csvlod-ai-mcp-server
Version:
CSVLOD-AI MCP Server v3.0 with Quantum Context Intelligence - Revolutionary Context Intelligence Engine and Multimodal Processor for sovereign AI development
440 lines • 18.1 kB
JavaScript
/**
* CSVLOD-AI Framework v3.0 - Context Intelligence Engine
* Revolutionary dynamic context system with semantic understanding
*/
import * as fs from 'fs';
import * as path from 'path';
export var ContextType;
(function (ContextType) {
ContextType["PRINCIPLE"] = "principle";
ContextType["STANDARD"] = "standard";
ContextType["VISION"] = "vision";
ContextType["LANDSCAPE"] = "landscape";
ContextType["INITIATIVE"] = "initiative";
ContextType["DESIGN"] = "design";
ContextType["PATTERN"] = "pattern";
ContextType["DECISION"] = "decision";
})(ContextType || (ContextType = {}));
export var RelationshipType;
(function (RelationshipType) {
RelationshipType["DEPENDS_ON"] = "depends_on";
RelationshipType["IMPLEMENTS"] = "implements";
RelationshipType["REFERENCES"] = "references";
RelationshipType["CONFLICTS_WITH"] = "conflicts_with";
RelationshipType["ENHANCES"] = "enhances";
RelationshipType["SUPERSEDES"] = "supersedes";
RelationshipType["DERIVED_FROM"] = "derived_from";
})(RelationshipType || (RelationshipType = {}));
/**
* Context Intelligence Engine - Core implementation
*/
export class ContextIntelligenceEngine {
constructor(projectRoot) {
this.projectRoot = projectRoot;
this.v3ConfigPath = path.join(projectRoot, '.context-v3');
this.cache = new Map();
this.performanceMetrics = {
contextLoadTime: [],
queryResponseTime: [],
cacheHitRatio: 0,
totalQueries: 0
};
this.graph = {
nodes: new Map(),
relationships: new Map(),
semanticIndex: new Map(),
versionHistory: []
};
this.initializeEngine();
}
/**
* Initialize the Context Intelligence Engine
*/
async initializeEngine() {
try {
// Load existing context graph
await this.loadContextGraph();
// Migrate v2.x context files if needed
if (this.graph.nodes.size === 0) {
await this.migrateV2Context();
}
// Build semantic index
await this.buildSemanticIndex();
console.log(`🧠 Context Intelligence Engine v3.0 initialized`);
console.log(`📊 Loaded ${this.graph.nodes.size} context nodes`);
console.log(`🔗 Mapped ${Array.from(this.graph.relationships.values()).reduce((a, b) => a + b.length, 0)} relationships`);
}
catch (error) {
console.error('Failed to initialize Context Intelligence Engine:', error);
}
}
/**
* Load context graph from v3.0 structure
*/
async loadContextGraph() {
const graphPath = path.join(this.v3ConfigPath, 'context-graph.json');
if (fs.existsSync(graphPath)) {
const graphData = JSON.parse(fs.readFileSync(graphPath, 'utf8'));
// Reconstruct Map objects from JSON
this.graph.nodes = new Map(graphData.nodes || []);
this.graph.relationships = new Map(graphData.relationships || []);
this.graph.semanticIndex = new Map(graphData.semanticIndex || []);
this.graph.versionHistory = graphData.versionHistory || [];
}
}
/**
* Migrate v2.x context files to v3.0 graph structure
*/
async migrateV2Context() {
const v2ContextPath = path.join(this.projectRoot, '.context');
const categories = ['principles', 'standards', 'vision', 'landscape', 'initiatives', 'designs'];
for (const category of categories) {
const categoryPath = path.join(v2ContextPath, category);
if (fs.existsSync(categoryPath)) {
const files = fs.readdirSync(categoryPath).filter(f => f.endsWith('.md'));
for (const file of files) {
const filePath = path.join(categoryPath, file);
const content = fs.readFileSync(filePath, 'utf8');
const node = {
id: `context_${category}_${path.parse(file).name}`,
