mcp-adr-analysis-server/dist/src/config/ai-config.d.ts

MCP server for analyzing Architectural Decision Records and project architecture

/**
 * AI Configuration for OpenRouter.ai Integration and CE-MCP
 *
 * This module handles configuration for AI execution capabilities,
 * supporting both legacy OpenRouter execution and the new CE-MCP
 * (Code Execution with MCP) paradigm.
 *
 * @see ADR-014: CE-MCP Architecture
 */
/**
 * Execution mode for AI operations
 *
 * - 'full': Execute prompts via OpenRouter (legacy)
 * - 'prompt-only': Return prompts without execution (legacy)
 * - 'ce-mcp': Return orchestration directives for host LLM (recommended)
 * - 'hybrid': Support both CE-MCP and OpenRouter fallback
 */
export type ExecutionMode = 'full' | 'prompt-only' | 'ce-mcp' | 'hybrid';
export interface AIConfig {
    /** OpenRouter API key for authentication */
    apiKey: string;
    /** Base URL for OpenRouter API */
    baseURL: string;
    /** Default AI model to use for prompt execution */
    defaultModel: string;
    /** Execution mode */
    executionMode: ExecutionMode;
    /** Site URL for OpenRouter rankings (optional) */
    siteUrl?: string;
    /** Site name for OpenRouter rankings (optional) */
    siteName?: string;
    /** Request timeout in milliseconds */
    timeout: number;
    /** Maximum retries for failed requests */
    maxRetries: number;
    /** Temperature for AI responses (0-1) */
    temperature: number;
    /** Maximum tokens for AI responses */
    maxTokens: number;
    /** Enable response caching */
    cacheEnabled: boolean;
    /** Cache TTL in seconds */
    cacheTTL: number;
    /** CE-MCP specific configuration */
    cemcp?: CEMCPSettings;
}
/**
 * CE-MCP specific settings
 */
export interface CEMCPSettings {
    /** Enable sandbox execution */
    sandboxEnabled: boolean;
    /** Sandbox execution timeout in ms */
    sandboxTimeout: number;
    /** Sandbox memory limit in bytes */
    sandboxMemoryLimit: number;
    /** Maximum file system operations */
    sandboxFsLimit: number;
    /** Allow network access in sandbox */
    sandboxNetworkAllowed: boolean;
    /** Enable lazy prompt loading */
    lazyPromptLoading: boolean;
    /** Use OpenRouter as fallback when CE-MCP fails */
    openRouterFallback: boolean;
}
export interface ModelConfig {
    /** Model identifier for OpenRouter */
    id: string;
    /** Human-readable model name */
    name: string;
    /** Model provider (openai, anthropic, etc.) */
    provider: string;
    /** Cost per 1K tokens (input) */
    inputCost: number;
    /** Cost per 1K tokens (output) */
    outputCost: number;
    /** Maximum context length */
    contextLength: number;
    /** Recommended use cases */
    useCases: string[];
}
/**
 * Available AI models for different use cases
 */
export declare const AVAILABLE_MODELS: Record<string, ModelConfig>;
/**
 * Default CE-MCP settings
 */
export declare const DEFAULT_CEMCP_SETTINGS: CEMCPSettings;
/**
 * Default AI configuration
 */
export declare const DEFAULT_AI_CONFIG: Omit<AIConfig, 'siteUrl' | 'siteName'> & {
    siteUrl: string;
    siteName: string;
};
/**
 * Load AI configuration from environment variables
 */
export declare function loadAIConfig(): AIConfig;
/**
 * Validate AI configuration
 */
export declare function validateAIConfig(config: AIConfig): void;
/**
 * Get model configuration by ID
 */
export declare function getModelConfig(modelId: string): ModelConfig | undefined;
/**
 * Check if AI execution is enabled (legacy OpenRouter mode)
 */
export declare function isAIExecutionEnabled(config: AIConfig): boolean;
/**
 * Check if CE-MCP mode is enabled
 */
export declare function isCEMCPEnabled(config: AIConfig): boolean;
/**
 * Check if OpenRouter fallback is available
 */
export declare function isOpenRouterFallbackAvailable(config: AIConfig): boolean;
/**
 * Get the effective execution mode based on configuration and available resources
 */
export declare function getEffectiveExecutionMode(config: AIConfig): ExecutionMode;
/**
 * Get recommended model for a specific use case
 */
export declare function getRecommendedModel(useCase: string, costSensitive?: boolean): string;
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