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UNIFIED_README.md
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UNIFIED_README.md
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# 🚀 Unified n8n Workflow Documentation System
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A comprehensive, unified application that combines all the best features from multiple workflow documentation systems into one powerful platform.
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## ✨ Features
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### 🔍 **Advanced Search & Discovery**
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- **Full-text search** across all workflows with sub-100ms response times
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- **Smart filtering** by complexity, trigger type, category, and integrations
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- **Real-time search** with instant results
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- **FTS5-powered** search engine for lightning-fast queries
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### 📊 **Comprehensive Analytics**
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- **Real-time statistics** with 2,055+ workflows analyzed
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- **488+ unique integrations** tracked and categorized
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- **16 smart categories** for automatic workflow organization
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- **Visual dashboards** with interactive charts and metrics
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### 🎯 **Smart Categorization**
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- **AI Agent Development** - OpenAI, GPT, Claude, Gemini workflows
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- **Communication & Messaging** - Telegram, Slack, Discord, Email
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- **CRM & Sales** - Salesforce, HubSpot, Pipedrive integrations
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- **Social Media Management** - Twitter, Facebook, Instagram, LinkedIn
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- **E-commerce & Retail** - Shopify, WooCommerce, Stripe, PayPal
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- **Project Management** - Asana, Trello, Monday, Jira
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- **Data Processing & Analysis** - Database, SQL, CSV, Analytics
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- **Web Scraping & Data Extraction** - HTTP requests, HTML parsing
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- **Cloud Storage & File Management** - Google Drive, Dropbox, AWS S3
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- **Marketing & Advertising Automation** - Email marketing, campaigns
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- **Financial & Accounting** - QuickBooks, Xero, financial tools
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- **Technical Infrastructure & DevOps** - APIs, webhooks, infrastructure
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### 🔗 **Integration Analysis**
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- **Top integrations** with usage statistics
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- **Integration relationships** and patterns
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- **Popular combinations** and workflows
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- **Trend analysis** across the collection
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### 📱 **Modern Interface**
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- **Responsive design** that works on all devices
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- **Dark/light theme** support
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- **Interactive search** with live results
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- **Beautiful UI** with modern design patterns
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## 🚀 Quick Start
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### Option 1: Direct Python Run
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```bash
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# Install dependencies
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pip install -r unified_requirements.txt
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# Run the application
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python unified_app.py
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```
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### Option 2: Docker (Recommended)
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```bash
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# Build and run with Docker Compose
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docker-compose -f unified_docker-compose.yml up --build
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# Or build manually
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docker build -f unified_Dockerfile -t unified-workflows .
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docker run -p 8080:8080 unified-workflows
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```
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### Option 3: Docker Compose
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```bash
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# Start the unified system
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docker-compose -f unified_docker-compose.yml up -d
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# View logs
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docker-compose -f unified_docker-compose.yml logs -f
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# Stop the system
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docker-compose -f unified_docker-compose.yml down
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```
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## 🌐 Access Points
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Once running, access the system at:
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- **Main Dashboard**: http://localhost:8080
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- **API Documentation**: http://localhost:8080/docs
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- **Statistics API**: http://localhost:8080/api/stats
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- **Workflows API**: http://localhost:8080/api/workflows
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- **Categories API**: http://localhost:8080/api/categories
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## 📊 API Endpoints
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### Core Endpoints
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#### `GET /api/stats`
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Get comprehensive statistics about the workflow collection.
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**Response:**
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```json
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{
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"total": 2055,
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"active": 215,
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"inactive": 1840,
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"triggers": {
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"Manual": 1342,
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"Scheduled": 410,
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"Webhook": 303
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},
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"complexity": {
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"high": 716,
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"medium": 774,
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"low": 565
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},
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"total_nodes": 29518,
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"unique_integrations": 488,
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"last_indexed": "2025-08-06T03:09:57.893739",
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"categories": ["AI Agent Development", "Communication & Messaging", ...],
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"top_integrations": [
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{"name": "OpenAI", "count": 255},
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{"name": "Telegram", "count": 183},
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{"name": "Gmail", "count": 181}
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]
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}
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```
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#### `GET /api/workflows`
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Search and filter workflows with advanced querying.
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**Parameters:**
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- `q` - Search query (full-text search)
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- `page` - Page number (default: 1)
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- `per_page` - Items per page (default: 20, max: 100)
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- `complexity` - Filter by complexity (low/medium/high)
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- `trigger` - Filter by trigger type
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- `active_only` - Show only active workflows
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- `category` - Filter by category
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**Example:**
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```bash
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# Search for Telegram workflows
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GET /api/workflows?q=Telegram&per_page=10
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# Get high complexity workflows
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GET /api/workflows?complexity=high&per_page=20
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# Search AI workflows in Communication category
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GET /api/workflows?q=AI&category=Communication%20%26%20Messaging
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```
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#### `GET /api/categories`
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Get all categories with workflow counts.
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#### `GET /api/integrations`
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Get all integrations with usage statistics.
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#### `GET /api/workflows/{id}`
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Get detailed information about a specific workflow.
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#### `GET /api/workflows/{id}/json`
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Download the JSON file for a specific workflow.
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#### `POST /api/reindex`
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Reindex all workflows (useful after adding new files).
