CharaChat leverages cutting-edge AI language models to facilitate engaging, personalized text-based conversations with virtual characters. Users can choose from a variety of predefined personas—such as friendly guides, storytellers and supportive companions—or create custom characters by setting personality traits, conversation goals and themes. The platform maintains contextual memory across sessions, enabling deeper interactions. Customizable backgrounds, avatars and specialized chat topics enhance immersion. CharaChat also offers chat log export, sharing options, and integration APIs for embedding AI characters into websites or apps. Ideal for roleplaying enthusiasts, writers seeking inspiration, language learners, or anyone looking for empathetic AI companionship, CharaChat combines versatility and ease of use to deliver an interactive, AI-driven dialogue experience.

ChatGPT Save & Copy is an innovative extension for Chrome that allows users to effortlessly export their conversations with ChatGPT. You can choose from a variety of formats such as TXT, HTML, PDF, DOC, CSV, MD, JSON, XML, and RTF. This flexibility makes it suitable for various needs, from saving records for academic purposes to sharing insights with colleagues. Just a few clicks can help you retain important chats, making information management more effective.

ClaudeSave is a Chrome browser extension designed to facilitate the saving of conversations with Anthropic Claude to GitHub Gists. With its user-friendly interface, users can quickly save messages, including text artifacts and attachments, to their GitHub account with just a click. The extension has recently added new features such as the ability to copy conversations in markdown format to the clipboard, enhancing its functionality for developers and frequent users. To use this tool, you need to install the extension, manage it through the Chrome extension manager, and set up a GitHub personal access token with permissions scoped to gists.

llm-reader provides a command-line interface that processes diverse documents—PDFs, presentations, Markdown, and HTML—from local files or URLs. Upon providing a document, it extracts text, splits it into semantic chunks, and creates an embedding-based vector store. Using your configured LLM (OpenAI or alternative), users can issue natural-language queries, receive concise answers, detailed summaries, or follow-up clarifications. It supports exporting the chat history, summary reports, and works offline for text extraction. With built-in caching and multiprocessing, llm-reader accelerates information retrieval from extensive documents, enabling developers, researchers, and analysts to quickly locate insights without manual skimming.