Workflow Templates

An AI inbox labelling manager that has reasoning attached to the ChatGPT inbox manager within n8n. Super simple yet highly effective automation. How it works: • Monitors Gmail inbox → triggers workflow when a new unread email is received. • Fetches email details including subject, body, and sender information. • Sends email content to OpenAI → uses AI to determine the most relevant label based on predefined rules. • AI uses a think tool → justifies why it selected that specific label. • Retrieves Gmail label IDs → matches AI’s choice to correct Gmail label for that email. • Adds the chosen label (e.g., Positive reply, priority email, etc) to the email automatically → optionally marks it as read/starred. • Continues monitoring → every new email is processed automatically, keeping the inbox organized. Set Up Steps • Connect Gmail account to the Gmail Node • Create OpenAI account & API key → go to OpenAI and sign up or log in. Once logged in, click Dashboard in the top menu. On the left sidebar, find API Keys and click Create new key. Copy this key — you’ll need it for n8n. Check your account balance → in the top-right, click your profile icon → Your Profile → Billing. Make sure your account has funds (e.g., $5 USD is enough for testing) so the API requests can run. Do these steps through this link: https://platform.openai.com/ • Retrieve Gmail label IDs → use the Gmail “get labels” node to fetch IDs for all labels you want the AI to use. • Use OpenAI (ChatGPT) node → set up system and user prompts with rules describing each label, and include the label IDs (Important). • Test the workflow → send example emails, check labeling, and refine AI prompt or label rules if needed. • Tip: Pin trigger data for testing (Gmail node "Watch Incoming Emails") → re-use the same email record to speed up testing without sending multiple emails. About this automation Handles multiple labels → adding new labels only requires updating the AI prompt (no extra nodes). Scales easily → works for any number of Gmail labels without cluttering the workflow. For a complete rundown on how to set this up watch my YouTube tutorial linked below See full video tutorial here: https://www.youtube.com/watch?v=7nda4drHcWw My LinkedIn: https://www.linkedin.com/in/seb-gardner-5b439a260/

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Gmail Auto-Reply with AI Automatically draft smart email replies using ChatGPT. Reclaim your time typing the same responses again and again. Who is this for? If you're overwhelmed with emails and constantly repeating yourself in replies, this workflow is for you. Whether you're a freelancer, business owner, or team lead, it saves you time by handling email triage and drafting replies for you. What does it solve? This workflow reads your unread Gmail messages and uses AI to: Decide whether the email needs a response Automatically draft a short, polite reply when appropriate Skip spam, newsletters, or irrelevant emails Save the AI-generated reply as a Gmail draft (you can edit it before sending) It takes email fatigue off your plate and keeps your inbox moving. How it works Trigger on New Email: Watches your Gmail inbox for unread messages. AI Agent Review: Analyzes the content to decide if a reply is needed. OpenAI ChatGPT: Drafts a short, polite reply (under 120 words). Create Gmail Draft: Saves the response as a draft for you to review. Label It: Applies a custom label like Action so you can easily find AI-handled emails. How to set up? Connect credentials: Gmail (OAuth2) OpenAI (API key) Create the Gmail label: In your Gmail, create a label named Action (case-sensitive). How to customize this workflow to your needs Change the AI prompt**: Add company tone, extra context, or different reply rules. Label more intelligently**: Add conditions or labels for “Newsletter,” “Meeting,” etc. Adjust frequency**: Change how often the Gmail Trigger polls your inbox. Add manual review**: Route drafts to a team member before sending.

