AutoGenAI: Adaptive Optimization of Prompts, Models and Generation
Strategies
Provides provider-agnostic tools for jointly comparing and
optimizing prompts, language-model providers, and generation strategies
for generative artificial intelligence workflows. Candidate configurations
can be evaluated using user-supplied scoring functions, cost and latency
measurements, robustness perturbations, Pareto-front screening, budget and
latency constraints, prompt evolution, adaptive routing, self-consistency,
and text-output ensembles. The core workflow is designed to run offline
with deterministic mock providers, while external model application
programming interfaces can be connected through user-defined provider
functions. Evolutionary search concepts are described by Goldberg (1989,
ISBN:0201157675), and multi-objective optimization concepts are related to
Deb, Pratap, Agarwal and Meyarivan (2002) <doi:10.1109/4235.996017>.
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