Workflow Templates

This workflow automates the process of creating and posting Instagram Reels, combining Google Drive, AI, Airtable, and the Facebook Graph API. It supports two content creation paths: Scheduled Random Video Selection & Posting Selects a random video from a Google Drive folder named "Random video mover" based on a schedule. Moves the video to a processing folder for posting. Manual Upload Trigger & Posting Watches a specific Google Drive folder ("n8n reels automation on instagram"). Triggers the workflow when a new video is uploaded. Core Process (applies to both paths) Download Video from Google Drive. AI Caption Generation with Google Gemini, using the file name as context. The AI creates concise captions with hashtags and a call-to-action. Airtable Logging to store video name, caption, and URL. Instagram Reels Posting via the Facebook Graph API. Recent Change In early 2025, Meta tightened its requirements for video_url and image_url parameters. URLs must now be direct, public links to the raw media file with no redirects or authentication. Google Drive links no longer work. Our Fix Store the binary file locally on the n8n server at /tmp/video.mp4. Serve the file through a public n8n webhook with the correct Content-Type. Use the webhook URL in the Facebook Graph API request. Upload succeeds without the “Media download has failed” error. Cleanup Deletes the temporary file after posting. Benefits Saves time with full automation. Improves engagement through AI-generated captions. Keeps content organized in Airtable. Works with Meta’s updated API requirements by hosting files directly from the n8n server.

Transform simple ideas into viral-ready Bigfoot vlogs! This automated workflow creates charming 8-scene video content featuring "Sam" the Bigfoot - a lovable, outdoorsy character inspired by popular YouTube adventure channels. How It Works The workflow transforms your creative concept into professional video content through three automated stages: Story Generation - AI creates an 8-scene narrative arc featuring Sam the Bigfoot, complete with character-consistent dialogue and engaging plot development Human Approval - Review and approve the generated storyline via Slack before proceeding to video production Video Production - Each scene is automatically converted into 8-second video clips using Google's VEO 3 AI, then uploaded to Google Drive for easy access Required Credentials Anthropic API - Add your Claude API key for story generation FAL API - Configure your FAL.ai key for VEO 3 video generation Slack OAuth - Set up Slack app with channel permissions for approvals Google Drive OAuth - Connect your Google Drive for video storage Configuration Steps Import the workflow into your n8n instance Update Slack channel ID in the notification nodes to match your desired channel Set Google Drive folder - Update the folder ID where videos should be stored Test the form trigger - The workflow starts with a web form for video ideas Customize character (optional) - Modify Sam's personality in the narrative prompts

**Content engine that ships fresh, SEO-ready articles every single day. ** Workflow: ⸻ Layout Blueprint • Purpose: Define content structure before writing begins. • What’s Included: • Search intent mapping • Internal link planning • Call-to-action (CTA) placement • Benefit: Ensures consistency, SEO alignment, and content goals are baked in early. ⸻ AI-Assisted Drafting • Tool: GPT generates the first draft. • Editor’s Role: • Focus on depth and accuracy • Align tone and style with existing site content • Context-Aware: Pulls insights from top-ranking articles already live on the site. ⸻ SEO Validation • Automated Checks for: • Keyword coverage • Readability scoring • Schema markup • Internal/external link quality • Outcome: Each piece is validated before hitting publish. ⸻ Media Production • Process: AI auto-generates relevant images. • Delivery: Visual assets are automatically added to the CMS library. ⸻ Optional Human Review: Team feedback via Slack or Teams if needed. ⸻ Automated Publishing • Action: Instantly publishes content to Webflow once approved. • Result: A fully streamlined pipeline from draft to live with minimal manual steps.

Spotify to YouTube Playlist Synchronization A workflow that maintains a YouTube playlist in sync with a Spotify playlist, featuring smart video matching and persistent synchronization. Key Features One-way Sync**: Spotify playlist → YouTube playlist (additions and deletions) Continuous Monitoring**: Automatic synchronization (every hour by default, but you can put any time you want) Smart Video Matching**: Considers video length and content relevance Auto-Recovery**: Automatically handles deleted YouTube videos Database Backup**: Persistent storage using Supabase Prerequisites Supabase project with the following table structure: CREATE TABLE IF NOT EXISTS musics ( id TEXT PRIMARY KEY, title TEXT NOT NULL, artist TEXT NOT NULL, duration INT8 NOT NULL, youtube_video_id TEXT, to_delete BOOLEAN DEFAULT FALSE ); Empty YouTube playlist (recommended as duplicates are not handled) Configured credentials for YouTube, Spotify, and Supabase APIs Properly set variables in all "variables" nodes (variables, variables1, variables2, variables3, variables4 (all the same)) Activate the workflow !

