mirror of
https://github.com/czlonkowski/n8n-mcp.git
synced 2026-01-31 06:52:04 +00:00
d2a250e23d
Fixed TypeError when generating metadata for templates with missing or invalid nodes_used data. Added safe JSON parsing with fallback to empty array. Root cause: Template -1000 (Canonical AI Tool Examples) has null nodes_used field, causing iteration error in summarizeNodes(). 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
542 lines
17 KiB
JavaScript
542 lines
17 KiB
JavaScript
#!/usr/bin/env node
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import { createDatabaseAdapter } from '../database/database-adapter';
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import { TemplateService } from '../templates/template-service';
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import * as fs from 'fs';
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import * as path from 'path';
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import * as zlib from 'zlib';
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import * as dotenv from 'dotenv';
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import type { MetadataRequest } from '../templates/metadata-generator';
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// Load environment variables
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dotenv.config();
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/**
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* Extract node configurations from a template workflow
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*/
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function extractNodeConfigs(
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templateId: number,
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templateName: string,
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templateViews: number,
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workflowCompressed: string,
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metadata: any
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): Array<{
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node_type: string;
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template_id: number;
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template_name: string;
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template_views: number;
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node_name: string;
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parameters_json: string;
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credentials_json: string | null;
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has_credentials: number;
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has_expressions: number;
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complexity: string;
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use_cases: string;
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}> {
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try {
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// Decompress workflow
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const decompressed = zlib.gunzipSync(Buffer.from(workflowCompressed, 'base64'));
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const workflow = JSON.parse(decompressed.toString('utf-8'));
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const configs: any[] = [];
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for (const node of workflow.nodes || []) {
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// Skip UI-only nodes (sticky notes, etc.)
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if (node.type.includes('stickyNote') || !node.parameters) {
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continue;
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}
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configs.push({
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node_type: node.type,
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template_id: templateId,
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template_name: templateName,
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template_views: templateViews,
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node_name: node.name,
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parameters_json: JSON.stringify(node.parameters),
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credentials_json: node.credentials ? JSON.stringify(node.credentials) : null,
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has_credentials: node.credentials ? 1 : 0,
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has_expressions: detectExpressions(node.parameters) ? 1 : 0,
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complexity: metadata?.complexity || 'medium',
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use_cases: JSON.stringify(metadata?.use_cases || [])
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});
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}
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return configs;
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} catch (error) {
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console.error(`Error extracting configs from template ${templateId}:`, error);
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return [];
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}
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}
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/**
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* Detect n8n expressions in parameters
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*/
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function detectExpressions(params: any): boolean {
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if (!params) return false;
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const json = JSON.stringify(params);
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return json.includes('={{') || json.includes('$json') || json.includes('$node');
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}
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/**
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* Insert extracted configs into database and rank them
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*/
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function insertAndRankConfigs(db: any, configs: any[]) {
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if (configs.length === 0) {
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console.log('No configs to insert');
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return;
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}
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// Clear old configs for these templates
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const templateIds = [...new Set(configs.map(c => c.template_id))];
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const placeholders = templateIds.map(() => '?').join(',');
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db.prepare(`DELETE FROM template_node_configs WHERE template_id IN (${placeholders})`).run(...templateIds);
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// Insert new configs
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const insertStmt = db.prepare(`
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INSERT INTO template_node_configs (
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node_type, template_id, template_name, template_views,
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node_name, parameters_json, credentials_json,
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has_credentials, has_expressions, complexity, use_cases
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) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
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`);
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for (const config of configs) {
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insertStmt.run(
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config.node_type,
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config.template_id,
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config.template_name,
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config.template_views,
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config.node_name,
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config.parameters_json,
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config.credentials_json,
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config.has_credentials,
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config.has_expressions,
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config.complexity,
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config.use_cases
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);
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}
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// Rank configs per node_type by template popularity
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db.exec(`
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UPDATE template_node_configs
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SET rank = (
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SELECT COUNT(*) + 1
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FROM template_node_configs AS t2
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WHERE t2.node_type = template_node_configs.node_type
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AND t2.template_views > template_node_configs.template_views
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)