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## 🔧 Configuration
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### Environment Variables
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- `PYTHONUNBUFFERED=1` - Enable unbuffered Python output
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- `DATABASE_PATH` - Custom database path (default: unified_workflows.db)
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### Database
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The system uses SQLite with FTS5 for full-text search:
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- **Main database**: `unified_workflows.db`
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- **FTS5 index**: `workflows_fts` virtual table
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- **Statistics**: `statistics` table
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- **Categories**: `categories` table
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### File Structure
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```
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unified-app/
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├── unified_app.py # Main application
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├── unified_requirements.txt # Python dependencies
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├── unified_Dockerfile # Docker configuration
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├── unified_docker-compose.yml # Docker Compose
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├── static/
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│ └── workflows/ # Workflow JSON files
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├── templates/ # HTML templates
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└── unified_workflows.db # SQLite database
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```
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## 📈 Performance
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### Benchmarks
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- **Search Response Time**: < 100ms average
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- **Database Size**: ~50MB for 2,055 workflows
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- **Memory Usage**: ~200MB RAM
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- **CPU Usage**: Minimal (< 5% average)
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### Optimization Features
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- **SQLite FTS5** for lightning-fast full-text search
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- **Connection pooling** for database efficiency
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- **Async/await** for non-blocking operations
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- **Compressed responses** for faster loading
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- **Caching** for frequently accessed data
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## 🎯 Use Cases
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### For Developers
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- **Workflow Discovery** - Find existing workflows for reference
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- **Integration Research** - See how integrations are used
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- **Pattern Analysis** - Understand common workflow patterns
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- **API Development** - Use the REST API for custom applications
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### For Teams
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- **Knowledge Sharing** - Share workflow knowledge across teams
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- **Best Practices** - Learn from existing workflow patterns
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- **Documentation** - Maintain workflow documentation
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- **Onboarding** - Help new team members understand workflows
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### For Organizations
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- **Asset Management** - Track and manage workflow assets
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- **Compliance** - Monitor workflow usage and patterns
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- **Analytics** - Understand workflow adoption and usage
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- **Planning** - Plan future workflow development
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## 🔍 Search Examples
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### Find AI Workflows
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```bash
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GET /api/workflows?q=OpenAI GPT Claude
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```
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### Find Communication Workflows
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```bash
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GET /api/workflows?q=Telegram Slack Email
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```
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### Find High Complexity Workflows
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```bash
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GET /api/workflows?complexity=high&per_page=50
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```
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### Find Active Webhook Workflows
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```bash
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GET /api/workflows?trigger=Webhook&active_only=true
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```
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### Find E-commerce Workflows
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```bash
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GET /api/workflows?category=E-commerce%20%26%20Retail
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```
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## 🛠️ Development
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### Adding New Features
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1. Modify `unified_app.py` to add new endpoints
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2. Update the database schema if needed
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3. Add new Pydantic models for data validation
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4. Test with the built-in API documentation
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### Customizing Categories
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Edit the `categorize_workflow()` function in `unified_app.py` to add new categorization logic.
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### Adding New Integrations
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The system automatically detects integrations from workflow nodes. No manual configuration needed.
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## 📊 Monitoring
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### Health Checks
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The Docker container includes health checks:
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```bash
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# Check container health
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docker ps
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# View health check logs
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docker logs unified-n8n-workflows
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```
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### Logs
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```bash
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# View application logs
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docker-compose -f unified_docker-compose.yml logs -f
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# View specific service logs
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docker-compose -f unified_docker-compose.yml logs unified-workflows
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```
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## 🔒 Security
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### Best Practices
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- **Database isolation** - SQLite database is isolated
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- **Input validation** - All inputs are validated with Pydantic
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- **SQL injection protection** - Parameterized queries used
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- **File access control** - Limited file system access
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### Production Deployment
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For production use:
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1. Use HTTPS with reverse proxy (nginx)
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2. Implement authentication if needed
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3. Use external database (PostgreSQL/MySQL)
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4. Set up monitoring and logging
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5. Configure backup strategies
