Google Drive and HTTP Request integration

This workflow automates the creation of AI-generated virtual try-on images for fashion eCommerce stores. Instead of relying on expensive and time-consuming photoshoots, the system uses AI to generate realistic images of models wearing selected clothing items. This n8n workflow automates the process of generating AI-powered virtual try-on images for a WooCommerce store. It fetches product data from a Google Sheet, uses the Fal.ai Nano Banana model to create an image of a model wearing the clothing item, and then updates both the Google Sheet and the WooCommerce product with the final generated image. Advantages ✅ Cost Reduction: Eliminates the need for professional photo shoots, saving on models, photographers, and studio expenses. ✅ Time Efficiency: Automates the entire workflow—from data input to product update—minimizing manual work. ✅ Scalability: Works seamlessly across large product catalogs, making it easy to update hundreds of products quickly. ✅ Enhanced eCommerce Experience: Provides shoppers with realistic previews of clothing on models, boosting trust and conversion rates. ✅ Marketing Flexibility: The generated images can also be repurposed for ads, social media, and promotional campaigns. ✅ Centralized Management: Google Sheets acts as the control center, making it easy to manage inputs and track results. How It Works The workflow operates in a sequential, loop-based manner to process multiple products from a spreadsheet. Here is the logical flow: Manual Trigger & Data Fetch: The workflow starts manually (e.g., by clicking "Test workflow"). It first reads data from a specified Google Sheet, looking for rows where the "IMAGE RESULT" column is empty. Loop Processing: It loops over each row of data fetched from the sheet. Each row should contain URLs for a model image and a product image, along with a WooCommerce product ID. API Request to Generate Image: For each item in the loop, the workflow sends a POST request to the Fal.ai Nano Banana API. The request includes the two image URLs and a prompt instructing the AI to create a photo of the model wearing the submitted clothing item. Polling for Completion: The AI processing is asynchronous. The workflow enters a polling loop: it waits for 60 seconds and then checks the status of the processing request. If the status is not COMPLETED, it waits and checks again. This loop continues until the image is ready. Fetching and Storing the Result: Once the status is COMPLETED, the workflow retrieves the URL of the generated image, downloads the image file, and uploads it to a designated folder in Google Drive. Updating Systems: The workflow then performs two crucial update steps: It updates the original Google Sheet row, writing the URL of the final generated image into the "IMAGE RESULT" column. It updates the corresponding product in WooCommerce, adding the generated image to the product's gallery. Loop Continuation: After processing one item, the workflow loops back to process the next row in the Google Sheet until all items are complete. Set Up Steps* To make this workflow functional, you need to configure three main connections: Step 1: Prepare the Google Sheet Create a Google Sheet with the following columns: IMAGE MODEL, IMAGE PRODUCT, PRODUCT ID, and IMAGE RESULT. Populate the first three columns for each product. The IMAGE RESULT column must be left blank; the workflow will fill it automatically. In the n8n workflow, configure the "Google Sheets" node to point to your specific Google Sheet and worksheet. Step 2: Configure the Fal.ai API Key Create an account at fal.ai and obtain your API key. In the n8n workflow, locate the three "HTTP Request" nodes named "Get Url image", "Get status", and "Create Image". Edit the credentials for these nodes (named "Fal.run API") and update the Value field in the Header Auth to be Key YOURAPIKEY (replacing YOURAPIKEY with your actual key). Step 3: Set Up WooCommerce API Ensure you have the API keys (Consumer Key and Consumer Secret) for your WooCommerce store's REST API. In the n8n workflow, locate the "WooCommerce" node. Edit its credentials and provide the required information: your store's URL and the API keys. This allows the workflow to authenticate and update your products. Need help customizing? Contact me for consulting and support or add me on Linkedin.

Working with Large Documents In Your VLM OCR Workflow Document workflows are popular ways to use AI but what happens when your document is too large for your app or your AI to handle? Whether its context window or application memory that's grinding to a halt, Subworkflow.ai is one approach to keep you going. > Subworkflow.ai is a third party API service to help AI developers work with documents too large for context windows and runtime memory. Prequisites You'll need a Subworkflow.ai API key to use the Subworkflow.ai service. Add the API key as a header auth credential. More details in the official docs https://docs.subworkflow.ai/category/api-reference How it Works Import your document into your n8n workflow Upload it to the Subworkflow.ai service via the Extract API using the HTTP node. This endpoint takes files up to 100mb. Once uploaded, this will trigger an Extract job on the service's side and the response is a "job" record to track progress. Poll Subworkflow.ai's Jobs endpoint and keep polling until the job is finished. You can use the "IF" node looping back unto itself to achieve this in n8n. Once the job is done, the Dataset of the uploaded document is ready for retrieval. Use the Datasets and DatasetItems API to retrieve whatever you need to complete your AI task. In this example, all pages are retrieved and run through a multimodal LLM to parse into markdown. A well-known process when parsing data tables or graphics are required. How to use Integrate Subworkflow's Extract API seemlessly into your existing document workflows to support larger documents from 100mb+ to up to 5000 pages. Customising the workflow Sometimes you don't want the entire document back especially if the document is quite large (think 500+ pages!), instead, use query parameters on the DatasetItems API to pick individual pages or a range of pages to reduce the load. Need Help? Official API documentation**: https://docs.subworkflow.ai/category/api-reference Join the discord**: https://discord.gg/RCHeCPJnYw

This workflow automates the entire process of creating, managing, and publishing AI-generated videos using OpenAI Sora2 Pro, Google Sheets, Google Drive, and YouTube. Advantages ✅ Fully Automated Video Pipeline From idea to YouTube publication with zero manual intervention after setup. ✅ Centralized Control via Google Sheets Simple spreadsheet interface — no need to use APIs or dashboards directly. ✅ AI-Powered Video Creation Uses OpenAI Sora2 Pro for generating professional-quality videos from text prompts. ✅ SEO-Optimized Titles with GPT-5 Automatically creates catchy, keyword-rich titles optimized for YouTube engagement. ✅ Cloud Integration Seamless use of Google Drive for file management and YouTube for publishing. ✅ Scalable and Repeatable Can handle multiple videos in sequence, triggered manually or at regular intervals. ✅ Error-Resilient and Transparent Uses conditional checks (“Completed?” node) and real-time updates in Google Sheets to ensure reliability and visibility. How it Works This workflow automates the entire process of generating AI videos and publishing them to YouTube, using a Google Sheet as the central control panel. Trigger & Data Fetch: The workflow is triggered either manually or on a schedule. It starts by reading a specific Google Sheet to find new video requests. A new request is identified as a row where the "PROMPT" and "DURATION" columns are filled, but the "VIDEO" column is empty. AI Video Generation: For each new request, it takes the prompt and duration, then sends a request to the Fal.ai Sora-2 Pro model via its API to generate the video. The system then enters a polling loop, checking the video generation status every 60 seconds until it is COMPLETED. Post-Processing & Upload: Once the video is ready, the workflow performs three parallel actions: Fetch Video & Upload to Drive: It retrieves the generated video file and uploads it to a specified folder in Google Drive for archiving. Generate YouTube Title: It sends the original prompt to OpenAI's GPT-5 (or another specified model) to generate an optimized, SEO-friendly title for the YouTube video. Publish to YouTube: It takes the generated video file and the AI-created title and uses the Upload-Post.com service to automatically publish the video to a connected YouTube channel. Update & Log: Finally, the workflow updates the original Google Sheet row with the URL of the archived video in Google Drive and the newly created YouTube video URL, providing a complete audit trail. Set up Steps To configure this workflow, follow these steps: Prepare the Google Sheet: Create a Google Sheet with at least these columns: PROMPT, DURATION, VIDEO, and YOUTUBE_URL. In the n8n "Get new video" and update nodes, configure the documentId and sheetName to point to your specific Google Sheet. Configure Fal.ai API Key: Create an account on fal.ai and obtain your API key. In both the "Create Video" and "Get status" HTTP Request nodes, set up the HTTP Header Authentication. Set the Name to Authorization and the Value to Key YOUR_API_KEY. Set up Upload-Post.com for YouTube: Create an account on Upload-Post.com and get your API key. Connect your YouTube channel as a "profile". In the "HTTP Request" node (for uploading), configure the Header Auth with Name: Authorization and Value: Apikey YOUR_UPLOAD_POST_API_KEY. Replace YOUR_USERNAME in the node's body parameters with the profile name you created on Upload-Post.com (e.g., test1). Configure OpenAI (Optional but Recommended): The "Generate title" node uses an OpenAI model. Ensure you have valid OpenAI API credentials set up in n8n for this node to function and create optimized titles. Finalize Paths and Activate: In the "Upload Video" node, specify the correct Google Drive folder ID where you want the videos to be saved. Once all credentials and paths are set, you can activate the workflow and set the "Schedule Trigger" node to run at your desired interval (e.g., every 5 minutes). Need help customizing? Contact me for consulting and support or add me on Linkedin.

🤖 Automated AI News Video Creation and Social Media Publishing Workflow ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 🎯 Overview: This workflow fully automates the creation and social media distribution of AI-generated news videos. It fetches news, crafts captions, generates avatar videos via HeyGen, stores them, and publishes them across Instagram, Facebook, and YouTube via Postiz. 🔄 WORKFLOW PROCESS: News Fetching: Reads the latest news from an RSS feed. AI Captioning: Generates concise, engaging captions using an AI agent (GPT-4o-mini). Video Generation: Creates an AI avatar video using HeyGen with the generated caption. Video Storage: Downloads the video and uploads it to Google Drive for archival. Data Logging: Records all news and video metadata into Google Sheets. Postiz Upload: Uploads the video to Postiz's internal storage for publishing. Social Publishing: Fetches Postiz integrations and routes the video to Instagram, Facebook, and YouTube after platform-specific content cleaning. ⚙️ KEY TECHNOLOGIES: RSS Feeds:** News source. LangChain (n8n nodes):** AI Agent and Chat OpenAI for caption generation. HeyGen API:** AI avatar video creation. Google Drive:** Video file storage. Google Sheets:** Data logging and tracking. Postiz API:** Unified social media publishing platform. ⚠️CRITICAL CONFIGURATIONS: API Keys:** Ensure HeyGen and Postiz API keys are correctly set in credentials and the 'Setup Heygen Parameters' node. HeyGen IDs:** Verify avatar_id and voice_id in 'Setup Heygen Parameters'. Postiz URL:** Confirm https://postiz.yourdomain.com is your correct Postiz instance URL across all HTTP Request nodes. Credentials:** All Google, OpenAI, and Postiz credentials must be properly linked. 📈BENEFITS: Automated content creation and distribution, saving significant time. Consistent branding and messaging across multiple platforms. Centralized logging for tracking and performance analysis. Scalable solution for high-volume content demands.

