mirror of
https://github.com/Zie619/n8n-workflows.git
synced 2025-11-25 19:37:52 +08:00
refactor: merge categorization scripts
Merge the logic from categorize_workflows.py into create_categories.py to simplify the categorization process. The categorize_workflows.py script is now deleted.
This commit is contained in:
Praveen Mudalgeri
@@ -1,216 +0,0 @@
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#!/usr/bin/env python3
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"""
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Script to categorize uncategorized n8n workflows based on filename patterns.
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This will help reduce the count of uncategorized workflows.
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"""
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import json
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from collections import defaultdict
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def load_categories():
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"""Load the search categories file."""
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with open('context/search_categories.json', 'r', encoding='utf-8') as f:
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return json.load(f)
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def load_unique_categories():
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"""Load the unique categories list."""
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with open('context/unique_categories.json', 'r', encoding='utf-8') as f:
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return json.load(f)
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def categorize_by_filename(filename):
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"""
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Categorize workflow based on filename patterns.
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Returns the most likely category or None if uncertain.
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"""
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filename_lower = filename.lower()
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# Security & Authentication
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if any(word in filename_lower for word in ['totp', 'bitwarden', 'auth', 'security']):
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return "Technical Infrastructure & DevOps"
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# Data Processing & File Operations
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if any(word in filename_lower for word in ['process', 'writebinaryfile', 'readbinaryfile', 'extractfromfile', 'converttofile']):
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return "Data Processing & Analysis"
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# Utility & Business Process Automation
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if any(word in filename_lower for word in ['noop', 'code', 'schedule', 'filter', 'splitout', 'wait', 'limit', 'aggregate']):
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return "Business Process Automation"
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# Webhook & API related
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if any(word in filename_lower for word in ['webhook', 'respondtowebhook', 'http']):
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return "Web Scraping & Data Extraction"
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# Form & Data Collection
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if any(word in filename_lower for word in ['form', 'typeform', 'jotform']):
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return "Data Processing & Analysis"
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# Local file operations
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if any(word in filename_lower for word in ['localfile', 'filemaker']):
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return "Cloud Storage & File Management"
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# Database operations
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if any(word in filename_lower for word in ['postgres', 'mysql', 'mongodb', 'redis', 'elasticsearch', 'snowflake']):
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return "Data Processing & Analysis"
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# AI & Machine Learning
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if any(word in filename_lower for word in ['openai', 'awstextract', 'awsrekognition', 'humanticai', 'openthesaurus']):
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return "AI Agent Development"
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# E-commerce specific
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if any(word in filename_lower for word in ['woocommerce', 'gumroad']):
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return "E-commerce & Retail"
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# Social media specific
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if any(word in filename_lower for word in ['facebook', 'linkedin', 'instagram']):
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return "Social Media Management"
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# Customer support
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if any(word in filename_lower for word in ['zendesk', 'intercom', 'drift', 'pagerduty']):
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return "Communication & Messaging"
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# Analytics & Tracking
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if any(word in filename_lower for word in ['googleanalytics', 'segment', 'mixpanel']):
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return "Data Processing & Analysis"
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# Development tools
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if any(word in filename_lower for word in ['git', 'github', 'gitlab', 'travisci', 'jenkins']):
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return "Technical Infrastructure & DevOps"
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# CRM & Sales tools
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if any(word in filename_lower for word in ['pipedrive', 'hubspot', 'salesforce', 'copper', 'orbit']):
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return "CRM & Sales"
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# Marketing tools
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if any(word in filename_lower for word in ['mailchimp', 'convertkit', 'sendgrid', 'mailerlite', 'lemlist']):
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return "Marketing & Advertising Automation"
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# Project management
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if any(word in filename_lower for word in ['asana', 'mondaycom', 'clickup', 'trello', 'notion']):
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return "Project Management"
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# Communication
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if any(word in filename_lower for word in ['slack', 'telegram', 'discord', 'mattermost', 'twilio']):
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return "Communication & Messaging"
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# Cloud storage
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if any(word in filename_lower for word in ['dropbox', 'googledrive', 'onedrive', 'awss3']):
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return "Cloud Storage & File Management"
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# Creative tools
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if any(word in filename_lower for word in ['canva', 'figma', 'bannerbear', 'editimage']):
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return "Creative Design Automation"
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# Video & content
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if any(word in filename_lower for word in ['youtube', 'vimeo', 'storyblok', 'strapi']):
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return "Creative Content & Video Automation"
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# Financial tools
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if any(word in filename_lower for word in ['stripe', 'chargebee', 'quickbooks', 'harvest']):
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return "Financial & Accounting"
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# Weather & external APIs
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if any(word in filename_lower for word in ['openweathermap', 'nasa', 'crypto', 'coingecko']):
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return "Web Scraping & Data Extraction"
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return None
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def main():
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"""Main function to categorize workflows."""
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print("Loading workflow categories...")
