_ids
     }
 

sgl-router/src/tokenizer/stop.rs

-use super::traits;
+use super::traits::{self, TokenIdType};
 use crate::metrics::TokenizerMetrics;
 use anyhow::Result;
 use std::collections::HashSet;
@@ -22,18 +22,18 @@ pub enum SequenceDecoderOutput {
 #[derive(Debug, Clone, Default)]
 pub struct StopSequenceConfig {
     /// Token IDs that trigger a stop
-    pub stop_tokens: HashSet<u32>,
+    pub stop_tokens: HashSet<TokenIdType>,
     /// String sequences that trigger a stop
     pub stop_sequences: Vec<String>,
     /// Token IDs for visible stops (included in output)
-    pub visible_stop_tokens: HashSet<u32>,
+    pub visible_stop_tokens: HashSet<TokenIdType>,
     /// String sequences for visible stops (included in output)
     pub visible_stop_sequences: Vec<String>,
 }
 
 impl StopSequenceConfig {
     /// Builder pattern - add a stop token
-    pub fn with_stop_token(mut self, token_id: u32) -> Self {
+    pub fn with_stop_token(mut self, token_id: TokenIdType) -> Self {
         self.stop_tokens.insert(token_id);
         self
     }
@@ -45,7 +45,7 @@ impl StopSequenceConfig {
     }
 
     /// Builder pattern - add a visible stop token
-    pub fn with_visible_stop_token(mut self, token_id: u32) -> Self {
+    pub fn with_visible_stop_token(mut self, token_id: TokenIdType) -> Self {
         self.visible_stop_tokens.insert(token_id);
         self
     }
@@ -64,7 +64,7 @@ pub struct StopSequenceDecoder {
     /// Buffer for partial matches (the "jail")
     jail_buffer: String,
     /// Accumulated tokens
-    token_buffer: Vec<u32>,
+    token_buffer: Vec<TokenIdType>,
     /// Offset where the prefix text starts (for context)
     prefix_offset: usize,
     /// Offset marking the end of previously decoded text
@@ -94,7 +94,7 @@ impl StopSequenceDecoder {
     }
 
     /// Process a single token
-    pub fn process_token(&mut self, token_id: u32) -> Result<SequenceDecoderOutput> {
+    pub fn process_token(&mut self, token_id: TokenIdType) -> Result<SequenceDecoderOutput> {
         let start = Instant::now();
 
         if self.stopped {
@@ -252,7 +252,10 @@ impl StopSequenceDecoder {
     }
 
     /// Process multiple tokens
-    pub fn process_tokens(&mut self, token_ids: &[u32]) -> Result<Vec<SequenceDecoderOutput>> {
+    pub fn process_tokens(
+        &mut self,
+        token_ids: &[TokenIdType],
+    ) -> Result<Vec<SequenceDecoderOutput>> {
         let mut outputs = Vec::new();
         for &token_id in token_ids {
             outputs.push(self.process_token(token_id)?);
@@ -302,7 +305,7 @@ impl StopSequenceDecoderBuilder {
         }
     }
 
-    pub fn stop_token(mut self, token_id: u32) -> Self {
+    pub fn stop_token(mut self, token_id: TokenIdType) -> Self {
         self.config.stop_tokens.insert(token_id);
         self
     }
@@ -312,7 +315,7 @@ impl StopSequenceDecoderBuilder {
         self
     }
 
-    pub fn visible_stop_token(mut self, token_id: u32) -> Self {
+    pub fn visible_stop_token(mut self, token_id: TokenIdType) -> Self {
         self.config.visible_stop_tokens.insert(token_id);
         self
     }

sgl-router/src/tokenizer/stream.rs

 // src/tokenizer/stream.rs
 
-use super::traits;
+use super::traits::{self, TokenIdType};
 use crate::metrics::TokenizerMetrics;
 use anyhow::Result;
 use std::sync::Arc;
@@ -18,7 +18,7 @@ pub struct DecodeStream {
 
     /// A temporary buffer of the necessary token_ids needed
     /// to produce valid string chunks
-    all_token_ids: Vec<u32>,
+    all_token_ids: Vec<TokenIdType>,
 
     prefix_offset: usize,
     read_offset: usize,
@@ -27,7 +27,7 @@ pub struct DecodeStream {
 impl DecodeStream {
     pub fn new(
         tokenizer: Arc<dyn traits::Tokenizer>,
-        prompt_token_ids: &[u32],
+        prompt_token_ids: &[TokenIdType],
         skip_special_tokens: bool,
     ) -> Self {
         let num_input_tokens = prompt_token_ids.len();
@@ -44,7 +44,7 @@ impl DecodeStream {
 