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Cold Calling Automation - End-to-End Automated Cold Calling with Apify, RAG, and WhatsApp The "Cold Calling Automation" workflow is designed to fully automate the end-to-end cold calling process by intelligently combining web scraping, AI-powered research, and WhatsApp messaging. Leveraging key technologies such as Apify for data scraping, RAG (Retrieval-Augmented Generation) for intelligent content creation, and WhatsApp integration for automated outreach, this workflow transforms raw prospect data into personalized, high-converting cold calling campaigns with minimal manual intervention. 💡 Why Use Cold Calling Automation? Scale Your Outreach:** Automate hundreds of personalized cold calls without manual effort or hiring additional staff. Intelligent Personalization:** RAG technology creates highly relevant, personalized messages based on prospect research. Multi-Channel Approach:** Seamlessly integrate WhatsApp messaging with traditional cold calling methods. Real-Time Optimization:** Continuously improve message performance and conversion rates through AI analysis. Cost-Effective:** Reduce cold calling costs while dramatically increasing reach and response rates. ⚡ Who Is This For? Sales Teams:** Looking to scale their cold calling efforts with intelligent automation and personalization. Lead Generation Agencies:** Needing to deliver high-volume, high-quality cold calling services to clients. Business Development Professionals:** Seeking to maximize outreach efficiency while maintaining personal touch. Small Business Owners:** Who want professional-grade cold calling capabilities without hiring expensive sales teams. Marketing Agencies:** Offering comprehensive lead generation and conversion services to clients. ❓ What Problem Does It Solve? Traditional cold calling is time-consuming, expensive, and often ineffective due to lack of personalization and poor timing. Manual prospect research, script writing, and call execution create bottlenecks that limit outreach scale. Generic messages result in low response rates and damaged brand reputation. This workflow solves these problems by automating the entire cold calling pipeline - from prospect identification and research to personalized message creation and delivery - while maintaining high quality and relevance that converts prospects into qualified leads. 🔧 What This Workflow Does ⏱ Prospect Scraping: Uses Apify to automatically scrape and identify high-quality prospects based on your target criteria. 🔍 Intelligent Research: Employs RAG technology to research each prospect and gather relevant business intelligence. ✍️ Personalized Content: Automatically generates custom messages, scripts, and talking points for each prospect. 📱 WhatsApp Integration: Delivers personalized messages through WhatsApp automation for maximum engagement. 📊 Performance Tracking: Monitors response rates, engagement metrics, and conversion data for continuous optimization. 🤖 AI-Powered Follow-up: Automatically handles initial responses and schedules appropriate follow-up actions. 📈 Campaign Analytics: Provides detailed insights on campaign performance and ROI metrics. 🔄 Continuous Learning: Improves message effectiveness and targeting based on campaign results. This workflow also using community node: @devlikeapro/n8n-nodes-waha 🔐 Setup Instructions Import the provided workflow JSON into your n8n instance (Cloud or self-hosted). Set up credentials: Apify API credentials for prospect scraping OpenAI API key for RAG and content generation WhatsApp Business API credentials or WAHA integration Database credentials for prospect and campaign tracking Email credentials for notifications and reporting Customize parameters: Target prospect criteria and scraping parameters Message templates and personalization rules Campaign timing and frequency settings Response handling and follow-up logic Performance tracking and reporting preferences Test the complete workflow with a small prospect list to verify scraping, personalization, and delivery. 🧩 Pre-Requirements Active n8n instance (Cloud or Self-hosted) Apify account with appropriate scraping credits OpenAI API key with sufficient usage limits WhatsApp Business account or WAHA setup Database system for prospect and campaign management Basic understanding of your target audience and value proposition 🛠️ Customize It Further Integrate with CRM systems to sync prospects and track conversion through sales pipeline. Add voice calling capabilities using VoIP services for complete omnichannel outreach. Implement A/B testing for message templates and timing optimization. Connect with social media platforms for multi-channel prospecting and engagement. Add sentiment analysis to optimize message tone and approach for different prospect types. Integrate with calendar systems for automatic meeting scheduling from qualified responses. 🧠 Nodes Used Apify nodes for prospect scraping and data collection OpenAI Chat Model and Embeddings for RAG implementation WhatsApp/WAHA nodes for message delivery and response handling Database nodes for prospect storage and campaign tracking HTTP Request nodes for API integrations and webhooks Code nodes for data processing and personalization logic Schedule Trigger for automated campaign execution Conditional nodes for response handling and follow-up logic Set nodes for parameter configuration and data transformation Split In Batches for efficient bulk processing 📊 Expected Results 50-80% increase** in cold calling efficiency and prospect reach 25-40% higher** response rates compared to generic cold calling 60-75% reduction** in manual research and message preparation time Real-time insights** into campaign performance and prospect engagement Scalable system** that grows with your business needs 📞 Support Made by: khaisa Studio Tag: automation, cold calling, lead generation, apify, RAG, whatsapp, AI, sales automation, outreach Category: Sales Automation & Lead Generation Need a custom? contact me for more tailored templates

Who’s it for This template is designed for anyone who wants to use Telegram as a personal AI assistant hub. If you often juggle tasks, emails, calendars, and expenses across multiple tools, this workflow consolidates everything into one seamless AI-powered agent. What it does Jarvis listens to your Telegram messages (text or audio) and processes them with OpenAI. Based on your request, it can:

This workflow allows users to generate AI videos using the cheaper model Google Veo3 Fast, save them to Google Drive, generate optimized titles with GPT-4o, and automatically upload them to YouTube and TikTok with Upload-Post. The entire process is triggered from a Google Sheet that acts as the central interface for input and output. IT automates video creation, uploading, and tracking, ensuring seamless integration between Google Sheets, Google Drive, Google Veo3 Fast, TikTok and YouTube. Benefits of this Workflow 💡 No Code Interface**: Trigger and control the video production pipeline from a simple Google Sheet. ⚙️ Full Automation**: Once set up, the entire video generation and publishing process runs hands-free. 🧠 AI-Powered Creativity**: Generates engaging YouTube and TikTok titles using GPT-4o. Leverages advanced generative video AI from Google Veo3. 📁 Cloud Storage & Backup**: Stores all generated videos on Google Drive for safekeeping. 📈 YouTube Ready**: Automatically uploads to YouTube with correct metadata, saving time and boosting visibility. 📈 TikTok Ready**: Automatically uploads to TikTok with correct metadata, saving time and boosting visibility. 🧪 Scalable**: Designed to process multiple video prompts by looping through new entries in Google Sheets. 🔒 API-First**: Utilizes secure API-based communication for all services. How It Works Trigger: The workflow can be started manually ("When clicking ‘Test workflow’") or scheduled ("Schedule Trigger") to run at regular intervals (e.g., every 5 minutes). Fetch Data: The "Get new video" node retrieves unfilled video requests from a Google Sheet (rows where the "VIDEO" column is empty). Video Creation: The "Set data" node formats the prompt and duration from the Google Sheet. The "Create Video" node sends a request to the Fal.run API (Google Veo3 Fast) to generate a video based on the prompt. Status Check: The "Wait 60 sec." node pauses execution for 60 seconds. The "Get status" node checks the video generation status. If the status is "COMPLETED," the workflow proceeds; otherwise, it waits again. Video Processing: The "Get Url Video" node fetches the video URL. The "Generate title" node uses OpenAI (GPT-4.1) to create an SEO-optimized YouTube and TikTok title. The "Get File Video" node downloads the video file. Upload & Update: The "Upload Video" node saves the video to Google Drive. The "HTTP Request" node uploads the video to YouTube via the Upload-Post API. The "HTTP Request" node uploads the video to TikTok via the Upload-Post API. The "Update Youtube URL" and "Update result" nodes update the Google Sheet with the video URL and YouTube link. Set Up Steps Google Sheet Setup: Create a Google Sheet with columns: PROMPT, DURATION, VIDEO, and YOUTUBE_URL. Share the Sheet link in the "Get new video" node. API Keys: Obtain a Fal.run API key (for Veo3) and set it in the "Create Video" node (Header: Authorization: Key YOURAPIKEY). Get an Upload-Post API key (for YouTube uploads) and configure the "HTTP Request" node (Header: Authorization: Apikey YOUR_API_KEY). Get an Upload-Post API key (for TikTok uploads) and configure the "HTTP Request" node (Header: Authorization: Apikey YOUR_API_KEY). YouTube Upload Configuration: Replace YOUR_USERNAME in the "HTTP Request" node with your Upload-Post profile name. Schedule Trigger: Configure the "Schedule Trigger" node to run periodically (e.g., every 5 minutes). Need help customizing? Contact me for consulting and support or add me on Linkedin.

🧾 What this workflow does This workflow takes a reference ad image and brand website, then uses GPT-4, LangChain, and Dumpling AI to generate 10 high-quality image variations for ad testing. These image variations are visually consistent but subtly different in background, mood, lighting, and tone — perfect for performance testing on platforms like Meta Ads or TikTok. 👤 Who is this for DTC marketers and brand designers testing ad creatives Creative teams automating visual experimentation Content agencies using AI for fast ad mockups Performance marketers running multivariate testing ⚙️ How to set up ✅ Requirements You’ll need the following tools set up in n8n: Google Drive (OAuth2 credential) Google Sheets (OAuth2 credential) OpenAI API (for GPT-4 or GPT-4o) Dumpling AI API (via HTTP header authentication) 🛠️ Steps to configure Google Sheet Setup Create a sheet with one column: Image URL Update the Sheet ID and tab name in the final Google Sheets node. Drive Setup Create a folder in Google Drive for storing the reference image. Replace the folderId in the “Upload Ad Image to Google Drive” node. Dumpling AI API Key Use n8n’s credential manager (HTTP Header Auth) — do not hardcode the key. OpenAI API Key Required for both image description and LangChain agent prompt generation. Form Inputs Required Brand Name Brand Website Ad Image (upload field) 🧠 How it works A user submits the brand name, website, and a reference ad image through a form. The image is uploaded to Google Drive. GPT-4o describes the image’s visual style (e.g., mood, lighting, composition). GPT-4 analyzes the brand’s website to define its visual aesthetic. A LangChain agent uses both analyses to create 10 tightly scoped variation prompts. Dumpling AI generates a new image for each prompt using its “FLUX.1-pro” model. Each new image’s link is logged into Google Sheets. 🛠️ How to customize 🧪 Change prompt logic to experiment with different variations (e.g., theme, season). 🎨 Switch image model in Dumpling AI to one that supports your desired style. 🔗 Log additional metadata (prompt, timestamp) to Google Sheets. 📤 Connect output images to Airtable, Notion, or a review tool like Figma. 🎯 Modify GPT system message to reflect a different tone or brand strategy. This workflow gives creative teams and marketers an instant, AI-powered ad image testing system — built on real brand visuals, not generic stock content.

Who’s it for This template is perfect for content creators, AI enthusiasts, marketers, and developers who want to automate the generation of cinematic videos using Google Vertex AI’s Veo 3 model. It’s also ideal for anyone experimenting with generative AI for video using n8n. What it does This workflow: Accepts a text prompt and a GCP access token via form. Sends the prompt to the Veo 3 (preview model) using Vertex AI’s predictLongRunning endpoint. Waits for the video rendering to complete. Fetches the final result and converts the base64-encoded video to a file. Uploads the resulting .mp4 to your Google Drive. Output How to set up Enable Vertex AI API in your GCP project: https://console.cloud.google.com/marketplace/product/google/aiplatform.googleapis.com Authenticate with GCP using Cloud Shell or local terminal: gcloud auth login gcloud config set project [YOUR_PROJECT_ID] gcloud auth application-default set-quota-project [YOUR_PROJECT_ID] gcloud auth print-access-token Copy the token and use it in the form when running the workflow. ⚠️ This token lasts ~1 hour. Regenerate as needed. Connect your Google Drive OAuth2 credentials to allow file upload. Import this workflow into n8n and execute it via form trigger. Requirements n8n (v1.94.1+)** A Google Cloud project with: Vertex AI API enabled Billing enabled A way to get Access Token A Google Drive OAuth2 credential connected to n8n How to customize the workflow You can modify the in the HTTP node to match your use case. Replace the Google Drive upload node with alternatives like Dropbox, S3, or YouTube upload. Extend the workflow to add subtitles, audio dubbing, or LINE/Slack alerts. Step-by-step for each major node: Prompt Input → Vertex Predict → Wait → Fetch Result → Convert to File → Upload Best Practices Followed No hardcoded API tokens Secure: GCP token is input via form, not stored in workflow All nodes are renamed with clear purpose All editable config grouped in Set node External References GCP Veo API Docs: https://cloud.google.com/vertex-ai/docs/generative-ai/video/overview Disclaimer This workflow uses official Google Cloud APIs and requires a valid GCP project. Access token should be generated securely using gcloud CLI. Do not embed tokens in the workflow itself. Notes on GCP Access Token To use the Vertex AI API in n8n securely: Run the following on your local machine or GCP Cloud Shell: gcloud auth login gcloud config set project your-project-id gcloud auth print-access-token Paste the token in the workflow form field when submitting. Do not hardcode the token into HTTP nodes or Set nodes — input it each time or use a secure credential vault.