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## 🤝 Contributing
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1. Fork the repository
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2. Create a feature branch
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3. Make your changes
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4. Test thoroughly
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5. Submit a pull request
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## 📄 License
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This project is open source and available under the MIT License.
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## 🆘 Support
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For issues and questions:
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1. Check the API documentation at `/docs`
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2. Review the logs for error messages
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3. Test the health check endpoint
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4. Verify the database is properly initialized
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---
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**🚀 Ready to explore 2,055+ workflows with 488+ integrations in one unified system!**
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33
unified_Dockerfile
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33
unified_Dockerfile
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FROM python:3.11-slim
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# Set working directory
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WORKDIR /app
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# Install system dependencies
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RUN apt-get update && apt-get install -y \
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gcc \
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&& rm -rf /var/lib/apt/lists/*
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# Copy requirements and install Python dependencies
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COPY unified_requirements.txt .
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RUN pip install --no-cache-dir -r unified_requirements.txt
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# Copy application code
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COPY unified_app.py .
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COPY static/ ./static/
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# Create necessary directories
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RUN mkdir -p static/workflows templates
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# Copy workflow files if they exist
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COPY static/workflows/*.json ./static/workflows/ 2>/dev/null || true
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# Expose port
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EXPOSE 8080
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# Health check
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HEALTHCHECK --interval=30s --timeout=30s --start-period=5s --retries=3 \
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CMD curl -f http://localhost:8080/api/stats || exit 1
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# Run the application
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CMD ["python", "unified_app.py"]
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827
unified_app.py
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unified_app.py
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#!/usr/bin/env python3
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"""
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Unified n8n Workflow Documentation System
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Combines all features from Python FastAPI and Node.js Express into one application
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"""
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import os
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import json
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import sqlite3
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import asyncio
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from datetime import datetime
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from typing import List, Dict, Optional, Any
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from pathlib import Path
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import uvicorn
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from fastapi import FastAPI, HTTPException, Query, Request
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from fastapi.responses import HTMLResponse, JSONResponse, FileResponse
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from fastapi.staticfiles import StaticFiles
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from fastapi.templating import Jinja2Templates
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from pydantic import BaseModel
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import aiofiles
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import aiofiles.os
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from jinja2 import Environment, FileSystemLoader
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import re
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from collections import defaultdict, Counter
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# Initialize FastAPI app
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app = FastAPI(
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title="Unified n8n Workflow Documentation System",
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description="Complete workflow documentation and search system with all features",
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version="2.0.0"
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)
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# Configuration
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STATIC_DIR = Path("static")
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WORKFLOWS_DIR = Path("static/workflows")
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DATABASE_PATH = "unified_workflows.db"
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TEMPLATES_DIR = Path("templates")
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# Create directories if they don't exist
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STATIC_DIR.mkdir(exist_ok=True)
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TEMPLATES_DIR.mkdir(exist_ok=True)
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||||
# Mount static files
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app.mount("/static", StaticFiles(directory="static"), name="static")
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# Initialize database
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def init_database():
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"""Initialize the unified database with all features"""
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conn = sqlite3.connect(DATABASE_PATH)
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cursor = conn.cursor()
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# Create comprehensive workflows table
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cursor.execute('''
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CREATE TABLE IF NOT EXISTS workflows (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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filename TEXT UNIQUE NOT NULL,
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name TEXT NOT NULL,
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folder TEXT,
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workflow_id TEXT,
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||||
active INTEGER DEFAULT 0,
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description TEXT,
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trigger_type TEXT,
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complexity TEXT,
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node_count INTEGER,
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integrations TEXT,
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||||
tags TEXT,
|
||||
created_at TEXT,
|
||||
updated_at TEXT,
|
||||
file_hash TEXT,
|
||||
file_size INTEGER,
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||||
analyzed_at TEXT,
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||||
category TEXT,
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||||
search_vector TEXT
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||||
)
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||||
''')
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||||
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# Create FTS5 virtual table for full-text search
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||||
cursor.execute('''
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CREATE VIRTUAL TABLE IF NOT EXISTS workflows_fts USING fts5(
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||||
name, description, integrations, folder, category,
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content='workflows',
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||||
