TOKEMIZER

nterprises today face an "AI Budget Paradox": premium proprietary models are too expensive for simple, repetitive tasks, while smaller local models often lack the reasoning depth required for complex logical constraints or code generation. The Hybrid Token Router solves this by introducing a highly efficient, autonomous "Gatekeeper" architecture. At its core, the system acts as a multi-tier intelligent broker. When a natural language task is ingested, our internal local model (a 4-bit quantized Qwen2.5-1.5B) first evaluates the prompt's complexity, assigning a strict score ranging from 0.0 to 1.0. For simple tasks (Score < 0.3), the system triggers our "Zero-Cost Local Routing." The prompt is processed entirely on-device by the Qwen model. This achieves maximum accuracy for basic factoid, summarization, or entity extraction tasks without spending a single API token. For complex tasks (Score > 0.3), such as advanced code debugging or deductive reasoning, the system activates "Dynamic External Procurement." The router maps the complexity score to an ordered array of allowed Fireworks AI models, intelligently selecting the most cost-effective yet capable model for the specific job. To further maximize efficiency, our proprietary Cost Optimization block compresses the prompt before transmission, drastically reducing the token footprint. Built entirely within a lightweight Docker container optimized for the linux/amd64 platform, the Hybrid Token Router is a self-contained, high-performance template for scalable and cost-aware AI orchestration.