Ambiance MCP Server

/** * @fileOverview: AI Context Analysis Output Formatters * @module: AISemanticFormatters * @keyFunctions: * - formatAISemanticOutput: Main formatter dispatcher * - formatAsXML: Machine-readable XML format * - formatAsMarkdown: Documentation-ready markdown format * - formatAsStructured: Detailed structured text format * @context: Provides multiple output formats for AI-powered context analysis results */ /** * Format AI context analysis output according to requested format */ export function formatAISemanticOutput(data: any, format: string): string { switch (format) { case 'xml': return formatAsXML(data); case 'markdown': return formatAsMarkdown(data); case 'structured': return formatAsStructured(data); case 'json': default: return JSON.stringify(data, null, 2); } } /** * Format as XML for machine processing */ export function formatAsXML(data: any): string { const escapeXml = (text: string) => text .replace(/&/g, '&amp;') .replace(/</g, '&lt;') .replace(/>/g, '&gt;') .replace(/"/g, '&quot;') .replace(/'/g, '&#39;'); return `<?xml version="1.0" encoding="UTF-8"?> <semantic_analysis> <metadata> <project_path>${escapeXml(data.projectPath)}</project_path> <query>${escapeXml(data.query)}</query> <task_type>${data.taskType}</task_type> <complexity>${data.complexity}</complexity> <processing_time>${data.metadata.processingTime}ms</processing_time> <token_usage> <estimated>${data.metadata.tokenUsage.estimated}</estimated> <ai_response>${data.metadata.tokenUsage.aiResponse}</ai_response> <max_allocated>${data.metadata.tokenUsage.maxAllocated}</max_allocated> </token_usage> </metadata> <local_compaction> <files_analyzed>${data.localCompaction.filesAnalyzed}</files_analyzed> <total_symbols>${data.localCompaction.totalSymbols}</total_symbols> <compression_ratio>${data.localCompaction.compressionRatio}</compression_ratio> <patterns> ${ data.localCompaction.patterns && Array.isArray(data.localCompaction.patterns) ? data.localCompaction.patterns .map((p: string) => `<pattern>${escapeXml(p)}</pattern>`) .join('\n ') : '<pattern>No patterns detected</pattern>' } </patterns> </local_compaction> <ai_analysis> <![CDATA[${data.analysis}]]> </ai_analysis> <context> ${data.context .map( (file: any) => ` <file> <path>${escapeXml(file.path)}</path> <language>${file.language}</language> <purpose>${escapeXml(file.purpose)}</purpose> <symbol_count>${file.symbols.length}</symbol_count> <exports>${file.exports.map((e: string) => `<export>${escapeXml(e)}</export>`).join('')}</exports> </file>` ) .join('')} </context> </semantic_analysis>`; } /** * Format as Markdown for documentation */ export function formatAsMarkdown(data: any): string { const formatDuration = (ms: number) => (ms > 1000 ? `${(ms / 1000).toFixed(1)}s` : `${ms}ms`); return `# 🤖 AI Context Analysis Report ## 📋 Analysis Overview - **Project:** \`${data.projectPath}\` - **Query:** ${data.query} - **Task Type:** ${data.taskType} - **Complexity:** ${data.complexity} - **Processing Time:** ${formatDuration(data.metadata.processingTime)} ## 📊 Compaction Results - **Files Analyzed:** ${data.localCompaction.filesAnalyzed} - **Total Symbols:** ${data.localCompaction.totalSymbols} - **Compression Ratio:** ${Math.round(data.localCompaction.compressionRatio * 100)}% - **Patterns Detected:** ${data.localCompaction.patterns.join(', ')} ## 🔍 AI Analysis ${data.analysis} ## 📁 Analyzed Files ${data.context .map( (file: any) => ` ### \`${file.path}\` - **Language:** ${file.language} - **Purpose:** ${file.purpose} - **Symbols:** ${file.symbols.length} - **Exports:** ${file.exports.join(', ') || 'None'} ` ) .join('')} ## 📈 Performance Metrics - **Token Usage:** - Estimated Context: ${data.metadata.tokenUsage.estimated} - AI Response: ${data.metadata.tokenUsage.aiResponse} - Max Allocated: ${data.metadata.tokenUsage.maxAllocated} - **Provider:** ${data.metadata.provider} (${data.metadata.model}) --- *Generated by AI-Powered Context Analysis*`; } /** * Format as structured text for detailed analysis */ export function formatAsStructured(data: any): string { const formatDuration = (ms: number) => (ms > 1000 ? `${(ms / 1000).toFixed(1)}s` : `${ms}ms`); return `🤖 AI-POWERED CONTEXT ANALYSIS REPORT ===================================== PROJECT INFORMATION ------------------ Path: ${data.projectPath} Query: ${data.query} Task Type: ${data.taskType} Complexity: ${data.complexity} Processing Time: ${formatDuration(data.metadata.processingTime)} COMPACTION STATISTICS -------------------- Files Analyzed: ${data.localCompaction.filesAnalyzed} Total Symbols: ${data.localCompaction.totalSymbols} Compression Ratio: ${Math.round(data.localCompaction.compressionRatio * 100)}% Detected Patterns: ${ data.localCompaction.patterns && Array.isArray(data.localCompaction.patterns) && data.localCompaction.patterns.length > 0 ? data.localCompaction.patterns.map((p: string) => ` • ${p}`).join('\n') : ' • No patterns detected' } AI ANALYSIS ----------- ${data.analysis} ANALYZED FILES -------------- ${data.context .map( (file: any, index: number) => ` ${index + 1}. ${file.path} Language: ${file.language} Purpose: ${file.purpose} Symbols: ${file.symbols && Array.isArray(file.symbols) ? file.symbols.length : 0} Exports: ${file.exports && Array.isArray(file.exports) ? file.exports.join(', ') || 'None' : 'None'} Key Symbols: ${ file.symbols && Array.isArray(file.symbols) && file.symbols.length > 0 ? file.symbols .slice(0, 3) .map((s: any) => ` - ${s.name || s} (${s.type || 'unknown'})`) .join('\n') : ' - No symbols available' } ` ) .join('')} PERFORMANCE METRICS ------------------ Token Usage: Estimated Context: ${data.metadata.tokenUsage.estimated} AI Response: ${data.metadata.tokenUsage.aiResponse} Max Allocated: ${data.metadata.tokenUsage.maxAllocated} Provider: ${data.metadata.provider} (${data.metadata.model}) ===================================== Generated by AI-Powered Context Analysis`; }