Who is this for? This template is for everyone who manages their blog entries in Notion and want to have an easy way to transform them to Webflow. What this workflow does This workflow syncs your blog posts saved in a Notion Database once a day to Webflow. Sync Notion properties, rich text and cover image with your collection. Works with most elements: H1, H2, H3, normal text, bold text, italic text, links, quotes, bulleted lists, numbered lists, and images (under 4MB). Set up steps Connect your accounts. Add a "slug" field in Notion. Add a "Sync to Webflow?" checkbox in Notion. Run a test and map your collection data. Whenever the workflow runs, all the checked posts will be updated in the Webflow collection, whether it's a new post or an existing one.

Who this template is for This template is for researchers, students, professionals, or content creators who need to quickly extract and summarize key insights from PDF documents using AI-powered analysis. Use case Converting lengthy PDF documents into structured, digestible summaries organized by topic with key insights. This is particularly useful for processing research papers, reports, whitepapers, or any document where you need to quickly understand the main topics and extract actionable insights without reading the entire document. How this workflow works Document Upload: Receives PDF files through a POST endpoint at /ai_pdf_summariser File Validation: Checks that the PDF is under 10MB and has fewer than 20 pages to meet API limits Content Extraction: Extracts text content from the PDF file AI Analysis: Uses OpenAI's GPT-4o-mini to analyze the document and break it down into distinct topics Insight Generation: For each topic, generates 3 key insights with titles and detailed explanations Format Response: Converts the structured data into markdown format for easy reading Return Results: Provides the formatted summary along with document metadata (file hash) Set up steps Configure OpenAI API: Set up your OpenAI credentials for the GPT-4o-mini model Deploy Webhook: The workflow automatically creates a POST endpoint at /ai_pdf_summariser Test Upload: Send a PDF file to the endpoint using a multipart/form-data request Adjust Limits: Modify the file size (10MB) and page count (20) validation limits if needed based on your requirements Customize Prompts: Update the system prompt in the Information Extractor node to change how topics and insights are generated The workflow includes comprehensive error handling for file validation failures (400 error) and processing errors (500 error), ensuring reliable operation even with problematic documents.

This workflow turns Slack into your content control hub and automates the full blog creation pipeline — from sourcing trending headlines, validating topics, drafting posts, and preparing content for your CMS. With one command in Slack, you can source news from RSS feeds, refine them with Gemini AI, generate high-quality blog posts, and get publish-ready output — all inside a single n8n workflow. ⸻ ⚙️ How It Works 1.Trigger in Slack Type start in a Slack channel to fetch trending headlines. Headlines are pulled from your configured RSS feeds. 2.Topic Generation (Gemini AI) Gemini rewrites RSS headlines into unique, non-duplicate topics. Slack displays these topics in a numbered list (e.g., reply with 2 to pick topic 2). 3.Content Validation When you reply with a number, Gemini validates and slightly rewrites the topic to ensure originality. Slack confirms the selected topic back to you. 4.Content Creation Gemini generates a LinkedIn/blog-style draft: Strong hook introduction 3–5 bullet insights A closing takeaway and CTA Optionally suggests asset ideas (e.g., image, infographic). 5.CMS-Ready Output Final draft is structured for publishing (markdown or plain text). You can expand this workflow to automatically send the output to your CMS (WordPress, Ghost, Notion, etc.). ⸻ 🛠 Setup Instructions Connect your Slack Bot to n8n. Configure your RSS Read nodes with feeds relevant to your niche. Add your Gemini API credentials in the AI node. Run the workflow: Type start in Slack → see trending topics. Reply with a number (e.g., gen 3) → get a generated blog draft in the same Slack thread. ⸻ 🎛 Customization Options • Change RSS sources to match your industry. • Adjust Gemini prompts for tone (educational, casual, professional). • Add moderation filters (skip sensitive or irrelevant topics). • Connect the final output step to your CMS, Notion, or Google Docs for publishing. ⸻ ✅ Why Use This Workflow? • One-stop flow: Sourcing → Validation → Writing → Publishing. • Hands-free control: Everything happens from Slack. • Flexible: Easily switch feeds, tone, or target CMS. • Scalable: Extend to newsletters, social posts, or knowledge bases.

