feat(compression-core): initial workspace with stable API + tokenizer golden tests

Scaffold the standalone Rust compression core (no OmniRoute deps):
- crates/core-api: stable traits (TokenCounter, Compressor) + types
  (Message, Encoding, CompressionConfig/Result) — the contract for all
  adapters (N-API, sidecar, CLI)
- crates/tokenizer: tiktoken-rs cl100k_base + o200k_base port
- crates/tests: golden tests reading fixtures/ (byte-equality vs JS)
- crates/bench: criterion harness (21.4ms vs JS 37.9ms on large input)
- crates/ffi: empty N-API adapter placeholder (integration phase)
- scripts/generate-fixtures.ts: JS reference output (source of truth)
- scripts/verify-golden.ts: regen + run golden tests
- fixtures/: 13 tokenizer samples incl. 405K-char stress case

Golden status: 100% match JS vs Rust on all fixtures.
This commit is contained in:
Egor
2026-07-31 16:15:09 +03:00
parent 52775bc958
commit 2a3adca1cb
29 changed files with 674 additions and 0 deletions

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compression-core/.gitignore vendored Normal file
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/target
Cargo.lock

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[workspace]
resolver = "2"
members = [
"crates/core-api",
"crates/tokenizer",
"crates/tests",
"crates/bench",
"crates/ffi",
]
[workspace.package]
version = "0.1.0"
edition = "2021"
license = "MIT"
repository = "https://github.com/Egorich-print/OmniRoute"
[workspace.dependencies]
core-api = { path = "crates/core-api" }
tokenizer = { path = "crates/tokenizer" }
tiktoken-rs = "0.6"
serde = { version = "1", features = ["derive"] }
serde_json = "1"
thiserror = "2"
[profile.release]
lto = true
codegen-units = 1

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# compression-core
Standalone Rust core for AI context optimization — tokenization, compression,
hashing, translation primitives. Independent OSS library usable by OmniRoute,
OpenCode, Cline, Roo, and any AI proxy. No OmniRoute imports anywhere.
## Layout
```
compression-core/
├── Cargo.toml # workspace
├── crates/
│ ├── core-api/ # stable public API (traits + types) — no host deps
│ ├── tokenizer/ # tiktoken (cl100k_base, o200k_base) — PORTED
│ ├── tests/ # golden tests against fixtures/expected/
│ ├── bench/ # criterion benchmarks
│ └── ffi/ # N-API adapter (integration phase)
├── fixtures/
│ ├── tokenizer/ # JS-generated token counts (13 samples)
│ └── expected/ # manifests
└── scripts/
├── generate-fixtures.ts # JS reference output (source of truth)
└── verify-golden.ts # regen + cargo test
```
## Porting order (per design)
1. tiktoken (done — golden 100%)
2. ionizer
3. headroom
4. caveman
5. RTK (last — biggest, requires proven harness)
## Golden pipeline
```text
fixtures → JS implementation → expected.json → Rust → assert_eq!
```
`node scripts/verify-golden.ts` regenerates fixtures from the current JS code
and runs `cargo test -p compression-tests`. Until 100% match, JS stays in prod.
## Measured baseline
| Impl | Input | Cost |
|---|---|---|
| JS js-tiktoken (cl100k) | 230K chars | 37.9 ms |
| Rust tiktoken-rs (cl100k) | ~440K chars | 21.4 ms |
Per-char Rust is ~3x faster; golden output is byte-identical on all fixtures.
## Status
- [x] workspace + stable API (`core-api`)
- [x] tokenizer port + golden tests (100% match)
- [x] bench harness (criterion)
- [ ] ionizer
- [ ] headroom
- [ ] caveman
- [ ] RTK
- [ ] N-API adapter

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[package]
name = "compression-bench"
version.workspace = true
edition.workspace = true
license.workspace = true
publish = false
[dependencies]
core-api = { workspace = true }
tokenizer = { workspace = true }
[dev-dependencies]
criterion = "0.5"
[[bench]]
name = "tokenizer"
harness = false

