by Lucas Walter
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
by Iniyavan JC
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.
by Marko
**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.
by Juan Carlos Cavero Gracia
This workflow turns any URL (news article, blog post, or even an n8n workflow page) into a vertical short video with your AI avatar explaining it ready for TikTok, Instagram Reels, and YouTube Shorts. It fetches the page, generates a tight 30–45s script and platform-optimized descriptions, captures a dynamic background of the page (animated scroll or static image), composes and renders the video with HeyGen (free split‑screen or paid clean cut‑out), and sends it to Upload-Post with an optional human review step. Note: You can generate full videos end‑to‑end using free trials—no credit card required—for all APIs used in this template (Google Gemini, ScreenshotOne, HeyGen, Upload‑Post).* Who Is This For? Creators & Marketers:** Explain articles, launches, and workflows without filming or editing. Media & Newsletters:** Turn breaking stories into clear, shareable shorts. Agencies:** Scale content creation with review gates and multi-account publishing. Founders & Product Teams:** Maintain an on-brand presence in minutes. What Problem Does It Solve? Making platform-native explainers is slow and inconsistent. This workflow: Writes the script with AI:** ~30s hook-led monologue with key facts. Optimizes per platform:** Tailored captions for TikTok, Reels, and Shorts. Generates the video automatically:** Uses the page itself as background + avatar voiceover. Publishes everywhere:** Optional review, then one-click multi-platform posting. How It Works URL Input: Paste any page to convert (article, blog, or workflow). AI Agent (Gemini): Reads the page and produces a single script (~30s) + platform-specific descriptions. Video Background: Animated scroll capture (9:16) or featured image via ScreenshotOne. HeyGen Composition & Render: Free: split-screen vertical (avatar bottom, background top). Paid: clean avatar cut‑out over video/image (background removal). Render & Poll: Waits for HeyGen to finish and retrieves the final MP4. Human Review (optional): Approve or reject in a simple form. Publish (Upload-Post): Uploads to TikTok, Instagram (Reels), and YouTube Shorts with AI-generated titles/descriptions. Setup Credentials (all offer free trials, no credit card required): HeyGen API (X-Api-Key) + your avatar_id and voice_id. ScreenshotOne API key. Upload-Post (connect your social accounts). Google Gemini (chat model). Variables in “Set Input Vars”: workflow_url: page to convert. background_removal: true (paid) or false (free). background_type: video (animated scroll) or photo (static). Publishing: Choose platforms in Upload-Post; enable review if you want to approve before posting. Requirements Accounts:** n8n, HeyGen, ScreenshotOne, Upload-Post, Google (Gemini). API Keys:** HeyGen, ScreenshotOne, Gemini; Upload-Post credentials. Assets:** An avatar and a voice available in HeyGen. Features URL → Short in minutes:** 9:16 vertical (720×1280). Pro script with hook:** Clear, natural, ~30s. Two render modes:** Split-screen (free) or clean cut‑out (paid). Background from the page:** Animated scroll or main image. Human-in-the-loop:** Approval before going live. Multi-publish:** TikTok, Instagram Reels, YouTube Shorts via Upload-Post. Start free:** Generate videos with free trials across all APIs—no credit card required.
by Harshil Agrawal
This workflow generates sensor data, which is used in another workflow for managing factory incident reports. Read more about this use case and how to build both workflows with step-by-step instructions in the blog post How to automate your factory’s incident reporting. Prerequisites AMQP, an ActiveMQ connection, and credentials Nodes Interval node triggers the workflow every second. Set node set the necessary values for the items that are addeed to the queue. AMQP Sender node sends a raw message to add to the queue.
by Moka Ouchi
What it does This workflow automatically downloads NASA's Astronomy Picture of the Day (APOD) every day. It then resizes the image to a 4K resolution (3840x2160), making it perfect for a desktop wallpaper, and uploads it to a specified Google Drive folder. If the APOD for the day is a video or another media type instead of an image, the workflow will skip the download process and send an alert to a designated Slack channel, informing you of the media type and title. Who's it for This template is ideal for: Space and astronomy enthusiasts who want a new stunning wallpaper every day. Anyone looking to automate file downloading and cloud storage management. n8n users who want to learn how to integrate APIs, schedule triggers, process images, and use conditional logic. How to set up Setup should take about 5-10 minutes. Configure Credentials: NASA: Get a free API key from NASA APIs and add your credentials in the Fetch APOD data node. Google Drive: Authenticate your Google account in the Upload to Google Drive node. Slack: Authenticate your Slack workspace in the Send Slack alert node. Set Workflow Variables: In the ⚙️ Configuration node, replace the placeholder values for DRIVE_FOLDER_ID and SLACK_CHANNEL_ID with your actual Google Drive folder ID and Slack channel ID. You can find the folder ID in the URL of your Google Drive folder. Activate the Workflow: Toggle the "Active" switch to ON in the top-right corner. The workflow will now run once every day. How to customize Change Image Size**: You can adjust the output resolution in the Resize image to 4K node. Use a different Cloud Storage**: Replace the Upload to Google Drive node with another cloud storage node like Dropbox or OneDrive. Adjust the Schedule**: Modify the Daily Trigger node to run more or less frequently.
