Prompt Optimizer is a powerful, versatile tool designed to enhance the quality of AI prompts, ultimately improving the output generated by large language models (LLMs). The repository, maintained by linshenkx, offers a comprehensive solution for crafting effective prompts, supporting various deployment methods and integrating with a wide range of AI models. The project's core purpose is to empower users to generate more precise, creative, and reliable responses from AI systems, catering to diverse needs from role-playing to knowledge graph extraction and creative writing.

The primary function of Prompt Optimizer is to facilitate the creation and refinement of prompts. It achieves this through a suite of features, including intelligent optimization, dual-mode optimization (system and user prompts), and real-time comparison of original and optimized prompts. The tool supports a broad spectrum of AI models, encompassing OpenAI, Gemini, DeepSeek, Zhipu AI, and SiliconFlow, ensuring compatibility with popular AI services. Furthermore, it extends its capabilities to image generation, offering both text-to-image (T2I) and image-to-image (I2I) functionalities, with integrated support for models like Gemini and Seedream.

A key strength of Prompt Optimizer lies in its multi-platform support. Users can access the tool through a web application, a desktop application, a Chrome extension, and Docker deployment. The web application provides a convenient, readily accessible option, while the desktop application offers enhanced performance and circumvents browser-based limitations, such as cross-origin resource sharing (CORS) issues. The Chrome extension streamlines prompt optimization directly within the user's browsing experience. Docker deployment provides a flexible and scalable solution for users who prefer containerized environments.

The tool's advanced features further enhance its utility. The "Advanced Test Mode" offers sophisticated capabilities, including context variable management, multi-turn conversation testing, and tool calling (function calling) support, enabling users to thoroughly test and debug their prompts. The image generation mode provides a user-friendly interface for creating and manipulating images based on text prompts or existing images. The inclusion of MCP (Model Context Protocol) support allows for seamless integration with applications like Claude Desktop, expanding the tool's interoperability.

The repository's README provides clear instructions for getting started, including links to the online version, Vercel deployment instructions, desktop application downloads, Chrome extension installation, and Docker deployment commands. The documentation also covers API key configuration, offering both interface-based and environment variable-based methods. The project emphasizes security, with the desktop application being a client-side application, ensuring that data is handled directly with the AI service providers, without the need for an intermediary server.

The project's roadmap outlines future development plans, including features like workspace/project management, prompt collection and template management, and further enhancements to image generation capabilities. The repository also includes comprehensive documentation, covering technical development guidelines, LLM parameter configuration, project structure, and product requirements. The project actively encourages community contributions, providing clear guidelines for developers to participate in its development. The project is licensed under the AGPL-3.0 license, promoting open-source usage and modification. The project also provides a Star History chart to visualize the project's popularity over time. The README also includes a detailed FAQ section addressing common issues, such as API connection problems and macOS desktop application issues.