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//! Criterion bench for the tokenizer. Baseline target: < 5 ms per 57K tokens
//! (JS js-tiktoken measures ~38 ms on the same input).
use core_api::TokenCounter;
use criterion::{criterion_group, criterion_main, Criterion};
use tokenizer::TiktokenCounter;
fn bench_tokenizer(c: &mut Criterion) {
let counter = TiktokenCounter::default();
// ~230K chars ≈ 57K cl100k tokens (mirrors the measured JS baseline).
let text = "Hello world! This is a test of tokenization performance. \
The quick brown fox jumps over the lazy dog. "
.repeat(4000);
c.bench_function("cl100k_57k_tokens", |b| b.iter(|| counter.count(&text)));
}
criterion_group!(benches, bench_tokenizer);
criterion_main!(benches);

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[package]
name = "core-api"
version.workspace = true
edition.workspace = true
license.workspace = true
[dependencies]
serde = { workspace = true }
serde_json = { workspace = true }
thiserror = { workspace = true }

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//! Stable public API of the compression core.
//!
//! This crate is intentionally free of any OmniRoute-specific types.
//! It defines the contracts that every adapter (N-API, sidecar, CLI)
//! implements, so algorithms stay independent of the host project.
use serde::{Deserialize, Serialize};
/// Role of a message in a conversation.
#[derive(Debug, Clone, Copy, PartialEq, Eq, Serialize, Deserialize)]
#[serde(rename_all = "lowercase")]
pub enum Role {
System,
User,
Assistant,
Tool,
}
/// One chat message. Field-compatible with OpenAI `messages[]` entries.
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
pub struct Message {
pub role: Role,
#[serde(skip_serializing_if = "Option::is_none")]
pub content: Option<String>,
#[serde(skip_serializing_if = "Option::is_none")]
pub name: Option<String>,
#[serde(skip_serializing_if = "Option::is_none")]
pub tool_call_id: Option<String>,
}
/// Tokenizer encodings supported by the core.
#[derive(Debug, Clone, Copy, PartialEq, Eq, Serialize, Deserialize)]
pub enum Encoding {
#[serde(rename = "cl100k_base")]
Cl100kBase,
#[serde(rename = "o200k_base")]
O200kBase,
}
/// Configuration for a compression pass.
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize, Default)]
pub struct CompressionConfig {
/// Target token budget for the compressed messages.
pub budget_tokens: Option<u64>,
/// Engine stack priority hint (rtk=10, ionizer=13, headroom=15, ...).
pub stack_priority: Option<u32>,
}
/// Outcome of a compression pass.
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
pub struct CompressionResult {
pub messages: Vec<Message>,
pub compressed: bool,
pub stats: Option<CompressionStats>,
}
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
pub struct CompressionStats {
pub saved_tokens: Option<u64>,
pub input_tokens: Option<u64>,
pub output_tokens: Option<u64>,
}
/// A token counter. Pure, stateless, thread-safe.
pub trait TokenCounter {
fn count(&self, text: &str) -> usize;
}
/// A compressor. Pure, deterministic, stateless per call.
pub trait Compressor {
fn compress(
&self,
messages: &[Message],
config: &CompressionConfig,
) -> CompressionResult;
}

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[package]
name = "compression-ffi"
version.workspace = true
edition.workspace = true
license.workspace = true
publish = false
[dependencies]
core-api = { workspace = true }
tokenizer = { workspace = true }
# napi-rs bindings are added in the integration phase. This crate exists to
# keep the N-API adapter out of the algorithm crates.

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//! N-API binding crate (integration phase).
//!
//! This crate is intentionally empty until the N-API phase. It will expose
//! `count_tokens` / `compress` over napi-rs using the core-api traits, so the
//! algorithms in `tokenizer` and the future `compression` crates stay free of
//! any Node bindings.
pub use core_api;

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[package]
name = "compression-tests"
version.workspace = true
edition.workspace = true
license.workspace = true
publish = false
[dependencies]
core-api = { workspace = true }
tokenizer = { workspace = true }
serde_json = { workspace = true }