Find which AI search topics each domain owns with SE Ranking and GPT Who is this for SEO teams wanting to understand topic-level AI search dominance across competitors Content strategists building editorial plans around AI visibility gaps Marketing managers benchmarking brand presence across AI search topics What this workflow does Pulls AI search prompts for your domain and up to 2 competitors, then uses GPT to cluster them into topics and reason about which domain owns each one — turning a flat list of prompts into a strategic competitive topic map. What you'll get AI search leaderboard with share of voice across ChatGPT, Perplexity, Gemini, AI Overviews, and AI Mode A topic-level competitive map showing which domain wins each topic area Prompt counts per domain per topic so you can see exactly where you're ahead or behind A one-line actionable insight per topic to guide your content strategy An overall winner and competitive summary saved to Google Sheets How it works Add your domain and 2 competitors in the form — pulls the AI search leaderboard across all 5 LLM engines Fetches up to 10 prompts per domain (both brand and target) for you and each competitor Filters competitor prompts to keep only SEO-relevant topics — removes noise like gaming or sports Sends all prompts to GPT with instructions to cluster them into topics and identify which domain appears most per topic GPT reasons about dominance per cluster and returns a structured competitive topic map Saves the leaderboard and topic map to separate tabs in Google Sheets Requirements SE Ranking community node installed SE Ranking API token (Get one here) OpenAI API key Google Sheets account (optional) Setup Install the SE Ranking community node Add your SE Ranking API credentials Add your OpenAI API credentials Connect your Google Sheets account and set a spreadsheet URL in each export node Activate the workflow — n8n generates a unique form URL you can share or embed Open the form, fill in your domain and competitors, and the workflow runs automatically Customization Change prompts_limit in the Configuration node to fetch more or fewer prompts per domain Change source in the Configuration node for a different regional database (us, uk, de, fr, es, etc.) Edit the system prompt in the GPT node to adjust how topics are clustered or how insights are written

Overview Auto-translate YouTube uploads to Japanese and post to Slack (DeepL + Slack) Who’s it for Marketing or community teams that follow English-speaking creators but share updates with Japanese audiences; language learners who want JP summaries of newly released videos; internal comms teams curating industry channels for a JP workspace. What it does This workflow detects new YouTube uploads, retrieves full metadata, translates the title and description into Japanese using DeepL, and posts a formatted message to a Slack channel. It also skips non-English titles to avoid unnecessary translation. How it works ・RSS watches a channel for new items. ・YouTube API fetches the full snippet (title/description). ・Text is combined into a single payload and sent to DeepL. ・The translated result + original metadata is merged and posted to Slack. Requirements ・YouTube OAuth (for reliable snippet retrieval) ・DeepL API key (Free or Pro) ・Slack OAuth How to set up ・Duplicate this template. ・Open the Config (Set) node and fill in YT_CHANNEL_ID, TARGET_LANG, SLACK_CHANNEL. ・Connect credentials for YouTube, DeepL, and Slack (don’t hardcode API keys in HTTP nodes). ・Click Execute workflow and verify one sample post. How to customize ・Change TARGET_LANG to any language supported by DeepL. ・Add filters (exclude Shorts, skip videos under N characters). ・Switch to Slack Blocks for richer formatting or thread replies. ・Add a fallback translator or retry logic on HTTP errors. Notes & limits DeepL Free/Pro have different endpoints/quotas and monthly character limits. YouTube and Slack also enforce rate limits. Keep credentials in n8n’s credential store; do not commit keys into templates. Rotate keys if you accidentally exposed them.

📸💰 Log receipt transactions from Telegram images to Excel using OCR and AI OCR + AI + Duplicate Protection (n8n Workflow) Overview This workflow automatically converts receipt images or payment proof sent via Telegram into structured financial records stored in Excel 365. Core flow: Take Photo → OCR → AI Structuring → Validation → Duplicate Check → Append to Excel The system is designed to reduce manual data entry errors and improve financial visibility by turning unstructured receipt images into reliable financial records. ⸻ How it works This workflow captures receipt images sent to a Telegram bot and converts them into structured financial records in Excel. When a user sends an image, the workflow downloads the file and extracts the text using OCR. The extracted text is then analyzed by an AI model (OpenAI or Gemini) to identify key transaction details such as date, amount, merchant, and transaction type. The workflow validates the extracted data and generates a unique duplicate key. It then checks Excel to ensure the transaction has not already been recorded. If no duplicate is found, the transaction is