import { z } from "zod";
/** Shared recipe for the public API, local workbench, and managed executor.
 * Supervised training has no rollout-group, reward, or relative-loss settings.
 */
export declare const SftRecipeSchema: z.ZodObject<{
    schemaVersion: z.ZodLiteral<"openpond.sftRecipe.v1">;
    method: z.ZodLiteral<"sft">;
    parameterization: z.ZodLiteral<"lora">;
    baseModel: z.ZodObject<{
        id: z.ZodString;
        revision: z.ZodString;
        tokenizerRevision: z.ZodString;
        chatTemplateHash: z.ZodString;
    }, z.core.$strip>;
    dataset: z.ZodObject<{
        trainSplit: z.ZodLiteral<"train">;
        validationSplit: z.ZodEnum<{
            frozen_eval: "frozen_eval";
            validation: "validation";
        }>;
        completionOnly: z.ZodBoolean;
        maxSequenceLength: z.ZodNumber;
        maxExamples: z.ZodDefault<z.ZodNumber>;
        selectionStrategy: z.ZodDefault<z.ZodLiteral<"stable_hash_top_n">>;
        selectionSeed: z.ZodDefault<z.ZodNumber>;
    }, z.core.$strip>;
    lora: z.ZodObject<{
        rank: z.ZodNumber;
        alpha: z.ZodNumber;
        dropout: z.ZodNumber;
        targetModules: z.ZodArray<z.ZodString>;
    }, z.core.$strip>;
    optimizer: z.ZodObject<{
        learningRate: z.ZodNumber;
        epochs: z.ZodNumber;
        maxSteps: z.ZodNumber;
        batchSize: z.ZodNumber;
        gradientAccumulationSteps: z.ZodNumber;
        seed: z.ZodNumber;
    }, z.core.$strip>;
    resourceLimits: z.ZodObject<{
        cpuThreads: z.ZodNumber;
        memoryBytes: z.ZodNumber;
        wallTimeMs: z.ZodNumber;
    }, z.core.$strip>;
}, z.core.$strip>;
export type SftRecipe = z.infer<typeof SftRecipeSchema>;
/** The first managed SFT worker has a deliberately bounded execution surface.
 * This is an executable requirement, not an advertised fleet capability.
 */
export declare const ManagedSftRecipeSchema: z.ZodObject<{
    schemaVersion: z.ZodLiteral<"openpond.sftRecipe.v1">;
    method: z.ZodLiteral<"sft">;
    parameterization: z.ZodLiteral<"lora">;
    baseModel: z.ZodObject<{
        id: z.ZodString;
        revision: z.ZodString;
        tokenizerRevision: z.ZodString;
        chatTemplateHash: z.ZodString;
    }, z.core.$strip>;
    dataset: z.ZodObject<{
        trainSplit: z.ZodLiteral<"train">;
        validationSplit: z.ZodEnum<{
            frozen_eval: "frozen_eval";
            validation: "validation";
        }>;
        selectionStrategy: z.ZodDefault<z.ZodLiteral<"stable_hash_top_n">>;
        selectionSeed: z.ZodDefault<z.ZodNumber>;
        completionOnly: z.ZodLiteral<true>;
        maxSequenceLength: z.ZodNumber;
        maxExamples: z.ZodDefault<z.ZodNumber>;
    }, z.core.$strip>;
    lora: z.ZodObject<{
        alpha: z.ZodNumber;
        rank: z.ZodNumber;
        dropout: z.ZodNumber;
        targetModules: z.ZodArray<z.ZodEnum<{
            down_proj: "down_proj";
            gate_proj: "gate_proj";
            k_proj: "k_proj";
            o_proj: "o_proj";
            q_proj: "q_proj";
            up_proj: "up_proj";
            v_proj: "v_proj";
        }>>;
    }, z.core.$strip>;
    optimizer: z.ZodObject<{
        learningRate: z.ZodNumber;
        epochs: z.ZodNumber;
        maxSteps: z.ZodNumber;
        batchSize: z.ZodNumber;
        gradientAccumulationSteps: z.ZodNumber;
        seed: z.ZodNumber;
    }, z.core.$strip>;
    resourceLimits: z.ZodObject<{
        cpuThreads: z.ZodNumber;
        memoryBytes: z.ZodNumber;
        wallTimeMs: z.ZodNumber;
    }, z.core.$strip>;
}, z.core.$strip>;
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