     /// Step appends a token_id to the internal state and tries to produce a text chunk.
     /// Returning `None` means the given id is not enough to produce a chunk.
-    pub fn step(&mut self, id: u32) -> Result<Option<String>> {
+    pub fn step(&mut self, id: TokenIdType) -> Result<Option<String>> {
         let start = Instant::now();
 
         self.all_token_ids.push(id);

sgl-router/src/tokenizer/tiktoken.rs

-use super::traits::{Decoder, Encoder, Encoding, SpecialTokens, Tokenizer as TokenizerTrait};
+use super::traits::{
+    Decoder, Encoder, Encoding, SpecialTokens, TokenIdType, Tokenizer as TokenizerTrait,
+};
 use anyhow::{Error, Result};
 use tiktoken_rs::{cl100k_base, p50k_base, p50k_edit, r50k_base, CoreBPE};
 
@@ -140,12 +142,10 @@ impl Encoder for TiktokenTokenizer {
 }
 
 impl Decoder for TiktokenTokenizer {
-    fn decode(&self, token_ids: &[u32], _skip_special_tokens: bool) -> Result<String> {
-        // Convert u32 to usize for tiktoken-rs
-        let tokens: Vec<usize> = token_ids.iter().map(|&id| id as usize).collect();
-
+    fn decode(&self, token_ids: &[TokenIdType], _skip_special_tokens: bool) -> Result<String> {
+        // tiktoken-rs 0.7.0 now uses u32 (Rank type)
         self.tokenizer
-            .decode(tokens)
+            .decode(token_ids.to_vec())
             .map_err(|e| Error::msg(format!("Decoding failed: {}", e)))
     }
 }
@@ -159,13 +159,13 @@ impl TokenizerTrait for TiktokenTokenizer {
         &self.special_tokens
     }
 
-    fn token_to_id(&self, _token: &str) -> Option<u32> {
+    fn token_to_id(&self, _token: &str) -> Option<TokenIdType> {
         // Tiktoken doesn't provide direct token-to-id mapping
         // We'd need to encode the token and check if it produces a single ID
         None
     }
 
-    fn id_to_token(&self, _id: u32) -> Option<String> {
+    fn id_to_token(&self, _id: TokenIdType) -> Option<String> {
         // Tiktoken doesn't provide direct id-to-token mapping
         // We can only decode IDs to text
         None

sgl-router/src/tokenizer/traits.rs

 use anyhow::Result;
+use std::collections::hash_map::DefaultHasher;
+use std::hash::{Hash, Hasher};
+
+/// Type alias for token IDs
+pub type TokenIdType = u32;
 
 /// Core encoding trait - separate from decoding for modularity
 pub trait Encoder: Send + Sync {
@@ -8,15 +13,15 @@ pub trait Encoder: Send + Sync {
 
 /// Core decoding trait - can be implemented independently
 pub trait Decoder: Send + Sync {
-    fn decode(&self, token_ids: &[u32], skip_special_tokens: bool) -> Result<String>;
+    fn decode(&self, token_ids: &[TokenIdType], skip_special_tokens: bool) -> Result<String>;
 }
 
 /// Combined tokenizer trait
 pub trait Tokenizer: Encoder + Decoder {
     fn vocab_size(&self) -> usize;
     fn get_special_tokens(&self) -> &SpecialTokens;
-    fn token_to_id(&self, token: &str) -> Option<u32>;
-    fn id_to_token(&self, id: u32) -> Option<String>;
+    fn token_to_id(&self, token: &str) -> Option<TokenIdType>;
+    fn id_to_token(&self, id: TokenIdType) -> Option<String>;
 }
 
 /// Contains the results of tokenizing text: token IDs, string tokens, and their spans
@@ -25,29 +30,45 @@ pub enum Encoding {
     /// Hugging Face
     Hf(Box<tokenizers::tokenizer::Encoding>),
     /// Sentence Piece
-    Sp(Vec<u32>),
-    /// Tiktoken (for GPT models)
-    Tiktoken(Vec<usize>),
+    Sp(Vec<TokenIdType>),
+    /// Tiktoken (for GPT models) - now uses u32 in tiktoken-rs 0.7.0
+    Tiktoken(Vec<TokenIdType>),
 }
 
 impl Encoding {
-    pub fn token_ids(&self) -> Vec<u32> {
+    /// Returns a reference to token IDs when possible, owned Vec for compatibility
+    pub fn token_ids(&self) -> Vec<TokenIdType> {
         match self {
             Encoding::Hf(inner) => inner.get_ids().to_vec(),
             Encoding::Sp(inner) => inner.clone(),
-            Encoding::Tiktoken(inner) => inner.iter().map(|&id| id as u32).collect(),
+            Encoding::Tiktoken(inner) => inner.clone(),
         }
     }
 
