Summary

TokenLens provides typed model metadata and utilities for AI applications to manage context windows, estimate costs, and optimize token usage. It targets developers building AI-powered applications, offering crucial insights for efficient and cost-effective operation, particularly with large language models.

How It Works

The library offers a canonical model registry with alias resolution and trusted metadata. It provides a strong TypeScript interface for model identification and safe helper functions. TokenLens normalizes usage across different providers and SDKs, enabling consistent context budgeting (remaining tokens, percentage used, next-turn budget) and compaction strategies (when to compact, how many tokens to remove). It also includes cost estimation based on source-linked pricing where available.

Quick Start & Requirements

• Install: npm i tokenlens (or pnpm add tokenlens, yarn add tokenlens).
• Prerequisites: Node.js (v18+ recommended for fetchModels without custom fetch), TypeScript.
• Links:
  • Models.dev data source: https://github.com/sst/models.dev
  • Sync command: pnpm -C packages/tokenlens sync:models

Highlighted Details

• Canonical model registry with alias resolution and minimal, trusted metadata.
• Strong TypeScript surface enabling model ID autocomplete and safe helper functions.
• Usage normalization across providers and SDKs, including Vercel AI SDK fields.
• Context budgeting utilities: calculates remaining tokens, percentage used, and next-turn budget.
• Compaction helpers: advises on when to compact and how many tokens to remove.
• Cost estimation: provides fast, rough USD costs using source-linked pricing from models.dev.

Maintenance & Community

• Relies on the models.dev dataset for model information (https://github.com/sst/models.dev).
• No specific community links (Discord/Slack) or contributor information provided in the README.

Licensing & Compatibility

• License: MIT.
• Compatibility: Permissive MIT license allows for commercial use and integration into closed-source applications.

Limitations & Caveats

• Many helper functions are deprecated in favor of a more focused API (getContext, getTokenCosts, getUsage).
• Cost outputs are estimates based on models.dev pricing; authoritative numbers require runtime API responses.
• Advanced context budgeting strategies (provider-default, combined, input-only) offer flexibility but require careful selection.