Squashed 'vendor/ruvector/' content from commit b64c2172
git-subtree-dir: vendor/ruvector git-subtree-split: b64c21726f2bb37286d9ee36a7869fef60cc6900
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ruv
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/**
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* Entity relationship generator for domain-specific graphs
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*/
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import { OpenRouterClient } from '../openrouter-client.js';
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import {
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EntityRelationshipOptions,
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GraphData,
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GraphNode,
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GraphEdge,
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GraphGenerationResult
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} from '../types.js';
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interface EntityData {
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id: string;
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labels: string[];
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properties: Record<string, unknown>;
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}
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interface RelationshipData {
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source: string;
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target: string;
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type: string;
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properties?: Record<string, unknown>;
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}
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export class EntityRelationshipGenerator {
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constructor(private client: OpenRouterClient) {}
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/**
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* Generate entity-relationship graph
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*/
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async generate(options: EntityRelationshipOptions): Promise<GraphGenerationResult<GraphData>> {
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const startTime = Date.now();
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// Generate entities
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const entities = await this.generateEntities(options);
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// Generate relationships
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const relationships = await this.generateRelationships(entities, options);
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// Convert to graph structure
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const nodes: GraphNode[] = entities.map(entity => ({
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id: entity.id,
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labels: entity.labels || ['Entity'],
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properties: entity.properties
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}));
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const edges: GraphEdge[] = relationships.map((rel, idx) => ({
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id: `rel_${idx}`,
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type: rel.type,
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source: rel.source,
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target: rel.target,
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properties: rel.properties || {}
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}));
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const data: GraphData = {
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nodes,
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edges,
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metadata: {
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domain: options.domain,
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generated_at: new Date(),
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total_nodes: nodes.length,
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total_edges: edges.length
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}
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};
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return {
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data,
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metadata: {
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generated_at: new Date(),
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model: this.client.getConfig().model || 'moonshot/kimi-k2-instruct',
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duration: Date.now() - startTime
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}
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};
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}
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/**
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* Generate domain-specific entities
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*/
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private async generateEntities(options: EntityRelationshipOptions): Promise<EntityData[]> {
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const systemPrompt = `You are an expert in ${options.domain} domain modeling. Generate realistic entities following best practices for ${options.domain} data models.`;
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const schemaInfo = options.entitySchema
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? `\n\nEntity schema to follow:\n${JSON.stringify(options.entitySchema, null, 2)}`
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: '';
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const userPrompt = `Generate ${options.entityCount} diverse entities for a ${options.domain} domain model.${schemaInfo}
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Each entity should have:
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- id: unique identifier (use snake_case)
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- labels: array of entity type labels (e.g., ["Product", "Digital"])
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- properties: object with entity properties (at least 3-5 meaningful properties)
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Make entities realistic and relevant to ${options.domain}. Include variety in types and attributes.
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Return a JSON array of entities.
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Example format:
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\`\`\`json
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[
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{
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"id": "product_laptop_001",
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"labels": ["Product", "Electronics", "Computer"],
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"properties": {
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"name": "UltraBook Pro 15",
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"category": "Laptops",
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"price": 1299.99,
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"brand": "TechCorp",
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"release_date": "2024-01-15",
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"stock": 45,
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"rating": 4.7
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}
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}
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]
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\`\`\``;
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return this.client.generateStructured<EntityData[]>(systemPrompt, userPrompt, {
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temperature: 0.8,
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maxTokens: Math.min(8000, options.entityCount * 150)
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});
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}
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/**
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* Generate relationships between entities
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*/
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private async generateRelationships(
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entities: EntityData[],
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options: EntityRelationshipOptions
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): Promise<RelationshipData[]> {
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// Calculate target relationship count based on density
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const maxPossibleRelationships = entities.length * (entities.length - 1);
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const targetRelationships = Math.floor(maxPossibleRelationships * options.relationshipDensity);
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const relationshipTypes = options.relationshipTypes || [
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'RELATES_TO',
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'PART_OF',
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'DEPENDS_ON',
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'SIMILAR_TO',
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'CONTAINS'
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];
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const systemPrompt = `You are an expert in ${options.domain} domain modeling. Create meaningful, realistic relationships between entities.`;
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const entityList = entities.slice(0, 100).map(e =>
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`- ${e.id} (${e.labels.join(', ')}): ${JSON.stringify(e.properties).substring(0, 100)}`
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).join('\n');
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const userPrompt = `Given these entities from a ${options.domain} domain:
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${entityList}
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Generate ${targetRelationships} meaningful relationships between them.