Generating contextual summaries is an token-intensive approach for RAG embeddings which can quickly rack up costs if your inference provider charges by token usage. Featherless.ai is an inference provider with a different pricing model - they charge a flat subscription fee (starting from $10) and allows for unlimited token usage instead. If you're typically spending over $10 - $25 a month, you may find Featherless to be a cheaper and more manageable option for your projects or team. For this template, Featherless's unlimited token usage is well suited for generating contextual summaries at high volumes for a majority of RAG workloads. LLM: moonshotai/Kimi-K2-Instruct Embeddings: models/gemini-embedding-001 How it works A large document is imported into the workflow using the HTTP node and its text extracted via the Extract from file node. For this demonstration, the UK highway code is used an an example. Each page is processed individually and a contextual summary is generated for it. The contextual summary generation involves taking the current page, preceding and following pages together and summarising the contents of the current page. This summary is then converted to embeddings using Gemini-embedding-001 model. Note, we're using a http request to use the Gemini embedding API as at time of writing, n8n does not support the new API's schema. These embeddings are then stored in a Qdrant collection which can then be retrieved via an agent/MCP server or another workflow. How to use Replace the large document import with your own source of documents such as google drive or an internal repo. Replace the manual trigger if you want the workflow to run as soon as documents become available. If you're using Google Drive, check out my Push notifications for Google Drive template. Expand and/or tune embedding strategies to suit your data. You may want to additionally embed the content itself and perform multi-stage queries using both. Requirements Featherless.ai Account and API Key Gemini Account and API Key for Embeddings Qdrant Vector store Customising this workflow Sparse Vectors were not included in this template due to scope but should be the next step to getting the most our of contextual retrieval. Be sure to explore other models on the Featherless.ai platform or host your own custom/finetuned models.

Automated Invoice Collection & Data Extraction Using Vision API and LLM This workflow automates the process of collecting uploaded invoices, extracting text using Google Vision API, and processing the extracted text with an LLM to produce structured data containing key transaction details such as date, voucher number, transaction detail, vendor, and transaction value. The final data is saved to Google Sheets and a notification is sent to Telegram in real time. ✨ Key Features Invoice Upload Form** Users can upload invoice images through a provided form. Google Drive Integration** Files are stored in a specified Google Drive folder with a shareable preview link. OCR via Google Vision API** Converts invoice images to text using TEXT_DETECTION. Data Structuring via LLM** Uses LLM model to parse and structure data. Structured Output Parser** Ensures consistent output with required columns. Data Cleaning** Cleans and formats numeric values without currency symbols. Google Sheets Sync** Appends or updates transaction data in Google Sheets (matched by file ID). Template: Google Sheets Telegram Notification** Sends a transaction summary directly to a Telegram chat/group. 🔐 Required Credentials Google Vision API Key** → for OCR processing. OpenRouter API Key** → to access the Gemini Flash LLM. Google Drive OAuth2** → to upload and download invoice files. Google Sheets OAuth2** → to write or update spreadsheet data. Telegram Bot Token** → to send notifications to Telegram. Telegram Chat ID** → target chat/group for notifications. 🎁 Benefits Fully automated** from invoice upload to structured reporting. Time-saving** by eliminating manual transaction data entry. Real-time integration** with Google Sheets for reporting and auditing. Instant notifications** via Telegram for quick transaction monitoring. Duplicate prevention** using file ID as a matching key. Flexible** for accounting, finance, or administrative teams.