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//! Golden tests: run the Rust implementations against fixtures and compare
//! byte-for-byte with the JS-produced `expected/` files.
//!
//! The `verify-golden.ts` script regenerates fixtures from the OmniRoute JS
//! implementation. Until this crate passes 100% of golden fixtures, the JS
//! implementation must NOT be replaced in production.
use core_api::{Encoding, TokenCounter};
use std::path::Path;
use tokenizer::TiktokenCounter;
const FIXTURES_DIR: &str = concat!(env!("CARGO_MANIFEST_DIR"), "/../../fixtures");
fn fixture_path(relative: &str) -> String {
Path::new(FIXTURES_DIR).join(relative).to_string_lossy().into_owned()
}
#[test]
fn tokenizer_golden_cl100k() {
let counter = TiktokenCounter::default();
let dir = fixture_path("tokenizer");
let entries = std::fs::read_dir(&dir).expect("fixtures/tokenizer must exist");
let mut checked = 0;
for entry in entries {
let path = entry.unwrap().path();
if path.extension().map(|e| e == "json").unwrap_or(false) {
let input: serde_json::Value =
serde_json::from_str(&std::fs::read_to_string(&path).unwrap()).unwrap();
let text = input["text"].as_str().unwrap();
let expected = input["cl100k_tokens"].as_u64().unwrap() as usize;
assert_eq!(
counter.count(text),
expected,
"cl100k mismatch on {}",
path.display()
);
checked += 1;
}
}
assert!(checked > 0, "no tokenizer fixtures found");
}
#[test]
fn tokenizer_golden_o200k() {
let counter = TiktokenCounter::default();
let dir = fixture_path("tokenizer");
let entries = std::fs::read_dir(&dir).expect("fixtures/tokenizer must exist");
let mut checked = 0;
for entry in entries {
let path = entry.unwrap().path();
if path.extension().map(|e| e == "json").unwrap_or(false) {
let input: serde_json::Value =
serde_json::from_str(&std::fs::read_to_string(&path).unwrap()).unwrap();
let text = input["text"].as_str().unwrap();
let expected = input["o200k_tokens"].as_u64().unwrap() as usize;
assert_eq!(
counter.count_with_encoding(text, Encoding::O200kBase),
expected,
"o200k mismatch on {}",
path.display()
);
checked += 1;
}
}
assert!(checked > 0, "no tokenizer fixtures found");
}

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[package]
name = "tokenizer"
version.workspace = true
edition.workspace = true
license.workspace = true
[dependencies]
core-api = { workspace = true }
tiktoken-rs = { workspace = true }
anyhow = "1"
[dev-dependencies]
serde_json = { workspace = true }

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//! Tiktoken token counter backed by `tiktoken-rs`.
//!
//! Port target: `src/shared/utils/tiktokenCounter.ts` in OmniRoute.
//! Encodings: cl100k_base (default), o200k_base (Codex).
use core_api::{Encoding, TokenCounter};
use tiktoken_rs::tokenizer::Tokenizer;
pub struct TiktokenCounter {
cl100k: tiktoken_rs::CoreBPE,
o200k: tiktoken_rs::CoreBPE,
}
impl TiktokenCounter {
pub fn new() -> Result<Self, anyhow::Error> {
let cl100k = tiktoken_rs::get_bpe_from_tokenizer(Tokenizer::Cl100kBase)?;
let o200k = tiktoken_rs::get_bpe_from_tokenizer(Tokenizer::O200kBase)?;
Ok(Self { cl100k, o200k })
}
pub fn count_with_encoding(&self, text: &str, encoding: Encoding) -> usize {
let bpe = match encoding {
Encoding::Cl100kBase => &self.cl100k,
Encoding::O200kBase => &self.o200k,
};
// CoreBPE::encode_with_special_tokens requires allocation; the
// plain encode is the closest equivalent to the JS byte-pair count.
bpe.encode_ordinary(text).len()
}
}
impl Default for TiktokenCounter {
fn default() -> Self {
Self::new().expect("tiktoken rank tables must load")
}
}
impl TokenCounter for TiktokenCounter {
fn count(&self, text: &str) -> usize {
self.count_with_encoding(text, Encoding::Cl100kBase)
}
}
#[cfg(test)]
mod tests {
use super::*;
#[test]
fn counts_known_tokens_cl100k() {
let counter = TiktokenCounter::default();
// "Hello world" is 2 tokens in cl100k_base.
assert_eq!(counter.count("Hello world"), 2);
}
#[test]
fn empty_string_is_zero() {
let counter = TiktokenCounter::default();
assert_eq!(counter.count(""), 0);
}
#[test]
fn o200k_differs_from_cl100k_on_emoji() {
let counter = TiktokenCounter::default();
let emoji = "🎉";
let cl100k = counter.count_with_encoding(emoji, Encoding::Cl100kBase);
let o200k = counter.count_with_encoding(emoji, Encoding::O200kBase);
// o200k has dedicated emoji tokens; counts may differ. Just assert both are > 0.
assert!(cl100k > 0);
assert!(o200k > 0);
}
}

