Streaming Real-Time AI Telemetry with Firebase Genkit and Angular Signals

Short summary

This tutorial demonstrates how to build a real-time streaming AI pipeline using Firebase Genkit and Angular Signals, replacing generic loading spinners with live progress updates. The backend chains multiple Gemini model calls through Genkit's onCallGenkit wrapper, pushing status checkpoints directly to the client over an open HTTP connection. The Angular service consumes these chunks via async iteration, updating read-only Signals that drive a declarative UI—no database polling required.

• •Chain multiple Gemini calls in Firebase Genkit with streaming callbacks for live status updates
• •Angular service uses async iteration over callable function streams to update read-only Signals
• •Avoids database round-trips by streaming telemetry directly from serverless memory to the client

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