Move beyond generic AI-generated content and create articles that are high-quality, factually reliable, and aligned with your unique expertise. This template orchestrates a sophisticated "research-first" content creation process. Instead of simply asking an AI to write an article from scratch, it first uses an AI planner to break your topic down into logical sub-questions. It then queries a Lookio assistant—which you've connected to your own trusted knowledge base of uploaded documents—to build a comprehensive research brief. Only then is this fact-checked brief handed to a powerful AI writer to compose the final article, complete with source links. This is the ultimate workflow for scaling expert-level content creation. Who is this for? Content marketers & SEO specialists:** Scale the creation of authoritative, expert-level blog posts that are grounded in factual, source-based information. Technical writers & subject matter experts:** Transform your complex internal documentation into accessible public-facing articles, tutorials, and guides. Marketing agencies:** Quickly generate high-quality, well-researched drafts for clients by connecting the workflow to their provided brand and product materials. What problem does this solve? Reduces AI "hallucinations":** By grounding the entire writing process in your own trusted knowledge base, the AI generates content based on facts you provide, not on potentially incorrect information from its general training data. Ensures comprehensive topic coverage:** The initial AI-powered "topic breakdown" step acts like an expert outliner, ensuring the final article is well-structured and covers all key sub-topics. Automates source citation:** The workflow is designed to preserve and integrate source URLs from your knowledge base directly into the final article as hyperlinks, boosting credibility and saving you manual effort. Scales expert content creation:** It effectively mimics the workflow of a human expert (outline, research, consolidate, write) but in an automated, scalable, and incredibly fast way. How it works This workflow follows a sophisticated, multi-step process to ensure the highest quality output: Decomposition: You provide an article title and guidelines via the built-in form. An initial AI call then acts as a "planner," breaking down the main topic into an array of 5-8 logical sub-questions. Fact-based research (RAG): The workflow loops through each of these sub-questions and queries your Lookio assistant. This assistant, which you have pre-configured by uploading your own documents, finds the relevant information and source links for each point. Consolidation: All the retrieved question-and-answer pairs are compiled into a single, comprehensive research brief. Final article generation: This complete, fact-checked brief is handed to a final, powerful AI writer (e.g., GPT-4o). Its instructions are clear: write a high-quality article using only the provided information and integrate the source links as hyperlinks where appropriate. Implementing the template 1. Set up your Lookio assistant (Prerequisite): Lookio is a platform for building intelligent assistants that leverage your organization's documents as a dedicated knowledge base. First, sign up at Lookio. You'll get 50 free credits to get started. Upload the documents you want to use as your knowledge base. Create a new assistant and then generate an API key. Copy your Assistant ID and your API Key for the next step. 2. Configure the workflow: Connect your AI provider (e.g., OpenAI) credentials to the two Language Model nodes. In the Query Lookio Assistant (HTTP Request) node, paste your Assistant ID in the body and add your Lookio API Key for authentication (we recommend using a Bearer Token credential). 3. Activate the workflow: Toggle the workflow to "Active" and use the built-in form to generate your first fact-checked article! Taking it further Automate publishing:* Connect the final *Article result* node to a *Webflow* or *WordPress** node to automatically create a draft post in your CMS. Generate content in bulk:* Replace the *Form Trigger* with an *Airtable* or *Google Sheet** trigger to automatically generate a whole batch of articles from your content calendar. Customize the writing style:* Tweak the system prompt in the final *New content - Generate the AI output** node to match your brand's specific tone of voice, add SEO keywords, or include specific calls-to-action.

AI-Powered Chart Generation from Web Data This n8n workflow automates the process of: Scraping real-time data from the web using GPT-4o with browsing capability Converting markdown tables into Chart.js-compatible JSON Rendering the chart using QuickChart.io Uploading the resulting image directly to your WordPress media library 🚀 Use Case Ideal for content creators, analysts, or automation engineers who need to: Automate generation of visual reports Create marketing-ready charts from live data Streamline research-to-publish workflows 🧠 How It Works 1. Prompt Input Trigger the workflow manually or via another workflow with a prompt string, e.g.: Generate a graph of apple's market share in the mobile phone market in Q1 2025 2. Web Search + Table Extraction The Message a model node uses GPT-4o with search to: Perform a real-time query Extract data into a markdown table Return the raw table + citation URLs 3. Chart Generation via AI Agent The Generate Chart AI Agent: Interprets the table Picks an appropriate chart type (bar, line, doughnut, etc.) Outputs valid Chart.js JSON using a strict schema 4. QuickChart API Integration The Create QuickChart node: Sends the Chart.js config to QuickChart.io Renders the chart into a PNG image 5. WordPress Image Upload The Upload image node: Uploads the PNG to your WordPress media library using REST API Uses proper headers for filename and content-type Returns the media GUID and full image URL 🧩 Nodes Used Manual Trigger or Execute Workflow Trigger OpenAI Chat Model (GPT-4o) LangChain Agent (Chart Generator) LangChain OutputParserStructured HTTP Request (QuickChart API + WordPress Upload) Code (Final result formatting) 🗂 Output Format The final Code node returns: { "research": { ...raw markdown table + citations... }, "graph_data": { ...Chart.js JSON... }, "graph_image": { ...WordPress upload metadata... }, "result_image_url": "https://your-wordpress.com/wp-content/uploads/...png" } ⚙️ Requirements OpenAI credentials (GPT-4o or GPT-4o-mini) WordPress REST API credentials with media write access QuickChart.io (free tier works) n8n v1.25+ recommended 📌 Notes Chart style and format are determined dynamically based on your table structure and AI interpretation. Make sure your OpenAI and WordPress credentials are connected properly. Outputs are schema-validated to ensure reliable rendering. 🖼 Sample Output