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workflows = load_categories()
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unique_categories = load_unique_categories()
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print(f"Total workflows: {len(workflows)}")
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# Count current categories
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category_counts = defaultdict(int)
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uncategorized_count = 0
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for workflow in workflows:
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if workflow['category']:
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category_counts[workflow['category']] += 1
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else:
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uncategorized_count += 1
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print(f"\nCurrent category distribution:")
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for category, count in sorted(category_counts.items()):
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print(f" {category}: {count}")
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print(f" Uncategorized: {uncategorized_count}")
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# Identify uncategorized workflows
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uncategorized_workflows = [w for w in workflows if not w['category']]
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print(f"\nAnalyzing {len(uncategorized_workflows)} uncategorized workflows...")
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# Categorize based on filename patterns
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suggested_categories = {}
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uncertain_workflows = []
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for workflow in uncategorized_workflows:
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filename = workflow['filename']
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suggested_category = categorize_by_filename(filename)
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if suggested_category:
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suggested_categories[filename] = suggested_category
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else:
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uncertain_workflows.append(filename)
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print(f"\nSuggested categorizations: {len(suggested_categories)}")
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print(f"Still uncertain: {len(uncategorized_workflows)}")
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# Show suggested categorizations
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if suggested_categories:
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print("\nSuggested categorizations:")
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for filename, category in sorted(suggested_categories.items()):
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print(f" {filename} → {category}")
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# Show uncertain workflows
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if uncertain_workflows:
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print(f"\nWorkflows that need manual review:")
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for filename in sorted(uncertain_workflows):
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print(f" {filename}")
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# Calculate potential improvement
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potential_categorized = len(suggested_categories)
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new_uncategorized_count = uncategorized_count - potential_categorized
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print(f"\nPotential improvement:")
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print(f" Current uncategorized: {uncategorized_count}")
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print(f" After auto-categorization: {new_uncategorized_count}")
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print(f" Reduction: {potential_categorized} workflows ({potential_categorized/uncategorized_count*100:.1f}%)")
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# Ask if user wants to apply suggestions
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if suggested_categories:
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response = input(f"\nWould you like to apply these {len(suggested_categories)} suggested categorizations? (y/n): ")
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if response.lower() in ['y', 'yes']:
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# Apply the categorizations
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for workflow in workflows:
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if workflow['filename'] in suggested_categories:
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workflow['category'] = suggested_categories[workflow['filename']]
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# Save the updated file
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with open('context/search_categories.json', 'w', encoding='utf-8') as f:
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json.dump(workflows, f, indent=2, ensure_ascii=False)
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print("✅ Categorizations applied and saved!")
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# Show new distribution
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new_category_counts = defaultdict(int)
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new_uncategorized_count = 0
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for workflow in workflows:
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if workflow['category']:
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new_category_counts[workflow['category']] += 1
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else:
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new_uncategorized_count += 1
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print(f"\nNew category distribution:")
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for category, count in sorted(new_category_counts.items()):
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print(f" {category}: {count}")
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print(f" Uncategorized: {new_uncategorized_count}")
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else:
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print("No changes applied.")
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if __name__ == "__main__":
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main()
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File diff suppressed because it is too large
Load Diff
@@ -47,6 +47,103 @@ def find_matching_category(tokens, integration_to_category):
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return ""
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def categorize_by_filename(filename):
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"""
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Categorize workflow based on filename patterns.
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Returns the most likely category or None if uncertain.
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"""
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filename_lower = filename.lower()
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# Security & Authentication
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if any(word in filename_lower for word in ['totp', 'bitwarden', 'auth', 'security']):
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return "Technical Infrastructure & DevOps"
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# Data Processing & File Operations
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if any(word in filename_lower for word in ['process', 'writebinaryfile', 'readbinaryfile', 'extractfromfile', 'converttofile', 'googlefirebasecloudfirestore', 'supabase', 'surveymonkey', 'renamekeys', 'readpdf', 'wufoo', 'splitinbatches', 'airtop', 'comparedatasets', 'spreadsheetfile']):
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return "Data Processing & Analysis"
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# Utility & Business Process Automation
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if any(word in filename_lower for word in ['noop', 'code', 'schedule', 'filter', 'splitout', 'wait', 'limit', 'aggregate', 'acuityscheduling', 'eventbrite', 'philipshue', 'stickynote', 'n8ntrainingcustomerdatastore', 'n8n']):
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return "Business Process Automation"
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# Webhook & API related
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if any(word in filename_lower for word in ['webhook', 'respondtowebhook', 'http', 'rssfeedread']):
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return "Web Scraping & Data Extraction"
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# Form & Data Collection
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if any(word in filename_lower for word in ['form', 'typeform', 'jotform']):
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return "Data Processing & Analysis"
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# Local file operations
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if any(word in filename_lower for word in ['localfile', 'filemaker']):
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return "Cloud Storage & File Management"
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# Database operations
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if any(word in filename_lower for word in ['postgres', 'mysql', 'mongodb', 'redis', 'elasticsearch', 'snowflake']):
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return "Data Processing & Analysis"
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# AI & Machine Learning