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. 1 — What Does It Do / Which Problem Does It Solve? This workflow turns Google Docs-based contract & form templates into ready-to-sign PDFs in minutes—all from a single chat flow. Automates repetitive document creation.** Instead of copying a rental, sales, or NDA template and filling it by hand every time, the bot asks for the required values and fills them in. Eliminates human error.** It lists every mandatory field so nothing is missed, and removes unnecessary clauses via conditional blocks. Speeds up approvals.** The final draft arrives as a direct PDF link—one click to send for signing. One template → unlimited variations.* Every new template you drop in Drive is auto-listed with zero workflow edits—*it scales effortlessly. 100 % no-code.** Runs on n8n + Google Apps Script—no extra backend, self-hosted or cloud. 2 — How It Works (Detailed Flow) 📝 Template Discovery 📂 The TemplateList node scans the Drive folder you specify via the ?mode=meta endpoint and returns an id / title / desc list. The bot shows this list in chat. 🎯 Selection & Metadata Fetch The user types a template name. 🔍 GetMetaData opens the chosen Doc, extracts META_JSON, placeholders, and conditional blocks, then lists mandatory & optional fields. 🗣 Data-Collection Loop The bot asks for every placeholder value. For each conditional block it asks 🟢 Yes / 🔴 No. Answers are accumulated in a data JSON object. ✅ Final Confirmation The bot summarizes the inputs → when the user clicks Confirm, the DocProcess sub-workflow starts. ⚙️ DocProcess Sub-Workflow | 🔧 Step | Node | Task | | --- | --- | --- | | 1 | User Choice Match Check | Verifies name–ID match; throws if wrong | | 2 | GetMetaData (renew) | Gets the latest placeholder list | | 3 | Validate JSON Format | Checks for missing / unknown fields | | 4 | CopyTemplate | Copies the Doc via Drive API | | 5 | FillDocument | Apps Script fills placeholders & removes blocks | | 6 | Generate PDF Link | Builds an export?format=pdf URL | 📎 Delivery The master agent sends 🔗 Download PDF & ✏️ Open Google Doc links. 🚫 Error Paths status:"ERROR", missing:[…] → bot lists missing fields and re-asks. unknown:[…] → template list is outdated; rerun TemplateList. Any Apps Script error → the returned message is shown verbatim in chat. 3 — 🚀 Setup Steps (Full Checklist) > Goal: Get a flawless PDF on the first run. > > > Mentally tick the ☑️ in front of every line as you go. > ☁️ A. Google Drive Preparation | Step | Do This | Watch Out For | | --- | --- | --- | | 1 | Create a Templates/ folder → put every template Doc inside | Exactly one folder; no sub-folders | | 2 | Placeholders in every Doc are {{UPPER_CASE}} | No Turkish chars or spaces | | 3 | Wrap optional clauses with [[BLOCK_NAME:START]]…[[BLOCK_NAME:END]] | The START tag must have a blank line above | | 4 | Add a META_JSON block at the very end | Script deletes it automatically after fill | | 5 | Right-click Doc > Details ▸ Description = 1-line human description | Shown by the bot in the list | | 6 | Create a second Generated/ folder (for copies) | Keeps Drive tidy | > 🔑 Folder ID (long alphanumerical) = <TEMPLATE_PARENT_ID> > > > We’ll paste this into the TemplateList node next. > Simple sample template → Template Link 🛠 B. Import the Workflow into n8n Settings ▸ Import Workflow ▸ DocAgent.json If nodes look Broken afterwards → no community-node problem; you only need to select credentials. 📑 C. Customize the TemplateList Node Open Template List node ⚙️ → replace '%3CYOUR_PARENT_ID%3E' in parents with the real folder ID in the URL. Right-click node > Execute Node. Copy the entire JSON response. In the editor paste it into: DocAgent → System Prompt (top) User Choice Match Check → System Prompt (top) Save. > ⚠️ Why manual? Caching the list saves LLM tokens. Whenever you add a template, rerun the node and update the prompts. > 🔗 D. Deploy the Apps Script | Step | Screen | Note | | --- | --- | --- | | 1 | Open Gist files GetMetaData.gs + FillDocument.gs → File ▸ Make a copy | Both files may live in one project | | 2 | Project Settings > enable Google Docs API ✔️ & Google Drive API ✔️ | Otherwise you’ll see 403 errors | | 3 | Deploy ▸ New deployment ▸ Web app | | | • Execute as | Me | | | • Who has access | Anyone | | | 4 | On the consent screen allow scopes:• …/auth/documents• …/auth/drive | Click Advanced › Go if Google warns | | 5 | Copy the Web App URL (e.g. https://script.google.com/macros/s/ABC123/exec) | If this URL changes, update n8n | Apps Script source code → Notion Link 🔧 E. Wire the Script URL in n8n | Node | Field | Action | | --- | --- | --- | | GetMetaData | URL | <WEB_APP_URL>?mode=meta&id={{ $json["id"] }} | | FillDocument | URL | <WEB_APP_URL> | > 💡 Prefer using an .env file? Add GAS_WEBAPP_URL=… and reference it as {{ $env.GAS_WEBAPP_URL }}. > 🔐 F. Add Credentials Google Drive OAuth2* → *Drive API (v3) Full Access Google Docs OAuth2** → same account LLM key** (OpenAI / Gemini) (Optional) Postgres Chat Memory credential for the corresponding node 🧪 G. First Run (Smoke Test) Switch the workflow Active. In the chat panel type /start. Bot lists templates → pick one. Fill mandatory fields, optionally toggle blocks → Confirm. 🔗 Download PDF link appears → ☑️ setup complete. ❌ H. Common Errors & Fixes | 🆘 Error | Likely Cause | Remedy | | --- | --- | --- | | 403: Apps Script permission denied | Web app access set to User | Redeploy as Anyone, re-authorize scopes | | placeholder validation failed | Missing required field | Provide the listed values → rerun DocProcess | | unknown placeholders: … | Template vs. agent mismatch | Check placeholder spelling (UPPER_CASE ASCII) | | Template ID not found | Prompt list is old | Rerun TemplateList → update both prompts | | Cannot find META_JSON | No meta block / wrong tag | Add [[META_JSON_START]] … [[META_JSON_END]], retry | ✅ Final Checklist [ ] Drive folder structure & template rules ready [ ] Workflow imported, folder ID set in node [ ] TemplateList output pasted into both prompts [ ] Apps Script deployed, URL set in nodes [ ] OAuth credentials & LLM key configured [ ] /start test passes, PDF link received 🙋‍♂️ Need Help with Customizations? Reach out for consulting & support on LinkedIn: Özgür Karateke Full Documentation → Notion Simple sample template → Template Link Apps Script source code → Notion Link

🤖🎵 This workflow automates the creation, storage, and cataloging of AI-generated music using the Eleven Music API, Google Sheets, and Google Drive. Key Advantages ✅ Fully Automated Music Generation Pipeline Once started, the workflow automatically: Reads track parameters Generates music via API Uploads the file Updates your spreadsheet No manual steps needed after initialization. ✅ Centralized Track Management A single Google Sheet acts as your project control center, letting you organize: Prompts Durations Generated URLs This avoids losing track of files and creates a ready-to-share catalog. ✅ Seamless Integration with Google Services The workflow: Reads instructions from Google Sheets Saves the MP3 to Google Drive Updates the same Sheet with the final link This ensures everything stays synchronized and easy to access. ✅ Scalable and Reliable Processing The loop-with-delay mechanism: Processes tracks sequentially Prevents API overload Ensures stable execution This is especially helpful when generating multiple long tracks. ✅ Easy Customization Because the prompts and durations come from Google Sheets: You can edit prompts at any time You can add more tracks without modifying the workflow You can clone the Sheet for different projects ✅ Ideal for Creators and Businesses This workflow is perfect for: Content creators generating background music Agencies designing custom soundtracks Businesses needing AI-generated audio assets Automated production pipelines How It Works The process operates as follows: The workflow starts manually via the "Execute workflow" trigger It retrieves a list of music track requests from a Google Sheets spreadsheet containing track titles, text prompts, and duration specifications The system processes each track request individually through a batch loop For each track, it sends the text prompt and duration to ElevenLabs Music API to generate studio-quality music The generated MP3 file (in 44100 Hz, 128 kbps format) is automatically uploaded to a designated Google Drive folder Once uploaded, the workflow updates the original Google Sheets with the direct URL to the generated music file A 1-minute wait period between each track generation prevents API rate limiting The process continues until all track requests in the spreadsheet have been processed Set Up Steps Prerequisites: ElevenLabs paid account with Music API access enabled Google Sheets spreadsheet with specific columns: TITLE, PROMPT, DURATION (ms), URL Google Drive folder for storing generated music files Configuration Steps: ElevenLabs API Setup: Enable Music Generation access in your ElevenLabs account Generate an API key from the ElevenLabs developer dashboard Configure HTTP Header authentication in n8n with name "xi-api-key" and your API value Google Sheets Preparation: Create or clone the music tracking spreadsheet with required columns Fill in track titles, detailed text prompts, and durations in milliseconds (10,000-300,000 ms) Configure Google Sheets OAuth credentials in n8n Update the document ID in the Google Sheets nodes Google Drive Configuration: Create a dedicated folder for music uploads Set up Google Drive OAuth credentials in n8n Update the folder ID in the upload node Workflow Activation: Ensure all API credentials are properly configured Test with a single track entry in the spreadsheet Verify music generation, upload, and spreadsheet update work correctly Execute the workflow to process all pending track requests The workflow automatically names files with timestamp prefixes (song_yyyyMMdd) and handles the complete lifecycle from prompt to downloadable music file. 👉 Subscribe to my new YouTube channel. Here I’ll share videos and Shorts with practical tutorials and FREE templates for n8n. Need help customizing? Contact me for consulting and support or add me on Linkedin.

Description This automation template is designed for content creators, social media managers, and influencers who want to streamline their video publishing workflow. It automatically detects new videos uploaded to a specific Google Drive folder, generates AI-powered descriptions based on video audio content, and simultaneously publishes them across Instagram, TikTok, and YouTube while tracking everything in Airtable. Note: This workflow uses upload-post.com API (free trial no credit card required) for multi-platform video distribution and requires API tokens for each service. The AI-generated descriptions are created using OpenAI's transcription and chat models to analyze video audio content.* Who Is This For? Content Creators & Influencers:** Automatically publish your videos across all major social platforms without manual work. Social Media Managers:** Maintain consistent posting schedules across multiple platforms with AI-generated, platform-optimized descriptions. Marketing Teams:** Scale video content distribution with automated workflows that include tracking and status monitoring. Video Producers:** Focus on creating content while the system handles the tedious task of multi-platform publishing and description generation. What Problem Does This Workflow Solve? Publishing the same video content across Instagram, TikTok, and YouTube is time-consuming and repetitive. You need to manually upload each video, write unique descriptions, and track publication status. This workflow addresses these challenges by: Automated Video Distribution:** Detects new videos in Google Drive and automatically uploads them to all three platforms simultaneously. AI-Powered Content Generation:** Uses OpenAI to transcribe video audio and generate engaging, platform-appropriate descriptions automatically. Centralized Tracking:** Maintains detailed records in Airtable including upload status, URLs, and metadata for each platform. Error Monitoring:** Provides real-time error notifications via Telegram to ensure you're always aware of any issues. How It Works Video Upload Detection: The workflow monitors a specific Google Drive folder for new video uploads using automated triggers. Content Analysis: Downloads the video, extracts audio, and uses OpenAI to transcribe and generate compelling descriptions. Airtable Integration: Creates and updates records to track video metadata, descriptions, and publication status. Multi-Platform Publishing: Simultaneously uploads the video to Instagram, TikTok, and YouTube using the upload-post.com API. Status Tracking: Updates Airtable records with publication status and platform-specific URLs for each successful upload. Setup Google Drive Configuration: Set up the Google Drive trigger to monitor your specific folder Configure OAuth2 credentials for Google Drive access OpenAI Integration: Add your OpenAI API key to enable audio transcription and description generation Airtable Setup: Create an Airtable base with fields for Video Name, Description, Platform Status, URLs, and Upload Date Add your Airtable API token and configure base/table IDs in the "Set Variables" node Upload-Post.com Account: Create an account at upload-post.com to get your API token Configure the token in the HTTP request nodes for each platform Set your user ID in the variables section Platform Accounts: Ensure your Instagram, TikTok, and YouTube accounts are connected to upload-post.com Error Notifications: (Optional) Configure Telegram bot credentials for error notifications Requirements Accounts:** Google Drive, OpenAI, Airtable, upload-post.com, Telegram (optional) API Keys & Credentials:** Google Drive OAuth2, OpenAI API Key, Airtable API Token, upload-post.com API Token Platform Setup:** Instagram, TikTok, and YouTube accounts connected to upload-post.com Transform your video publishing workflow from hours of manual work to a fully automated system that handles everything from content analysis to multi-platform distribution and tracking.

