vibe-coder-mcp/build/tools/context-curator/services/llm-integration.d.ts

Production-ready MCP server with complete agent integration, multi-transport support, and comprehensive development automation tools for AI-assisted workflows.

import { OpenRouterConfig } from '../../../types/workflow.js';
import type { IntentAnalysisResult, PromptRefinementResult, FileDiscoveryResult, RelevanceScoringResult, MetaPromptGenerationResult, ProjectTypeAnalysisResult, LanguageAnalysisResult } from '../types/llm-tasks.js';
export declare class ContextCuratorLLMService {
    private static instance;
    private configLoader;
    private constructor();
    static getInstance(): ContextCuratorLLMService;
    private performResilientLlmCall;
    private isRetryableNetworkError;
    private categorizeNetworkError;
    private getSuggestedAction;
    performIntentAnalysis(userPrompt: string, codemapContent: string, config: OpenRouterConfig, additionalContext?: {
        projectType?: string;
        projectAnalysis?: ProjectTypeAnalysisResult;
        languageAnalysis?: LanguageAnalysisResult;
        existingPatterns?: string[];
        patternConfidence?: {
            [pattern: string]: number;
        };
        patternEvidence?: {
            [pattern: string]: string[];
        };
        technicalConstraints?: string[];
    }): Promise<IntentAnalysisResult>;
    performPromptRefinement(originalPrompt: string, intentAnalysis: IntentAnalysisResult, codemapContent: string, config: OpenRouterConfig, additionalContext?: {
        projectAnalysis?: ProjectTypeAnalysisResult;
        languageAnalysis?: LanguageAnalysisResult;
        existingPatterns?: string[];
        patternConfidence?: {
            [pattern: string]: number;
        };
        patternEvidence?: {
            [pattern: string]: string[];
        };
        technicalConstraints?: string[];
        qualityRequirements?: string[];
        timelineConstraints?: string;
        teamExpertise?: string[];
    }): Promise<PromptRefinementResult>;
    performFileDiscovery(originalPrompt: string, intentAnalysis: IntentAnalysisResult, codemapContent: string, config: OpenRouterConfig, searchStrategy?: 'semantic_similarity' | 'keyword_matching' | 'semantic_and_keyword' | 'structural_analysis', additionalContext?: {
        filePatterns?: string[];
        excludePatterns?: string[];
        focusDirectories?: string[];
        maxFiles?: number;
        tokenBudget?: number;
    }): Promise<FileDiscoveryResult>;
    private fixAbstractFileNames;
    private findBestFilePathMatch;
    private retryRelevanceScoring;
    private processFilesInChunks;
    performRelevanceScoring(originalPrompt: string, intentAnalysis: IntentAnalysisResult, refinedPrompt: string, fileDiscoveryResult: FileDiscoveryResult, config: OpenRouterConfig, scoringStrategy?: 'semantic_similarity' | 'keyword_density' | 'structural_importance' | 'hybrid', additionalContext?: {
        codemapContent?: string;
        projectAnalysis?: ProjectTypeAnalysisResult;
        languageAnalysis?: LanguageAnalysisResult;
        architecturalPatterns?: Record<string, unknown>;
        priorityWeights?: {
            semantic: number;
            keyword: number;
            structural: number;
        };
        categoryFilters?: string[];
        minRelevanceThreshold?: number;
    }, externalTaskId?: string): Promise<RelevanceScoringResult>;
    performMetaPromptGeneration(originalPrompt: string, intentAnalysis: IntentAnalysisResult, refinedPrompt: string, relevanceScoringResult: RelevanceScoringResult, config: OpenRouterConfig, additionalContext?: {
        codemapContent?: string;
        projectAnalysis?: ProjectTypeAnalysisResult;
        languageAnalysis?: LanguageAnalysisResult;
        architecturalPatterns?: string[];
        patternConfidence?: {
            [pattern: string]: number;
        };
        patternEvidence?: {
            [pattern: string]: string[];
        };
        technicalConstraints?: string[];
        qualityRequirements?: string[];
        teamExpertise?: string[];
        timelineConstraints?: string;
        existingGuidelines?: string[];
    }): Promise<MetaPromptGenerationResult>;
    private calculateSimpleFallbackScore;
    private extractCategoriesFromPath;
}
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