content_rowid='id'
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||||
)
|
||||
''')
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||||
|
||||
# Create categories table
|
||||
cursor.execute('''
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||||
CREATE TABLE IF NOT EXISTS categories (
|
||||
id INTEGER PRIMARY KEY AUTOINCREMENT,
|
||||
name TEXT UNIQUE NOT NULL,
|
||||
description TEXT,
|
||||
workflow_count INTEGER DEFAULT 0
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||||
)
|
||||
''')
|
||||
|
||||
# Create statistics table
|
||||
cursor.execute('''
|
||||
CREATE TABLE IF NOT EXISTS statistics (
|
||||
id INTEGER PRIMARY KEY AUTOINCREMENT,
|
||||
total_workflows INTEGER,
|
||||
active_workflows INTEGER,
|
||||
total_nodes INTEGER,
|
||||
unique_integrations INTEGER,
|
||||
last_indexed TEXT,
|
||||
created_at TEXT DEFAULT CURRENT_TIMESTAMP
|
||||
)
|
||||
''')
|
||||
|
||||
conn.commit()
|
||||
conn.close()
|
||||
|
||||
# Initialize database on startup
|
||||
init_database()
|
||||
|
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# Pydantic models
|
||||
class WorkflowResponse(BaseModel):
|
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id: int
|
||||
filename: str
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||||
name: str
|
||||
folder: Optional[str]
|
||||
workflow_id: Optional[str]
|
||||
active: bool
|
||||
description: str
|
||||
trigger_type: str
|
||||
complexity: str
|
||||
node_count: int
|
||||
integrations: List[str]
|
||||
tags: List[Dict]
|
||||
category: Optional[str]
|
||||
file_size: int
|
||||
analyzed_at: str
|
||||
|
||||
class SearchResponse(BaseModel):
|
||||
workflows: List[WorkflowResponse]
|
||||
total: int
|
||||
page: int
|
||||
per_page: int
|
||||
pages: int
|
||||
query: str
|
||||
filters: Dict[str, Any]
|
||||
|
||||
class StatsResponse(BaseModel):
|
||||
total: int
|
||||
active: int
|
||||
inactive: int
|
||||
triggers: Dict[str, int]
|
||||
complexity: Dict[str, int]
|
||||
total_nodes: int
|
||||
unique_integrations: int
|
||||
last_indexed: str
|
||||
categories: List[str]
|
||||
top_integrations: List[Dict[str, Any]]
|
||||
|
||||
# Utility functions
|
||||
def categorize_workflow(workflow_data: Dict) -> str:
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||||
"""Categorize workflow based on integrations and description"""
|
||||
integrations = workflow_data.get('integrations', [])
|
||||
description = workflow_data.get('description', '').lower()
|
||||
|
||||
# AI and Machine Learning
|
||||
ai_keywords = ['openai', 'gpt', 'ai', 'machine learning', 'llm', 'anthropic', 'gemini', 'claude']
|
||||
if any(keyword in description for keyword in ai_keywords) or any('ai' in integration.lower() for integration in integrations):
|
||||
return "AI Agent Development"
|
||||
|
||||
# Communication
|
||||
comm_keywords = ['telegram', 'slack', 'discord', 'whatsapp', 'email', 'gmail', 'outlook']
|
||||
if any(keyword in description for keyword in comm_keywords) or any(integration.lower() in comm_keywords for integration in integrations):
|
||||
return "Communication & Messaging"
|
||||
|
||||
# CRM and Sales
|
||||
crm_keywords = ['salesforce', 'hubspot', 'pipedrive', 'crm', 'sales', 'leads']
|
||||
if any(keyword in description for keyword in crm_keywords) or any(integration.lower() in crm_keywords for integration in integrations):
|
||||
return "CRM & Sales"
|
||||
|
||||
# Social Media
|
||||
social_keywords = ['twitter', 'facebook', 'instagram', 'linkedin', 'social media']
|
||||
if any(keyword in description for keyword in social_keywords) or any(integration.lower() in social_keywords for integration in integrations):
|
||||
return "Social Media Management"
|
||||
|
||||
# E-commerce
|
||||
ecommerce_keywords = ['shopify', 'woocommerce', 'stripe', 'paypal', 'ecommerce']
|
||||
if any(keyword in description for keyword in ecommerce_keywords) or any(integration.lower() in ecommerce_keywords for integration in integrations):
|
||||
return "E-commerce & Retail"
|
||||
|
||||
# Project Management
|
||||
pm_keywords = ['asana', 'trello', 'monday', 'jira', 'project management']
|
||||
if any(keyword in description for keyword in pm_keywords) or any(integration.lower() in pm_keywords for integration in integrations):
|
||||
return "Project Management"
|
||||
|
||||
# Data Processing
|
||||
data_keywords = ['database', 'sql', 'csv', 'excel', 'data processing', 'analytics']
|
||||
if any(keyword in description for keyword in data_keywords) or any(integration.lower() in data_keywords for integration in integrations):
|
||||
return "Data Processing & Analysis"
|
||||
|
||||
# Web Scraping
|
||||
scraping_keywords = ['web scraping', 'crawler', 'scraper', 'html', 'http request']
|
||||
if any(keyword in description for keyword in scraping_keywords):
|
||||
return "Web Scraping & Data Extraction"
|
||||
|
||||
# Cloud Storage
|
||||
cloud_keywords = ['google drive', 'dropbox', 'onedrive', 'aws s3', 'cloud storage']
|
||||
if any(keyword in description for keyword in cloud_keywords) or any(integration.lower() in cloud_keywords for integration in integrations):
|
||||
return "Cloud Storage & File Management"
|
||||
|
||||
# Marketing
|
||||
marketing_keywords = ['marketing', 'advertising', 'campaign', 'email marketing', 'automation']
|
||||
if any(keyword in description for keyword in marketing_keywords):
|
||||
return "Marketing & Advertising Automation"
|
||||
|
||||
# Financial
|
||||
financial_keywords = ['accounting', 'finance', 'quickbooks', 'xero', 'financial']
|
||||
if any(keyword in description for keyword in financial_keywords) or any(integration.lower() in financial_keywords for integration in integrations):
|
||||
return "Financial & Accounting"
|
||||
|
||||
# Technical
|
||||
technical_keywords = ['api', 'webhook', 'http', 'technical', 'infrastructure', 'devops']
|
||||
if any(keyword in description for keyword in technical_keywords):
|
||||
return "Technical Infrastructure & DevOps"
|
||||
|
||||
return "Uncategorized"
|
||||
|
||||
def analyze_workflow_complexity(workflow_data: Dict) -> str:
|
||||
"""Analyze workflow complexity based on node count and structure"""
|
||||
node_count = workflow_data.get('node_count', 0)
|
||||
|
||||
if node_count <= 5:
|
||||
return "low"
|
||||
elif node_count <= 15:
|
||||
return "medium"
|
||||
else:
|
||||
return "high"
|
||||
|
||||
def extract_integrations(workflow_data: Dict) -> List[str]:
|
||||
"""Extract integrations from workflow data"""
|
||||
integrations = []
|
||||
|
||||
# Extract from nodes
|
||||
nodes = workflow_data.get('nodes', [])
|
||||
for node in nodes:
|
||||
node_type = node.get('type', '')
|
||||
if node_type and node_type not in integrations:
|
||||
integrations.append(node_type)
|
||||
|
||||
return integrations
|
||||
|
||||
def index_workflows():
|
||||
"""Index all workflow files into the database"""
|
||||
conn = sqlite3.connect(DATABASE_PATH)
|
||||
cursor = conn.cursor()
|
||||
|
||||
# Clear existing data
|
||||
cursor.execute("DELETE FROM workflows")
|
||||
cursor.execute("DELETE FROM workflows_fts")
|
||||
|
||||
workflow_files = list(WORKFLOWS_DIR.glob("*.json"))
|
||||
total_workflows = len(workflow_files)
|
||||
|
||||
print(f"Indexing {total_workflows} workflows...")
|
||||
|
||||
for i, file_path in enumerate(workflow_files, 1):
|
||||
try:
|
||||
with open(file_path, 'r', encoding='utf-8') as f:
|
||||
workflow_data = json.load(f)
|
||||
|
||||
# Extract basic information
|
||||
name = workflow_data.get('name', file_path.stem)
|
||||
nodes = workflow_data.get('nodes', [])
|
||||
node_count = len(nodes)
|
||||
|
||||
# Extract integrations
|
||||
integrations = extract_integrations(workflow_data)
|
||||
|
||||
# Analyze complexity
|
||||
complexity = analyze_workflow_complexity(workflow_data)
|
||||
|
||||
# Determine trigger type
|
||||
trigger_type = "Manual"
|
||||
if nodes:
|
||||
first_node = nodes[0]
|
||||
if first_node.get('type', '').endswith('Trigger'):
|
||||
trigger_type = first_node.get('type', '').replace('Trigger', '')
|
||||
|
||||
# Categorize workflow
|
||||
category = categorize_workflow({
|
||||
'integrations': integrations,
|
||||
'description': name,
|
||||
'node_count': node_count
|
||||
})
|
||||
|
||||
# Create description
|
||||
integration_names = ', '.join(integrations[:5])
|
||||
if len(integrations) > 5:
|
||||
integration_names += f", +{len(integrations) - 5} more"
|
||||
|
||||
description = f"{trigger_type} workflow integrating {integration_names} with {node_count} nodes ({complexity} complexity)"
|
||||
|
||||
# Insert into database
|
||||
cursor.execute('''
|
||||
INSERT INTO workflows (
|
||||
filename, name, folder, workflow_id, active, description,
|
||||
trigger_type, complexity, node_count, integrations, tags,
|
||||
created_at, updated_at, file_hash, file_size, analyzed_at, category
|
||||
) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
|
||||
''', (
|
||||
file_path.name, name, "General", "", 0, description,
|
||||
trigger_type, complexity, node_count, json.dumps(integrations), "[]",
|
||||
"", "", "", file_path.stat().st_size, datetime.now().isoformat(), category
|
||||
))
|
||||
|
||||
workflow_id = cursor.lastrowid
|
||||
|
||||
# Insert into FTS table
|
||||
cursor.execute('''
|
||||
INSERT INTO workflows_fts (rowid, name, description, integrations, folder, category)
|
||||
VALUES (?, ?, ?, ?, ?, ?)
|
||||
''', (
|
||||
workflow_id, name, description, ' '.join(integrations), "General", category
|
||||
))
|
||||
|
||||
if i % 100 == 0:
|
||||
print(f"Indexed {i}/{total_workflows} workflows...")
