# Prompt Optimization

PromptPilot is an intelligent solution platform that focuses on optimizing large models and achieving user task intentions. Through interactive feedback, the platform can automatically optimize multi-step, multimodal, and multi-scenario tasks, providing users with efficient intelligent solutions, suitable for enterprises and individuals to improve work efficiency and task completion quality.

PromptWizard is a task-aware prompt optimization framework developed by Microsoft. It employs a self-evolution mechanism that allows large language models (LLMs) to generate, critique, and refine their own prompts and examples, continuously improving through iterative feedback and synthesis. This adaptive approach enhances task performance through evolutionary instructions and contextually learned examples. The three key components of this framework include feedback-driven optimization, critique and synthesis of diverse examples, and self-generated Chain of Thought (CoT) steps. The significance of PromptWizard lies in its ability to significantly enhance LLM performance on specific tasks by optimizing prompts and examples to improve model performance and interpretability.

Prompt Hippo is a dedicated tool for testing prompts for large language models (LLMs), utilizing scientific methods to ensure prompt quality and effectiveness. This tool helps users save time during prompt testing, increasing overall work efficiency. It also integrates with LangServe, allowing users to test and optimize custom agents, ensuring their reliability and safety in production environments.

AutoPrompt is a framework for prompt optimization, designed to automatically generate high-quality and detailed prompts tailored to user intent through an intent calibration process. The framework builds a dataset of challenging edge cases iteratively and optimizes prompts accordingly, thus reducing the workload of manual prompt engineering and effectively addressing issues of prompt sensitivity and inherent ambiguity.

LMOps is a foundation research and technology for AI products based on LLMs and generative AI models. It provides functionalities such as automatic prompt optimization, Promptist, extensible prompts, general prompt retrieval, LLM retrieval, as well as fundamental features including structured prompting, extensible prompting, LLM accelerator, LLM customization, and contextual understanding learning. LMOps links include microsoft/unilm and microsoft/torchscale. It is applicable to various scenarios, such as text-to-image generation, long sequence prompt consumption, and prompt extension. LMOps is an open-source project under the MIT License.