When a prompt enters the system, the tokenizer slices raw text into discrete tokens, calculating immediate memory pressure against your context window limit. During retrieval-augmented generation and tool routing, query embeddings index vector memory, dynamically assembling context before invoking external endpoints. Finally, the inference core samples probabilities under your temperature setting. Higher values widen token sampling dispersion, driving latency and hallucination risk.