by SalmonRK-AI
📘 Multi-Photo Facebook Post (Windows Directory) – How to Use ✅ Requirements To run this automation, make sure you have the following: ✅ n8n installed on your local Windows machine ✅ Cloudinary or any other file hosting service for uploading image files ✅ Facebook Page Access Token with the required permissions (pages_manage_posts, pages_read_engagement, pages_show_list, etc.) 🚀 How to Use Import the provided n8n workflow template into your n8n instance. Verify the image directory path – ensure that the images you want to post are stored in a local folder (e.g. E:\Autopost-media\YourPage\Images). Check the caption and hashtag files – this includes: description.txt (for the post message) hashtag.txt (for additional tags) Set your Facebook credentials – insert your Facebook Page Access Token in the designated credential field in the workflow. ⚙️ How It Works (Workflow Logic) Read Text Files The workflow reads description.txt and hashtag.txt from the local directory. These are combined to form the message body for the Facebook post. Select Images to Post The Limit node defines how many images to post per run (e.g. 3 images). Selected image files are uploaded to a file server (like Cloudinary) to obtain public URLs. Post to Facebook (Multi-Photo) A multi-photo post is created using the uploaded image URLs and the composed message. Move Posted Images After the post is successfully published, the original image files are moved to a new folder. The destination folder is automatically created using the current date (e.g. E:\Autopost-media\YourPage\Images\20250614).
by Navneet Singh Arora
Automated Job Search & AI Relevance Evaluator Overview This n8n template automates the entire job hunting process by cross-referencing a candidate's PDF resume with live job listings from the JSearch API. It automatically filters for fresh, unapplied roles, uses Google Gemini AI to critically evaluate each job's relevance against the candidate's specific experience, and logs highly tailored matches directly into a Notion database for seamless tracking. 🚀 How it works Context & Extraction: The workflow fetches existing applications from your Notion database to prevent duplicate tracking, then reads and extracts plain text directly from a local PDF resume. Role Discovery: A Google Gemini node isolates the candidate's current job title to formulate a precise search query. This query is sent to the JSearch API (via RapidAPI) to pull live job listings. Smart Filtering: Natively filters out jobs posted more than 14 days ago and jobs that already exist in your Notion tracker, ensuring only fresh, unseen postings are processed. AI Evaluation: The core of the workflow! Google Gemini acts as an expert technical recruiter, comparing the candidate's resume against each job description. It generates a "Relevance Score" (1-100), a "Skill Match Score", extracts remote/salary info, and summarizes why the job is a good fit. Notion Logging: Structured insights for each matched role are formatted and pushed directly as a rich database page into your Notion tracking board. 🎮 How to use API Credentials: Add your Google Gemini API Key and your RapidAPI key (subscribed to the JSearch API) in their respective nodes. Notion Setup: Connect your Notion credential and update the two Notion nodes with your specific target Database ID. File Path: Update the File Selector to point to your PDF resume (e.g., /home/node/.n8n-files/My-Resume.pdf). Search Customization: Open the "Search for Jobs via RapidAPI" node to manually tweak your target location, industry keywords, or pagination limits. ⚙️ Requirements Google Gemini API Key RapidAPI Key (for JSearch API) Notion Account (with a pre-configured Job Tracker database) n8n Environment: Designed for self-hosted instances with local file access. 🎯 Use Cases Automated Job Hunting: Wake up to a pre-vetted, automatically scored list of highly relevant job openings perfectly matched to your exact resume. Recruiting Pipelines: Scale candidate sourcing by automatically comparing an inbound candidate's resume against thousands of active job board posts. Freelance Lead Generation: Independent contractors or agencies can use this to find companies actively hiring for the exact technical skills they offer.
by Jimleuk
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.
by Jay Emp0
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
by Nijan
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.
by Guillaume Duvernay
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.