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Relationship types to use: ${relationshipTypes.join(', ')}
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Each relationship should have:
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- source: source entity id
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- target: target entity id
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- type: relationship type (use UPPER_SNAKE_CASE)
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- properties: optional properties describing the relationship
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Make relationships logical and realistic for ${options.domain}. Avoid creating too many relationships from/to the same entity.
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Return a JSON array of relationships.
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Example format:
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\`\`\`json
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[
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{
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"source": "product_laptop_001",
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"target": "category_electronics",
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"type": "BELONGS_TO",
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"properties": {
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"primary": true,
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"added_date": "2024-01-15"
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}
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}
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]
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\`\`\``;
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return this.client.generateStructured<RelationshipData[]>(systemPrompt, userPrompt, {
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temperature: 0.7,
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maxTokens: Math.min(8000, targetRelationships * 80)
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});
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}
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/**
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* Generate schema-aware entities and relationships
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*/
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async generateWithSchema(
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schema: {
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entities: Record<string, {
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properties: Record<string, string>;
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relationships?: string[];
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}>;
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relationships: Record<string, {
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from: string;
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to: string;
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properties?: Record<string, string>;
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}>;
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},
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count: number
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): Promise<GraphData> {
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const systemPrompt = 'You are an expert at generating synthetic data that conforms to strict schemas.';
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const userPrompt = `Generate ${count} instances of entities and relationships following this exact schema:
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${JSON.stringify(schema, null, 2)}
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Return a JSON object with:
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- nodes: array of entities matching the entity types in the schema
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- edges: array of relationships matching the relationship types in the schema
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Ensure all properties match their specified types and all relationships connect valid entity types.
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Example format:
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\`\`\`json
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{
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"nodes": [...],
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"edges": [...]
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}
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\`\`\``;
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return this.client.generateStructured<GraphData>(
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systemPrompt,
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userPrompt,
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{
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temperature: 0.7,
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maxTokens: Math.min(8000, count * 200)
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}
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);
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}
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/**
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* Analyze entity-relationship patterns
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*/
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async analyzeERPatterns(data: GraphData): Promise<{
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entityTypeDistribution: Record<string, number>;
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relationshipTypeDistribution: Record<string, number>;
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avgRelationshipsPerEntity: number;
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densityScore: number;
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}> {
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const entityTypeDistribution: Record<string, number> = {};
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const relationshipTypeDistribution: Record<string, number> = {};
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const entityDegrees = new Map<string, number>();
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// Count entity types
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for (const node of data.nodes) {
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for (const label of node.labels) {
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entityTypeDistribution[label] = (entityTypeDistribution[label] || 0) + 1;
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}
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}
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// Count relationship types and degrees
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for (const edge of data.edges) {
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relationshipTypeDistribution[edge.type] = (relationshipTypeDistribution[edge.type] || 0) + 1;
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entityDegrees.set(edge.source, (entityDegrees.get(edge.source) || 0) + 1);
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entityDegrees.set(edge.target, (entityDegrees.get(edge.target) || 0) + 1);
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}
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const degrees = Array.from(entityDegrees.values());
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const avgRelationshipsPerEntity = degrees.length > 0
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? degrees.reduce((a, b) => a + b, 0) / degrees.length
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: 0;
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const maxPossibleEdges = data.nodes.length * (data.nodes.length - 1);
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const densityScore = maxPossibleEdges > 0
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? data.edges.length / maxPossibleEdges
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: 0;
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return {
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entityTypeDistribution,
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relationshipTypeDistribution,
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avgRelationshipsPerEntity,
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densityScore
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};
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}
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}
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/**
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* Create an entity relationship generator
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*/
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export function createEntityRelationshipGenerator(client: OpenRouterClient): EntityRelationshipGenerator {
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return new EntityRelationshipGenerator(client);
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}
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