✅ What problem does this workflow solve? Shopify and E-Commerce store owners often struggle to create engaging 3D videos from static product images. This workflow automates that entire process—from image upload to video delivery—so store owners can get professional-looking 3D videos without any manual editing or follow-up. ⚙️ What does this workflow do? Accepts a 2D product image and name via a public n8n form. Generates a unique slug and folder in Google Drive for the product. Uploads the original image to Google Drive and logs data in a spreadsheet. Removes the background from the image using remove.bg API. Uploads the cleaned image to Google Drive and updates the spreadsheet. Creates a 3D product video using the cleaned image via the Fal.ai API. Periodically checks the video creation status. Once completed, download the video, upload it to Google Drive, and log the link. Notifies the store owner via email with the video download link. 🔧 Setup 🟢 Google Services Google Drive**: Create and connect a folder where all product assets will be stored. Google Spreadsheet**: A spreadsheet to log the product name, original image link, cleaned image link, and final video URL. Gmail**: Connect Gmail to send the final notification email to the store owner. 🔑 API Keys Required Remove.bg**: Get an API key from remove.bg. Fal.ai**: Sign up at fal.ai and obtain your API key to use the image-to-video generation service. 🧠 How it Works 📝 1. Product Form Submission A store owner submits the product name and 2D image via a public n8n form. 🗂 2. Organize in Google Drive A unique slug is generated for the product. A new folder is created inside Google Drive using that slug. The original image is uploaded into the folder. 📊 3. Record in a Spreadsheet The product name and original image URL are stored in a Google Sheet. 🧹 4. Background Removal The uploaded image is processed through remove.bg API to eliminate noisy or cluttered backgrounds. The cleaned image is uploaded back into the product’s Drive folder. The cleaned image link is updated in the spreadsheet. 🎥 5. Create 3D Video (via Fal.ai) The cleaned image is passed to the Fal.ai video generation API. The workflow periodically checks the status until the video is ready. ☁️ 6. Store Final Video Once the video is ready, the file is downloaded. The final video is uploaded into the same Google Drive folder. Its link is saved in the spreadsheet next to the respective product entry. 📧 7. Notify the Store Owner An automated email is sent to the store owner with the video link, letting them know it's ready for use—no waiting, no manual follow-up needed. 👤 Who can use it? This workflow is ideal for: 🛍 Shopify Sellers 🧺 E-commerce Store Owners 📸 Product Photographers 🎬 Marketing Teams 🤖 Automation Enthusiasts If you want to automate 3D product video creation using AI—this is the no-code workflow you’ve been waiting for!

Welcome to my VEO3 Video Generator Workflow! This automated workflow transforms simple text descriptions into professional 8-second videos using Google's cutting-edge VEO3 AI model. Users submit video ideas through a web form, and the system automatically generates optimized prompts, creates high-quality videos with native audio, and delivers them via Google Drive - all powered by Claude 4 Sonnet for intelligent prompt optimization. This workflow has the following sequence: VEO3 Generator Form - Web form interface for users to input video content, format, and duration Video Prompt Generator - AI agent powered by Claude 4 Sonnet that: Analyzes user input for video content requirements Creates factual, professional video titles Generates detailed VEO3 prompts with subject, context, action, style, camera motion, composition, ambiance, and audio elements Optimizes prompts for 16:9 landscape format and 8-second duration Create VEO3 Video - Submits the optimized prompt to fal.ai VEO3 API for video generation Wait 30 seconds - Initial waiting period for video processing to begin Check VEO3 Status - Monitors the video generation status via fal.ai API Video completed? - Decision node that checks if video generation is finished If not completed: Returns to wait cycle If completed: Proceeds to video retrieval Get VEO3 Video URL - Retrieves the final video download URL from fal.ai Download VEO3 Video - Downloads the generated MP4 video file Merge - Combines video data with metadata for final processing Save Video to Google Drive - Uploads the video to specified Google Drive folder Video Output - Displays completion message with Google Drive link to user The following accesses are required for the workflow: Anthropic API** (Claude 4 Sonnet): Documentation Fal.ai API** (VEO3 Model): Create API key at https://fal.ai/dashboard/keys Google Drive API**: Documentation Workflow Features: User-friendly web form**: Simple interface for video content input AI-powered prompt optimization**: Claude 4 Sonnet creates professional VEO3 prompts Automatic video generation**: Leverages Google's VEO3 model via fal.ai Status monitoring**: Real-time tracking of video generation progress Google Drive integration**: Automatic upload and sharing of generated videos Structured output**: Consistent video titles and professional prompt formatting Audio optimization**: VEO3's native audio generation with ambient sounds and music Current Limitations: Format**: Only 16:9 landscape videos supported Duration**: Only 8-second videos supported Processing time**: Videos typically take 60-120 seconds to generate Use Cases: Content creation**: Generate videos for social media, websites, and presentations Marketing materials**: Create promotional videos and advertisements Educational content**: Produce instructional and explanatory videos Prototyping**: Rapid video concept development and testing Creative projects**: Artistic and experimental video generation Business presentations**: Professional video content for meetings and pitches Feel free to contact me via LinkedIn, if you have any questions!

This workflow is designed to process PDF documents using Mistral's OCR capabilities, store the extracted text in a Qdrant vector database, and enable Retrieval-Augmented Generation (RAG) for answering questions. Here’s how it functions: Once configured, the workflow automates document ingestion, vectorization, and intelligent querying, enabling powerful RAG applications. Benefits End-to-End Automation** No manual interaction is needed: documents are read, processed, and made queryable with minimal setup. Scalable and Modular** The workflow uses subflows and batching, making it easy to scale and customize. Multi-Model Support** Combines Mistral for OCR, OpenAI for embeddings, and Gemini for intelligent answering—taking advantage of the strengths of each. Real-Time Q\&A** With RAG integration, users can query document content through natural language and receive accurate responses grounded in the PDF data. Light or Full Mode** Users can choose to index full page content or only summarized text, optimizing for either performance or richness. How It Works PDF Processing with Mistral OCR: The workflow starts by uploading a PDF file to Mistral's API, which performs OCR to extract text and metadata. The extracted content is split into manageable chunks (e.g., pages or sections) for further processing. Vector Storage in Qdrant: The extracted text is converted into embeddings using OpenAI's embedding model. These embeddings are stored in a Qdrant vector database, enabling efficient similarity searches for RAG. Question-Answering with RAG: When a user submits a question via a chat interface, the workflow retrieves relevant text chunks from Qdrant using vector similarity. A language model (Google Gemini) generates answers based on the retrieved context, providing accurate and context-aware responses. Optional Summarization: The workflow includes an optional summarization step using Google Gemini to condense the extracted text for faster processing or lighter RAG usage. Set Up Steps To deploy this workflow in n8n, follow these steps: Configure Qdrant Database: Replace QDRANTURL and COLLECTION in the "Create collection" and "Refresh collection" nodes with your Qdrant instance details. Ensure the Qdrant collection is configured with the correct vector size (e.g., 1536 for OpenAI embeddings) and distance metric (e.g., Cosine). Set Up Credentials: Add credentials for: Mistral Cloud API (for OCR processing). OpenAI API (for embeddings). Google Gemini API (for chat and summarization). Google Drive (if sourcing PDFs from Drive). Qdrant API (for vector storage). PDF Source Configuration: If using Google Drive, specify the folder ID in the "Search PDFs" node. Alternatively, modify the workflow to accept PDFs from other sources (e.g., direct uploads or external APIs). Customize Text Processing: Adjust chunk size and overlap in the "Token Splitter" node to optimize for your document type. Choose between raw text or summarized content for RAG by toggling between the "Set page" and "Summarization Chain" nodes. Test the RAG: Trigger the workflow manually or via a chat message to verify OCR, embedding, and Qdrant storage. Use the "Question and Answer Chain" node to test query responses. Optional Sub-Workflows: The workflow supports execution as a sub-workflow for batch processing (e.g., handling multiple PDFs). Need help customizing? Contact me for consulting and support or add me on Linkedin.

Who is this for? This workflow is ideal for social media managers, content creators, marketers, and small businesses who want to automate Instagram Carousel posts using Google Sheets and Google Drive. It is also suitable for anyone looking to streamline repetitive Instagram publishing tasks with n8n, Cloudinary, and the Instagram Graph API. What problem is this workflow solving? / Use case Managing and publishing Instagram Carousel posts manually can be time-consuming, especially when handling multiple accounts or campaigns. This workflow solves that by automatically fetching scheduled posts from Google Sheets, uploading images from Google Drive to Cloudinary, and publishing them to Instagram, saving time and reducing the risk of errors. What this workflow does This n8n workflow checks a Google Sheet every 5 minutes for new Carousel posts marked as "ToDo." When found, it uploads images from a specified Google Drive folder to Cloudinary, prepares the media on Instagram using the Graph API, and publishes the Carousel post with the given caption. Setup Prepare a Google Sheet to track posts and image folder URLs. Example : https://docs.google.com/spreadsheets/d/1WEUHeQXFMYsWVAW3DykWwpANxxD3DxH-S6c0i06dW1g/edit?usp=sharing Upload post images to a dedicated Google Drive folder. Set up a Cloudinary account and gather API credentials. Obtain Instagram access_token and ig_business_id for API publishing. Configure the n8n workflow with required credentials and your custom intervals. How to customize this workflow to your needs Adjust the schedule trigger interval to fit your publishing frequency. Expand the Google Sheet with additional metadata as required. Modify the filter logic to support different content types or statuses. Add extra automation steps, such as sending notifications after publishing.

Who’s it for? Content Creators E-commerce Stores Marketing Team Description: Generate unique UGC images for your products. Simply upload a product image into a Google Drive folder, and the workflow will instantly generate 50 unique, high-quality AI UGC images using Nano Banana via Fal.ai. All results are automatically saved back into the same folder, ready to use across social media, e-commerce stores, and marketing campaigns. How it works? 📺 YouTube Video Tutorial: 1 - Trigger: Upload a new Product Image (with white background) to a Folder in your Google Drive 2 - Generate 50 different Image Prompts for your Product 3 - Loop over each Prompt Generated 4 - Generate UGC Content thanks to Fal.ai (Nano Banana) 5 - Upload UGC Content on the initial Google Drive Folder Cost: 0.039$ / image== How to set up? Accounts & APIs In the Edit Field "Setup" Node replace all ==[YOUR_API_TOKEN]== with your API Token : Fal.ai (gemini-25-flash-image/edit): https://fal.ai/models/fal-ai/gemini-25-flash-image/edit/api In Credentials on your n8n Dashboard, connect the following accounts using ==Client ID / Secret==: Google Drive: https://docs.n8n.io/integrations/builtin/credentials/google/ Requirements Base Image of your Product preferably have a White Background Your Google Drive Folder and every Files it contains should be publicly available Customizations Change the amount of total UGC Generated: In Generate Prompts → Message → "Your task is to generate 50" Modify the instructions to generate the UGC Prompts: In Generate Prompts → Message Change the amount of Base Image: In Generate Image → Body Parameters → JSON → image_urls Change the amount of UGC Generated per prompt: In Generate Image → Body Parameters → JSON → num_images Modify the Folder where UGC Generated are stored: In Upload File → Parent Folder

