feat: library overhaul for any LLM

Author: johannschopplich

.github/workflows/ci.yml

@@ -17,7 +17,7 @@ jobs:
       - uses: pnpm/action-setup@v3
       - uses: actions/setup-node@v4
         with:
-          node-version: 20
+          node-version: 22
           cache: pnpm
       - run: pnpm install
       - run: pnpm run lint
@@ -29,7 +29,7 @@ jobs:
       - uses: pnpm/action-setup@v3
       - uses: actions/setup-node@v4
         with:
-          node-version: 20
+          node-version: 22
           cache: pnpm
       - run: pnpm install
       - run: pnpm run test:types
@@ -41,7 +41,7 @@ jobs:
       - uses: pnpm/action-setup@v3
       - uses: actions/setup-node@v4
         with:
-          node-version: 20
+          node-version: 22
           cache: pnpm
       - run: pnpm install
       - run: pnpm run test

.github/workflows/release.yml

@@ -18,7 +18,7 @@ jobs:
       - uses: pnpm/action-setup@v3
       - uses: actions/setup-node@v4
         with:
-          node-version: 20
+          node-version: 22
           registry-url: https://registry.npmjs.org/
           cache: pnpm
 

README.md

@@ -1,6 +1,8 @@
 # tokenx
 
-GPT token count and context size utilities when approximations are good enough. For advanced use cases, please use a full tokenizer like [`gpt-tokenizer`](https://github.com/niieani/gpt-tokenizer). This library is intended to be used for quick estimations and to avoid the overhead of a full tokenizer, e.g. when you want to limit your bundle size.
+Fast and lightweight token count estimation for any LLM without requiring a full tokenizer. This library provides quick approximations that are good enough for most use cases while keeping your bundle size minimal.
+
+For advanced use cases requiring precise token counts, please use a full tokenizer like [`gpt-tokenizer`](https://github.com/niieani/gpt-tokenizer).
 
 ## Benchmarks
 
@@ -11,18 +13,20 @@ The following table shows the accuracy of the token count approximation for diff
 | --- | --- | --- | --- |
 | Short English text | 10 | 11 | 10.00% |
 | German text with umlauts | 56 | 49 | 12.50% |
-| Metamorphosis by Franz Kafka (English) | 31892 | 33930 | 6.39% |
-| Die Verwandlung by Franz Kafka (German) | 40621 | 34908 | 14.06% |
-| 道德經 by Laozi (Chinese) | 14387 | 11919 | 17.15% |
-| TypeScript ES5 Type Declarations (~ 4000 loc) | 48408 | 51688 | 6.78% |
+| Metamorphosis by Franz Kafka (English) | 31892 | 35705 | 11.96% |
+| Die Verwandlung by Franz Kafka (German) | 40621 | 35069 | 13.67% |
+| 道德經 by Laozi (Chinese) | 14387 | 12059 | 16.18% |
+| TypeScript ES5 Type Declarations (~ 4000 loc) | 48553 | 52434 | 7.99% |
 <!-- END GENERATED TOKEN COUNT TABLE -->
 
 ## Features
 
-- 🌁 Estimate token count without a full tokenizer
-- 📐 Supports multiple model context sizes
-- 🗣️ Supports accented characters, like German umlauts or French accents
+- ⚡ Fast token estimation without a full tokenizer
+- 🌍 Multi-language support with configurable language rules
+- 🗣️ Built-in support for accented characters (German, French, Spanish, etc.)
+- 🔧 Configurable and extensible
 - 🪽 Zero dependencies
+- 📦 Tiny bundle size
 
 ## Installation
 
@@ -42,76 +46,72 @@ yarn add tokenx
 ## Usage
 
 ```ts
-import {
-  approximateMaxTokenSize,
-  approximateTokenSize,
-  isWithinTokenLimit
-} from 'tokenx'
+import { estimateTokenCount, isWithinTokenLimit } from 'tokenx'
 
-const prompt = 'Your prompt goes here.'
-const inputText = 'Your text goes here.'
+const text = 'Your text goes here.'
 
-// Estimate the number of tokens in the input text
-const estimatedTokens = approximateTokenSize(inputText)
+// Estimate the number of tokens in the text
+const estimatedTokens = estimateTokenCount(text)
 console.log(`Estimated token count: ${estimatedTokens}`)
 
-// Calculate the maximum number of tokens allowed for a given model
-const modelName = 'gpt-3.5-turbo'
-const maxResponseTokens = 1000
-const availableTokens = approximateMaxTokenSize({
-  prompt,
-  modelName,
-  maxTokensInResponse: maxResponseTokens
-})
-console.log(`Available tokens for model ${modelName}: ${availableTokens}`)
-
-// Check if the input text is within a specific token limit
+// Check if text is within a specific token limit
 const tokenLimit = 1024
-const withinLimit = isWithinTokenLimit(inputText, tokenLimit)
+const withinLimit = isWithinTokenLimit(text, tokenLimit)
 console.log(`Is within token limit: ${withinLimit}`)
-```
 
-## API
-
-### `approximateTokenSize`
+// Use custom options for different languages or models
+const customOptions = {
+  defaultCharsPerToken: 4, // More conservative estimation
+  languageConfigs: [
+    { pattern: /[你我他]/g, averageCharsPerToken: 1.5 }, // Custom Chinese rule
+  ]
+}
 
-Estimates the number of tokens in a given input string based on common English patterns and tokenization heuristics. Work well for other languages too, like German.
-
-**Usage:**
-
-```ts
-const estimatedTokens = approximateTokenSize('Hello, world!')
+const customEstimate = estimateTokenCount(text, customOptions)
+console.log(`Custom estimate: ${customEstimate}`)
 ```
 
-**Type Declaration:**
-
-```ts
-function approximateTokenSize(input: string): number
-```
+## API
 
-### `approximateMaxTokenSize`
+### `estimateTokenCount`
 
-Calculates the maximum number of tokens that can be included in a response given the prompt length and model's maximum context size.
+Estimates the number of tokens in a given input string using heuristic rules that work across multiple languages and text types.
 
