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ADK Progress Bridge

A technical implementation pattern for Google ADK (Agent Development Kit) to bring real-time tool execution progress and deep system observability to Vue.js frontends.

❓ The Problem: The "Black Box" Tool

In the standard ADK architecture, tools are treated as atomic "black boxes". Users often experience a "silence gap" during long-running tasks, leading to a loss of trust and clarity.

💡 The Solution: Async Generator Bridge + Health Engine

We transform standard tools into Async Generators. instead of just returning a value, the tool yields intermediate status updates which are streamed to the frontend via SSE or WebSockets.

Furthermore, we've integrated a dedicated Health Engine (health.py) that monitors 670+ system metrics in real-time, injecting them into the progress stream for ultimate visibility.

Key Architectural Pillars

  • Native Python Async Generators: Lightweight, zero-dependency progress tracking.
  • Bi-directional WebSockets: Sub-millisecond sync for task control, cancellation, and interactive input.
  • Health Subsystem: Decoupled metrics collection and broadcasting engine.
  • Absolute Fidelity: Fully verified with 100% test coverage and Pydantic v2 alignment.

🚀 Getting Started

Backend (Python)

  • @progress_tool Decorator: Track your tool's progress.
  • HealthEngine: Deep system observability out of the box.
  • BroadcastMetricsManager: Centralized metrics broadcasting.

Frontend (Vue.js)

  • useAgentStream: Composable for connecting via SSE or WS.
  • Live Dashboard: Reactive state including logs, progress bars, and system health.

📚 Documentation

For detailed protocol specs, see SPEC.md. For scalability and production deployment, see SCALABILITY.md and DEPLOYMENT.md.

🤖 AI Agent Skill

Includes a pre-configured skill at .agent/skills/progress-bridge/SKILL.md.

License

License: MIT

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