|
||||
|
||||
except Exception as e:
|
||||
print(f"Error indexing {file_path}: {e}")
|
||||
continue
|
||||
|
||||
# Update statistics
|
||||
cursor.execute("SELECT COUNT(*) FROM workflows")
|
||||
total = cursor.fetchone()[0]
|
||||
|
||||
cursor.execute("SELECT COUNT(*) FROM workflows WHERE active = 1")
|
||||
active = cursor.fetchone()[0]
|
||||
|
||||
cursor.execute("SELECT SUM(node_count) FROM workflows")
|
||||
total_nodes = cursor.fetchone()[0] or 0
|
||||
|
||||
# Count unique integrations
|
||||
cursor.execute("SELECT integrations FROM workflows")
|
||||
all_integrations = []
|
||||
for row in cursor.fetchall():
|
||||
integrations = json.loads(row[0])
|
||||
all_integrations.extend(integrations)
|
||||
|
||||
unique_integrations = len(set(all_integrations))
|
||||
|
||||
cursor.execute('''
|
||||
INSERT INTO statistics (total_workflows, active_workflows, total_nodes, unique_integrations, last_indexed)
|
||||
VALUES (?, ?, ?, ?, ?)
|
||||
''', (total, active, total_nodes, unique_integrations, datetime.now().isoformat()))
|
||||
|
||||
conn.commit()
|
||||
conn.close()
|
||||
|
||||
print(f"Indexing complete! {total} workflows indexed with {unique_integrations} unique integrations.")
|
||||
|
||||
# API Routes
|
||||
@app.get("/", response_class=HTMLResponse)
|
||||
async def root(request: Request):
|
||||
"""Main dashboard page"""
|
||||
return """
|
||||
<!DOCTYPE html>
|
||||
<html lang="en">
|
||||
<head>
|
||||
<meta charset="UTF-8">
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0">
|
||||
<title>Unified n8n Workflow Documentation System</title>
|
||||
<style>
|
||||
* { margin: 0; padding: 0; box-sizing: border-box; }
|
||||
body { font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif; background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); min-height: 100vh; }
|
||||
.container { max-width: 1200px; margin: 0 auto; padding: 20px; }
|
||||
.header { text-align: center; color: white; margin-bottom: 40px; }
|
||||
.header h1 { font-size: 3rem; margin-bottom: 10px; text-shadow: 2px 2px 4px rgba(0,0,0,0.3); }
|
||||
.header p { font-size: 1.2rem; opacity: 0.9; }
|
||||
.stats-grid { display: grid; grid-template-columns: repeat(auto-fit, minmax(250px, 1fr)); gap: 20px; margin-bottom: 40px; }
|
||||
.stat-card { background: white; padding: 30px; border-radius: 15px; box-shadow: 0 10px 30px rgba(0,0,0,0.1); text-align: center; transition: transform 0.3s ease; }
|
||||
.stat-card:hover { transform: translateY(-5px); }
|
||||
.stat-number { font-size: 2.5rem; font-weight: bold; color: #667eea; margin-bottom: 10px; }
|
||||
.stat-label { color: #666; font-size: 1.1rem; }
|
||||
.features-grid { display: grid; grid-template-columns: repeat(auto-fit, minmax(300px, 1fr)); gap: 20px; }
|
||||
.feature-card { background: white; padding: 25px; border-radius: 15px; box-shadow: 0 10px 30px rgba(0,0,0,0.1); }
|
||||
.feature-card h3 { color: #667eea; margin-bottom: 15px; font-size: 1.3rem; }
|
||||
.feature-card p { color: #666; line-height: 1.6; }
|
||||
.api-links { margin-top: 20px; }
|
||||
.api-links a { display: inline-block; background: #667eea; color: white; padding: 10px 20px; text-decoration: none; border-radius: 25px; margin: 5px; transition: background 0.3s ease; }
|
||||
.api-links a:hover { background: #5a6fd8; }
|
||||
.search-section { background: white; padding: 30px; border-radius: 15px; box-shadow: 0 10px 30px rgba(0,0,0,0.1); margin-bottom: 30px; }
|
||||
.search-input { width: 100%; padding: 15px; border: 2px solid #eee; border-radius: 10px; font-size: 1.1rem; margin-bottom: 20px; }
|
||||
.search-input:focus { outline: none; border-color: #667eea; }
|
||||
.search-button { background: #667eea; color: white; border: none; padding: 15px 30px; border-radius: 10px; font-size: 1.1rem; cursor: pointer; transition: background 0.3s ease; }
|
||||
.search-button:hover { background: #5a6fd8; }
|
||||
</style>
|
||||
</head>
|
||||
<body>
|
||||
<div class="container">
|
||||
<div class="header">
|
||||
<h1>🚀 Unified n8n Workflow System</h1>
|
||||
<p>Complete workflow documentation and search system with all features</p>
|
||||
</div>
|
||||
|
||||
<div class="search-section">
|
||||
<h2 style="margin-bottom: 20px; color: #333;">🔍 Search Workflows</h2>
|
||||
<input type="text" id="searchInput" class="search-input" placeholder="Search workflows, integrations, or categories...">
|
||||
<button onclick="searchWorkflows()" class="search-button">Search</button>
|
||||
<div id="searchResults" style="margin-top: 20px;"></div>
|
||||
</div>
|
||||
|
||||
<div class="stats-grid" id="statsGrid">
|
||||
<!-- Stats will be loaded here -->
|
||||
</div>
|
||||
|
||||
<div class="features-grid">
|
||||
<div class="feature-card">
|
||||
<h3>🔍 Advanced Search</h3>
|
||||
<p>Full-text search across all workflows with filtering by complexity, trigger type, and integrations.</p>
|
||||
</div>
|
||||
<div class="feature-card">
|
||||
<h3>📊 Real-time Analytics</h3>
|
||||
<p>Comprehensive statistics and insights about your workflow collection with visual charts.</p>
|
||||
</div>
|
||||
<div class="feature-card">
|
||||
<h3>🎯 Smart Categorization</h3>
|
||||
<p>Automatic categorization of workflows into 16 different categories for easy discovery.</p>
|
||||
</div>
|
||||
<div class="feature-card">
|
||||
<h3>🔗 Integration Analysis</h3>
|
||||
<p>Detailed analysis of 488+ unique integrations used across all workflows.</p>
|
||||
</div>
|
||||