type: category,
content: content,
metadata: {
category: category,
lastUpdated: new Date(),
version: '3.0.0',
tags: [],
autoUpdateEnabled: true
},
relationships: [],
embeddings: [],
lastAccessed: new Date(),
usageFrequency: 0,
effectivenessScore: 0.0
};
this.graph.nodes.set(node.id, node);
}
}
}
// Save updated graph
await this.saveContextGraph();
}
/**
* Build semantic index for fast context retrieval
*/
async buildSemanticIndex() {
const startTime = Date.now();
for (const [nodeId, node] of this.graph.nodes) {
// Extract keywords and concepts from content
const keywords = this.extractKeywords(node.content);
const concepts = this.extractConcepts(node.content);
// Build reverse index
for (const keyword of [...keywords, ...concepts]) {
if (!this.graph.semanticIndex.has(keyword)) {
this.graph.semanticIndex.set(keyword, []);
}
this.graph.semanticIndex.get(keyword).push(nodeId);
}
}
const buildTime = Date.now() - startTime;
console.log(`🔍 Semantic index built in ${buildTime}ms`);
}
/**
* Query context using dynamic intelligence
*/
async query(request) {
const startTime = Date.now();
try {
// Predict required context
const prediction = await this.predictRequiredContext(request);
// Optimize context loading strategy
const strategy = this.optimizeContextLoading(request.query);
// Load context nodes based on strategy
const nodes = await this.loadContextNodes(strategy);
// Find relationships
const relationships = this.findRelevantRelationships(nodes);
// Calculate confidence and generate reasoning
const confidence = this.calculateConfidence(nodes, request);
const reasoning = this.generateReasoning(nodes, relationships, request);
// Update usage metrics
this.updateUsageMetrics(nodes, startTime);
const response = {
nodes: nodes,
relationships: relationships,
confidence: confidence,
reasoning: reasoning,
suggestions: this.generateSuggestions(nodes),
loadTime: Date.now() - startTime
};
return response;
}
catch (error) {
console.error('Context query failed:', error);
throw error;
}
}
/**
* Predict required context for a task
*/
async predictRequiredContext(request) {
// Analyze query intent and domain
const keywords = this.extractKeywords(request.query);
const domain = this.identifyDomain(request.query);
// Find relevant nodes using semantic index
const candidateNodes = [];
for (const keyword of keywords) {
const nodes = this.graph.semanticIndex.get(keyword) || [];
candidateNodes.push(...nodes);
}
// Remove duplicates and score by relevance
const uniqueNodes = [...new Set(candidateNodes)];
const scoredNodes = uniqueNodes.map(nodeId => ({
id: nodeId,
score: this.calculateRelevanceScore(nodeId, keywords, domain)
})).sort((a, b) => b.score - a.score);
// Select top nodes based on confidence threshold
const selectedNodes = scoredNodes
.filter(n => n.score > 0.3)
.slice(0, 10)
.map(n => n.id);
return {
requiredNodes: selectedNodes,
confidence: scoredNodes.length > 0 ? scoredNodes[0].score : 0,
reasoning: `Selected ${selectedNodes.length} nodes based on semantic analysis`,
alternatives: [selectedNodes.slice(0, 5), selectedNodes.slice(5, 10)],
estimatedLoadTime: selectedNodes.length * 10 // 10ms per node estimate
};
}
/**
* Optimize context loading strategy
*/
optimizeContextLoading(query) {
const prediction = this.predictRequiredContext({ query, maxResults: 10 });
// Categorize nodes by priority
const priority1 = []; // Core context
const priority2 = []; // Supporting context
const priority3 = []; // Extended context
// Logic to categorize based on query analysis
// This is a simplified implementation
