/**
 * Targeted prewarm — pulls profile.prewarm tiers into VRAM at server startup
 * so the first real Claude call doesn't eat cold-load latency.
 *
 * Behavior is profile policy, not magic:
 *   - dev-rtx5080:        prewarm = ["instant"]
 *   - dev-rtx5080-llama:  prewarm = ["instant"]
 *   - m5-max:             prewarm = []  (cold-load on unified memory is ~free)
 *
 * Each prewarm attempt logs a {kind: "prewarm", ...} NDJSON event with
 * model, success/failure, elapsed_ms, and residency. That keeps benchmarks
 * able to distinguish cold from warm and keeps adoption data clean.
 *
 * Failures are logged but never thrown — server startup must not depend on
 * Ollama being reachable. If the model is missing or Ollama is down, the
 * server still comes up; the user sees the prewarm failure in the log.
 */
import { type Tier } from "./tiers.js";
import type { RunContext } from "./runContext.js";
import type { Logger } from "./observability.js";
/** Per-tier prewarm timeout: max(floor, 2× the tier's runtime timeout). */
declare function prewarmTimeoutForTier(ctx: RunContext, tier: Tier): number;
/** Exported for tests. */
export { prewarmTimeoutForTier };
/** True while a runPrewarm pass is active. Safe to call from anywhere. */
export declare function isPrewarmInProgress(): boolean;
/**
 * If prewarm is still running, emit one `prewarm:in_progress_request` event
 * tagged with the tool name. Callers use this from the tool wrap in
 * createServer so tool code itself doesn't need to know about prewarm.
 * Never throws; log failures are swallowed by the logger itself.
 */
export declare function notePrewarmInProgressRequest(logger: Logger, tool: string): void;
/**
 * Run prewarm for the given tiers. Each tier issues a minimal generate
 * (`prompt: "ok", num_predict: 1`) with `keep_alive: -1` so the model
 * stays resident afterwards.
 *
 * Returns the count of successful prewarms; never throws.
 */
export declare function runPrewarm(ctx: RunContext, tiers: Tier[]): Promise<number>;
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