mirror of
https://github.com/czlonkowski/n8n-mcp.git
synced 2026-02-06 21:43:07 +00:00
feat: add template metadata generation and smart discovery
- Implement OpenAI batch API integration for metadata generation - Add search_templates_by_metadata tool with advanced filtering - Enhance list_templates to include descriptions and optional metadata - Generate metadata for 2,534 templates (97.5% coverage) - Update README with Template Tools section and enhanced Claude setup - Add comprehensive documentation for metadata system Enables intelligent template discovery through: - Complexity levels (simple/medium/complex) - Setup time estimates (5-480 minutes) - Target audience filtering (developers/marketers/analysts) - Required services detection - Category and use case classification Co-Authored-By: Claude <noreply@anthropic.com>
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czlonkowski
@@ -3,13 +3,34 @@ 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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async function fetchTemplates(mode: 'rebuild' | 'update' = 'rebuild', generateMetadata: boolean = false) {
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async function fetchTemplates(mode: 'rebuild' | 'update' = 'rebuild', generateMetadata: boolean = false, metadataOnly: boolean = false) {
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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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@@ -27,66 +48,48 @@ async function fetchTemplates(mode: 'rebuild' | 'update' = 'rebuild', generateMe
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// Initialize database
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const db = await createDatabaseAdapter('./data/nodes.db');
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// Only drop tables in rebuild mode
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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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// Ignore errors if tables don't exist
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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\n');
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}
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// Apply schema with updated constraint
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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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// Pre-create FTS5 tables if supported
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const hasFTS5 = db.checkFTS5Support();
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if (hasFTS5) {
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console.log('🔍 Creating FTS5 tables for template search...');
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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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// Create FTS5 virtual table
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db.exec(`
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CREATE VIRTUAL TABLE IF NOT EXISTS templates_fts USING fts5(
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name, description, content=templates
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);
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`);
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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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// Create triggers to keep FTS5 in sync
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db.exec(`
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CREATE TRIGGER IF NOT EXISTS templates_ai AFTER INSERT ON templates BEGIN
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INSERT INTO templates_fts(rowid, name, description)
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VALUES (new.id, new.name, new.description);
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END;
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`);
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db.exec(`
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CREATE TRIGGER IF NOT EXISTS templates_au AFTER UPDATE ON templates BEGIN
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UPDATE templates_fts SET name = new.name, description = new.description
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WHERE rowid = new.id;
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END;
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`);
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db.exec(`
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CREATE TRIGGER IF NOT EXISTS templates_ad AFTER DELETE ON templates BEGIN
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DELETE FROM templates_fts WHERE rowid = old.id;
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END;
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`);
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console.log('✅ FTS5 tables created successfully\n');
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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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console.log('⚠️ Failed to create FTS5 tables:', error);
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console.log(' Template search will use LIKE fallback\n');
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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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} else {
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console.log('ℹ️ FTS5 not supported in this SQLite build');
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console.log(' Template search will use LIKE queries\n');
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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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@@ -104,7 +107,7 @@ async function fetchTemplates(mode: 'rebuild' | 'update' = 'rebuild', generateMe
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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);
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}, mode); // Pass the mode parameter!
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console.log('\n'); // New line after progress
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@@ -148,8 +151,11 @@ async function generateTemplateMetadata(db: any, service: TemplateService) {
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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
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const templatesWithoutMetadata = repository.getTemplatesWithoutMetadata(500);
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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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@@ -159,23 +165,44 @@ async function generateTemplateMetadata(db: any, service: TemplateService) {
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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: parseInt(process.env.OPENAI_BATCH_SIZE || '100'),
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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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templateId: t.id,
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name: t.name,
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description: t.description,
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nodes: JSON.parse(t.nodes_used),
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workflow: t.workflow_json_compressed
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? JSON.parse(Buffer.from(t.workflow_json_compressed, 'base64').toString())
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: (t.workflow_json ? JSON.parse(t.workflow_json) : undefined)
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}));
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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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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: JSON.parse(t.nodes_used),
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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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@@ -210,11 +237,12 @@ async function generateTemplateMetadata(db: any, service: TemplateService) {
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}
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// Parse command line arguments
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function parseArgs(): { mode: 'rebuild' | 'update', generateMetadata: boolean } {
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function parseArgs(): { mode: 'rebuild' | 'update', generateMetadata: boolean, metadataOnly: 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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// Check for --mode flag
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const modeIndex = args.findIndex(arg => arg.startsWith('--mode'));
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@@ -237,25 +265,31 @@ function parseArgs(): { mode: 'rebuild' | 'update', generateMetadata: boolean }
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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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// Show help if requested
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if (args.includes('--help') || args.includes('-h')) {
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console.log('Usage: npm run fetch:templates [options]\n');
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console.log('Options:');
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console.log(' --mode=rebuild|update Rebuild from scratch or update existing (default: rebuild)');
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console.log(' --update Shorthand for --mode=update');
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console.log(' --generate-metadata Generate AI metadata for templates (requires OPENAI_API_KEY)');
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console.log(' --generate-metadata Generate AI metadata after fetching templates');
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console.log(' --metadata Shorthand for --generate-metadata');
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console.log(' --metadata-only Only generate metadata, skip template fetching');
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console.log(' --help, -h Show this help message');
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process.exit(0);
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}
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return { mode, generateMetadata };
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return { mode, generateMetadata, metadataOnly };
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}
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// Run if called directly
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if (require.main === module) {
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const { mode, generateMetadata } = parseArgs();
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fetchTemplates(mode, generateMetadata).catch(console.error);
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const { mode, generateMetadata, metadataOnly } = parseArgs();
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fetchTemplates(mode, generateMetadata, metadataOnly).catch(console.error);
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}
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export { fetchTemplates };
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