TokenForge — Hybrid Token-Efficient Routing Agent

The Problem Large language models are expensive and slow. Most systems send every query to an LLM — even trivial ones like "What is 12 × 4?" or "Hello!" — wasting tokens, money, and latency on tasks that never needed a model at all. There's no intelligent gatekeeper deciding which queries truly require an LLM. The Solution TokenForge (NeuroRoute) is a cost-aware routing layer that classifies each incoming query and routes it down the cheapest path that still guarantees a correct answer. Simple, deterministic queries are solved locally at zero token cost; only genuinely complex reasoning is escalated to a remote LLM. The result is the same answer quality at a fraction of the cost. How It Works A three-step pipeline: (1) Classify the query intent, (2) Route it to the optimal engine — a local AST math/logic engine or remote Fireworks AI — and (3) Execute & Measure, logging tokens saved and latency for every decision in real time Technical Implementation Local path: AST-based safe evaluation — secure parsing of math expressions with no unsafe eval(). Intent understanding: Sentence Transformers for semantic query classification. Remote path: Fireworks AI for heavy reasoning tasks. Live dashboard: An interactive interface (built on Base44) with a real-time query feed, routing decisions, latency tracking, and a cumulative token-savings counter. Impact Roughly half of all queries are resolved locally at zero token cost, with average latency in the low hundreds of milliseconds — delivering a direct, measurable reduction in LLM spend while preserving accuracy. Built for the AMD Developer Hackathon (ACT II), Track 1: Routing. Try it live: https://smart-ubiquitous-route-flow.base44.app .