Priompt is an open-source, self-hosted prompt management system designed to streamline and enhance the use of Large Language Models (LLMs) like those from OpenAI, Google, and others. It addresses the growing complexity of managing prompts – the instructions given to LLMs – as projects scale and teams collaborate. Instead of relying on scattered text files or hardcoded prompts within applications, Priompt provides a centralized platform for versioning, organizing, testing, and deploying prompts. Its core philosophy centers around treating prompts as code, enabling best practices like version control, collaboration, and automated testing.

The repository offers a comprehensive suite of features. At its heart is a robust prompt editor with syntax highlighting and support for various prompt templating languages like Jinja2. This allows developers to create dynamic prompts that adapt based on input data. Crucially, Priompt supports prompt versioning using Git, enabling rollback to previous versions and tracking changes over time. Collaboration is facilitated through role-based access control, allowing teams to manage permissions and ensure prompt integrity. The system also includes a powerful API for programmatic access, making it easy to integrate Priompt into existing workflows and applications.

A key differentiator for Priompt is its focus on prompt evaluation and testing. It allows users to define evaluation datasets and metrics to assess the performance of different prompt versions. This is vital for ensuring prompts consistently deliver desired results and for identifying areas for improvement. The evaluation framework supports various evaluation methods, including comparing LLM outputs against expected answers or using custom evaluation functions. This testing capability moves prompt engineering from a largely manual and subjective process to a more data-driven and repeatable one. Furthermore, Priompt supports A/B testing of prompts, allowing users to compare the performance of different prompts in a live environment.

The architecture of Priompt is modular and designed for scalability. It's built using FastAPI (Python) for the backend and React for the frontend, making it relatively easy to deploy and maintain. It supports various LLM providers through integrations, and the architecture is extensible to accommodate new providers as they emerge. Deployment options include Docker, making it suitable for containerized environments, and it can be self-hosted on various cloud platforms or on-premise infrastructure. The repository includes detailed documentation and examples to guide users through installation, configuration, and usage.

In essence, Priompt aims to be the "Git for prompts," providing the tools and infrastructure necessary to manage prompts effectively throughout their lifecycle. It's particularly valuable for organizations that are heavily invested in LLMs and require a robust, scalable, and collaborative solution for prompt engineering and management. The project is actively maintained and welcomes contributions from the open-source community, indicating a commitment to ongoing development and improvement.