/**
 * Interface for model parameters used in AI requests.
 * All parameters are optional except temperature.
 */
export interface ModelParameters {
    /**
     * Controls randomness in generation (0.0 = deterministic, 2.0 = very random).
     * - 0.0-0.3: Factual, focused output
     * - 0.4-0.7: Balanced
     * - 0.8-1.2: Creative, varied
     * Range: 0.0-2.0, Default: 0.8
     */
    temperature: number;
    /**
     * Penalizes token repetition (higher = less repetition).
     * Range: 0.0-2.0, Default: 1.1
     */
    repeatPenalty?: number;
    /**
     * Nucleus sampling threshold - limits token selection to cumulative probability.
     * Range: 0.0-1.0, Default: 0.9
     */
    topP?: number;
    /**
     * Limits token selection to k most likely tokens.
     * Range: 1-100, Default: 40
     */
    topK?: number;
    /**
     * Penalizes tokens proportional to their frequency (reduces overused words).
     * Range: -2.0-2.0, Default: 0.0
     */
    frequencyPenalty?: number;
    /**
     * Penalizes all previously used tokens equally (encourages new concepts).
     * Range: -2.0-2.0, Default: 0.0
     */
    presencePenalty?: number;
    /**
     * Number of previous tokens to consider for repetition penalty.
     * Use -1 to consider entire context window (num_ctx).
     * Range: 0-2048 or -1, Default: 64
     */
    repeatLastN?: number;
    /**
     * Maximum number of tokens to generate in the response.
     * Controls output length.
     * Range: 1+, Default: 128 (model-specific)
     */
    numPredict?: number;
    /**
     * Context window size in tokens.
     * Larger values allow model to reference more previous text.
     * Range: 128-4096+ (model-specific), Default: 2048
     */
    numCtx?: number;
    /**
     * Number of tokens to process in parallel during generation.
     * Higher values = faster but more memory usage.
     * Range: 1-512, Default: 512 (model-specific)
     */
    numBatch?: number;
}
/**
 * Interface for parameter overrides that can be applied to default model parameters.
 * All parameters are optional - only specify what you want to override.
 */
export interface ModelParameterOverrides {
    /** Override the base temperature setting */
    temperatureOverride?: number;
    /** Repeat penalty override */
    repeatPenalty?: number;
    /** Nucleus sampling (top-p) override */
    topP?: number;
    /** Top-k sampling override */
    topK?: number;
    /** Frequency penalty override */
    frequencyPenalty?: number;
    /** Presence penalty override */
    presencePenalty?: number;
    /** Repeat last N tokens override */
    repeatLastN?: number;
    /** Maximum tokens to generate (snake_case for Ollama API compatibility) */
    num_predict?: number;
    /** Context window size (snake_case for Ollama API compatibility) */
    num_ctx?: number;
    /** Batch size for parallel processing (snake_case for Ollama API compatibility) */
    num_batch?: number;
}
/**
 * Interface for model configuration from models.config
 */
export interface ModelConfig {
    temperature?: number;
    maxTokens?: number;
    contextLength?: number;
}
/**
 * Service for managing and validating model parameters for AI requests
 * Handles parameter combination, validation, and conversion to API formats
 */
export declare class ModelParameterManagerService {
    private static readonly DEFAULT_TEMPERATURE;
    /**
     * Get the effective model parameters, combining config defaults and use case overrides
     * @param modelConfig The model configuration from models.config
     * @param overrides Optional overrides from the use case
     * @returns Final model parameters to use
     */
    static getEffectiveParameters(modelConfig: ModelConfig, overrides?: ModelParameterOverrides): ModelParameters;
    /**
     * Validate parameter values are within acceptable ranges
     * @param parameters The parameters to validate
     * @returns Validated parameters with any out-of-range values corrected
     */
    static validateParameters(parameters: ModelParameters): ModelParameters;
    /**
     * Create parameter subset for logging (only non-undefined values)
     * @param parameters The parameters to filter
     * @returns Object with only defined parameters
     */
    static getDefinedParameters(parameters: ModelParameters): Record<string, any>;
    /**
     * Create parameter object for Ollama API request
     * @param parameters The validated parameters
     * @returns Object suitable for the Ollama API options field
     */
    static toOllamaOptions(parameters: ModelParameters): Record<string, any>;
    /**
     * Create default parameters for a given model type or use case
     *
     * Available presets:
     * - 'creative' / 'creative_writing': Optimized for novels, stories, narrative fiction
     * - 'factual': Optimized for reports, documentation, journalism
     * - 'poetic': Optimized for poetry, lyrics, artistic expression
     * - 'dialogue': Optimized for character dialogue, conversational content
     * - 'technical': Optimized for code documentation, technical guides
     * - 'marketing': Optimized for advertisements, promotional content
     * - 'analytical': General analytical tasks (legacy)
     * - 'balanced': General balanced approach (default)
     *
     * @param modelType The type of model or use case
     * @returns Default parameters for the model type
     *
     * For detailed documentation about each preset, see docs/OLLAMA_PARAMETERS.md
     */
    static getDefaultParametersForType(modelType: string): ModelParameters;
    /**
     * Compare two parameter sets and return the differences
     * @param params1 First parameter set
     * @param params2 Second parameter set
     * @returns Object showing differences
     */
    static compareParameters(params1: ModelParameters, params2: ModelParameters): Record<string, {
        from: any;
        to: any;
    }>;
    /**
     * Generate a summary string of the parameters for logging
     * @param parameters The parameters to summarize
     * @returns Human-readable parameter summary
     */
    static summarizeParameters(parameters: ModelParameters): string;
}
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