appended to the Excel sheet. The user receives a confirmation message in Telegram indicating whether the transaction was successfully recorded or rejected due to missing data or duplication. Workflow Nodes The workflow contains the following nodes: Telegram Trigger Edit Fields (extract chat_id and image_id) Condition (validate image exists) Telegram Get File Tesseract OCR AI Agent (ChatGPT / Gemini) Edit Field (JSON Output Parsing) Excel 365 – Get Configuration Edit Field – Normalize & Generate duplicate_key Condition – Validate required fields Excel 365 – Lookup duplicate_key Condition – Duplicate Check Excel 365 – Append Transaction Telegram – Send Confirmation Message 🧠 What This Workflow Does This workflow automatically: Captures receipt images from Telegram Extracts text using OCR Converts OCR text into structured transaction data using AI Validates required financial fields Prevents duplicate transaction entries Saves valid records into Excel Sends confirmation messages to Telegram Setup steps Create a Telegram bot using @BotFather and copy the Bot Token. Add Telegram credentials in n8n using the Bot Token. Prepare an Excel file in OneDrive or SharePoint with a TRANSACTIONS sheet. Configure Microsoft Excel credentials in n8n. Add either OpenAI or Google Gemini credentials for the AI parsing step. If running self-hosted n8n, ensure Tesseract OCR is installed. Activate the workflow and send a receipt image to the Telegram bot to test. 🎯 Key Benefits • Reduce financial recording errors • Eliminate repetitive manual data entry • Improve cashflow visibility • Simple photo-based financial recording • Scalable foundation for AI-powered financial automation 🚀 Use Cases This workflow is useful for: • Small business owners • Online sellers • Freelancers • Finance administrators • Personal expense tracking 📌 Notes • Duplicate detection is based on a composite transaction key • OCR accuracy depends on image quality • AI parsing improves recognition compared to OCR-only approaches 🧱 Requirements To run this workflow you need: • n8n (Cloud or Self-Hosted) • Telegram Bot Token • Microsoft Excel 365 Account • OpenAI API Key or Google Gemini API Key • Tesseract OCR (for self-hosted installations) 🏁 Result After setup, users can simply send receipt photos to Telegram and the workflow will automatically convert them into structured financial records stored in Excel. No manual bookkeeping required. Built for automation lovers, small businesses, and teams who want simple but powerful financial tracking using n8n.

LinkedIn Content Generation Workflow Summary Automated workflow that transforms Notion content notes into publication-ready LinkedIn posts using Claude AI. Monitors Notion database and generates multiple variations based on structured outlines, so that the author can pick the one they like most. Use Cases Automate LinkedIn content creation from content planning database. Generate multiple post variations from a single outline. Maintain consistent voice and formatting across all posts. Scale content production while preserving quality. How It Works Trigger - Monitors Notion "Content Plan" database hourly for updates. Conditional Check - Verifies "LinkedIn Post (Main)" tag and "Ready for Writing" status Main Post - Claude generates single post from project name and notes Outline Analysis - Parallel process creates 3 distinct post concepts with different angles Multi-Post Generation - Each outline becomes a complete LinkedIn post Save to Notion - All posts automatically saved to database AI Setup: Claude Sonnet 4.5 (claude-sonnet-4-5-20250929) Main post: temperature 0.8 (creative) Multi-post: default temperature (consistent) How to Use Setup a content database in notion, or link your existing one: Use field mapping as outlined below or update field mapping in n8n template. Add content to Notion: Project name (topic) Notes (article content/key points) Tag: "LinkedIn Post (Main)" Status: "Ready for Writing" Workflow triggers automatically (hourly check) Retrieve posts from Notion database Review and publish to LinkedIn Requirements Credentials: Notion API (access to Content Plan database) Anthropic API key OpenAI API Key Notion Database: Connect Database Required properties: Project name (text) Notes (rich text) Tags (multi-select with "LinkedIn Post (Main)") Status (select with "Ready for Writing") Notes: Posts optimized for 1800 character limit Generates both single posts and multi-angle variations

Using the power and ease of Telegram, send a simple text or audio message to a bot with a request to add a new Task to your Notion Tasks database. How it works ChatGPT is used to transacribe the audio or text message, parse it, and determine the title to add as a new Notion Task. You can optionally include a "do date" as well and ChatGPT will include that when creating the task. Once complete you will receive a simple confirmation message back. Minimal Setup Required Just follow n8n's instructions on how to connect to Telegram and create your own chatBot, provide the chatID in the 2 Telegram nodes, and you're finished! A few optional settings include tweaking the ChatGPT system prompt (unnecessary) and the timezone for your Notion Task(s).