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`);
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// Keep only top 10 per node_type
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db.exec(`
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DELETE FROM template_node_configs
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WHERE id NOT IN (
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SELECT id FROM template_node_configs
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WHERE rank <= 10
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ORDER BY node_type, rank
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)
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`);
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console.log(`✅ Extracted and ranked ${configs.length} node configurations`);
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}
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/**
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* Extract node configurations from existing templates
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*/
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async function extractTemplateConfigs(db: any, service: TemplateService) {
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console.log('📦 Extracting node configurations from templates...');
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const repository = (service as any).repository;
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const allTemplates = repository.getAllTemplates();
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const allConfigs: any[] = [];
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let configsExtracted = 0;
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for (const template of allTemplates) {
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if (template.workflow_json_compressed) {
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const metadata = template.metadata_json ? JSON.parse(template.metadata_json) : null;
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const configs = extractNodeConfigs(
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template.id,
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template.name,
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template.views,
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template.workflow_json_compressed,
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metadata
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);
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allConfigs.push(...configs);
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configsExtracted += configs.length;
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}
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}
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if (allConfigs.length > 0) {
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insertAndRankConfigs(db, allConfigs);
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// Show stats
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const configStats = db.prepare(`
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SELECT
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COUNT(DISTINCT node_type) as node_types,
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COUNT(*) as total_configs,
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AVG(rank) as avg_rank
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FROM template_node_configs
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`).get() as any;
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console.log(`📊 Node config stats:`);
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console.log(` - Unique node types: ${configStats.node_types}`);
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console.log(` - Total configs stored: ${configStats.total_configs}`);
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console.log(` - Average rank: ${configStats.avg_rank?.toFixed(1) || 'N/A'}`);
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} else {
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console.log('⚠️ No node configurations extracted');
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}
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}
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async function fetchTemplates(
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mode: 'rebuild' | 'update' = 'rebuild',
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generateMetadata: boolean = false,
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metadataOnly: boolean = false,
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extractOnly: boolean = false
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) {
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// If extract-only mode, skip template fetching and only extract configs
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if (extractOnly) {
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console.log('📦 Extract-only mode: Extracting node configurations from existing templates...\n');
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const db = await createDatabaseAdapter('./data/nodes.db');
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// Ensure template_node_configs table exists
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try {
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const tableExists = db.prepare(`
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SELECT name FROM sqlite_master
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WHERE type='table' AND name='template_node_configs'
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`).get();
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if (!tableExists) {
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console.log('📋 Creating template_node_configs table...');
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const migrationPath = path.join(__dirname, '../../src/database/migrations/add-template-node-configs.sql');
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const migration = fs.readFileSync(migrationPath, 'utf8');
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db.exec(migration);
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console.log('✅ Table created successfully\n');
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}
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} catch (error) {
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console.error('❌ Error checking/creating template_node_configs table:', error);
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if ('close' in db && typeof db.close === 'function') {
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db.close();
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}
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process.exit(1);
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}
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const service = new TemplateService(db);
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await extractTemplateConfigs(db, service);
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if ('close' in db && typeof db.close === 'function') {
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db.close();
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}
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return;
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}
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// If metadata-only mode, skip template fetching entirely
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if (metadataOnly) {
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console.log('🤖 Metadata-only mode: Generating metadata for existing templates...\n');
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if (!process.env.OPENAI_API_KEY) {
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console.error('❌ OPENAI_API_KEY not set in environment');
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process.exit(1);
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}
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const db = await createDatabaseAdapter('./data/nodes.db');
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const service = new TemplateService(db);
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await generateTemplateMetadata(db, service);
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if ('close' in db && typeof db.close === 'function') {
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db.close();
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}
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return;
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}
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const modeEmoji = mode === 'rebuild' ? '🔄' : '⬆️';
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const modeText = mode === 'rebuild' ? 'Rebuilding' : 'Updating';
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console.log(`${modeEmoji} ${modeText} n8n workflow templates...\n`);
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if (generateMetadata) {
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console.log('🤖 Metadata generation enabled (using OpenAI)\n');
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}
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// Ensure data directory exists
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const dataDir = './data';
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if (!fs.existsSync(dataDir)) {
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fs.mkdirSync(dataDir, { recursive: true });
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}