for (const nodeId of this.graph.nodes.keys()) {
const node = this.graph.nodes.get(nodeId);
if (node.type === ContextType.PRINCIPLE || node.type === ContextType.STANDARD) {
priority1.push(nodeId);
}
else if (node.type === ContextType.VISION || node.type === ContextType.LANDSCAPE) {
priority2.push(nodeId);
}
else {
priority3.push(nodeId);
}
}
return {
priority1: priority1.slice(0, 5),
priority2: priority2.slice(0, 10),
priority3: priority3.slice(0, 15),
totalLoadTime: (priority1.length * 5) + (priority2.length * 10) + (priority3.length * 15),
memoryFootprint: (priority1.length + priority2.length + priority3.length) * 1024 // 1KB per node estimate
};
}
/**
* Load context nodes based on strategy
*/
async loadContextNodes(strategy) {
const startTime = Date.now();
const nodes = [];
// Load priority 1 nodes immediately
for (const nodeId of strategy.priority1) {
const node = this.graph.nodes.get(nodeId);
if (node) {
node.lastAccessed = new Date();
node.usageFrequency++;
nodes.push(node);
}
}
// Background load priority 2 nodes
for (const nodeId of strategy.priority2) {
const node = this.graph.nodes.get(nodeId);
if (node) {
node.lastAccessed = new Date();
nodes.push(node);
}
}
const loadTime = Date.now() - startTime;
this.performanceMetrics.contextLoadTime.push(loadTime);
return nodes;
}
/**
* Find relevant relationships between nodes
*/
findRelevantRelationships(nodes) {
const relationships = [];
const nodeIds = new Set(nodes.map(n => n.id));
for (const nodeId of nodeIds) {
const nodeRelationships = this.graph.relationships.get(nodeId) || [];
for (const rel of nodeRelationships) {
if (nodeIds.has(rel.target)) {
relationships.push(rel);
}
}
}
return relationships;
}
/**
* Calculate confidence score for context response
*/
calculateConfidence(nodes, request) {
if (nodes.length === 0)
return 0;
const keywords = this.extractKeywords(request.query);
let totalScore = 0;
for (const node of nodes) {
const nodeKeywords = this.extractKeywords(node.content);
const overlap = keywords.filter(k => nodeKeywords.includes(k)).length;
const score = overlap / Math.max(keywords.length, nodeKeywords.length);
totalScore += score;
}
return Math.min(totalScore / nodes.length, 1.0);
}
/**
* Generate reasoning for context selection
*/
generateReasoning(nodes, relationships, request) {
const nodeTypes = [...new Set(nodes.map(n => n.type))];
const relationshipTypes = [...new Set(relationships.map(r => r.type))];
return `Selected ${nodes.length} context nodes spanning ${nodeTypes.join(', ')} with ${relationships.length} relationships (${relationshipTypes.join(', ')}) based on semantic analysis of query: "${request.query}"`;
}
/**
* Generate suggestions for context improvement
*/
generateSuggestions(nodes) {
const suggestions = [];
if (nodes.length < 3) {
suggestions.push("Consider adding more specific context for better results");
}
const types = new Set(nodes.map(n => n.type));
if (!types.has(ContextType.PRINCIPLE)) {
suggestions.push("Include framework principles for better guidance");
}
if (!types.has(ContextType.STANDARD)) {
suggestions.push("Add technical standards for implementation consistency");
}
return suggestions;
}
/**
* Update usage metrics for performance monitoring
*/
updateUsageMetrics(nodes, startTime) {
const queryTime = Date.now() - startTime;
this.performanceMetrics.queryResponseTime.push(queryTime);
this.performanceMetrics.totalQueries++;
// Update effectiveness scores for nodes
for (const node of nodes) {
node.effectivenessScore = (node.effectivenessScore + 0.1) / 1.1; // Simple running average
}
}
/**
* Save context graph to persistent storage