Transcript → AI Analysis → Formatted Doc This workflow automatically converts Fathom meeting transcripts into beautifully formatted Google Docs with AI-generated summaries, key points, decisions, and action items. Good to know Works fully with Fathom free account Webhook responds immediately to prevent Fathom timeout and duplicate triggers Validates transcript quality (3+ conversation turns) before AI processing to save costs Uses Google Gemini API (generous free tier and rate limits, typically enough to avoid paying for API requests, but check latest pricing at Google AI Pricing) Creates temporary HTML file that's auto-deleted after conversion Who's it for Individuals or teams using Fathom for meetings who want more control and flexibility with their AI meeting analysis and storage independently of Fathom, as well as automatic, formatted documentation without manual note-taking. Perfect for recurring syncs, client meetings, or interview debriefs. How it works Fathom webhook triggers when meeting ends and sends transcript data Validates transcript has meaningful conversation (3+ turns) Google Gemini AI analyzes transcript and generates structured summary (key points, decisions, actions, next steps) Creates formatted HTML with proper styling Uploads to Google Drive and converts to native Google Doc Reduces page margins for readability and deletes temporary HTML file Requirements Fathom account with API webhook access (available on free tier) Google Drive account (OAuth2) Google Docs account (OAuth2) Google Gemini API key (Get free key here) How to set up Add credentials: Google Drive OAuth2, Google Docs OAuth2, Google Gemini API Copy the webhook URL from the Get Fathom Meeting webhook node (Test URL first, change to Production URL when ready) In Fathom: Settings → API Access → Add → Add webhook URL and select all events including "Transcript" Test with a short meeting, verify Google Doc appears in Drive Activate workflow Customizing this workflow Change save location: Edit "Upload File as HTML" node → update "Parent Folder" Modify AI output: Edit "AI Meeting Analysis" node → customize the prompt to add/remove sections (e.g., risks, follow-ups, sentiment, etc) Adjust document margins: Edit "Reduce Page Margins" node → change margin pixel values Add notifications: E.g. add Slack/Email node after "Convert to Google Doc" to notify team when summary is ready Quick Troubleshooting "Transcript Present?" fails: Fathom must send transcript_merged with 3+ conversation turns (i.e. only send to Gemini for analysis if there's a genuine transcript) HTML as plain text: Check "Convert to Google Doc" uses POST to /copy endpoint 401/403 errors: Re-authorize Google credentials Inadequate meeting notes: Edit prompts in "AI Meeting Analysis" node Sample File and Storage Output Google Doc meeting notes - sample Google Drive sample folder output:

Overview Automate your entire LinkedIn content machine — from research and image generation to scheduling and posting — with this AI-powered workflow. This workflow pulls in past content ideas, researches new ones using Perplexity, generates a new post (with image) using your brand's voice and style, saves the output to Google Sheets, and auto-posts twice a week to LinkedIn. It’s perfect for founders, creators, and marketers who want to stay consistent on LinkedIn without manually writing or designing every post. Who’s it for Solo founders or marketers building a LinkedIn presence Content creators growing their audience Agencies managing client content calendars Anyone who wants to post consistently without spending hours on content How it works Pulls old ideas from a Google Sheet Schedules content creation using n8n’s cron node Uses Perplexity to research current topics and trends Feeds the data into an AI agent (like Claude or GPT) to generate post copy Creates a branded image using a reference style and OpenAI’s image model Saves post content + image URL into Google Sheets Twice a week, selects one ready post, downloads the image, and publishes it to LinkedIn How to set up Add your Google Sheet ID and column names for posts Connect your OpenAI (or Claude) and Perplexity API keys Upload a brand-style reference image to Google Drive Configure your LinkedIn account and connect the node Adjust the cron schedule for both post creation and auto-posting (Optional) Edit the AI prompt to match your personal voice or niche Requirements Google Drive & Sheets access OpenAI or Claude API key Perplexity API key LinkedIn credentials (via n8n’s LinkedIn integration) How to customize Change the prompt for the AI to fit your voice or audience Swap out Perplexity for another research method Adjust how often you want posts scheduled or published Swap LinkedIn for Twitter, Slack, or another platform Add Notion or Airtable as your CMS backend

Who is this for? Content creators, digital marketers, and social media managers who want to automate the creation of short-form videos for platforms like TikTok, YouTube Shorts, and Instagram Reels without extensive video editing skills. What problem does this workflow solve? Creating engaging short-form videos consistently is time-consuming and requires multiple tools and skills. This workflow automates the entire process from ideation to publishing, significantly reducing the manual effort needed while maintaining content quality. What this workflow does This all-in-one solution transforms ideas into fully produced short-form videos through a 5-step process: Generate video captions from ideas stored in a Google Sheet Create AI-generated images using Flux and the OpenAI API Convert images to videos using Kling's API Add voice-overs to your content with Eleven Labs Complete the video production with Creatomate by adding templates, transitions, and combining all elements The workflow handles everything from sourcing content ideas to rendering the final video, and even notifies you on Discord when videos are ready. Setup (Est. time: 20-30 minutes) Before getting started, you'll need: n8n installation (tested on version 1.81.4) OpenAI API Key (free trial credits available) PiAPI (free trial credits available) Eleven Labs (free account) Creatomate API Key (free trial credits available) Google Sheets API enabled in Google Cloud Console Google Drive API enabled in Google Cloud Console OAuth 2.0 Client ID and Client Secret from your Google Cloud Console Credentials How to customize this workflow to your needs Adjust the Google Sheet structure to include additional data like video length, duration, style, etc. Modify the prompt templates for each AI service to match your brand voice and content style Update the Creatomate template to reflect your visual branding Configure notification preferences in Discord to manage your workflow This workflow combines multiple AI technologies to create a seamless content production pipeline, saving you hours of work per video and allowing you to focus on strategy rather than production.

AI-Powered Product Video Generator (Foreplay + Gemini + Sora 2) Sign Up For Foreplay HERE Automatically generate personalized, cinematic-quality product videos using Foreplay’s ad data, Google Gemini AI for creative prompts, and Sora 2 for text-to-video generation. Who’s it for? Perfect for marketers, brand managers, or creators who want to produce quick, high-quality video ads without manual scripting or editing. How it works Fetch product data and related competitor videos from Foreplay. Use Gemini AI to generate creative text-to-video prompts. Send the prompt and image to Kie.ai to generate a short, cinematic product video. Save the finished video automatically to Google Drive. How to set up Connect your Foreplay, Google Drive, Gemini, and Kie.ai credentials. Set your product image folder's permission (Google Drive) as public. Add your API keys inside the Set Workflow Credentials node. Then run the workflow manually to generate your first video ad!

What if AI didn't just write content—but actually thought about how to write it? This n8n workflow revolutionizes content creation by deploying multiple specialized AI agents that handle every aspect of blog writing—from research to publication-ready posts. The breakthrough? AI that creates its own prompts, dynamically adapting to different topics and business needs without constant human intervention. Plus, it doesn’t stop at writing — the system also scans all your website URLs, finds the best internal matches for each topic, and inserts SEO-optimized anchor links automatically. 🤖 The Self-Thinking Content System 🧠 Cognitive Content Creation: Unlike basic AI writing tools, this system thinks through the entire content strategy 🔄 Fully Automated Workflow: Set it up once and produce complete, SEO-optimized blog posts with minimal oversight 🎯 Industry-Adaptive Intelligence: Automatically tailors content approach based on your specific niche and audience 📊 Data-Driven Decisions: AI agents analyze search intent and competitive landscape before writing a single word ⚡ Modular AI Architecture: Specialized agents handle different stages of content creation for superior quality ⚙️ Workflow Breakdown 1️⃣ Keyword Research & Content Ideation Identifies high-value topics with traffic potential Analyzes search intent to match user expectations Maps content opportunities your competitors are missing 2️⃣ Dynamic Prompt Generation Revolutionary feature: AI creates its own writing instructions Customizes prompts based on topic complexity and audience needs Eliminates the need for prompt engineering expertise 3️⃣ Modular AI Writing Process Research Agent gathers comprehensive topic information Structure Agent creates logical, engaging outlines Writing Agent produces in-depth, authoritative content Each agent specializes in its role for maximum quality 4️⃣ Final Refinements Editing Agent polishes grammar, tone, and readability SEO Agent optimizes for search engines without sacrificing quality Fact-checking protocols ensure accuracy and credibility 5️⃣ Publication-Ready Output Delivers complete, formatted blog posts ready for immediate use Includes meta descriptions, title suggestions, and header structure Automatically organizes content in your preferred format 6️⃣ Smart Internal Linking Collects all URLs from your website automatically Identifies the best matching pages for each topic Inserts optimized anchor words with hyperlinks for SEO boost 🎯 Perfect For: Content Marketers who need consistent, high-quality output Business Owners looking to maintain an authoritative blog without the time investment Digital Agencies scaling content creation for multiple clients SEO Professionals focusing on quality content that ranks Solopreneurs who can't afford to spend days writing blog posts 📦 What's Included: ⚙️ Complete n8n Workflow: Pre-configured with all necessary nodes and connections 🌐 Internal Linking Function: Automatically matches your content with existing URLs and inserts SEO-friendly anchor words 🔌 AI Agent Configuration: Ready-to-use AI agent settings for each content creation stage 📊 Airtable Database Structure: Pre-built tables and fields specifically designed for content writing. Requires minimal human editing 🚀 Getting Started: Import the provided workflow into your n8n instance Configure your preferred AI provider credentials Set your content parameters and business information Trigger the workflow and watch as complete blog posts are generated Use immediately or make minor adjustments to match your style perfectly ⚡ Technical Requirements: Access to n8n (self-hosted or cloud) OpenAI API account (or alternative AI provider) Basic familiarity with workflow automation Optional: WordPress, Shopify or similar CMS for direct publishing integration This template is based on a video of Wayne Eagle 💡 You can also connect this workflow with my SEO Keyword Research Automation using DataForSEO and Airtable and my SEO-Based Keyword Categorization & Clustering Strategy Workflow with Airtable, both available on my profile, to build a fully automated, end-to-end SEO content machine. Stop spending countless hours writing blog posts or wasting money on mediocre content writers. Upgrade to an AI system that thinks for itself and produces truly exceptional content at scale.

🤹🤖 This workflow (AI Document Generator with Anthropic Agent Skills and Uploading to Google Drive) automates the process of generating, downloading, and storing professionally formatted files (PDF, DOCX, PPTX, XLSX) using the Anthropic Claude API and Google Drive. This workflow connects user prompts with the Anthropic API to generate professional documents in multiple formats, automatically retrieves and uploads them to Google Drive — providing a complete AI-powered document automation system. Key Advantages ✅ Full Automation** From user input to file delivery, the entire pipeline — creation, extraction, download, and upload — runs without manual intervention. ✅ Multi-Format Support** Handles four major business document types: PPTX (Presentations) PDF (Reports) DOCX (Documents) XLSX (Spreadsheets) ✅ Professional Output** Each format includes tailored Claude system prompts with detailed formatting and design principles: Layout structure Typography Visual hierarchy Consistency and readability This ensures that every file produced follows professional standards. ✅ Easy Customization** You can modify the prompt templates or add new Skills using the “Get All Skills” node. The form and switch logic make it simple to extend with additional file types or workflows. ✅ Seamless Cloud Integration** Generated files are automatically uploaded to a Google Drive folder, enabling: Centralized storage Easy sharing and access Automatic organization ✅ Reusable and Scalable** This workflow can be used as a foundation for: Automated report generation Client deliverables Internal documentation systems AI-driven content creation pipelines How it Works This n8n workflow enables users to create professional documents using Anthropic's Claude AI and automatically save them to Google Drive. The process works as follows: Form Trigger: The workflow starts with a web form where users submit a prompt and select their desired file type (PPTX, PDF, DOCX, or XLSX). Document Type Routing: A switch node routes the request based on the selected file type to the appropriate document creation node. AI Document Generation: Each document type has a dedicated HTTP Request node that calls Anthropic's Messages API with: Specific system prompts tailored for each document type (PowerPoint, PDF, Word, or Excel) The user's input prompt Appropriate Anthropic skills (pptx, pdf, docx, xlsx) for specialized document creation Code execution capabilities for complex formatting File ID Extraction: Custom JavaScript code nodes extract the generated file ID from Anthropic's response using recursive search algorithms to handle nested response structures. File Download: HTTP Request nodes download the actual file content from Anthropic's Files API using the extracted file ID. Cloud Storage: Finally, the downloaded files are automatically uploaded to a specified Google Drive folder, organized and ready for use. Set Up Steps API Configuration: Set up HTTP Header authentication with Anthropic API Add x-api-key header with your Anthropic API key Configure required headers: anthropic-version and anthropic-beta Google Drive Integration: Connect Google Drive OAuth2 credentials Specify the target folder ID where documents will be uploaded Ensure proper permissions for file upload operations Custom Skills (Optional): Use the "Get All Skills" node to retrieve available custom skills Update skill_id fields in JSON bodies if using custom Anthropic skills Modify the form dropdown to include custom skill options if needed Form Configuration: The form is pre-configured with prompt field and file type selection No additional setup required for basic functionality Execution: Activate the workflow Access the form trigger URL Submit prompts and select desired output formats Generated files will automatically appear in the specified Google Drive folder The workflow handles the entire process from AI-powered document creation to cloud storage, providing a seamless automated solution for professional document generation. 👉 Subscribe to my new YouTube channel. Here I’ll share videos and Shorts with practical tutorials and FREE templates for n8n. Need help customizing? Contact me for consulting and support or add me on Linkedin.