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// Initialize database
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const db = await createDatabaseAdapter('./data/nodes.db');
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// Handle database schema based on mode
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if (mode === 'rebuild') {
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try {
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// Drop existing tables in rebuild mode
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db.exec('DROP TABLE IF EXISTS templates');
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db.exec('DROP TABLE IF EXISTS templates_fts');
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console.log('🗑️ Dropped existing templates tables (rebuild mode)\n');
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// Apply fresh schema
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const schema = fs.readFileSync(path.join(__dirname, '../../src/database/schema.sql'), 'utf8');
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db.exec(schema);
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console.log('📋 Applied database schema\n');
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} catch (error) {
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console.error('❌ Error setting up database schema:', error);
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throw error;
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}
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} else {
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console.log('📊 Update mode: Keeping existing templates and schema\n');
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// In update mode, only ensure new columns exist (for migration)
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try {
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// Check if metadata columns exist, add them if not (migration support)
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const columns = db.prepare("PRAGMA table_info(templates)").all() as any[];
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const hasMetadataColumn = columns.some((col: any) => col.name === 'metadata_json');
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if (!hasMetadataColumn) {
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console.log('📋 Adding metadata columns to existing schema...');
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db.exec(`
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ALTER TABLE templates ADD COLUMN metadata_json TEXT;
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ALTER TABLE templates ADD COLUMN metadata_generated_at DATETIME;
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`);
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console.log('✅ Metadata columns added\n');
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}
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} catch (error) {
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// Columns might already exist, that's fine
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console.log('📋 Schema is up to date\n');
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}
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}
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// FTS5 initialization is handled by TemplateRepository
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// No need to duplicate the logic here
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// Create service
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const service = new TemplateService(db);
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// Progress tracking
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let lastMessage = '';
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const startTime = Date.now();
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try {
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await service.fetchAndUpdateTemplates((message, current, total) => {
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// Clear previous line
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if (lastMessage) {
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process.stdout.write('\r' + ' '.repeat(lastMessage.length) + '\r');
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}
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const progress = total > 0 ? Math.round((current / total) * 100) : 0;
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lastMessage = `📊 ${message}: ${current}/${total} (${progress}%)`;
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process.stdout.write(lastMessage);
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}, mode); // Pass the mode parameter!
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console.log('\n'); // New line after progress
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// Get stats
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const stats = await service.getTemplateStats();
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const elapsed = Math.round((Date.now() - startTime) / 1000);
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console.log('✅ Template fetch complete!\n');
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console.log('📈 Statistics:');
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console.log(` - Total templates: ${stats.totalTemplates}`);
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console.log(` - Average views: ${stats.averageViews}`);
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console.log(` - Time elapsed: ${elapsed} seconds`);
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console.log('\n🔝 Top used nodes:');
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stats.topUsedNodes.forEach((node: any, index: number) => {
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console.log(` ${index + 1}. ${node.node} (${node.count} templates)`);
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});
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// Extract node configurations from templates
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console.log('');
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await extractTemplateConfigs(db, service);
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// Generate metadata if requested
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if (generateMetadata && process.env.OPENAI_API_KEY) {
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console.log('\n🤖 Generating metadata for templates...');
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await generateTemplateMetadata(db, service);
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} else if (generateMetadata && !process.env.OPENAI_API_KEY) {
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console.log('\n⚠️ Metadata generation requested but OPENAI_API_KEY not set');
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}
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} catch (error) {
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console.error('\n❌ Error fetching templates:', error);
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process.exit(1);
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}
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// Close database
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if ('close' in db && typeof db.close === 'function') {
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db.close();
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}
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}
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// Generate metadata for templates using OpenAI
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async function generateTemplateMetadata(db: any, service: TemplateService) {
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try {
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const { BatchProcessor } = await import('../templates/batch-processor');
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const repository = (service as any).repository;
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// Get templates without metadata (0 = no limit)
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const limit = parseInt(process.env.METADATA_LIMIT || '0');
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const templatesWithoutMetadata = limit > 0
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? repository.getTemplatesWithoutMetadata(limit)
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: repository.getTemplatesWithoutMetadata(999999); // Get all
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if (templatesWithoutMetadata.length === 0) {
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console.log('✅ All templates already have metadata');
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return;
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}
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console.log(`Found ${templatesWithoutMetadata.length} templates without metadata`);
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// Create batch processor
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const batchSize = parseInt(process.env.OPENAI_BATCH_SIZE || '50');
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console.log(`Processing in batches of ${batchSize} templates each`);
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// Warn if batch size is very large
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if (batchSize > 100) {
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console.log(`⚠️ Large batch size (${batchSize}) may take longer to process`);