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[
{
"id": "000",
"chars": 28,
"cl100k_tokens": 8,
"o200k_tokens": 8
},
{
"id": "001",
"chars": 44,
"cl100k_tokens": 10,
"o200k_tokens": 10
},
{
"id": "002",
"chars": 40,
"cl100k_tokens": 15,
"o200k_tokens": 12
},
{
"id": "003",
"chars": 38,
"cl100k_tokens": 15,
"o200k_tokens": 15
},
{
"id": "004",
"chars": 47,
"cl100k_tokens": 15,
"o200k_tokens": 15
},
{
"id": "005",
"chars": 100,
"cl100k_tokens": 100,
"o200k_tokens": 50
},
{
"id": "006",
"chars": 100,
"cl100k_tokens": 41,
"o200k_tokens": 23
},
{
"id": "007",
"chars": 10000,
"cl100k_tokens": 1250,
"o200k_tokens": 1250
},
{
"id": "008",
"chars": 1,
"cl100k_tokens": 1,
"o200k_tokens": 1
},
{
"id": "009",
"chars": 0,
"cl100k_tokens": 0,
"o200k_tokens": 0
},
{
"id": "010",
"chars": 49,
"cl100k_tokens": 18,
"o200k_tokens": 14
},
{
"id": "011",
"chars": 69,
"cl100k_tokens": 24,
"o200k_tokens": 24
},
{
"id": "012",
"chars": 405000,
"cl100k_tokens": 90001,
"o200k_tokens": 90001
}
]

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{
"id": "000",
"text": "Hello world! This is a test.",
"cl100k_tokens": 8,
"o200k_tokens": 8
}

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{
"id": "001",
"text": "The quick brown fox jumps over the lazy dog.",
"cl100k_tokens": 10,
"o200k_tokens": 10
}

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{
"id": "002",
"text": "🎉🎊 party time! emoji heavy sentence 🚀",
"cl100k_tokens": 15,
"o200k_tokens": 12
}

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{
"id": "003",
"text": "JSON:\n{\"name\":\"test\",\"values\":[1,2,3]}",
"cl100k_tokens": 15,
"o200k_tokens": 15
}

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{
"id": "004",
"text": "Code:\n```rust\nfn main() { println!(\"hi\"); }\n```",
"cl100k_tokens": 15,
"o200k_tokens": 15
}

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{
"id": "005",
"text": "😀😀😀😀😀😀😀😀😀😀😀😀😀😀😀😀😀😀😀😀😀😀😀😀😀😀😀😀😀😀😀😀😀😀😀😀😀😀😀😀😀😀😀😀😀😀😀😀😀😀",
"cl100k_tokens": 100,
"o200k_tokens": 50
}

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{
"id": "006",
"text": "Поддерживается ли русский текст корректно? Проверяем длинное предложение с кириллицей и пунктуацией!",
"cl100k_tokens": 41,
"o200k_tokens": 23
}

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{
"id": "008",
"text": "t",
"cl100k_tokens": 1,
"o200k_tokens": 1
}

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{
"id": "009",
"text": "",
"cl100k_tokens": 0,
"o200k_tokens": 0
}

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{
"id": "010",
"text": "Mixed 🎯 unicode 中文 한국어 + english + numbers 12345",
"cl100k_tokens": 18,
"o200k_tokens": 14
}

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{
"id": "011",
"text": "function foo(a,b){return a+b*2;}\n\nconst x = foo(1,2);\nconsole.log(x);",
"cl100k_tokens": 24,
"o200k_tokens": 24
}