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.

This workflow automates the creation and management of a Retrieval-Augmented Generation (RAG) system using Qdrant as a vector store and Google Drive as the document source. It enables full or incremental updates to documents in the Qdrant vector database and integrates with a chatbot using Google Gemini for question answering. Here is a clear and professional description in English of the n8n workflow “Create a RAG with Qdrant and update single files”, including its benefits: Benefits Efficient RAG Setup** Seamlessly integrates OpenAI, Qdrant, and Google Drive to create a scalable RAG pipeline. Single File Update** You can replace the vector representation of a single file without reprocessing the entire collection—ideal for maintaining document freshness. Flexible File Source** Works with Google Drive, allowing document management and updates from a familiar interface. How It Works This workflow is designed to create a Retrieval-Augmented Generation (RAG) system using Qdrant as a vector store and Google Drive as a document source. It consists of four main phases: Collection Setup**: Creates or clears a Qdrant collection to store vectorized documents. Configures the collection with cosine distance metrics and other parameters. Document Processing**: Retrieves files from a specified Google Drive folder. Downloads and processes each file (text extraction, chunking, and embedding using OpenAI). Stores the embeddings in Qdrant for vector search. Single-File Update**: Allows updating or deleting a specific file in the Qdrant collection by referencing its Google Drive ID. Re-embeds the file and updates the vector store. RAG Querying**: Uses a chat trigger to receive user questions. Retrieves relevant documents from Qdrant using vector similarity. Generates answers using Google Gemini as the language model. Set Up Steps Configure Qdrant: Replace QDRANTURL and COLLECTION in the "Create collection" and "Clear collection" HTTP nodes. Ensure Qdrant API credentials are correctly set in the credentials section. Google Drive Integration: Specify the Google Drive folder ID in the "Get files" node. Ensure Google Drive OAuth credentials are configured. OpenAI and Gemini Keys: Add OpenAI API credentials for embeddings (used in "Embeddings OpenAI" nodes). Configure Google Gemini credentials for the chat model. Single-File Update: Set the file_id in the "Edit Fields3" node to target a specific Google Drive file for updates. Testing: Trigger the workflow manually to populate the Qdrant collection. Use the chat interface to test RAG responses. Need help customizing? Contact me for consulting and support or add me on Linkedin.

Automate High-Quality Voice with Google Text-to-Speech & n8n Effortlessly convert any text into stunningly realistic, high-quality audio with this powerful n8n workflow. Leveraging Google's advanced Text-to-Speech (TTS) AI, this template provides a complete, end-to-end solution for generating, storing, and tracking voiceovers automatically. Whether you're a content creator, marketer, or developer, this workflow saves you countless hours by transforming your text-based scripts into ready-to-use audio files. The entire process is initiated from a simple form, making it accessible for users of all technical levels. Features & Benefits 🗣️ Studio-Quality Voices: Leverage Google's cutting-edge AI to produce natural and expressive speech in a wide variety of voices and languages. 🚀 Fully Automated Pipeline: From text submission to final file storage, every step is handled automatically. Simply input your script and let the workflow do the rest. ☁️ Seamless Cloud Integration: Automatically uploads generated audio files to Google Drive for easy access and sharing. 📊 Organized Asset Management: Logs every generated audio file in an Airtable base, complete with the original script, a direct link to the file, and its duration. ⚙️ Simple & Customizable: The workflow is ready to use out-of-the-box but can be easily customized. Change the trigger, add notification steps, or integrate it with other services in your stack. Perfect For a Variety of Use Cases 🎬 Content Creators: Generate consistent voiceovers for YouTube videos, podcasts, and social media content without needing a microphone. 📈 Marketers: Create professional-sounding audio for advertisements, product demos, and corporate presentations quickly and efficiently. 🎓 Educators: Develop accessible e-learning materials, audiobooks, and language lessons with clear, high-quality narration. 💻 Developers: Integrate dynamic voice generation into applications, build interactive voice response (IVR) systems, or provide audio feedback for user actions. How The Workflow Operates Initiate with a Form: The process begins when you submit a script, a desired voice, and language through a simple n8n Form Trigger. Synthesize Speech: The workflow sends the text to Google's Text-to-Speech API, which generates the audio and returns it as a base64 encoded file. Process and Upload: The data is converted into a binary audio file and uploaded directly to a specified folder in your Google Drive. Enrich Metadata: The workflow then retrieves the audio file's duration using the fal.ai ffmpeg API, adding valuable metadata. Log Everything: Finally, it creates a new record in your Airtable base, storing the asset name, description (your script), content type, file URLs from Google Drive, and the audio duration for perfect organization. What You'll Need To use this workflow, you will need active accounts for the following services: Google Cloud oAuth2 Client Credentials:** With the Text-to-Speech API enabled. Google Drive:** For audio file storage. Airtable:** For logging and asset management. fal.ai:** For the ffmpeg API used to get audio duration.

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

PDF Invoice Extractor (AI) End-to-end pipeline: Watch Drive ➜ Download PDF ➜ OCR text ➜ AI normalize to JSON ➜ Upsert Buyer (Account) ➜ Create Opportunity ➜ Map Products ➜ Create OLI via Composite API ➜ Archive to OneDrive. Node by node (what it does & key setup) 1) Google Drive Trigger Purpose**: Fire when a new file appears in a specific Google Drive folder. Key settings**: Event: fileCreated Folder ID: google drive folder id Polling: everyMinute Creds: googleDriveOAuth2Api Output**: Metadata { id, name, ... } for the new file. 2) Download File From Google Purpose**: Get the file binary for processing and archiving. Key settings**: Operation: download File ID: ={{ $json.id }} Creds: googleDriveOAuth2Api Output**: Binary (default key: data) and original metadata. 3) Extract from File Purpose**: Extract text from PDF (OCR as needed) for AI parsing. Key settings**: Operation: pdf OCR: enable for scanned PDFs (in options) Output**: JSON with OCR text at {{ $json.text }}. 4) Message a model (AI JSON Extractor) Purpose: Convert OCR text into **strict normalized JSON array (invoice schema). Key settings**: Node: @n8n/n8n-nodes-langchain.openAi Model: gpt-4.1 (or gpt-4.1-mini) Message role: system (the strict prompt; references {{ $json.text }}) jsonOutput: true Creds: openAiApi Output (per item): $.message.content → the parsed **JSON (ensure it’s an array). 5) Create or update an account (Salesforce) Purpose: Upsert **Buyer as Account using an external ID. Key settings**: Resource: account Operation: upsert External Id Field: tax_id__c External Id Value: ={{ $json.message.content.buyer.tax_id }} Name: ={{ $json.message.content.buyer.name }} Creds: salesforceOAuth2Api Output: Account record (captures Id) for downstream **Opportunity. 6) Create an opportunity (Salesforce) Purpose**: Create Opportunity linked to the Buyer (Account). Key settings**: Resource: opportunity Name: ={{ $('Message a model').item.json.message.content.invoice.code }} Close Date: ={{ $('Message a model').item.json.message.content.invoice.issue_date }} Stage: Closed Won Amount: ={{ $('Message a model').item.json.message.content.summary.grand_total }} AccountId: ={{ $json.id }} (from Upsert Account output) Creds: salesforceOAuth2Api Output**: Opportunity Id for OLI creation. 7) Build SOQL (Code / JS) Purpose: Collect unique product **codes from AI JSON and build a SOQL query for PricebookEntry by Pricebook2Id. Key settings**: pricebook2Id (hardcoded in script): e.g., 01sxxxxxxxxxxxxxxx Source lines: $('Message a model').first().json.message.content.products Output**: { soql, codes } 8) Query PricebookEntries (Salesforce) Purpose**: Fetch PricebookEntry.Id for each Product2.ProductCode. Key settings**: Resource: search Query: ={{ $json.soql }} Creds: salesforceOAuth2Api Output**: Items with Id, Product2.ProductCode (used for mapping). 9) Code in JavaScript (Build OLI payloads) Purpose: Join lines with PBE results and Opportunity Id ➜ build **OpportunityLineItem payloads. Inputs**: OpportunityId: ={{ $('Create an opportunity').first().json.id }} Lines: ={{ $('Message a model').first().json.message.content.products }} PBE rows: from previous node items Output**: { body: { allOrNone:false, records:[{ OpportunityLineItem... }] } } Notes**: Converts discount_total ➜ per-unit if needed (currently commented for standard pricing). Throws on missing PBE mapping or empty lines. 10) Create Opportunity Line Items (HTTP Request) Purpose**: Bulk create OLIs via Salesforce Composite API. Key settings**: Method: POST URL: https://<your-instance>.my.salesforce.com/services/data/v65.0/composite/sobjects Auth: salesforceOAuth2Api (predefined credential) Body (JSON): ={{ $json.body }} Output**: Composite API results (per-record statuses). 11) Update File to One Drive Purpose: Archive the **original PDF in OneDrive. Key settings**: Operation: upload File Name: ={{ $json.name }} Parent Folder ID: onedrive folder id Binary Data: true (from the Download node) Creds: microsoftOneDriveOAuth2Api Output**: Uploaded file metadata. Data flow (wiring) Google Drive Trigger → Download File From Google Download File From Google → Extract from File → Update File to One Drive Extract from File → Message a model Message a model → Create or update an account Create or update an account → Create an opportunity Create an opportunity → Build SOQL Build SOQL → Query PricebookEntries Query PricebookEntries → Code in JavaScript Code in JavaScript → Create Opportunity Line Items Quick setup checklist 🔐 Credentials: Connect Google Drive, OneDrive, Salesforce, OpenAI. 📂 IDs: Drive Folder ID (watch) OneDrive Parent Folder ID (archive) Salesforce Pricebook2Id (in the JS SOQL builder) 🧠 AI Prompt: Use the strict system prompt; jsonOutput = true. 🧾 Field mappings: Buyer tax id/name → Account upsert fields Invoice code/date/amount → Opportunity fields Product name must equal your Product2.ProductCode in SF. ✅ Test: Drop a sample PDF → verify: AI returns array JSON only Account/Opportunity created OLI records created PDF archived to OneDrive Notes & best practices If PDFs are scans, enable OCR in Extract from File. If AI returns non-JSON, keep “Return only a JSON array” as the last line of the prompt and keep jsonOutput enabled. Consider adding validation on parsing.warnings to gate Salesforce writes. For discounts/taxes in OLI: Standard OLI fields don’t support per-line discount amounts directly; model them in UnitPrice or custom fields. Replace the Composite API URL with your org’s domain or use the Salesforce node’s Bulk Upsert for simplicity.

