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Hybrid Token Router
This project is an autonomous AI task routing agent designed to solve a diverse set of natural language tasks while attempting to minimize the number of Fireworks AI tokens consumed. Rather than sending every request to a cloud model, the agent intelligently decides whether a task can be completed locally using a lightweight GGUF language model or whether it requires a more capable Fireworks AI model. This approach significantly reduces cloud inference costs while maintaining a high level of accuracy. To improve reliability, the system includes an answer validation stage. Local responses are checked for structural correctness, formatting requirements, and category-specific constraints before being accepted. If a response fails validation or the task is determined to be too complex for the local model, the agent automatically falls back to the most appropriate Fireworks AI model selected from the list of models provided at runtime. This allows the system to preserve accuracy while minimizing unnecessary cloud usage.
13 Jul 2026