Who’s it for This workflow is for marketers, founders, and content strategists who want to identify business opportunities by analyzing Reddit discussions. It’s ideal for B2B, SaaS, and tech professionals looking for fresh LinkedIn post ideas or trend insights. How it works / What it does This workflow automatically: Fetches Reddit posts & comments based on a selected subreddit and keyword. Extracts pain points & insights using OpenAI (ChatGPT) to identify key frustrations and trends. Generates LinkedIn post ideas with headlines, hooks, and CTAs tailored for professional audiences. Saves all results into Google Sheets for easy tracking, editing, and sharing. It uses AI to turn unstructured Reddit conversations into actionable content marketing opportunities. How to set up Clone this workflow in your n8n instance. Configure credentials: Reddit OAuth2 (for fetching posts & comments) OpenAI API key (no hardcoding—use credentials in n8n) Google Sheets OAuth2 (for output) Run the workflow or trigger it using the built-in Form Trigger (provide subreddit & keyword). Check the generated Google Sheet for analyzed insights and post suggestions. Requirements n8n (self-hosted or cloud) Reddit account with API credentials OpenAI API key (GPT-4o recommended) Google Sheets account How to customize the workflow Change the AI prompt to adjust tone or depth of insights. Add filtering logic to target posts with higher engagement. Modify the Google Sheets output schema to include custom fields. Extend it with Slack/Email notifications to instantly share top insights.

🎙️ n8n Workflow: Voice Message Transcription with Access Control This n8n workflow enables automated transcription of voice messages in Telegram groups with built-in access control and intelligent fallback mechanisms. It's designed for teams that need to convert audio messages to text while maintaining security and handling various audio formats. 📌 Section 1: Trigger & Access Control ⚡ Receive Message (Telegram Trigger) Purpose: Captures incoming messages from users in your Telegram group. How it works: When a user sends a message (voice, audio, or text), the workflow is triggered and the sender's information is captured. Benefit: Serves as the entry point for the entire transcription pipeline. 🔐 Sender Verification Purpose: Validates whether the sender has permission to use the transcription service. Logic: Check sender against authorized users list If authorized → Proceed to next step If not authorized → Send "Access denied" message and stop workflow Benefit: Prevents unauthorized users from consuming AI credits and accessing the service. 📌 Section 2: Message Type Detection 🎵 Audio/Voice Recognition Purpose: Identifies the type of incoming message and audio format. Why it's needed: Telegram handles different audio types with different statuses: Voice notes (voice messages) Audio files (standard audio attachments) Text messages (no audio content) Process: Check if message contains audio/voice content If no audio file detected → Send "No audio file found" message If audio detected → Assign file ID and proceed to format detection 🧩 File Type Determination (IF Node) Purpose: Identifies the specific audio format for proper processing. Supported formats: OGG (Telegram voice messages) MPEG/MP3 MP4/M4A Other audio formats Logic: If format recognized → Proceed to transcription If format not recognized → Send "File format not recognized" message Benefit: Ensures compatibility with transcription services by validating file types upfront. 📌 Section 3: Primary Transcription (OpenAI) 📥 File Download Purpose: Downloads the audio file from Telegram for processing. 🤖 OpenAI Transcription Purpose: Transcribes audio to text using OpenAI's Whisper API. Why OpenAI: High-quality transcription with cost-effective pricing. Process: Send downloaded file to OpenAI transcription API Simultaneously send notification: "Transcription started" If successful → Assign transcribed text to variable and proceed If error occurs → Trigger fallback mechanism Benefit: Fast, accurate transcription with multi-language support. 📌 Section 4: Fallback Transcription (Gemini) 🛟 Gemini Backup Transcription Purpose: Provides a safety net if OpenAI transcription fails. Process: Receives file only if OpenAI node returns an error Downloads and processes the same audio file Sends to Google Gemini for transcription Assigns transcribed text to the same text variable Benefit: Ensures high reliability—if one service fails, the other takes over automatically. 📌 Section 5: Message Length Handling 📏 Text Length Check (IF Node) Purpose: Determines if the transcribed text exceeds Telegram's character limit. Logic: If text ≤ 4000 characters → Send directly to Telegram If text > 4000 characters → Split into chunks Why: Telegram has a 4,000-character limit per message. ✂️ Text Splitting (Code Node) Purpose: Breaks long transcriptions into 4,000-character segments. Process: Receives text longer than 4,000 characters Splits text into chunks of ≤4,000 characters Maintains readability by avoiding mid-word breaks Outputs array of text chunks 📌 Section 6: Response Delivery 💬 Send Transcription (Telegram Node) Purpose: Delivers the transcribed text back to the Telegram group. Behavior: Short messages:** Sent as a single message Long messages:** Sent as multiple sequential messages Benefit: Users receive complete transcriptions regardless of length, ensuring no content is lost. 