-    pub fn token_ids_ref(&self) -> &[u32] {
+    /// Returns a reference to token IDs where possible
+    pub fn token_ids_ref(&self) -> &[TokenIdType] {
         match self {
             Encoding::Hf(inner) => inner.get_ids(),
             Encoding::Sp(inner) => inner,
-            Encoding::Tiktoken(_) => {
-                // Tiktoken uses usize, we can't return a reference to u32
-                // This is a limitation - callers should use token_ids() for Tiktoken
-                &[]
-            }
+            Encoding::Tiktoken(inner) => inner, // Now works with tiktoken-rs 0.7.0!
+        }
+    }
+
+    /// Get a hash of the token IDs for caching purposes
+    pub fn get_hash(&self) -> u64 {
+        let mut hasher = DefaultHasher::new();
+        self.hash(&mut hasher);
+        hasher.finish()
+    }
+}
+
+/// Hash implementation for Encoding
+impl Hash for Encoding {
+    fn hash<H: Hasher>(&self, state: &mut H) {
+        match self {
+            Encoding::Hf(inner) => inner.get_ids().hash(state),
+            Encoding::Sp(inner) => inner.hash(state),
+            Encoding::Tiktoken(inner) => inner.hash(state),
         }
     }
 }

sgl-router/tests/test_chat_template.rs

+#[cfg(test)]
+mod tests {
+    use sglang_router_rs::tokenizer::chat_template::{ChatMessage, ChatTemplateProcessor};
+
+    #[test]
+    #[cfg(feature = "huggingface")]
+    fn test_chat_message_helpers() {
+        let system_msg = ChatMessage::system("You are a helpful assistant");
+        assert_eq!(system_msg.role, "system");
+        assert_eq!(system_msg.content, "You are a helpful assistant");
+
+        let user_msg = ChatMessage::user("Hello!");
+        assert_eq!(user_msg.role, "user");
+        assert_eq!(user_msg.content, "Hello!");
+
+        let assistant_msg = ChatMessage::assistant("Hi there!");
+        assert_eq!(assistant_msg.role, "assistant");
+        assert_eq!(assistant_msg.content, "Hi there!");
+    }
+
+    #[test]
+    #[cfg(feature = "huggingface")]
+    fn test_llama_style_template() {
+        // Test a Llama-style chat template
+        let template = r#"
+{%- if messages[0]['role'] == 'system' -%}
+    {%- set system_message = messages[0]['content'] -%}
+    {%- set messages = messages[1:] -%}
+{%- else -%}
+    {%- set system_message = '' -%}
+{%- endif -%}
+
+{{- bos_token }}
+{%- if system_message %}
+{{- '<|start_header_id|>system<|end_header_id|>\n\n' + system_message + '<|eot_id|>' }}
+{%- endif %}
+
+{%- for message in messages %}
+    {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n' + message['content'] + '<|eot_id|>' }}
+{%- endfor %}
+
+{%- if add_generation_prompt %}
+    {{- '<|start_header_id|>assistant<|end_header_id|>\n\n' }}
+{%- endif %}
+"#;
+
+        let processor = ChatTemplateProcessor::new(
+            template.to_string(),
+            Some("<|begin_of_text|>".to_string()),
+            Some("<|end_of_text|>".to_string()),
+        );
+
+        let messages = vec![
+            ChatMessage::system("You are a helpful assistant"),
+            ChatMessage::user("What is 2+2?"),
+        ];
+
+        let result = processor.apply_chat_template(&messages, true).unwrap();
+
+        // Check that the result contains expected markers
+        assert!(result.contains("<|begin_of_text|>"));