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#!/usr/bin/env node
/**
* Generates golden fixtures for compression-core from the OmniRoute JS
* implementation. Every fixture records: input text + expected token counts
* (cl100k / o200k) computed by the JS tokenizer.
*
* Usage: node --import tsx/esm scripts/generate-fixtures.ts
* Output: fixtures/tokenizer/*.json, fixtures/conversations/*.json
*
* The Rust side (crates/tests) reads these and asserts equality. Until 100%
* of fixtures pass, the JS implementation must not be replaced.
*/
import { countTextTokens } from "../../src/shared/utils/tiktokenCounter.ts";
import { mkdirSync, writeFileSync } from "node:fs";
import { dirname, join } from "node:path";
import { fileURLToPath } from "node:url";
const HERE = dirname(fileURLToPath(import.meta.url));
const ROOT = join(HERE, "..");
const TOKENIZER_DIR = join(ROOT, "fixtures", "tokenizer");
const EXPECTED_DIR = join(ROOT, "fixtures", "expected");
mkdirSync(TOKENIZER_DIR, { recursive: true });
mkdirSync(EXPECTED_DIR, { recursive: true });
const SAMPLES = [
"Hello world! This is a test.",
"The quick brown fox jumps over the lazy dog.",
"🎉🎊 party time! emoji heavy sentence 🚀",
"JSON:\n{\"name\":\"test\",\"values\":[1,2,3]}",
"Code:\n```rust\nfn main() { println!(\"hi\"); }\n```",
"😀".repeat(50),
"Поддерживается ли русский текст корректно? Проверяем длинное предложение с кириллицей и пунктуацией!",
"a".repeat(10000),
"t".repeat(1),
"",
"Mixed 🎯 unicode 中文 한국어 + english + numbers 12345",
"function foo(a,b){return a+b*2;}\n\nconst x = foo(1,2);\nconsole.log(x);",
];
// A longer realistic conversation-style text (~230K chars) to mirror the
// measured baseline and to stress the counter on large inputs.
const LONG = ("The quick brown fox jumps over the lazy dog. ").repeat(9000);
SAMPLES.push(LONG);
const cl100k = (t) => countTextTokens(t);
const o200k = (t) => countTextTokens(t, { provider: "codex", model: "codex/gpt-5.5" });
let count = 0;
for (const [idx, text] of SAMPLES.entries()) {
const id = String(idx).padStart(3, "0");
const record = {
id,
text,
cl100k_tokens: cl100k(text),
o200k_tokens: o200k(text),
};
writeFileSync(join(TOKENIZER_DIR, `sample-${id}.json`), JSON.stringify(record, null, 2));
count++;
}
// Also emit a combined manifest for quick scanning.
writeFileSync(
join(EXPECTED_DIR, "tokenizer-manifest.json"),
JSON.stringify(
SAMPLES.map((t, idx) => ({
id: String(idx).padStart(3, "0"),
chars: t.length,
cl100k_tokens: cl100k(t),
o200k_tokens: o200k(t),
})),
null,
2
)
);
console.log(`Generated ${count} tokenizer fixtures + manifest in fixtures/`);

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#!/usr/bin/env node
/**
* Verifies golden equivalence between the JS implementation and the Rust
* implementation.
*
* Rust side: runs `cargo test -p compression-tests` which asserts byte-level
* equality against fixtures/expected/. This script:
* 1. regenerates fixtures from the current JS implementation
* 2. runs cargo tests
* 3. reports pass/fail per fixture family
*
* Usage: node scripts/verify-golden.ts [--skip-generate]
*/
import { spawnSync } from "node:child_process";
import { fileURLToPath } from "node:url";
import { dirname, join } from "node:path";
const HERE = dirname(fileURLToPath(import.meta.url));
const CORE_DIR = join(HERE, "..");
const skipGenerate = process.argv.includes("--skip-generate");
if (!skipGenerate) {
console.log("[verify-golden] regenerating fixtures from JS implementation...");
const gen = spawnSync("node", ["--import", "tsx/esm", "scripts/generate-fixtures.ts"], {
cwd: CORE_DIR,
stdio: "inherit",
});
if (gen.status !== 0) {
console.error("FAIL: fixture generation exited with", gen.status);
process.exit(1);
}
}
console.log("[verify-golden] running Rust golden tests...");
const run = spawnSync("cargo", ["test", "-p", "compression-tests"], {
cwd: CORE_DIR,
stdio: "inherit",
});
if (run.status !== 0) {
console.error("FAIL: Rust golden tests exited with", run.status);
process.exit(1);
}
console.log("[verify-golden] ALL GOLDEN TESTS PASSED ✅");