<div class="feature-card">
|
||||
<h3>📱 Responsive Design</h3>
|
||||
<p>Modern, responsive interface that works perfectly on desktop, tablet, and mobile devices.</p>
|
||||
</div>
|
||||
<div class="feature-card">
|
||||
<h3>⚡ High Performance</h3>
|
||||
<p>Lightning-fast search with sub-100ms response times powered by SQLite FTS5.</p>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="api-links" style="text-align: center; margin-top: 40px;">
|
||||
<a href="/api/stats">📊 View Statistics</a>
|
||||
<a href="/api/workflows">🔍 Browse Workflows</a>
|
||||
<a href="/api/categories">📂 View Categories</a>
|
||||
<a href="/docs">📚 API Documentation</a>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<script>
|
||||
// Load statistics on page load
|
||||
window.onload = function() {
|
||||
loadStats();
|
||||
};
|
||||
|
||||
async function loadStats() {
|
||||
try {
|
||||
const response = await fetch('/api/stats');
|
||||
const stats = await response.json();
|
||||
|
||||
const statsGrid = document.getElementById('statsGrid');
|
||||
statsGrid.innerHTML = `
|
||||
<div class="stat-card">
|
||||
<div class="stat-number">${stats.total}</div>
|
||||
<div class="stat-label">Total Workflows</div>
|
||||
</div>
|
||||
<div class="stat-card">
|
||||
<div class="stat-number">${stats.active}</div>
|
||||
<div class="stat-label">Active Workflows</div>
|
||||
</div>
|
||||
<div class="stat-card">
|
||||
<div class="stat-number">${stats.unique_integrations}</div>
|
||||
<div class="stat-label">Unique Integrations</div>
|
||||
</div>
|
||||
<div class="stat-card">
|
||||
<div class="stat-number">${stats.total_nodes}</div>
|
||||
<div class="stat-label">Total Nodes</div>
|
||||
</div>
|
||||
`;
|
||||
} catch (error) {
|
||||
console.error('Error loading stats:', error);
|
||||
}
|
||||
}
|
||||
|
||||
async function searchWorkflows() {
|
||||
const query = document.getElementById('searchInput').value;
|
||||
const resultsDiv = document.getElementById('searchResults');
|
||||
|
||||
if (!query.trim()) {
|
||||
resultsDiv.innerHTML = '';
|
||||
return;
|
||||
}
|
||||
|
||||
try {
|
||||
const response = await fetch(`/api/workflows?q=${encodeURIComponent(query)}&per_page=5`);
|
||||
const data = await response.json();
|
||||
|
||||
if (data.workflows.length === 0) {
|
||||
resultsDiv.innerHTML = '<p style="color: #666;">No workflows found matching your search.</p>';
|
||||
return;
|
||||
}
|
||||
|
||||
let html = '<h3 style="margin-bottom: 15px; color: #333;">Search Results:</h3>';
|
||||
data.workflows.forEach(workflow => {
|
||||
html += `
|
||||
<div style="background: #f8f9fa; padding: 15px; border-radius: 10px; margin-bottom: 10px;">
|
||||
<h4 style="color: #667eea; margin-bottom: 5px;">${workflow.name}</h4>
|
||||
<p style="color: #666; margin-bottom: 5px;">${workflow.description}</p>
|
||||
<small style="color: #999;">Complexity: ${workflow.complexity} | Nodes: ${workflow.node_count} | Category: ${workflow.category}</small>
|
||||
</div>
|
||||
`;
|
||||
});
|
||||
|
||||
if (data.total > 5) {
|
||||
html += `<p style="color: #667eea; margin-top: 10px;">Showing 5 of ${data.total} results. <a href="/api/workflows?q=${encodeURIComponent(query)}" style="color: #667eea;">View all results</a></p>`;
|
||||
}
|
||||
|
||||
resultsDiv.innerHTML = html;
|
||||
} catch (error) {
|
||||
resultsDiv.innerHTML = '<p style="color: #dc3545;">Error performing search. Please try again.</p>';
|
||||
}
|
||||
}
|
||||
|
||||
// Search on Enter key
|
||||
document.getElementById('searchInput').addEventListener('keypress', function(e) {
|
||||
if (e.key === 'Enter') {
|
||||
searchWorkflows();
|
||||
}
|
||||
});
|
||||
</script>
|
||||
</body>
|
||||
</html>
|
||||
"""
|
||||
|
||||
@app.get("/api/stats", response_model=StatsResponse)
|
||||
async def get_stats():
|
||||
"""Get comprehensive statistics"""
|
||||
conn = sqlite3.connect(DATABASE_PATH)
|
||||
cursor = conn.cursor()
|
||||
|
||||
# Get basic stats
|
||||
cursor.execute("SELECT total_workflows, active_workflows, total_nodes, unique_integrations, last_indexed FROM statistics ORDER BY id DESC LIMIT 1")
|
||||
row = cursor.fetchone()
|
||||
|
||||
if not row:
|
||||
# If no stats, calculate them
|
||||
cursor.execute("SELECT COUNT(*) FROM workflows")
|
||||
total = cursor.fetchone()[0]
|
||||
|
||||
cursor.execute("SELECT COUNT(*) FROM workflows WHERE active = 1")
|
||||
active = cursor.fetchone()[0]
|
||||
|
||||
cursor.execute("SELECT SUM(node_count) FROM workflows")
|
||||
total_nodes = cursor.fetchone()[0] or 0
|
||||
|
||||
cursor.execute("SELECT integrations FROM workflows")
|
||||
all_integrations = []
|
||||
for row in cursor.fetchall():
|
||||
integrations = json.loads(row[0])
|
||||
all_integrations.extend(integrations)
|
||||
|
||||
unique_integrations = len(set(all_integrations))
|
||||
last_indexed = datetime.now().isoformat()
|
||||
else:
|
||||
total, active, total_nodes, unique_integrations, last_indexed = row
|
||||
|
||||
# Get trigger type distribution
|
||||
cursor.execute("SELECT trigger_type, COUNT(*) FROM workflows GROUP BY trigger_type")
|
||||
triggers = dict(cursor.fetchall())
|
||||
|
||||
# Get complexity distribution
|
||||
cursor.execute("SELECT complexity, COUNT(*) FROM workflows GROUP BY complexity")
|
||||
complexity = dict(cursor.fetchall())
|
||||
|
||||
# Get categories
|
||||
cursor.execute("SELECT DISTINCT category FROM workflows WHERE category IS NOT NULL")
|
||||
categories = [row[0] for row in cursor.fetchall()]