+        assert!(result.contains("<|start_header_id|>system<|end_header_id|>"));
+        assert!(result.contains("You are a helpful assistant"));
+        assert!(result.contains("<|start_header_id|>user<|end_header_id|>"));
+        assert!(result.contains("What is 2+2?"));
+        assert!(result.contains("<|start_header_id|>assistant<|end_header_id|>"));
+    }
+
+    #[test]
+    #[cfg(feature = "huggingface")]
+    fn test_chatml_template() {
+        // Test a ChatML-style template
+        let template = r#"
+{%- for message in messages %}
+    {{- '<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>\n' }}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+{%- endif %}
+"#;
+
+        let processor = ChatTemplateProcessor::new(template.to_string(), None, None);
+
+        let messages = vec![
+            ChatMessage::user("Hello"),
+            ChatMessage::assistant("Hi there!"),
+            ChatMessage::user("How are you?"),
+        ];
+
+        let result = processor.apply_chat_template(&messages, true).unwrap();
+
+        // Check ChatML format
+        assert!(result.contains("<|im_start|>user\nHello<|im_end|>"));
+        assert!(result.contains("<|im_start|>assistant\nHi there!<|im_end|>"));
+        assert!(result.contains("<|im_start|>user\nHow are you?<|im_end|>"));
+        assert!(result.ends_with("<|im_start|>assistant\n"));
+    }
+
+    #[test]
+    #[cfg(feature = "huggingface")]
+    fn test_template_without_generation_prompt() {
+        let template = r#"
+{%- for message in messages -%}
+{{ message.role }}: {{ message.content }}
+{% endfor -%}
+{%- if add_generation_prompt -%}
+assistant:
+{%- endif -%}
+"#;
+
+        let processor = ChatTemplateProcessor::new(template.to_string(), None, None);
+
+        let messages = vec![ChatMessage::user("Test")];
+
+        // Test without generation prompt
+        let result = processor.apply_chat_template(&messages, false).unwrap();
+        assert_eq!(result.trim(), "user: Test");
+
+        // Test with generation prompt
+        let result_with_prompt = processor.apply_chat_template(&messages, true).unwrap();
+        assert!(result_with_prompt.contains("assistant:"));
+    }
+
+    #[test]
+    #[cfg(feature = "huggingface")]
+    fn test_template_with_special_tokens() {
+        let template = r#"{{ bos_token }}{% for msg in messages %}{{ msg.content }}{{ eos_token }}{% endfor %}"#;
+
+        let processor = ChatTemplateProcessor::new(
+            template.to_string(),
+            Some("<s>".to_string()),
+            Some("</s>".to_string()),
+        );
+
+        let messages = vec![ChatMessage::user("Hello")];
+
+        let result = processor.apply_chat_template(&messages, false).unwrap();
+        assert_eq!(result, "<s>Hello</s>");
+    }
+
+    #[test]
+    #[cfg(feature = "huggingface")]
+    fn test_empty_messages() {
+        let template =
+            r#"{% for msg in messages %}{{ msg.role }}: {{ msg.content }}\n{% endfor %}"#;
+
+        let processor = ChatTemplateProcessor::new(template.to_string(), None, None);
+
+        let messages = vec![];
+        let result = processor.apply_chat_template(&messages, false).unwrap();
+        assert_eq!(result, "");
+    }
+
+    // Integration test with actual tokenizer file loading would go here
+    // but requires a real tokenizer_config.json file
+}