Move beyond generic AI-generated content and create articles that are high-quality, factually reliable, and aligned with your unique expertise. This template orchestrates a sophisticated "research-first" content creation process. Instead of simply asking an AI to write an article from scratch, it first uses an AI planner to break your topic down into logical sub-questions. It then queries a Super assistant—which you've connected to your own trusted knowledge sources like Notion, Google Drive, or PDFs—to build a comprehensive research brief. Only then is this fact-checked brief handed to a powerful AI writer to compose the final article, complete with source links. This is the ultimate workflow for scaling expert-level content creation. Who is this for? Content marketers & SEO specialists:** Scale the creation of authoritative, expert-level blog posts that are grounded in factual, source-based information. Technical writers & subject matter experts:** Transform your complex internal documentation into accessible public-facing articles, tutorials, and guides. Marketing agencies:** Quickly generate high-quality, well-researched drafts for clients by connecting the workflow to their provided brand and product materials. What problem does this solve? Reduces AI "hallucinations":** By grounding the entire writing process in your own trusted knowledge base, the AI generates content based on facts you provide, not on potentially incorrect information from its general training data. Ensures comprehensive topic coverage:** The initial AI-powered "topic breakdown" step acts like an expert outliner, ensuring the final article is well-structured and covers all key sub-topics. Automates source citation:** The workflow is designed to preserve and integrate source URLs from your knowledge base directly into the final article as hyperlinks, boosting credibility and saving you manual effort. Scales expert content creation:** It effectively mimics the workflow of a human expert (outline, research, consolidate, write) but in an automated, scalable, and incredibly fast way. How it works This workflow follows a sophisticated, multi-step process to ensure the highest quality output: Decomposition: You provide an article title and guidelines via the built-in form. An initial AI call then acts as a "planner," breaking down the main topic into an array of 5-8 logical sub-questions. Fact-based research (RAG): The workflow loops through each of these sub-questions and queries your Super assistant. This assistant, which you have pre-configured and connected to your own knowledge sources (Notion pages, Google Drive folders, PDFs, etc.), finds the relevant information and source links for each point. Consolidation: All the retrieved question-and-answer pairs are compiled into a single, comprehensive research brief. Final article generation: This complete, fact-checked brief is handed to a final, powerful AI writer (e.g., GPT-5). Its instructions are clear: write a high-quality article using only the provided information and integrate the source links as hyperlinks where appropriate. Implementing the template Set up your Super assistant (Prerequisite): First, go to Super, create an assistant, connect it to your knowledge sources (Notion, Drive, etc.), and copy its Assistant ID and your API Token. Configure the workflow: Connect your AI provider (e.g., OpenAI) credentials to the two Language Model nodes (GPT 5 mini and GPT 5 chat). In the Query Super Assistant (HTTP Request) node, paste your Assistant ID in the body and add your Super API Token for authentication (we recommend using a Bearer Token credential). Activate the workflow: Toggle the workflow to "Active" and use the built-in form to generate your first fact-checked article! Taking it further Automate publishing:* Connect the final *Article result* node to a *Webflow* or *WordPress** node to automatically create a draft post in your CMS. Generate content in bulk:* Replace the *Form Trigger* with an *Airtable* or *Google Sheet** trigger to automatically generate a whole batch of articles from your content calendar. Customize the writing style:* Tweak the system prompt in the final *New content - Generate the AI output** node to match your brand's specific tone of voice, add SEO keywords, or include specific calls-to-action.