Extract data from any PDF or image invoice dropped in Google Drive directly into Google Sheets – powered by AI OCR. Free, fully modifiable n8n workflow. Optional add-ons for pro features. 🚀 What this template does Stop typing invoice data by hand. Drop a PDF or phone-snapshot into your Invoices Inbox folder in Google Drive and this n8n workflow will: Auto-OCR the document with the Mistral OCR API Match any fields you list in Row 1 of your Google Sheet (totally schema-agnostic) Append a clean, structured row – every time Works with both PDFs and images, in any language supported by Mistral. Template JSON included, ready to import into self-hosted or n8n Cloud 👀 Who’s this for? Freelancers & agencies processing client invoices Small finance teams on Google Workspace Anyone self-hosting n8n who wants an AI OCR flow without glue-code No coding skills required – but flow tweaking is possible for power users. 🛠 Upcoming PRO Add-Ons I am also working on PRO add-ons for this template: Add-On #1 – Error Handling & Alerts (ships Jul 2025)• Flags missing fields, branches to Email/Slack notification; prevents silent failures Add-On #2 – Auto-Currency Converter (ships Jul 2025)• Detects invoice currency symbol/code → converts Total into your base currency via a free FX API Add-On #3 – VAT / GST Breakdown (ships Jul 2025)• Extracts VAT number, net, tax rate, tax amount, gross – ready for EU/UK/AU filings To pre-order these please see: https://ysqander.gumroad.com/l/N8N-AI-Workflow-Invoice-Data-Extraction-LITE

Overview This n8n templates helps you to authomatically search Linkeding jobs. It uses AI (Gemini or OpenAPI) to match your resume with each job description and write a sample cover letter for each job and update the job google sheet. You can receive daily matched linkedin job alerts by telegram. Prerequisites AI API Key from one model like: Google Gemini OpenAI Telegram Bot Token - Create via @BotFather Google Sheets - OAuth2 credentials Google Drive - OAuth2 credentials Setup Upload your resume Upload your CV in PDF format in google drive and configure google drive node to read your resume from list of google drive files. You need to configure Google Drive OAuth2 and grant access to your drive before that. You can find useful infomration about how to configure Googel OAuth2 API key in n8n documents. Create Google sheet You need to create a google sheet document consist of two sheets, one sheet for define job filter criteria and second sheet to store job search result. You can download this Google Sheet Template and copy in your personal space. Then you can add your job filter in Google sheet. You can search job by keywords, location, remote type, job type and easy apply. You need to configure Google Sheet OAuth2 and grant access to your drive before that. Conifgure Telegram Bot You need to create a new Telegram Bot in @BotFather and insert API Key in Telegram node and you need to TELEGRAM_CHAT_ID to your telegram ID.

Social Media Content Publishing Factory for Streamlined Content Creation Across Platforms Who is this for? This workflow is designed for content creators, social media managers, and marketing teams who need to efficiently create and publish content across multiple social media platforms. It's perfect for businesses looking to maintain a consistent presence across X (Twitter), Instagram, Facebook, LinkedIn, Threads, and YouTube Shorts without spending hours crafting platform-specific content manually. What problem is this workflow solving? Creating tailored content for different social media platforms is time-consuming and requires understanding each platform's unique requirements and audience expectations. This workflow solves the challenge of: Maintaining consistent messaging across platforms while respecting platform-specific formats Generating optimized content that follows best practices for each platform Creating accompanying visuals without graphic design skills Streamlining the approval process before publishing Reducing the time spent on repetitive content creation tasks What this workflow does This automated content factory takes your content idea and transforms it into platform-optimized posts for all major social media channels. The workflow: Accepts your content idea or topic through a chat interface Leverages AI to generate tailored content for each platform (X/Twitter, Instagram, Facebook, LinkedIn, Threads, YouTube Shorts) Creates appropriate images using AI image generation Sends content for approval via email before publishing Publishes approved content to selected platforms Maintains chat memory to improve future content generation Setup Connect your social media platform credentials (X/Twitter, Instagram, Facebook, LinkedIn) Set up your email account for the approval process Configure your OpenAI API key for AI content generation Update the image generation service credentials (Pollinations.ai is used by default) Customize the system prompts and schemas in the Google Docs nodes with your brand voice and content requirements How to customize this workflow to your needs Modify the system prompts in the Google Docs nodes to match your brand voice and content strategy Adjust the social media schemas to include specific fields relevant to your content Update the approval process to include additional stakeholders if needed Add or remove social media platforms based on your marketing strategy Customize the image generation prompts to better match your visual branding Integrate with your existing content calendar or CRM systems This workflow eliminates the need to manually craft different versions of the same content for each platform, saving hours of work while ensuring your social media presence remains consistent and optimized for maximum engagement.

Description This comprehensive n8n automation template orchestrates a complete end-to-end workflow for generating engaging short-form Point-of-View (POV) style videos using multiple AI services and automatically publishing them across major social media platforms. It takes ideas from a Google Sheet and transforms them into finished videos with captions, voiceovers, and platform-specific descriptions, ready for distribution. Who Is This For? Content Creators & Agencies:** Mass-produce unique short-form video content for various clients or channels with minimal manual effort. Digital Marketers:** Automate video content pipelines to boost online presence and engagement across multiple platforms simultaneously. Social Media Managers:** Schedule and distribute consistent video content efficiently without juggling multiple tools and manual uploads. Businesses:** Leverage AI to create branded video content for marketing, reducing production time and costs. What Problem Does This Workflow Solve? Creating and distributing high-quality short-form video content consistently across multiple social networks is incredibly time-consuming and resource-intensive. This workflow tackles these challenges by: Automating Idea-to-Video Pipeline:** Generates video concepts, image prompts, scripts, images, video clips, and voiceovers using AI. Streamlining Video Assembly:** Automatically combines generated assets into a final video using a template. Generating Platform-Optimized Descriptions:** Creates relevant descriptions for posts by transcribing the final video audio. Automating Multi-Platform Publishing:** Uploads the final video and description to TikTok, Instagram, YouTube, Facebook, and LinkedIn simultaneously. Reducing Manual Workload:** Drastically cuts down the time and effort required for video production and distribution. Centralized Tracking:** Updates a Google Sheet with results, costs, and status for easy monitoring. How It Works Trigger & Input: Runs on a daily schedule (configurable) and fetches new video ideas from a designated Google Sheet. AI Content Generation: Uses OpenAI to generate video captions and image prompts based on the idea. Uses PiAPI (Flux) to generate images from prompts. Uses PiAPI (Kling) to generate video clips from the images (Image-to-Video). Uses OpenAI to generate a voiceover script based on the captions. Uses ElevenLabs to generate voiceover audio from the script and uploads it to Google Drive. Video Assembly: Combines the generated video clips, captions, and voiceover audio using a Creatomate template to render the final video. Description Generation: Uploads the final video to Google Drive, extracts the audio using OpenAI (Whisper), and generates a social media description using OpenAI (GPT). Multi-Platform Distribution: Uses upload-post.com to upload the final video and generated description to TikTok, Instagram, YouTube, Facebook, and LinkedIn. Tracking & Notification: Updates the original Google Sheet row with output details (video link, costs, tokens used) and sends a completion notification via Discord. Setup Accounts & API Keys: Obtain accounts and generate API keys/credentials for: n8n Google Cloud Platform (for Google Sheets & Google Drive APIs + OAuth Credentials) OpenAI PiAPI ElevenLabs Creatomate upload-post.com Discord (Webhook URL) Google Sheet: Make a copy of the provided Google Sheet Template and connect it in the Load Google Sheet node. Creatomate Template: Set up a video template in Creatomate (use the provided JSON source code as a base) and note its Template ID. Configure Nodes: Enter all API Keys/Credentials in the Set API Keys node and other relevant credential sections (Google nodes, upload-post nodes, etc.). Configure Google Drive nodes (Folder IDs, Permissions). Configure the upload-post.com nodes with your user identifier and necessary platform details (e.g., Facebook Page ID). Customize AI prompts within the OpenAI nodes (Generate Video Captions, Generate Image Prompts, Generate Script, Generate Description...) if desired. Set the Discord Webhook URL in the Notify me on Discord node. Enable Google APIs: Ensure Google Drive API and Google Sheets API are enabled in your Google Cloud Project. Requirements Accounts:** n8n, Google (Sheets, Drive, Cloud Platform), OpenAI, PiAPI, ElevenLabs, Creatomate, The social media api Upload-Post, Discord. API Keys & Credentials:** API Keys for OpenAI, PiAPI, ElevenLabs, Creatomate, upload-post.com. Google Cloud OAuth 2.0 Credentials. Discord Webhook URL. Templates:** A configured Google Sheet based on the template, a configured Creatomate video template. (Potentially) Paid Plans:** Some services (OpenAI, PiAPI, Creatomate, upload-post.com) may require paid plans depending on usage volume after free trials/credits are exhausted. Use this template to build a powerful, automated video content factory, scaling your production and distribution efforts across the social media landscape.

📊 Description Automate short-term trading research by generating high-quality trade ideas using MCP (Market Context Protocol) signals and AI-powered analysis. 📈🤖 This workflow evaluates market context, catalysts, momentum, and risk factors to produce structured trade ideas with clear reasoning, confidence scores, and execution notes. Designed for fast-moving markets, it helps traders and analysts spot actionable opportunities consistently—without manual screening or emotional bias. Perfect for systematic traders, research teams, and AI-driven trading desks. ⚡📊 🔁 What This Template Does 1️⃣ Ingests market context and asset data from MCP inputs. 📥 2️⃣ Normalizes symbols, sectors, and time horizons for analysis. 🧾 3️⃣ Evaluates short-term momentum and catalyst strength. 🚀 4️⃣ Analyzes risk, volatility, and downside exposure. ⚠️ 5️⃣ Uses AI to generate a structured trade thesis. 🤖 6️⃣ Assigns a confidence score and risk level to each idea. 📊 7️⃣ Produces clear entry logic, rationale, and trade direction. 🧠 8️⃣ Filters out low-quality or low-conviction setups. 🚫 9️⃣ Outputs clean JSON-ready trade ideas for downstream systems. 🔁 ⭐ Key Benefits ✅ Automates short-term trade idea generation ✅ Reduces emotional bias with AI-based scoring ✅ Combines market context, catalysts, and momentum ✅ Produces structured, repeatable trade logic ✅ Saves hours of manual chart and news analysis ✅ Ideal for fast-paced trading environments 🧩 Features MCP (Market Context Protocol) data ingestion AI-powered trade thesis generation Confidence and risk scoring logic Short-term momentum and catalyst analysis Strict structured output for automation reliability Easy integration into dashboards or execution systems 🔐 Requirements MCP-compatible market data source OpenAI API credentials (GPT-4o or GPT-4o-mini recommended) n8n instance with AI nodes enabled Defined schema for trade idea output 🎯 Target Audience Short-term and swing traders Quant and discretionary trading teams Market research analysts Fintech platforms generating trade signals Automation engineers building trading workflows

Voiceflow is a no-code platform that allows you to design, prototype, and deploy conversational assistants across multiple channels—such as chat, voice, and phone—with advanced logic and natural language understanding. It supports integration with APIs, webhooks, and even tools like Twilio for phone agents. It's perfect for building customer support agents, voice bots, or intelligent assistants. This workflow connects n8n and Voiceflow with tools like Google Calendar, Qdrant (vector database), OpenAI, and an order tracking API to power a smart, multi-channel conversational agent. There are 3 main webhook endpoints in n8n that Voiceflow interacts with: n8n_order – receives user input related to order tracking, queries an API, and responds with tracking status. n8n_appointment – processes appointment booking, reformats date input using OpenAI, and creates a Google Calendar event. n8n_rag – handles general product/service questions using a RAG (Retrieval-Augmented Generation) system backed by: Google Drive document ingestion, Qdrant vector store for search, and OpenAI models for context-based answers. Each webhook is connected to a corresponding "Capture" block inside Voiceflow, which sends data to n8n and waits for the response. How It Works This n8n workflow integrates Voiceflow for chatbot/voice interactions, Google Calendar for appointment scheduling, and RAG (Retrieval-Augmented Generation) for knowledge-based responses. Here’s the flow: Trigger**: Three webhooks (n8n_order, n8n_appointment, n8n_rag) receive inputs from Voiceflow (chat, voice, or phone calls). Each webhook routes requests to specific functions: Order Tracking: Fetches order status via an external API. Appointment Scheduling: Uses OpenAI to parse dates, creates Google Calendar events, and confirms via WhatsApp. RAG System: Queries a Qdrant vector store (populated with Google Drive documents) to answer customer questions using GPT-4. AI Processing**: OpenAI Chains: Convert natural language dates to Google Calendar formats and generate responses. RAG Pipeline: Embeds documents (via OpenAI), stores them in Qdrant, and retrieves context-aware answers. Voiceflow Integration: Routes responses back to Voiceflow for multi-channel delivery (chat, voice, or phone). Outputs**: Confirmation messages (e.g., "Event created successfully"). Dynamic responses for orders, appointments, or product support. Setup Steps Prerequisites: APIs**: Google Calendar & Drive OAuth credentials. Qdrant vector database (hosted or cloud). OpenAI API key (for GPT-4 and embeddings). Configuration: Qdrant Setup: Run the "Create collection" and "Refresh collection" nodes to initialize the vector store. Populate it with documents using the Google Drive → Qdrant pipeline (embeddings generated via OpenAI). Voiceflow Webhooks: Link Voiceflow’s "Captures" to n8n’s webhook URLs (n8n_order, n8n_appointment, n8n_rag). Google Calendar: Authenticate the Google Calendar node and set event templates (e.g., summary, description). RAG System: Configure the Qdrant vector store and OpenAI embeddings nodes. Adjust the Retrieve Agent’s system prompt for domain-specific queries (e.g., electronics store support). Optional: Add Twilio for phone-agent capabilities. Customize OpenAI prompts for tone/accuracy. PS. You can import a Twilio number to assign it to your agent for becoming a Phone Agent Need help customizing? Contact me for consulting and support or add me on Linkedin