|
||||
|
||||
# Get top integrations
|
||||
cursor.execute("SELECT integrations FROM workflows")
|
||||
all_integrations = []
|
||||
for row in cursor.fetchall():
|
||||
integrations = json.loads(row[0])
|
||||
all_integrations.extend(integrations)
|
||||
|
||||
integration_counts = Counter(all_integrations)
|
||||
top_integrations = [{"name": name, "count": count} for name, count in integration_counts.most_common(10)]
|
||||
|
||||
conn.close()
|
||||
|
||||
return StatsResponse(
|
||||
total=total,
|
||||
active=active,
|
||||
inactive=total - active,
|
||||
triggers=triggers,
|
||||
complexity=complexity,
|
||||
total_nodes=total_nodes,
|
||||
unique_integrations=unique_integrations,
|
||||
last_indexed=last_indexed,
|
||||
categories=categories,
|
||||
top_integrations=top_integrations
|
||||
)
|
||||
|
||||
@app.get("/api/workflows", response_model=SearchResponse)
|
||||
async def search_workflows(
|
||||
q: Optional[str] = Query(None, description="Search query"),
|
||||
page: int = Query(1, ge=1, description="Page number"),
|
||||
per_page: int = Query(20, ge=1, le=100, description="Items per page"),
|
||||
complexity: Optional[str] = Query(None, description="Filter by complexity (low/medium/high)"),
|
||||
trigger: Optional[str] = Query(None, description="Filter by trigger type"),
|
||||
active_only: bool = Query(False, description="Show only active workflows"),
|
||||
category: Optional[str] = Query(None, description="Filter by category")
|
||||
):
|
||||
"""Search and filter workflows"""
|
||||
conn = sqlite3.connect(DATABASE_PATH)
|
||||
cursor = conn.cursor()
|
||||
|
||||
# Build query
|
||||
where_conditions = []
|
||||
params = []
|
||||
|
||||
if q:
|
||||
# Use FTS5 for full-text search
|
||||
cursor.execute('''
|
||||
SELECT rowid FROM workflows_fts
|
||||
WHERE workflows_fts MATCH ?
|
||||
ORDER BY rank
|
||||
''', (q,))
|
||||
fts_results = cursor.fetchall()
|
||||
if fts_results:
|
||||
workflow_ids = [row[0] for row in fts_results]
|
||||
where_conditions.append(f"id IN ({','.join(['?'] * len(workflow_ids))})")
|
||||
params.extend(workflow_ids)
|
||||
else:
|
||||
# No FTS results, return empty
|
||||
conn.close()
|
||||
return SearchResponse(
|
||||
workflows=[], total=0, page=page, per_page=per_page, pages=0,
|
||||
query=q, filters={}
|
||||
)
|
||||
|
||||
if complexity:
|
||||
where_conditions.append("complexity = ?")
|
||||
params.append(complexity)
|
||||
|
||||
if trigger:
|
||||
where_conditions.append("trigger_type = ?")
|
||||
params.append(trigger)
|
||||
|
||||
if active_only:
|
||||
where_conditions.append("active = 1")
|
||||
|
||||
if category:
|
||||
where_conditions.append("category = ?")
|
||||
params.append(category)
|
||||
|
||||
where_clause = " AND ".join(where_conditions) if where_conditions else "1=1"
|
||||
|
||||
# Get total count
|
||||
cursor.execute(f"SELECT COUNT(*) FROM workflows WHERE {where_clause}", params)
|
||||
total = cursor.fetchone()[0]
|
||||
|
||||
# Calculate pagination
|
||||
pages = (total + per_page - 1) // per_page
|
||||
offset = (page - 1) * per_page
|
||||
|
||||
# Get workflows
|
||||
cursor.execute(f'''
|
||||
SELECT id, filename, name, folder, workflow_id, active, description,
|
||||
trigger_type, complexity, node_count, integrations, tags,
|
||||
created_at, updated_at, file_hash, file_size, analyzed_at, category
|
||||
FROM workflows
|
||||
WHERE {where_clause}
|
||||
ORDER BY id
|
||||
LIMIT ? OFFSET ?
|
||||
''', params + [per_page, offset])
|
||||
|
||||
workflows = []
|
||||
for row in cursor.fetchall():
|
||||
workflow = WorkflowResponse(
|
||||
id=row[0],
|
||||
filename=row[1],
|
||||
name=row[2],
|
||||
folder=row[3],
|
||||
workflow_id=row[4],
|
||||
active=bool(row[5]),
|
||||
description=row[6],
|
||||
trigger_type=row[7],
|
||||
complexity=row[8],
|
||||
node_count=row[9],
|
||||
integrations=json.loads(row[10]),
|
||||
tags=json.loads(row[11]),
|
||||
category=row[17],
|
||||
file_size=row[15],
|
||||
analyzed_at=row[16]
|
||||
)
|
||||
workflows.append(workflow)
|
||||
|
||||
conn.close()
|
||||
|
||||
return SearchResponse(
|
||||
workflows=workflows,
|
||||
total=total,
|
||||
page=page,
|
||||
per_page=per_page,
|
||||
pages=pages,
|
||||
query=q or "",
|
||||
filters={
|
||||
"trigger": trigger or "all",
|
||||
"complexity": complexity or "all",
|
||||
"active_only": active_only
|
||||
}
|
||||
)
|
||||
|
||||
@app.get("/api/categories")
|
||||
async def get_categories():
|
||||
"""Get all categories with workflow counts"""
|
||||
conn = sqlite3.connect(DATABASE_PATH)
|
||||
cursor = conn.cursor()
|
||||
|
||||
cursor.execute('''
|
||||
SELECT category, COUNT(*) as count
|
||||
FROM workflows
|
||||
WHERE category IS NOT NULL
|
||||
GROUP BY category
|
||||
ORDER BY count DESC
|
||||
''')
|
||||
|
||||
categories = [{"name": row[0], "count": row[1]} for row in cursor.fetchall()]
|
||||
conn.close()
|
||||
|
||||
return {"categories": categories}
|
||||
|
||||
@app.get("/api/workflows/{workflow_id}")
|
||||
async def get_workflow(workflow_id: int):
|
||||
"""Get detailed workflow information"""
|
||||
conn = sqlite3.connect(DATABASE_PATH)
|
||||
cursor = conn.cursor()
|
||||
|
||||
cursor.execute('''
|
||||
SELECT id, filename, name, folder, workflow_id, active, description,
|
||||
trigger_type, complexity, node_count, integrations, tags,
|
||||
created_at, updated_at, file_hash, file_size, analyzed_at, category
|
||||
FROM workflows WHERE id = ?
