General-purpose AI Agent
A hybrid AI routing system designed to balance high-level performance with strict operational cost efficiency. By deploying a dual-tier architecture, the agent utilizes a local student model to handle basic prompts within a resource-constrained Docker environment. Complex requests involving advanced logic or coding are automatically escalated to powerful teacher models via external APIs. To ensure reliability, the system incorporates a validation layer that detects errors in local outputs and triggers a secondary review when necessary. The framework further reduces overhead through prompt compression and strict formatting controls to minimise token consumption. Ultimately, this approach demonstrates how dynamic classification can maintain high accuracy while significantly lowering the expenses associated with enterprise AI deployments.
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