 **Usage:**
 
 ```ts
-const maxTokens = approximateMaxTokenSize({
-  prompt: 'Sample prompt',
-  modelName: 'text-davinci-003',
-  maxTokensInResponse: 500
+const estimatedTokens = estimateTokenCount('Hello, world!')
+
+// With custom options
+const customEstimate = estimateTokenCount('Bonjour le monde!', {
+  defaultCharsPerToken: 4,
+  languageConfigs: [
+    { pattern: /[éèêëàâîï]/i, averageCharsPerToken: 3 }
+  ]
 })
 ```
 
 **Type Declaration:**
 
 ```ts
-function approximateMaxTokenSize({ prompt, modelName, maxTokensInResponse }: {
-  prompt: string
-  modelName: ModelName
-  /** The maximum number of tokens to generate in the reply. 1000 tokens are roughly 750 English words. */
-  maxTokensInResponse?: number
-}): number
+function estimateTokenCount(
+  text?: string,
+  options?: TokenEstimationOptions
+): number
+
+interface TokenEstimationOptions {
+  /** Default average characters per token when no language-specific rule applies */
+  defaultCharsPerToken?: number
+  /** Custom language configurations to override defaults */
+  languageConfigs?: LanguageConfig[]
+}
+
+interface LanguageConfig {
+  /** Regular expression to detect the language */
+  pattern: RegExp
+  /** Average number of characters per token for this language */
+  averageCharsPerToken: number
+}
 ```
 
 ### `isWithinTokenLimit`
@@ -122,12 +122,18 @@ Checks if the estimated token count of the input is within a specified token lim
 
 ```ts
 const withinLimit = isWithinTokenLimit('Check this text against a limit', 100)
+// With custom options
+const customCheck = isWithinTokenLimit('Text', 50, { defaultCharsPerToken: 3 })
 ```
 
 **Type Declaration:**
 
 ```ts
-function isWithinTokenLimit(input: string, tokenLimit: number): boolean
+function isWithinTokenLimit(
+  text: string,
+  tokenLimit: number,
+  options?: TokenEstimationOptions
+): boolean
 ```
 
 ## License

build.config.ts

@@ -2,8 +2,8 @@
   "name": "tokenx",
   "type": "module",
   "version": "0.4.1",
-  "packageManager": "pnpm@9.14.4",
-  "description": "GPT token estimation and context size utilities without a full tokenizer",
+  "packageManager": "pnpm@10.11.0",
+  "description": "Fast and lightweight token estimation for any LLM without requiring a full tokenizer",
   "author": "Johann Schopplich <hello@johannschopplich.com>",
   "license": "MIT",
   "homepage": "https://github.com/johannschopplich/tokenx#readme",
@@ -16,50 +16,43 @@
   },
   "keywords": [
     "ai",
-    "gpt",
+    "llm",
     "token",
-    "tiktoken"
+    "tokenizer",
+    "estimation",
+    "tiktoken",
+    "anthropic",
+    "openai"
   ],
   "sideEffects": false,
   "exports": {
     ".": {
-      "types": "./dist/index.d.mts",
-      "import": {
-        "types": "./dist/index.d.mts",
-        "default": "./dist/index.mjs"
-      },
-      "require": {
-        "types": "./dist/index.d.cts",
-        "default": "./dist/index.cjs"
-      },
-      "default": "./dist/index.mjs"
+      "types": "./dist/index.d.ts",
+      "default": "./dist/index.js"
     }
   },
-  "main": "./dist/index.cjs",
-  "module": "./dist/index.mjs",
   "types": "./dist/index.d.ts",
   "files": [
     "dist"
   ],
   "scripts": {
-    "build": "unbuild",
+    "build": "tsdown",
     "docs:generate": "tsx scripts/generateTable.ts",
-    "dev": "unbuild --stub",
     "lint": "eslint .",
     "lint:fix": "eslint . --fix",
     "test": "vitest",
     "test:types": "tsc --noEmit",
     "release": "bumpp"
   },
   "devDependencies": {
-    "@antfu/eslint-config": "^3.11.2",
-    "@types/node": "^22.10.1",
-    "bumpp": "^9.8.1",
-    "eslint": "^9.15.0",
-    "gpt-tokenizer": "^2.7.0",
-    "tsx": "^4.19.2",
-    "typescript": "^5.7.2",
-    "unbuild": "^3.0.0-rc.11",
-    "vitest": "^2.1.6"
+    "@antfu/eslint-config": "^4.13.2",
+    "@types/node": "^22.15.29",
+    "bumpp": "^10.1.1",
+    "eslint": "^9.28.0",
+    "gpt-tokenizer": "^2.9.0",
+    "tsdown": "^0.12.6",
+    "tsx": "^4.19.4",
+    "typescript": "^5.8.3",
+    "vitest": "^3.2.0"
   }
 }