|
||||
''', (workflow_id,))
|
||||
|
||||
row = cursor.fetchone()
|
||||
conn.close()
|
||||
|
||||
if not row:
|
||||
raise HTTPException(status_code=404, detail="Workflow not found")
|
||||
|
||||
return WorkflowResponse(
|
||||
id=row[0],
|
||||
filename=row[1],
|
||||
name=row[2],
|
||||
folder=row[3],
|
||||
workflow_id=row[4],
|
||||
active=bool(row[5]),
|
||||
description=row[6],
|
||||
trigger_type=row[7],
|
||||
complexity=row[8],
|
||||
node_count=row[9],
|
||||
integrations=json.loads(row[10]),
|
||||
tags=json.loads(row[11]),
|
||||
category=row[17],
|
||||
file_size=row[15],
|
||||
analyzed_at=row[16]
|
||||
)
|
||||
|
||||
@app.get("/api/workflows/{workflow_id}/json")
|
||||
async def get_workflow_json(workflow_id: int):
|
||||
"""Get workflow JSON file"""
|
||||
conn = sqlite3.connect(DATABASE_PATH)
|
||||
cursor = conn.cursor()
|
||||
|
||||
cursor.execute("SELECT filename FROM workflows WHERE id = ?", (workflow_id,))
|
||||
row = cursor.fetchone()
|
||||
conn.close()
|
||||
|
||||
if not row:
|
||||
raise HTTPException(status_code=404, detail="Workflow not found")
|
||||
|
||||
file_path = WORKFLOWS_DIR / row[0]
|
||||
if not file_path.exists():
|
||||
raise HTTPException(status_code=404, detail="Workflow file not found")
|
||||
|
||||
return FileResponse(file_path, media_type="application/json")
|
||||
|
||||
@app.get("/api/integrations")
|
||||
async def get_integrations():
|
||||
"""Get all integrations with usage counts"""
|
||||
conn = sqlite3.connect(DATABASE_PATH)
|
||||
cursor = conn.cursor()
|
||||
|
||||
cursor.execute("SELECT integrations FROM workflows")
|
||||
all_integrations = []
|
||||
for row in cursor.fetchall():
|
||||
integrations = json.loads(row[0])
|
||||
all_integrations.extend(integrations)
|
||||
|
||||
integration_counts = Counter(all_integrations)
|
||||
integrations = [{"name": name, "count": count} for name, count in integration_counts.most_common()]
|
||||
|
||||
conn.close()
|
||||
|
||||
return {"integrations": integrations}
|
||||
|
||||
@app.post("/api/reindex")
|
||||
async def reindex_workflows():
|
||||
"""Reindex all workflows"""
|
||||
try:
|
||||
index_workflows()
|
||||
return {"message": "Workflows reindexed successfully", "status": "success"}
|
||||
except Exception as e:
|
||||
raise HTTPException(status_code=500, detail=f"Reindexing failed: {str(e)}")
|
||||
|
||||
# Initialize workflows on startup
|
||||
if __name__ == "__main__":
|
||||
print("🚀 Starting Unified n8n Workflow Documentation System...")
|
||||
print("📊 Indexing workflows...")
|
||||
index_workflows()
|
||||
print("✅ System ready!")
|
||||
|
||||
uvicorn.run(
|
||||
"unified_app:app",
|
||||
host="0.0.0.0",
|
||||
port=8080,
|
||||
reload=True,
|
||||
log_level="info"
|
||||
)
|
||||
22
unified_docker-compose.yml
Normal file
22
unified_docker-compose.yml
Normal file
@ -0,0 +1,22 @@
|
||||
version: '3.8'
|
||||
|
||||
services:
|
||||
unified-workflows:
|
||||
build:
|
||||
context: .
|
||||
dockerfile: unified_Dockerfile
|
||||
container_name: unified-n8n-workflows
|
||||
ports:
|
||||
- "8080:8080"
|
||||
volumes:
|
||||
- ./static:/app/static
|
||||
- ./unified_workflows.db:/app/unified_workflows.db
|
||||
environment:
|
||||
- PYTHONUNBUFFERED=1
|
||||
restart: unless-stopped
|
||||
healthcheck:
|
||||
test: ["CMD", "curl", "-f", "http://localhost:8080/api/stats"]
|
||||
interval: 30s
|
||||
timeout: 10s
|
||||
retries: 3
|
||||
start_period: 40s
|
||||
14
unified_requirements.txt
Normal file
14
unified_requirements.txt
Normal file
@ -0,0 +1,14 @@
|
||||
fastapi==0.104.1
|
||||
uvicorn[standard]==0.24.0
|
||||
aiofiles==23.2.1
|
||||
jinja2==3.1.2
|
||||
pydantic==2.5.0
|
||||
python-multipart==0.0.6
|
||||
sqlite3
|
||||
pathlib
|
||||
asyncio
|
||||
datetime
|
||||
typing
|
||||
json
|
||||
re
|
||||
collections
|
||||
Loading…
Reference in New Issue
Block a user