
Linq developers can now build iMessage Apps. These are interactive mini-apps that run inside a iMessages conversation. A user can shop, play a game, book a flight, or pay. None of it requires leaving the iMessage thread. There is no deep link to an external browser. There is no ‘tap here to finish in the app.’ Previously, an agent’s main API option was to send a link. The user then had to follow it somewhere else. iMessage Apps remove that handoff. TL;DR Linq̵
Linq has released a new messaging feature called iMessage Apps that allows developers to build interactive mini-applications that run directly within iMessage conversations. These apps render as tappable cards in the message thread and can handle workflows like payments, game moves, ticket bookings, and flight reservations without requiring users to leave the conversation or click external links. The feature works by using a new message part type called imessage_app, which displays interactive content to recipients who have the corresponding Messages extension installed, while showing text-only captions as a fallback for those without the app. This approach trades broader reach, since it only works on iMessage and not on SMS or RCS, in exchange for enabling stateful, in-place updates where a single card can be modified as workflows progress.

WebBrain is a free, open-source browser agent for Chrome and Firefox. It reads pages, extracts data, and automates multi-step tasks. Unlike most browser AI plugins, it can also run entirely on a local model. It is built by Emre Sokullu and licensed under MIT. The full source lives on GitHub. Run the agent against a local model, and no page data leaves your machine. Connect a cloud API when you want more capability. What is WebBrain? WebBrain lives in your browser’s side panel

In this tutorial, we build a RAG-Anything workflow and use it to explore how multimodal retrieval works across text, tables, equations, and images. We start by preparing the Colab environment, installing the required packages, and securely entering our OpenAI API key at runtime to keep the notebook practical and safe to run. We then create a synthetic multimodal report, generate a chart and PDF, convert the content into RAG-Anything’s direct content_list format, and insert it into the retrieval
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