*/
async saveContextGraph() {
const graphPath = path.join(this.v3ConfigPath, 'context-graph.json');
const graphData = {
graph_version: "3.0.0",
created_at: new Date().toISOString(),
nodes: Array.from(this.graph.nodes.entries()),
relationships: Array.from(this.graph.relationships.entries()),
semantic_index: Array.from(this.graph.semanticIndex.entries()),
metadata: {
migration_source: "v2.x static files",
total_nodes: this.graph.nodes.size,
total_relationships: Array.from(this.graph.relationships.values()).reduce((a, b) => a + b.length, 0)
}
};
fs.writeFileSync(graphPath, JSON.stringify(graphData, null, 2));
}
/**
* Extract keywords from text content
*/
extractKeywords(content) {
// Simple keyword extraction - in production would use NLP
const words = content
.toLowerCase()
.replace(/[^\w\s]/g, ' ')
.split(/\s+/)
.filter(word => word.length > 3)
.filter(word => !['that', 'this', 'with', 'from', 'they', 'will', 'have', 'more'].includes(word));
// Return unique keywords
return [...new Set(words)];
}
/**
* Extract concepts from text content
*/
extractConcepts(content) {
// Simple concept extraction - in production would use more sophisticated NLP
const concepts = [];
// Look for common technical concepts
const patterns = [
/\b(framework|architecture|pattern|design|principle|standard)\b/gi,
/\b(api|database|security|performance|testing)\b/gi,
/\b(agent|ai|ml|intelligence|automation)\b/gi
];
for (const pattern of patterns) {
const matches = content.match(pattern) || [];
concepts.push(...matches.map(m => m.toLowerCase()));
}
return [...new Set(concepts)];
}
/**
* Identify domain from query
*/
identifyDomain(query) {
const domains = {
'technical': ['code', 'api', 'database', 'security', 'performance'],
'architecture': ['design', 'pattern', 'structure', 'system'],
'ai': ['agent', 'intelligence', 'ml', 'automation'],
'business': ['requirement', 'process', 'workflow', 'user']
};
const queryLower = query.toLowerCase();
for (const [domain, keywords] of Object.entries(domains)) {
if (keywords.some(keyword => queryLower.includes(keyword))) {
return domain;
}
}
return 'general';
}
/**
* Calculate relevance score for a node
*/
calculateRelevanceScore(nodeId, keywords, domain) {
const node = this.graph.nodes.get(nodeId);
if (!node)
return 0;
const nodeKeywords = this.extractKeywords(node.content);
const overlap = keywords.filter(k => nodeKeywords.includes(k)).length;
const keywordScore = overlap / Math.max(keywords.length, 1);
// Boost score for domain relevance
const domainBoost = this.identifyDomain(node.content) === domain ? 0.2 : 0;
// Boost score for usage frequency and effectiveness
const usageBoost = Math.min(node.usageFrequency / 100, 0.1);
const effectivenessBoost = node.effectivenessScore * 0.1;
return Math.min(keywordScore + domainBoost + usageBoost + effectivenessBoost, 1.0);
}
/**
* Get performance metrics
*/
getPerformanceMetrics() {
const avgLoadTime = this.performanceMetrics.contextLoadTime.length > 0
? this.performanceMetrics.contextLoadTime.reduce((a, b) => a + b) / this.performanceMetrics.contextLoadTime.length
: 0;
const avgQueryTime = this.performanceMetrics.queryResponseTime.length > 0
? this.performanceMetrics.queryResponseTime.reduce((a, b) => a + b) / this.performanceMetrics.queryResponseTime.length
: 0;
return {
contextLoadTime: [avgLoadTime],
queryResponseTime: [avgQueryTime],
cacheHitRatio: this.performanceMetrics.cacheHitRatio,
totalQueries: this.performanceMetrics.totalQueries
};
}
}
export default ContextIntelligenceEngine;
//# sourceMappingURL=context-intelligence-engine.js.map