maitrix-org/PromptAgent

Employs Monte Carlo Tree Search (MCTS) to strategically sample model errors and iteratively refine prompts through reward simulation, unifying prompt sampling and evaluation in a single principled framework. Supports diverse model backends including OpenAI APIs, PaLM, Hugging Face text generation models, and vLLM for local inference, with YAML-based configuration for flexible experimentation. Integrates with BIG-bench tasks and the LLM Reasoners library, enabling optimization across reasoning and knowledge-intensive domains.

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