import type { Api, Model as ApiModel } from "./types";
/** User-facing thinking levels, ordered least to most intensive. */
export declare const enum Effort {
    Minimal = "minimal",
    Low = "low",
    Medium = "medium",
    High = "high",
    XHigh = "xhigh",
    Max = "max"
}
export declare const THINKING_EFFORTS: readonly Effort[];
/**
 * Static fallback model injected when Cloudflare AI Gateway discovery
 * returns no results. Ensures the provider always has at least one usable
 * model entry in the catalog.
 */
export declare const CLOUDFLARE_FALLBACK_MODEL: ApiModel<"anthropic-messages">;
/**
 * Returns a copy of the model with canonical thinking metadata attached.
 *
 * This helper belongs to catalog enrichment only. Runtime consumers should
 * trust `model.thinking` and avoid inferring capabilities on demand.
 */
export declare function enrichModelThinking<TApi extends Api>(model: ApiModel<TApi>): ApiModel<TApi>;
/**
 * Returns a copy of the model with thinking metadata recomputed from the
 * canonical rules, replacing any existing `thinking`.
 */
export declare function refreshModelThinking<TApi extends Api>(model: ApiModel<TApi>): ApiModel<TApi>;
/**
 * Extract the GLM generation from a Zhipu/ZAI model id: `glm-5.3` and
 * `glm-5.3-flash` -> 5.3, `glm-5` and `glm-5-turbo` -> 5, `glm-4.7` -> 4.7.
 * Returns undefined for ids that are not a plain GLM generation, including the
 * vision line (`glm-5v-turbo`), so those never inherit text-model corrections.
 */
export declare function glmGeneration(modelId: string): number | undefined;
/**
 * Apply upstream metadata corrections to a mutable array of models.
 *
 * Each model is first normalized through `refreshModelThinking()` so generated
 * catalogs keep canonical thinking metadata and policy fixes in one pass.
 */
export declare function applyGeneratedModelPolicies(models: ApiModel<Api>[]): void;
/**
 * Link OpenAI model variants to their context promotion targets.
 *
 * When a model's context is exhausted, the agent can promote to a sibling
 * model with a larger context window on the same provider:
 * - `OpenAI code backend-spark` variants promote to `gpt-5.5`.
 *
 * `gpt-5.5` itself is a 1M-context model and is not demoted to `gpt-5.4`
 * (which has a smaller window), so it has no promotion target.
 */
export declare function linkOpenAIPromotionTargets(models: ApiModel<Api>[]): void;
/**
 * Returns the supported thinking efforts declared on the model metadata.
 *
 * Catalog enrichment is responsible for normalizing bundled model metadata up front.
 * Runtime callers must treat explicit `model.thinking` on custom models as authoritative
 * so proxy-specific overrides from `models.yml` survive request construction.
 *
 * @throws Error when a reasoning-capable model is missing thinking metadata
 */
export declare function getSupportedEfforts<TApi extends Api>(model: ApiModel<TApi>): readonly Effort[];
/**
 * Clamps a requested thinking level against explicit model metadata.
 *
 * Non-reasoning models always resolve to `undefined`.
 */
export declare function clampThinkingLevelForModel<TApi extends Api>(model: ApiModel<TApi> | undefined, requested: Effort | undefined): Effort | undefined;
export declare function requireSupportedEffort<TApi extends Api>(model: ApiModel<TApi>, effort: Effort): Effort;
/** Maps a normalized thinking effort to Google's `thinkingLevel` enum values. */
export declare function mapEffortToGoogleThinkingLevel<TApi extends Api>(model: ApiModel<TApi>, effort: Effort): "MINIMAL" | "LOW" | "MEDIUM" | "HIGH";
/** Maps a normalized thinking effort to Anthropic adaptive effort values. */
export declare function mapEffortToAnthropicAdaptiveEffort<TApi extends Api>(model: ApiModel<TApi>, effort: Effort): "low" | "medium" | "high" | "xhigh" | "max";
/**
 * Returns true for Anthropic models with Opus 4.7 API restrictions:
 * - Sampling parameters (temperature/top_p/top_k) return 400 error
 * - Thinking content is omitted by default (needs display: "summarized")
 */
export declare function hasOpus47ApiRestrictions(modelId: string): boolean;