Files
zesdex/src/app/runtime/context/tokens.rs
T
asepharyana c219b6ec58 feat(context): tambah context::tokens dengan tiktoken-rs
Ganti tiga heuristik char-count (/3 di shortsend, /4 di loop turn, /4
di status bar) yang saling tidak konsisten dengan satu BPE tokenizer
nyata. tiktoken-rs membundel vocab lewat include_str! saat build, jadi
tidak ada akses jaringan saat runtime.
2026-07-16 07:49:43 +07:00

70 lines
2.5 KiB
Rust

//! Unified token-count estimation for context-window budgeting.
//!
//! Flow: text -> `tiktoken_rs::o200k_base_singleton()` (BPE vocab embedded
//! in the binary via `include_str!`, no network access) -> `encode_ordinary`
//! -> token count.
//!
//! Why: replaces three independent char-count heuristics that disagreed
//! with each other (`/3` in the old `shortsend.rs`, `/4` in the turn
//! loop, `/4` again in the status bar) with one real BPE tokenizer.
//! `o200k_base` is an approximation for non-OpenAI providers but is far
//! closer than a flat byte-per-token guess; it's only used for the
//! 85%/95% budget thresholds, not for billing-accurate counts.
use crate::dto::chat::message::ChatMessage;
/// Count tokens in a single string under `o200k_base`.
///
/// Return: the BPE token count for `text`. `encode_ordinary` (not
/// `encode`/`encode_with_special_tokens`) is used deliberately — message
/// content that happens to contain a special-token-shaped substring
/// (e.g. literal text `<|endoftext|>` pasted by a user) must be counted
/// as ordinary text, not interpreted as a control token.
pub fn count_tokens(text: &str) -> usize {
tiktoken_rs::o200k_base_singleton().encode_ordinary(text).len()
}
/// Count tokens in a `ChatMessage`'s text content.
///
/// Return: 0 for a message with no `content` (e.g. an assistant message
/// that only carries `tool_calls`).
pub fn count_message_tokens(msg: &ChatMessage) -> usize {
msg.content.as_deref().map_or(0, count_tokens)
}
#[cfg(test)]
mod tests {
use super::*;
use crate::dto::chat::message::ChatMessage;
#[test]
fn empty_string_has_zero_tokens() {
assert_eq!(count_tokens(""), 0);
}
#[test]
fn known_short_phrase_has_expected_token_count() {
// Verified empirically against tiktoken-rs 0.12's o200k_base:
// "hello world" -> [24912, 2375], i.e. 2 tokens.
assert_eq!(count_tokens("hello world"), 2);
}
#[test]
fn known_code_snippet_has_expected_token_count() {
// Verified empirically: 9 tokens under o200k_base.
assert_eq!(count_tokens("fn main() { println!(\"hi\"); }"), 9);
}
#[test]
fn message_with_no_content_counts_zero() {
let msg = ChatMessage::assistant(None);
assert_eq!(count_message_tokens(&msg), 0);
}
#[test]
fn message_token_count_matches_count_tokens_on_its_content() {
let msg = ChatMessage::user("hello world");
assert_eq!(count_message_tokens(&msg), count_tokens("hello world"));
}
}