klotz: copilotkit*

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  1. Anmol Baranwal writes a comprehensive guide to AG-UI, an open protocol that standardizes how agents communicate with user-facing applications by replacing custom streaming layers with a unified event stream. The protocol connects agentic backends to frontends across any framework and surface, defining 31 event types grouped into 8 categories covering runs, text, tool calls, reasoning, state, activity, subagents, and custom events. It operates alongside MCP (agent-to-tool) and A2A (agent-to-agent) as the user-facing layer, and its 1.0 specification is stable, backwards compatible, and backed by major tech companies.
    - Google, Microsoft, Amazon, and Oracle have adopted the protocol
    - SDKs for TypeScript, Python, and .NET are generated from a shared JSON Schema, with community SDKs for Go, Ruby, Rust, Dart, Kotlin, Java, and C++
    - Transport-agnostic design supports HTTP SSE, WebSockets, and Protobuf binary format
    - AG-UI 1.0 adds subagent support, multimodal tool results, human-in-the-loop interrupts, and token usage tracking
    - CopilotKit Intelligence uses captured interaction data with Automatic Learning to extract insights and generate Skills that improve agent behavior over time
  2. OpenTag is an open-source, self-hosted alternative to Claude for Slack. It enables users to run AI agents directly within Slack threads that can read conversations, answer queries, execute tools, and render rich, generative UI elements like tables and bar charts. Built on the CopilotKit SDK, it allows for complete ownership of the runtime and model without per-seat pricing or vendor lock-in.

    - Open-source Slack AI agent
    - Generative UI for rich message rendering
    - Human-in-the-loop approval gates
    - Multi-platform support via adapters (Discord, Telegram, WhatsApp)
    - Self-hosted architecture for privacy and control
  3. This article introduces Codebase Navigator, a tool designed to simplify the process of understanding large, unfamiliar GitHub repositories. By pasting a repository URL, users can interact with an AI assistant that provides a live dependency graph built from actual import statements, a code viewer, and a full file tree. Unlike standard AI assistants that often hallucinate file paths, this tool uses real data to visualize connections between files in real time. Built with a modern tech stack including Next.js, CopilotKit, and React Flow, the project can be run entirely for free using local LLMs via Ollama. The author provides a deep dive into the architecture, the technical implementation of the dependency resolution, and how the tool maintains state across multiple UI panels.

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