RAG track

Challenges r1–r2. Retrieval-Augmented Generation: embed your data, rank it against the query, and feed the model the closest matches (r1), then chunk long documents so a specific question matches a specific passage (r2). Builds on Foundations. Needs a local embedding model: ollama pull embeddinggemma.