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if any(word in filename_lower for word in ['openai', 'awstextract', 'awsrekognition', 'humanticai', 'openthesaurus', 'googletranslate', 'summarize']):
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return "AI Agent Development"
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# E-commerce specific
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if any(word in filename_lower for word in ['woocommerce', 'gumroad']):
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return "E-commerce & Retail"
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# Social media specific
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if any(word in filename_lower for word in ['facebook', 'linkedin', 'instagram']):
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return "Social Media Management"
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# Customer support
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if any(word in filename_lower for word in ['zendesk', 'intercom', 'drift', 'pagerduty']):
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return "Communication & Messaging"
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# Analytics & Tracking
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if any(word in filename_lower for word in ['googleanalytics', 'segment', 'mixpanel']):
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return "Data Processing & Analysis"
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# Development tools
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if any(word in filename_lower for word in ['git', 'github', 'gitlab', 'travisci', 'jenkins', 'uptimerobot', 'gsuiteadmin', 'debughelper', 'bitbucket']):
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return "Technical Infrastructure & DevOps"
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# CRM & Sales tools
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if any(word in filename_lower for word in ['pipedrive', 'hubspot', 'salesforce', 'copper', 'orbit', 'agilecrm']):
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return "CRM & Sales"
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# Marketing tools
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if any(word in filename_lower for word in ['mailchimp', 'convertkit', 'sendgrid', 'mailerlite', 'lemlist', 'sendy', 'postmark', 'mailgun']):
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return "Marketing & Advertising Automation"
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# Project management
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if any(word in filename_lower for word in ['asana', 'mondaycom', 'clickup', 'trello', 'notion', 'toggl', 'microsofttodo', 'calendly', 'jira']):
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return "Project Management"
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# Communication
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if any(word in filename_lower for word in ['slack', 'telegram', 'discord', 'mattermost', 'twilio', 'emailreadimap', 'teams', 'gotowebinar']):
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return "Communication & Messaging"
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# Cloud storage
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if any(word in filename_lower for word in ['dropbox', 'googledrive', 'onedrive', 'awss3', 'googledocs']):
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return "Cloud Storage & File Management"
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# Creative tools
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if any(word in filename_lower for word in ['canva', 'figma', 'bannerbear', 'editimage']):
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return "Creative Design Automation"
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# Video & content
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if any(word in filename_lower for word in ['youtube', 'vimeo', 'storyblok', 'strapi']):
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return "Creative Content & Video Automation"
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# Financial tools
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if any(word in filename_lower for word in ['stripe', 'chargebee', 'quickbooks', 'harvest']):
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return "Financial & Accounting"
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# Weather & external APIs
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if any(word in filename_lower for word in ['openweathermap', 'nasa', 'crypto', 'coingecko']):
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return "Web Scraping & Data Extraction"
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return ""
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def main():
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# Load definition categories
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integration_to_category = load_def_categories()
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@@ -72,6 +169,11 @@ def main():
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"category": category
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})
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# Second pass for categorization
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for item in search_categories:
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if not item['category']:
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item['category'] = categorize_by_filename(item['filename'])
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# Sort by filename for consistency
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search_categories.sort(key=lambda x: x['filename'])
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@@ -10,6 +10,21 @@ import sys
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from pathlib import Path
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from typing import List, Dict, Any
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from categorize_workflows import categorize_by_filename
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def load_categories():
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"""Load the search categories file."""
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try:
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with open('context/search_categories.json', 'r', encoding='utf-8') as f:
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return json.load(f)
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except (FileNotFoundError, json.JSONDecodeError):
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return []
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def save_categories(data):
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"""Save the search categories file."""
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with open('context/search_categories.json', 'w', encoding='utf-8') as f:
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json.dump(data, f, indent=2, ensure_ascii=False)
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class WorkflowImporter:
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"""Import n8n workflows with progress tracking and error handling."""
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@@ -56,6 +71,32 @@ class WorkflowImporter:
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if result.returncode == 0:
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print(f"✅ Imported: {file_path.name}")
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# Categorize the workflow and update search_categories.json
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suggested_category = categorize_by_filename(file_path.name)
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all_workflows_data = load_categories()
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found = False
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for workflow_entry in all_workflows_data:
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if workflow_entry.get('filename') == file_path.name:
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workflow_entry['category'] = suggested_category
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found = True
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break
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if not found:
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# Add new workflow entry if not found (e.g., first import)
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all_workflows_data.append({
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"filename": file_path.name,
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"category": suggested_category,
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"name": file_path.stem, # Assuming workflow name is filename without extension
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"description": "", # Placeholder, can be updated manually
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"nodes": [] # Placeholder, can be updated manually
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})
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save_categories(all_workflows_data)
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print(f" Categorized '{file_path.name}' as '{suggested_category or 'Uncategorized'}'")
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return True
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else:
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error_msg = result.stderr.strip() or result.stdout.strip()
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@@ -141,6 +182,7 @@ def check_n8n_available() -> bool:
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def main():
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"""Main entry point."""
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sys.stdout.reconfigure(encoding='utf-8')
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print("🔧 N8N Workflow Importer")
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print("=" * 40)
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