OpenLIT is an open source platform for observability in GenAI and LLM applications.
OpenLIT is an open source AI engineering platform focused on observability for generative AI and large language model (LLM) applications. It helps developers simplify the AI development process and improve development efficiency and application performance by providing code transparency, privacy protection, performance visualization and other functions. As an open source project, users are free to view the code or host it themselves, ensuring data security and privacy. Its main advantages include easy integration, support for OpenTelemetry native integration, and provision of fine-grained usage insights. OpenLIT is aimed at AI developers, data scientists and enterprises, aiming to help them better build, optimize and manage AI applications. The specific price is not yet clear, but judging from the open source features, it may provide free use of basic functions.
The target audience is mainly AI developers, data scientists and enterprises. For AI developers, OpenLIT provides tools to simplify the development process and optimize performance; for data scientists, it helps to better understand and analyze the behavior of AI models; for enterprises, OpenLIT can improve the observability and management efficiency of AI applications and ensure data security and privacy.
The AI development team uses OpenLIT's prompt management function to efficiently manage and version control a large number of AI prompts, improving development efficiency.
Data scientists use the Openground test function to compare the performance of different LLMs on specific tasks and provide data support for model selection.
Enterprises use OpenLIT's security key management function to ensure the safe storage and use of sensitive information such as API keys and protect enterprise data assets.
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