AI RADIO JOCKEY FOR BLR NOW
DA3: AI Radio Jockey — 3-Container Architecture Name of the DA3: AI Radio Jockey (AI-RJ) — DA3 BY: Kaustubh Introduction This DA (Design Assignment) implements an automated AI Radio Jockey pipeline running in three containers: a News Fetcher + Gemini script generator, an Audio Mixer (TTS + mixer), and an Icecast streaming server. The system continuously pulls news from Firestore, converts it into conversational RJ-style scripts using the Gemini API, synthesizes voice and mixes it with music beds/jingles, and streams the final audio via Icecast. Objectives Objectives of Part 1 — News Fetcher & Script Generator Continuously fetch latest news items from Firestore. Normalize and filter news by category and recency. Send news text to the Gemini API (or other LLM) to generate RJ-style voice scripts, transitions, and metadata (segment id, estimated length, tone). Save results to a shared location (shared volume, HTTP endpoint, or message queue) for the Mixer to pick up...