The customization of LiberChat at Prediction Guard was driven by the need to provide a private chat interface for customers using Prediction Guard, ensuring secure and private communication for running large language models. Prediction Guard's customers, who prioritize privacy and security, wanted a private chat interface for the models hosted on Prediction Guard or a non-proprietary interface for using the models. By leveraging the open-source nature of LiberChat, Prediction Guard was able to integrate its own branding, features like toxicity checks, and unique AI models, ensuring a distinct and privacy-conserving user experience for its customers.
We recently gathered some Practical AI listeners for a live webinar with Danny from LibreChat to discuss the future of private, open source chat UIs. During the discussion we hear about the motivations behind LibreChat, why enterprise users are hosting their own chat UIs, and how Danny (and the LibreChat community) is creating amazing features (like RAG and plugins).
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