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console.log(` Consider using OPENAI_BATCH_SIZE=50 for faster results`);
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}
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const processor = new BatchProcessor({
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apiKey: process.env.OPENAI_API_KEY!,
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model: process.env.OPENAI_MODEL || 'gpt-4o-mini',
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batchSize: batchSize,
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outputDir: './temp/batch'
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});
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// Prepare metadata requests
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const requests: MetadataRequest[] = templatesWithoutMetadata.map((t: any) => {
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let workflow = undefined;
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try {
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if (t.workflow_json_compressed) {
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const decompressed = zlib.gunzipSync(Buffer.from(t.workflow_json_compressed, 'base64'));
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workflow = JSON.parse(decompressed.toString());
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} else if (t.workflow_json) {
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workflow = JSON.parse(t.workflow_json);
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}
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} catch (error) {
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console.warn(`Failed to parse workflow for template ${t.id}:`, error);
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}
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// Parse nodes_used safely
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let nodes: string[] = [];
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try {
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if (t.nodes_used) {
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nodes = JSON.parse(t.nodes_used);
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// Ensure it's an array
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if (!Array.isArray(nodes)) {
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console.warn(`Template ${t.id} has invalid nodes_used (not an array), using empty array`);
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nodes = [];
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}
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}
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} catch (error) {
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console.warn(`Failed to parse nodes_used for template ${t.id}:`, error);
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nodes = [];
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}
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return {
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templateId: t.id,
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name: t.name,
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description: t.description,
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nodes: nodes,
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workflow
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};
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});
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// Process in batches
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const results = await processor.processTemplates(requests, (message, current, total) => {
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process.stdout.write(`\r📊 ${message}: ${current}/${total}`);
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});
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console.log('\n');
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// Update database with metadata
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const metadataMap = new Map();
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for (const [templateId, result] of results) {
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if (!result.error) {
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metadataMap.set(templateId, result.metadata);
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}
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}
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if (metadataMap.size > 0) {
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repository.batchUpdateMetadata(metadataMap);
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console.log(`✅ Updated metadata for ${metadataMap.size} templates`);
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}
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// Show stats
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const stats = repository.getMetadataStats();
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console.log('\n📈 Metadata Statistics:');
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console.log(` - Total templates: ${stats.total}`);
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console.log(` - With metadata: ${stats.withMetadata}`);
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console.log(` - Without metadata: ${stats.withoutMetadata}`);
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console.log(` - Outdated (>30 days): ${stats.outdated}`);
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} catch (error) {
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console.error('\n❌ Error generating metadata:', error);
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}
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}
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// Parse command line arguments
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function parseArgs(): { mode: 'rebuild' | 'update', generateMetadata: boolean, metadataOnly: boolean, extractOnly: boolean } {
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const args = process.argv.slice(2);
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let mode: 'rebuild' | 'update' = 'rebuild';
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let generateMetadata = false;
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let metadataOnly = false;
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let extractOnly = false;
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// Check for --mode flag
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const modeIndex = args.findIndex(arg => arg.startsWith('--mode'));
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if (modeIndex !== -1) {
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const modeArg = args[modeIndex];
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const modeValue = modeArg.includes('=') ? modeArg.split('=')[1] : args[modeIndex + 1];
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if (modeValue === 'update') {
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mode = 'update';
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}
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}
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// Check for --update flag as shorthand
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if (args.includes('--update')) {
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mode = 'update';
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}
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// Check for --generate-metadata flag
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if (args.includes('--generate-metadata') || args.includes('--metadata')) {
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generateMetadata = true;
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}
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// Check for --metadata-only flag
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if (args.includes('--metadata-only')) {
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metadataOnly = true;
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}
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// Check for --extract-only flag
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if (args.includes('--extract-only') || args.includes('--extract')) {
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extractOnly = true;
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}
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// Show help if requested
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if (args.includes('--help') || args.includes('-h')) {
|
||
console.log('Usage: npm run fetch:templates [options]\n');
|
||
console.log('Options:');
|
||
console.log(' --mode=rebuild|update Rebuild from scratch or update existing (default: rebuild)');
|
||
console.log(' --update Shorthand for --mode=update');
|
||
console.log(' --generate-metadata Generate AI metadata after fetching templates');
|
||
console.log(' --metadata Shorthand for --generate-metadata');
|
||
console.log(' --metadata-only Only generate metadata, skip template fetching');
|
||
console.log(' --extract-only Only extract node configs, skip template fetching');
|
||
console.log(' --extract Shorthand for --extract-only');
|
||
console.log(' --help, -h Show this help message');
|
||
process.exit(0);
|
||
}
|
||
|
||
return { mode, generateMetadata, metadataOnly, extractOnly };
|
||
}
|
||
|
||
// Run if called directly
|
||
if (require.main === module) {
|
||
const { mode, generateMetadata, metadataOnly, extractOnly } = parseArgs();
|
||
fetchTemplates(mode, generateMetadata, metadataOnly, extractOnly).catch(console.error);
|
||
}
|
||
|
||
export { fetchTemplates }; |