masahiro hanawa
Templates by masahiro hanawa
Extract video metadata & auto-upload to YouTube with GPT-4o SEO optimization
Video Metadata Extraction & YouTube Auto-Upload with AI Automatically process video files, extract metadata, generate AI-optimized titles/descriptions/tags, and upload directly to YouTube with proper categorization and thumbnail handling. Key Features YouTube Node Integration: Direct video upload to YouTube with full metadata Binary Data Handling: Proper video and thumbnail binary processing AI-Powered SEO Optimization: Generates engaging titles, descriptions, and tags Video Metadata Extraction: Analyzes video properties (duration, resolution, codec) Thumbnail Processing: Extracts or uploads custom thumbnails Category Auto-Selection: AI determines optimal YouTube category How It Works Video Intake: Receives video file via webhook or cloud storage trigger Metadata Extraction: Analyzes video file for technical properties AI Content Generation: Creates SEO-optimized title, description, and tags Thumbnail Processing: Extracts frame or uses provided thumbnail YouTube Upload: Uploads video with all metadata Post-Upload Processing: Retrieves video ID, creates playlist entry Notification: Sends confirmation with video URL Required Credentials YouTube OAuth2 (for video upload) OpenAI API (for AI metadata generation) Google Drive or Dropbox (optional, for cloud storage triggers) Gmail (for notifications) Google Sheets (for tracking) Unique Features Uses YouTube node for direct video upload (rarely used in templates) Binary data manipulation for video and thumbnail handling AI-generated SEO metadata optimized for YouTube algorithm Category detection using AI classification Merge node with chooseBranch for conditional flows Example Request json { "videoFile": "<binary data>", "projectName": "Product Demo 2024", "targetAudience": "developers", "language": "en", "thumbnailFile": "<binary data>", "playlistId": "PLxxxxxxxx", "publishTime": "2024-01-15T14:00:00Z" } Supported Video Formats MP4, MOV, AVI, MKV, WebM Maximum file size: 128GB (YouTube limit) Recommended: MP4 with H.264 codec Output json { "videoId": "dQw4w9WgXcQ", "videoUrl": "https://youtu.be/dQw4w9WgXcQ", "title": "AI-Generated Title", "description": "SEO-optimized description...", "tags": ["tag1", "tag2", "tag3"], "category": "Science & Technology", "uploadStatus": "processed", "thumbnailUrl": "https://i.ytimg.com/vi/..." }
By masahiro hanawaAutomate event registration and QR check-ins with Google Sheets, Gmail, and Slack
Who is this for? This template is ideal for event organizers, conference managers, and community teams who need an automated participant management system. Perfect for workshops, conferences, meetups, or any event requiring registration and check-in tracking. What this workflow does This workflow provides end-to-end event management with two main flows: Registration Flow: ⦁ Receives participant registration via webhook ⦁ Generates unique ticket ID and stores in Google Sheets ⦁ Creates QR code using the QR Code node ⦁ Sends confirmation email with QR code attached Check-in Flow: ⦁ Scans and decodes QR code at venue entrance ⦁ Validates ticket against participant database ⦁ Blocks duplicate check-ins with clear error messages ⦁ Sends Slack notification for VIP arrivals ⦁ Returns real-time attendance statistics Setup Create a Google Sheet with columns: Ticket ID, Event ID, Name, Email, Ticket Type, Registered At, Checked In, Check-in Time Connect your Google Sheets and Gmail credentials Configure Slack for VIP notifications Set up the webhook URLs in your registration form Requirements ⦁ Google Sheets (participant database) ⦁ Gmail account (confirmation emails) ⦁ Slack workspace (VIP notifications) How to customize ⦁ Add capacity limits by checking row count before registration ⦁ Modify QR code size and format in the QR Code node ⦁ Add additional ticket types beyond VIP/standard ⦁ Integrate with payment systems for paid events
By masahiro hanawaTranslate and localize multilingual content with DeepL and GPT-4o-mini
Translate and localize content using DeepL and GPT-4o-mini Managing high-quality translations across multiple languages often requires more than just machine translation; it requires cultural context and quality assurance. This workflow automates the entire pipeline, from initial translation to AI-driven quality scoring and cultural localization. Who is this for? Content Teams: To automate the first draft and review process for blog posts or documentation. Marketing Agencies: To localize campaign copy for international markets quickly. Product Managers: To manage UI/UX copy across different regions with consistent glossary support. How it works Content Intake: A Webhook receives the source text and a list of target languages. Language Detection & Validation: The workflow identifies the source language and validates the requested target codes. Parallel Processing: Using the Split Out node, the workflow processes each target language simultaneously. DeepL Translation: High-quality neural machine translation is performed for each language. AI Quality Review: GPT-4o-mini acts as a professional linguist, scoring the translation on accuracy, fluency, and style, and flagging any issues. Cultural Localization: A specialized node applies region-specific formatting for dates and currencies. Aggregation & Reporting: All results are unified, logged to Google Sheets, emailed via Gmail, and returned as a JSON response to the initial requester. How to set up Credentials: Connect your DeepL API, OpenAI, Google Sheets, and Gmail accounts. Google Sheets: Create a sheet with headers: Job ID, Source Text, Languages, Avg Quality, and Completed. Paste the Sheet ID into the Google Sheets node. Webhook: Use the production URL in your CMS or app to trigger the workflow with a POST request. Requirements DeepL API Key (Free or Pro) OpenAI API Key (for GPT-4o-mini) Google Account (for Sheets and Gmail) How to customize Adjust AI Rubric: Modify the "AI Quality Review" prompt to focus on specific brand voice guidelines or technical terminology. Glossary Support: Update the DeepL node to include specific Glossary IDs for industry-specific jargon. Localization Rules: Add more regions or specific formatting rules (like measurement conversions) in the "Apply Localization" Code node.
By masahiro hanawa