sgl-router/tests/test_chat_template_loading.rs

+#[cfg(test)]
+mod tests {
+    use std::fs;
+    use tempfile::TempDir;
+
+    #[test]
+    #[cfg(feature = "huggingface")]
+    fn test_load_chat_template_from_file() {
+        use sglang_router_rs::tokenizer::chat_template::ChatMessage;
+        use sglang_router_rs::tokenizer::huggingface::HuggingFaceTokenizer;
+
+        // Create temporary directory
+        let temp_dir = TempDir::new().unwrap();
+        let template_path = temp_dir.path().join("template.jinja");
+
+        // Write a test template
+        let template_content = r#"
+{%- for message in messages %}
+    {{- '<|' + message['role'] + '|>' + message['content'] }}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|assistant|>' }}
+{%- endif %}
+"#;
+        fs::write(&template_path, template_content).unwrap();
+
+        // Create a mock tokenizer config
+        let tokenizer_config = r#"{
+            "version": "1.0",
+            "truncation": null,
+            "padding": null,
+            "added_tokens": [],
+            "normalizer": null,
+            "pre_tokenizer": {
+                "type": "Whitespace"
+            },
+            "post_processor": null,
+            "decoder": null,
+            "model": {
+                "type": "BPE",
+                "vocab": {
+                    "hello": 0,
+                    "world": 1,
+                    "<s>": 2,
+                    "</s>": 3
+                },
+                "merges": []
+            }
+        }"#;
+
+        let tokenizer_path = temp_dir.path().join("tokenizer.json");
+        fs::write(&tokenizer_path, tokenizer_config).unwrap();
+
+        // Load tokenizer with custom chat template
+        let tokenizer = HuggingFaceTokenizer::from_file_with_chat_template(
+            tokenizer_path.to_str().unwrap(),
+            Some(template_path.to_str().unwrap()),
+        )
+        .unwrap();
+
+        // Test that the custom template is used
+        let messages = vec![
+            ChatMessage::user("Hello"),
+            ChatMessage::assistant("Hi there"),
+        ];
+
+        let result = tokenizer.apply_chat_template(&messages, true).unwrap();
+
+        // Verify the custom template format
+        assert!(result.contains("<|user|>Hello"));
+        assert!(result.contains("<|assistant|>Hi there"));
+        assert!(result.ends_with("<|assistant|>"));
+    }
+
+    #[test]
+    #[cfg(feature = "huggingface")]
+    fn test_override_existing_template() {
+        use sglang_router_rs::tokenizer::chat_template::ChatMessage;
+        use sglang_router_rs::tokenizer::huggingface::HuggingFaceTokenizer;
+
+        // Create temporary directory
+        let temp_dir = TempDir::new().unwrap();
+
+        // Create tokenizer config with a built-in template
+        let tokenizer_config_path = temp_dir.path().join("tokenizer_config.json");
+        let config_with_template = r#"{
+            "chat_template": "built-in: {% for msg in messages %}{{ msg.content }}{% endfor %}"
+        }"#;
+        fs::write(&tokenizer_config_path, config_with_template).unwrap();
+
+        // Create the actual tokenizer file
+        let tokenizer_json = r#"{
+            "version": "1.0",
+            "truncation": null,
+            "padding": null,
+            "added_tokens": [],
+            "normalizer": null,
+            "pre_tokenizer": {
+                "type": "Whitespace"
+            },
+            "post_processor": null,
+            "decoder": null,
+            "model": {
+                "type": "BPE",
+                "vocab": {
+                    "test": 0,
+                    "<s>": 1,
+                    "</s>": 2
+                },
+                "merges": []
+            }
+        }"#;
+        let tokenizer_path = temp_dir.path().join("tokenizer.json");
+        fs::write(&tokenizer_path, tokenizer_json).unwrap();
+
+        // Create custom template that should override
+        let custom_template_path = temp_dir.path().join("custom.jinja");
+        let custom_template =
+            r#"CUSTOM: {% for msg in messages %}[{{ msg.role }}]: {{ msg.content }}{% endfor %}"#;
+        fs::write(&custom_template_path, custom_template).unwrap();
+
+        // Load with custom template - should override the built-in one
+        let tokenizer = HuggingFaceTokenizer::from_file_with_chat_template(
+            tokenizer_path.to_str().unwrap(),
+            Some(custom_template_path.to_str().unwrap()),
+        )
+        .unwrap();
+
+        let messages = vec![ChatMessage::user("Test")];
+        let result = tokenizer.apply_chat_template(&messages, false).unwrap();
+
+        // Should use CUSTOM template, not built-in
+        assert!(result.starts_with("CUSTOM:"));
+        assert!(result.contains("[user]: Test"));
+        assert!(!result.contains("built-in:"));
+    }
+
+    #[test]
+    #[cfg(feature = "huggingface")]
+    fn test_set_chat_template_after_creation() {
+        use sglang_router_rs::tokenizer::chat_template::ChatMessage;
+        use sglang_router_rs::tokenizer::huggingface::HuggingFaceTokenizer;
+
+        // Create temporary directory and tokenizer file
+        let temp_dir = TempDir::new().unwrap();
+        let tokenizer_json = r#"{
+            "version": "1.0",
+            "truncation": null,
+            "padding": null,
+            "added_tokens": [],
+            "normalizer": null,
+            "pre_tokenizer": {
+                "type": "Whitespace"
+            },
+            "post_processor": null,
+            "decoder": null,
+            "model": {
+                "type": "BPE",
+                "vocab": {
+                    "test": 0,
+                    "<s>": 1,
+                    "</s>": 2
+                },
+                "merges": []
+            }
+        }"#;
+        let tokenizer_path = temp_dir.path().join("tokenizer.json");
+        fs::write(&tokenizer_path, tokenizer_json).unwrap();
+
+        // Load tokenizer without custom template
+        let mut tokenizer =
+            HuggingFaceTokenizer::from_file(tokenizer_path.to_str().unwrap()).unwrap();
+
+        // Set a template after creation (mimics Python's behavior)
+        let new_template =
+            "NEW: {% for msg in messages %}{{ msg.role }}: {{ msg.content }}; {% endfor %}";
+        tokenizer.set_chat_template(new_template.to_string());
+
+        let messages = vec![ChatMessage::user("Hello"), ChatMessage::assistant("World")];
+        let result = tokenizer.apply_chat_template(&messages, false).unwrap();
+
+        assert!(result.starts_with("NEW:"));
+        assert!(result.contains("user: Hello;"));
+        assert!(result.contains("assistant: World;"));
+    }
+}