Show HN: Chatforge – drag two local LLM conversations together to merge context (github.com)

Chatforge, a new local AI chat interface, allows users to merge two conversations by simply dragging one onto the other, creating a unified dialogue that retains the context from both. This innovative feature transforms conversations into composite knowledge, enabling users to ask questions that leverage facts from both chats. With persistent memory, the model retains information about users across sessions, enhancing the personalization of interactions. Additionally, a forthcoming LoRA compilation feature will allow users to permanently embed merged contexts into model weights for more efficient future interactions. The significance of Chatforge for the AI/ML community lies in its approach to treating conversations as dynamic and interconnected rather than isolated sessions. It runs entirely locally on a user's GPU, ensuring privacy and control over data, while providing advanced functionalities like auto fact extraction. Developed using Python and React, it integrates easily with existing local AI models, making it a versatile tool for anyone looking to enhance their conversational AI experience. This project showcases a shift towards more sophisticated and user-friendly AI interactions, paving the way for more advanced and personalized AI applications.