📊 Workflow Overview Table | Section | Node Name | Purpose | |---------|-----------|---------| | 1. Trigger | Receive Message | Captures incoming Telegram messages | | 2. Access Control | Sender Verification | Validates user permissions | | 3. Detection | Audio/Voice Recognition | Identifies message type and audio format | | 4. Validation | File Type Check | Verifies supported audio formats | | 5. Download | File Download | Retrieves audio file from Telegram | | 6. Primary AI | OpenAI Transcription | Main transcription service | | 7. Fallback AI | Gemini Transcription | Backup transcription service | | 8. Processing | Text Length Check | Determines if splitting is needed | | 9. Splitting | Code Node | Breaks long text into chunks | | 10. Response | Send to Telegram | Delivers transcribed text | 🎯 Key Benefits 🔐 Secure access control: Only authorized users can trigger transcriptions 💰 Cost management: Prevents unauthorized credit consumption 🎵 Multi-format support: Handles various Telegram audio types 🛡️ High reliability: Dual-AI fallback ensures transcription success 📱 Telegram-optimized: Automatically handles message length limits 🌍 Multi-language: Both AI services support numerous languages ⚡ Real-time notifications: Users receive status updates during processing 🔄 Automatic chunking: Long transcriptions are intelligently split 🧠 Smart routing: Files are processed through the optimal path 📊 Complete delivery: No content loss regardless of transcription length 🚀 Use Cases Team meetings:** Transcribe voice notes from team discussions Client communications:** Convert client voice messages to searchable text Documentation:** Create text records of verbal communications Accessibility:** Make audio content accessible to all team members Multi-language teams:** Leverage AI transcription for various languages

What it's for: This is a base template for anyone trying to develop a Slack bot AI Agent. This base allows for multiple inputs (Voice, Picture, Video, and Text inputs) to be processed by an AI model of their choosing to a get a User started. From here, the User may connect any tools that they see fit to the AI Agent for their n8n workflows. NOTE: This build is specifically for integrating a Slack bot into a CHAT Channel If you want to allow the Slack bot to be integrated into the whole workspace, you'll need to adjust some of the nodes and bot parameters How it works: Input: Slack message mentioning a bot in a chat channel n8n Processing: Switch node determines the type: Voice Message Picture Message Video Message Text Message (Currently uses OpenAI and Gemini to analyze Voice/Photo/Video content but feel free to change these nodes with other models) AI Agent Proccessing: LLM of your choosing examines message and based on system prompt, generates an output Output: AI Output is sent back in Slack Message How to use: 1. Create your Slack bot and generate access token This part will be longest part of the guide but feel free to Youtube search "How to install Slack AI agent" or soemthing similar in case it's hard to follow Sign in to the Slack website then go to: https://api.slack.com/apps/ Click "Create App" (Top Right Corner) Choose "From Scratch" Enter desired name of App (bot) and desired workspace Go to "OAuth and Permissions" tab on the left side of the webpage Scroll to "Bot Token Scopes" and Add Permissions: app_metions:read channels:history channels:join channels:read chat:write files:read links:read links:write (Feel free to add other permissions here. These are just the ones that will be needed for the automation to work) Next, go to "Event Subscriptions" and paste your n8n webhook URL (Find webhook URL by clicking on the Slack trigger node and there should be a dropdown for webhook URL at the very top) Go back to "OAuth & Permissions" Tab and install your bot to the Slack workspace (should be a green button under the "Bot User OAuth Token" (Remember where this token is for later because you'll need it to create the n8n credentials) Add the bot to your channel by going to your channel, then type "@[your bot name]" Should be a message from Slack to add bot to Channel Congrats for following along, you've added the bot to your channel! 2. Create Credentials in n8n Open Slack trigger node Click create credential Paste access token (If you followed the steps above, it'll be under "OAuth & Permissions" -> Copy the "Bot User OAuth Token" and paste it in n8n accesss Save 3. Add Bot Token to HTTP Request nodes Open HTTP Request Nodes (Nodes under the "Downlaod" Note - Scroll down and paste your Bot Access token under "Header Parameters". Should be a placeholder "[Your bot access token goes here]". NOTE**: Replace everything, including the square brackets Do not** remove "Bearer". Only replace the placeholder. Finalized Authorization value should be: "Bearer + [Your bot access token]" NOT "[Your bot access token ONLY]" 4. Change ALL Slack nodes to your Slack Workspace and Channel Open the nodes, change workspace to your workspace Change channel to your channel Do this for all nodes 5. Create LLM access token (Different per LLM but search your LLM + API in google) (You will have to create an account with the LLM platform) Buy credits to use LLM API Generate Access token Paste token in LLM node Choose your model Requirements: Slack Bot Access Token Google Gemini Access Token (For Picture and Video messages) OpenAI Access Token (For Voice messages) LLM Access Token (Your preference for the AI Agent) Customizing this workflow: To personalize the AI Output, adjust the system prompt (give context or directions on the AI's role) Add tools to the AI agent to give it more utility besides a personalied LLM (Example: Calendars, Databases, etc).

