[Rust Frontend] Add /tokenize and /detokenize endpoints

[TanNgocDo]

Summary

Adds POST /tokenize and POST /detokenize (being tracked in #44280) to the Rust server, matching the Python OpenAI server's root-path endpoints. Encoding/decoding runs entirely in-process via DynTokenizer — the inference engine is not involved.

• /tokenize accepts both forms (serde untagged):
  • Completion: encodes the raw prompt string (no chat template); add_special_tokens defaults to true.
  • Chat: renders messages through the chat template, then encodes; add_special_tokens defaults to false (the template adds specials). Reuses convert_message / normalize_generation_prompt_mode from chat_completions/convert so message lowering and the add_generation_prompt / continue_final_message rules stay in lockstep with chat completions.
  • Response carries count, max_model_len, tokens, and (when return_token_strs is set) token_strs.
• /detokenize decodes token IDs back to text with skip_special_tokens = false, matching Python.
• Unknown model names return 404 model_not_found; conflicting generation flags and continue_final_message without a trailing assistant message return 400.

Parity with Python

Behavior was checked against serving_tokenization.py / protocol.py: defaults for add_special_tokens (completion true / chat false), add_generation_prompt (true), the tokenize-{base} request-id format, the token_strs-only-when-requested rule, and skip_special_tokens = false on detokenize.

Known gaps vs Python (intentional for this PR): media_io_kwargs / mm_processor_kwargs on the chat form are not modeled yet.

Not a duplicate

Ran the AGENTS.md §1 checks:

gh pr list --repo vllm-project/vllm --state open --search "tokenize rust"
gh pr list --repo vllm-project/vllm --state open --search "rust detokenize"

The only tokenize-related open PR, #36054 ("[Bugfix] Fix tokenize endpoint malformed token_strs"), touches Python only (vllm/entrypoints/serve/tokenize/, tests/entrypoints/openai/). No open PR adds these endpoints to the Rust server — this is net-new functionality in the rust/ tree.

Testing

cargo test -p vllm-server     # 161 passed
cargo test -p vllm-chat       # all passed
cargo clippy -p vllm-server -p vllm-chat --tests   # clean
cargo fmt --check             # clean

Added integration tests under routes/tests.rs covering:

• completion round-trips through /detokenize
• add_special_tokens toggles the token IDs
• return_token_strs returns a parallel token_strs array
• count / max_model_len are populated
• chat form: generation prompt increases token count; continue-final vs new-assistant differ
• /detokenize decodes an explicit token sequence (independent of /tokenize)
• error paths: conflicting flags → 400, continue-without-assistant → 400, unknown model → 404, empty token list → empty prompt

AI assistance disclosure

AI assistance (Claude Code) was used to:

• investigate the Python reference logic — tracing serving_tokenization.py / protocol.py to confirm field defaults, request-id format, the token_strs / skip_special_tokens rules, and error semantics, so the Rust endpoints match the existing OpenAI server behavior;
• generate the unit/integration tests for these endpoints.

The implementation and all test cases were reviewed line-by-line by the submitter, and the test suite + clippy were run locally with the results above.

[github-actions]

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[BugenZhao]

@codex review

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[BugenZhao]

Thanks!

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[BugenZhao]

Rest LGTM. Thanks!