Piyush Kumar@PiyushKumar

This project implements a hybrid token-efficient AI agent designed to solve a wide variety of tasks while minimizing unnecessary LLM usage. The system first classifies each incoming task and routes it to the most appropriate execution path. Deterministic problems such as mathematical computations, fuzzy matching, symbolic reasoning, and rule-based operations are solved locally for maximum speed and zero token cost. More complex tasks including summarization, code generation, logical reasoning, debugging, named entity recognition, and factual question answering are handled using Fireworks AI models selected dynamically through the provided ALLOWED_MODELS environment variable. The application is fully containerized using Docker, reads tasks from /input/tasks.json, writes results to /output/results.json, and complies with the evaluation harness by using environment-based configuration, Linux AMD64 compatibility, and efficient routing to reduce latency and inference costs while maintaining high accuracy.

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