This workflow automates news aggregation and summarization by fetching relevant articles from Gnews.io and using AI to create concise, professional summaries delivered via Slack What Makes This Different: Real-Time News Aggregation** - Fetches current news articles from Gnews.io API based on user-specified topics AI-Powered Summarization** - Uses GPT-4.1 to intelligently select and summarize the most relevant articles Professional Formatting** - Generates clean, readable summaries with proper dates and article links Form-Based Input** - Simple web form interface for topic specification Automated Delivery** - Sends summarized news directly to Slack for immediate consumption Intelligent Filtering** - AI selects the top 15 most relevant articles from search results Key Benefits of Automated News Summarization: Time Efficiency** - Transforms hours of news reading into minutes of focused summaries Comprehensive Coverage** - AI ensures all important financial and business developments are captured Professional Quality** - Generates publication-ready summaries with proper formatting Real-Time Updates** - Always delivers the latest news on any topic Centralized Access** - All news summaries delivered to one Slack channel Customizable Topics** - Search for news on any subject matter Who's it for This template is designed for business professionals, financial analysts, content creators, journalists, and anyone who needs to stay updated on specific topics without spending hours reading through multiple news sources. It's perfect for professionals who want to stay informed about industry developments, market trends, or any specific subject matter while maintaining productivity. How it works / What it does This workflow creates an automated news summarization system that transforms topic searches into professional news summaries. The system: Receives topic input through a simple web form interface Fetches news articles from Gnews.io API based on the specified topic Maps article data to prepare for AI processing Uses AI to select the 15 most relevant articles related to financial advancements, tools, research, and applications Generates professional summaries with clear, readable language and proper formatting Includes article links and current date for complete context Delivers summaries via Slack notification for immediate review Key Innovation: Intelligent News Curation - Unlike basic news aggregators, this system uses AI to intelligently filter and summarize only the most relevant articles, saving time while ensuring comprehensive coverage of important developments. How to set up 1. Configure Form Trigger Set up n8n form trigger with "topic" field (required) Configure form title as "News Search" Test form submission functionality Ensure proper data flow to subsequent nodes 2. Configure Gnews.io API Get your API key**: Sign up at gnews.io and obtain your API key from the dashboard Add API key to workflow**: In the "Get GNews articles" HTTP Request node, replace "ADD YOUR API HERE" with your actual Gnews.io API key Example configuration**: { "q": "{{ $json.topic }}", "lang": "en", "apikey": "your-actual-api-key-here" } Configure search parameters**: Ensure language is set to "en" for English articles Test API connectivity**: Run a test execution to verify news articles are returned correctly 3. Configure OpenAI API Set up OpenAI API credentials in n8n Ensure proper API access and quota limits Configure the GPT-4.1 Model node for AI summarization Test AI model connectivity and response quality 4. Configure Slack Integration Set up Slack API credentials in n8n Configure Slack channel ID for news delivery Set up proper message formatting for news summaries Test Slack notification delivery 5. Test the Complete Workflow Submit test form with sample topic (e.g., "artificial intelligence") Verify Gnews.io returns relevant articles Check that AI generates appropriate news summaries Confirm Slack notification contains formatted news summary Requirements n8n instance** with form trigger and HTTP request capabilities OpenAI API** access for AI-powered news summarization Gnews.io API** credentials for news article fetching Slack workspace** with API access for news delivery Active internet connection** for real-time API interactions How to customize the workflow Modify News Search Parameters Adjust the number of articles to summarize (currently set to 15) Add more search depth options or date ranges Implement language filtering for different regions Add news source filtering or preferences Enhance AI Capabilities Customize AI prompts for specific industries or niches Add support for multiple languages Implement different summary styles (brief, detailed, bullet points) Add content quality scoring and relevance filtering Expand News Sources Integrate with additional news APIs (NewsAPI, Bing News, etc.) Add support for RSS feed integration Implement trending topic detection Add competitor news monitoring Improve News Delivery Add email notifications alongside Slack Implement news scheduling capabilities Add news approval workflows Implement news performance tracking Business Features Add news analytics and engagement metrics Implement A/B testing for different summary formats Add news calendar integration Implement