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Fireworks AI competition agent built as a production-grade, batch-processing Docker container. The image reads task data from /input/tasks.json, routes each task through a confidence-based orchestration pipeline, invokes Fireworks only when deterministic preprocessing is not sufficient, and writes final structured answers to /output/results.json. The repository emphasizes accuracy first and token efficiency second, with modular agents for factual knowledge, mathematical reasoning, sentiment classification, summarization, named entity recognition, code debugging, logical reasoning, and code generation. It includes deterministic routing, validation, repair attempts, structured logging, token tracking, and offline-learning scaffolding for future router training. The container is optimized for reproducibility, non-root execution, minimal privileges, and easy local development with Docker Compose while remaining fully compliant with the competitionโs file-based batch workflow.
11 Jul 2026