Ruthwik000

Ruthwik000 / tokenfirewall

Public

Scalable LLM cost enforcement middleware for Node.js with budget protection and multi-provider support

www.npmjs.compackagetokenfirewall ai-cost-management anthropic automatic-failover budget cost-control
12
0
80% credibility
Found Mar 05, 2026 at 12 stars -- GitGems finds repos before they trend. Get early access to the next one.
Sign Up Free
AI Analysis
TypeScript
AI Summary

TokenFirewall is a library that automatically monitors costs for AI language model usage across multiple providers, enforces spending limits, and switches to backup models on failures.

How It Works

1
🔍 Discover TokenFirewall

You learn about a smart helper that watches your AI chatting costs to avoid surprise bills.

2
📦 Add to your app

You simply include this helpful tool in your existing project.

3
💰 Choose your spending limit

You decide on a monthly dollar amount you're happy with for AI usage.

4
🛡️ Switch on protection

You activate the safeguard so it starts watching automatically.

5
👀 Chat with AI normally

Everything works just like before, but now costs are tracked in real-time and blocked if over limit.

6
🔄 Smart switches on issues

When one AI option struggles, it quietly tries a reliable backup to keep things running.

✅ Peace of mind achieved

Your app stays reliable, bills stay predictable, and you get clear reports on every penny spent.

Sign up to see the full architecture

5 more

Sign Up Free

Star Growth

See how this repo grew from 12 to 12 stars Sign Up Free
Repurpose This Repo

Repurpose is a Pro feature

Generate ready-to-use prompts for X threads, LinkedIn posts, blog posts, YouTube scripts, and more -- with full repo context baked in.

Unlock Repurpose
AI-Generated Review

What is tokenfirewall?

TokenFirewall is TypeScript middleware for Node.js that intercepts fetch calls to LLM APIs from providers like OpenAI, Anthropic, Gemini, Grok, and Kimi, automatically tracking token usage and calculating real-time costs to enforce monthly budgets. Set a dollar limit once, choose block or warn mode, and it prevents overruns without changing your API code—ideal for scalable LLM inference where costs can spiral. It also offers intelligent model routing for automatic failover to cheaper or larger-context backups on failures.

Why is it gaining traction?

Unlike basic wrappers requiring SDK swaps, it patches global fetch for zero-code integration across any HTTP-based LLM call, with built-in pricing for 40+ models and dynamic registration for customs. Developers love the surprise-bill protection via strict budget enforcement, plus routing strategies that handle rate limits or context overflows seamlessly. Multi-provider unification simplifies cost oversight in hybrid setups.

Who should use this?

Node.js backend teams running production LLM apps on tight budgets, like chatbots or RAG pipelines needing scalable cost enforcement. AI engineers building multi-provider systems who want failover without manual retries. Startups scaling LLM clusters wary of vendor lock-in or surprise invoices.

Verdict

Grab it for budget-conscious LLM projects—solid docs, examples, and TypeScript types make it production-ready despite 12 stars and 0.800000011920929% credibility score signaling early maturity. Test in staging first; lacks tests but delivers core value out of the box.

(198 words)

Sign up to read the full AI review Sign Up Free

Similar repos coming soon.