team collaboration features for news sharing Key Features Real-time news aggregation** - Fetches current news articles from Gnews.io API AI-powered summarization** - Uses GPT-4.1 to intelligently select and summarize relevant articles Professional formatting** - Generates clean, readable summaries with proper dates and links Form-based input** - Simple interface for topic specification Automated workflow** - End-to-end automation from topic input to news delivery Intelligent filtering** - AI selects the most relevant articles from search results Slack integration** - Centralized delivery of news summaries Scalable news processing** - Handles multiple topic searches efficiently Technical Architecture Highlights AI-Powered News Summarization OpenAI GPT-4.1 integration** - Advanced language model for intelligent news summarization Content filtering** - AI selects the 15 most relevant articles from search results Professional formatting** - Generates clean, readable summaries with proper structure Quality consistency** - Maintains professional tone and formatting standards News API Integration Gnews.io API** - Comprehensive news search with article extraction Real-time data** - Access to current, relevant news articles Content mapping** - Efficiently processes article data for AI analysis Search optimization** - Efficient query construction for better news results Form-Based Input System n8n form trigger** - Simple, user-friendly input interface for topic specification Data validation** - Ensures required topic field is properly filled Parameter extraction** - Converts form data to search parameters Error handling** - Graceful handling of incomplete or invalid inputs News Delivery System Slack integration** - Professional news summary delivery Formatted output** - Clean, readable summaries with dates and article links Centralized access** - All news summaries delivered to one location Real-time delivery** - Immediate notification of news summaries Use Cases Financial analysts** needing to stay updated on market developments and industry news Business professionals** requiring daily news summaries on specific topics Content creators** needing current information for articles and social media posts Journalists** requiring comprehensive news coverage on specific subjects Research teams** needing to track developments in their field of expertise Investment professionals** requiring real-time updates on market trends Academic researchers** needing to stay informed about industry developments Corporate communications** teams requiring news monitoring for crisis management Business Value Time Efficiency** - Reduces news reading time from hours to minutes Cost Savings** - Eliminates need for manual news monitoring and summarization Comprehensive Coverage** - AI ensures all important developments are captured Scalability** - Handles unlimited topic searches without additional resources Quality Assurance** - AI ensures professional-quality summaries every time Real-Time Updates** - Always delivers the latest news on any topic Research Integration** - Incorporates current information for relevant, timely insights This template revolutionizes news consumption by combining AI-powered summarization with real-time news aggregation, creating an automated system that delivers professional-quality news summaries on any topic from a simple form submission.

Overview This workflow turns photos sent to a LINE bot into tiny AI-generated diary entries and saves everything neatly in Google Drive. Each time a user sends an image, the workflow creates a timestamped photo file and a matching text file with a short diary sentence, stored inside a year/month folder structure (KidsDiary/YYYY/MM). It’s a simple way to keep a lightweight visual diary for kids or daily life without manual typing. LINE Photo to AI Diary with Goo… Who this is for Parents who want to archive kids’ photos with a short daily comment People who often send photos to LINE and want them auto-organized in Drive Anyone who prefers a low-friction, “take a photo and forget” style diary How it works Trigger: A LINE Webhook receives an image message from the user. Extract metadata: The workflow extracts the messageId and replyToken. Download image: It calls the LINE content API to fetch the image as binary. AI diary text: OpenAI Vision generates a one-sentence, diary-style caption (about 50 Japanese characters). Folder structure: A KidsDiary/YYYY/MM folder is created (or reused) in Google Drive. Save files: The photo is saved as YYYY-MM-DD_HHmmss.jpg and the diary text as YYYY-MM-DD_HHmmss_diary.txt in the same folder. Confirm on LINE: The bot replies to the user that the photo and diary have been saved. How to set up Connect your LINE Messaging API credentials in the HTTP Request nodes. Connect your Google Drive credential in the Google Drive nodes and choose a root folder. Make sure the webhook URL is correctly registered in the LINE Developers console. Customization ideas Change the AI prompt to adjust tone (e.g., more playful, more sentimental). Localize the diary language or add an English translation. Add a second branch to post the saved diary entry to Slack, Notion, or email. Organize Google Drive folders by child’s name instead of only by date.