This workflow automates the generation and delivery of personalized business documents (e.g., contracts, job offers, invoices, pay slips) in PDF format. The data source is a Google Sheet, and the documents are created using CraftMyPDF, then uploaded to Google Drive and optionally sent via email. This workflow is ideal for bulk document generation (contracts, invoices, etc.) with minimal manual intervention. Benefits Fully Automated**: Once triggered, it handles the whole pipeline end-to-end—no manual editing or document creation needed. Customizable**: Works with any type of business document as long as you provide a CraftMyPDF template. Scalable**: Processes multiple entries in batch, ideal for HR departments or finance teams. Integrated**: Seamlessly connects Google Sheets, CraftMyPDF, Google Drive, and Gmail. Trackable**: Updates the original spreadsheet to keep track of which documents have been processed. Requirements Self-hosted n8n instance (required for some advanced node usage). Google Sheet template with columns like: FIRST NAME, LAST NAME, ADDRESS, etc. A CraftMyPDF account with a ready-made template. Google OAuth2 credentials for Sheets, Drive, and Gmail integrations. How It Works Trigger & Data Fetch: The workflow starts with a manual trigger ("When clicking ‘Execute workflow’"). It retrieves employee data from a Google Sheet ("Get employees"), filtering rows where the "DONE" column is empty. PDF Generation & Processing: The "Loop Over Items" node processes each employee record individually. The "Create agreement" node uses CraftMyPDF to generate a PDF contract, populating it with employee details (name, address, email, etc.). A conditional node ("Success?") checks if PDF creation was successful. PDF Handling & Notifications: The PDF is fetched ("Get agreement") and uploaded to Google Drive ("Upload agreement") with a filename like [First-Name]-[Last-Name].pdf. An email with the PDF attachment is sent to the employee via Gmail ("Send email with PDF"). Tracking & Completion: The Google Sheet row is updated with "x" in the "DONE" column ("Update row") to mark completion. The workflow merges results and loops until all records are processed. Set Up Steps Prerequisites: Use the self-hosted version of n8n (required for this workflow). Clone the provided Google Sheet template. Configure CraftMyPDF: Create an account on CraftMyPDF. Design a PDF template and note its Template ID. Insert this ID in the "Create agreement" node. Credentials Setup: Connect nodes to: Google Sheets (to fetch/update data). Google Drive (to store PDFs). Gmail (to send emails). CraftMyPDF (for PDF generation). Customization: Adjust field mappings in the "Create agreement" node to match your PDF template placeholders. Modify the email template in "Send email with PDF" as needed. Execution: Run the workflow manually. It will process all rows lacking a "DONE" marker, generating PDFs, sending emails, and updating the sheet automatically. Need help customizing? Contact me for consulting and support or add me on Linkedin.

CV → Match → Screen → Decide, all automated This workflow automatically processes candidate CVs from email, intelligently matches them to job descriptions, performs AI-powered screening analysis, and sends actionable summaries to your team in Slack. Good to know Handles both PDF and Word document CVs automatically Two-stage JD matching: prioritizes role mentioned in candidate's email, falls back to CV analysis if needed Uses Google Gemini API for AI screening (generous free tier and rate limits, typically enough to avoid paying for API requests, but check latest pricing at Google AI Pricing) All CVs stored in Google Drive with standardized naming (candidate name + date/time) Complete audit trail logged in Google Sheets Who's it for Hiring teams and recruiters who want to automate first-round CV screening while maintaining quality. Perfect for companies receiving high volumes of applications across multiple roles, especially in tech, sales, or automation-focused positions. How it works Gmail monitors inbox for CVs with specific label and downloads attachments Detects file type (PDF or Word) and converts/standardizes format for text extraction AI agent matches candidate to best-fit job description by analyzing email context first (if candidate mentioned a role), or CV content as fallback (selects up to 3 potential JD matches) If multiple JDs matched, second AI agent selects the single best fit AI recruiter agent analyzes CV against selected JD and generates structured screening report (strengths, weaknesses, risk/reward factors, overall fit score 0-10 with justification) Extracts candidate details (name, email) from CV text Logs complete analysis to Google Sheets tracker Sends formatted summary to Slack with Proceed/Reject action buttons for instant team decisions Requirements Gmail account with API access Google Drive account (OAuth2) Google Sheets account (OAuth2) Slack workspace with bot permissions Google Gemini API key (Get free key here) Google Drive folders: one for CVs, one for Job Descriptions (as PDFs or Google Docs) How to set up Add credentials: Gmail OAuth2, Google Drive OAuth2, Google Sheets OAuth2, Slack OAuth2, Google Gemini API Create Gmail label (e.g., "CV-Screening") for incoming candidate emails In "Receive CV via Email" node: select your Gmail label for filtering Create two Google Drive folders: "Candidate CVs" and "Job Descriptions" In "Upload CV - PDF" and "Stream Doc/Docx File" nodes: update folder ID to your "Candidate CVs" folder In "Access JD Files" node: update folder ID to your "Job Descriptions" folder Create Google Sheet named "AI Candidate Screening" with columns matching the sample AI Candidate Screening sheet In "Append row in sheet" node: select your Google Sheet In "Send Candidate Screening Confirmation" node: select your Slack channel Activate workflow Customizing this workflow Change JD matching logic: Edit "JD Matching Agent" node prompt to adjust how CVs are matched to roles (e.g., weight technical skills vs. experience). Change "Company Description" in AI prompts: Insert your "Company Description" in System Message sections in "JD Matching Agent" and "Detailed JD Matching Agent" nodes Modify screening criteria: Edit "Recruiter Scoring Agent" node system message to focus on specific qualities (culture fit, leadership, technical depth, etc.) Add more storage locations: Add nodes to save CVs to other systems (Notion, Airtable, ATS platforms) Customize Slack message: Edit "Send Candidate Screening Confirmation" node to change formatting, add more context, or include additional candidate data Auto-proceed logic: Add IF node after screening to auto-proceed candidates with fit score above threshold (e.g., 8+/10) Add email responses: Connect nodes to automatically email candidates (confirmation, rejection, interview invite) Add human-in-the-loop: Sub-workflow triggered by Slack response or email response, to update Sheet with approve/reject status Add candidate email responses + interview scheduling**: For approved candidates, trigger email to candidate with Cal.com or Calendly link so they can book their interview Quick Troubleshooting No CVs being processed: Check Gmail label is correctly set in "Receive CV via Email" node and emails are being labeled Word documents failing: Verify "Stream Doc/Docx File" node has correct parent folder ID and Google Drive credentials authorized JD matching returns no results: Check "Access JD Files" node folder ID points to your Job Descriptions folder, and JD files are named clearly (e.g., "Marketing Director JD.pdf") JD matching is not relevant for my company: Update the "Company Description" in the System Messages in the "JD Matching Agent" and "Detailed JD Matching Agent" nodes "Can't find matching JD": Ensure candidate's email mentions role name OR their CV clearly indicates relevant experience for available JDs Google Sheets errors: Verify sheet name is "AI Candidate Screening" and column headers exactly match workflow expectations (Submission ID, Date, CV, First Name, etc.) Slack message not appearing: Re-authorize Slack credentials and confirm channel ID in "Send Candidate Screening Confirmation" node Missing candidate name/email: CV text must be readable - check PDF extraction quality or try converting complex CVs to simpler format 401/403 API errors: Re-authorize all OAuth2 credentials (Gmail, Google Drive, Google Sheets, Slack) AI analysis quality issues: Edit system prompts in "JD Matching Agent" and "Recruiter Scoring Agent" nodes to refine screening criteria Sample Outputs Google Sheets - AI Candidate Screening - sample Slack confirmation message Acknowledgments This workflow was inspired by Nate Herk's YouTube demonstration on building a resume analysis system. This implementation builds upon that foundation by adding dynamic job description matching (initial + detailed JD matching agents), Slack Block Kit integration with interactive buttons, updated Google Drive API methods for document handling, and enhanced candidate data capture in Google Sheets.

Social Media Spark (SMS) — Automated Viral Content Engine Automate your entire content workflow: discover viral ideas, generate posts in your tone, repurpose for X, and auto-publish — reducing 90% of manual effort. 🚀 What it Does Scrapes competitors or niche profiles on LinkedIn to find high-performing posts. Classifies and saves evergreen content ideas for later use. Generates fresh posts in your own voice with matching images. Repurposes content for X (Twitter) in a platform-optimized style. Automatically publishes content to LinkedIn and X on your schedule. Allows on-demand commands via Telegram for research or instant content generation. 🧩 Why Use It Save time:** no more manual scraping, idea collection, or formatting. Stay consistent:** maintain a daily content pipeline. Multi-platform leverage:** create once, adapt for LinkedIn and X. Creative control:** mix automation with optional human review. Scalable:** extend to more platforms, analytics, and workflows as you grow. 🔧 Prerequisites & Setup Before importing or activating the workflow, prepare these: AI Provider (OpenAI / Gemini / OpenRouter)** For classifying posts, generating new content, repurposing for X. Google Sheets** Central database for competitors, ideas, generated posts, and posting status. Google Drive** Stores generated images. Apify & Browseract** Scrapes LinkedIn profiles, posts, and performs research tasks. LinkedIn API** Needed for automated LinkedIn publishing. X (Twitter) API** Requires OAuth 1.0a for image uploads and OAuth 2.0 for text posting. Telegram Bot** Enables on-demand commands and notifications. Set your Telegram User ID in the trigger node. > 🔎 In each sub-workflow, look for nodes marked “Configure Me!” to replace example prompts, search keywords, sheet IDs, etc. ⚙️ How It Works (Simplified Flow) Scrape & Classify: Collect high-engagement posts → keep evergreen ones. Generate Content: Rewrite ideas into new posts in your voice → create images. Repurpose for X: Adapt LinkedIn posts for short-form, high-impact tweets. Auto-Publish: Post daily on LinkedIn and X. Control via Telegram: Manually trigger scraping, research, or post generation. 💡 Best Practices & Tips Keep all API keys private — never share them in public repos or screenshots. Adjust cron schedules (e.g., scraping on weekends, posting on weekdays) to fit your content rhythm. Add Human-in-the-Loop review steps for brand-sensitive content. Extend to other platforms (Instagram, TikTok, YouTube Shorts) as needed. Experiment with prompt variations for different tones or creative styles. Add analytics logging (likes, comments, clicks) to measure content performance. 🙋‍♂️ Who is This For Solo creators & founders** who want to post consistently but don’t have time for daily ideation. Small marketing teams** that need to keep up with trends without spending hours on research. Consultants & thought leaders** who want to amplify their personal brand on LinkedIn and X. Startups & bootstrapped businesses** that need a lean but reliable content engine. Content strategists** who want a data-driven, repeatable pipeline for finding and using what works. Or anyone who wants to boost social presence by 300% 💡 Why SMS Stands Out Authentic voice:** Uses your own tone and style (defined in prompts and examples), so posts feel personal — not generic AI fluff. Data-driven:** Pulls from real, viral posts in your niche to inspire fresh content. Quality over quantity:** Focuses only on proven viral ideas instead of churning random posts. Consistent growth:** Keeps your posting regular, so you stay visible and relevant. Efficient workflow:** Minimizes manual work while letting you step in when needed (e.g., for approvals or special campaigns). > ⚡ SMS combines real market data with your unique voice — so you post smarter, not just more often.

Overview This n8n workflow automates the creation and publishing of Instagram carousel posts by downloading images from Google Drive, uploading them to Cloudinary for hosting, and publishing them as a coordinated carousel post via Facebook Graph API. This workflow is perfect for social media managers and content creators who need to publish coordinated multi-image posts from cloud-stored assets with minimal manual intervention. Key Features Multi-Image Processing: Handles multiple images for carousel posts automatically Cloud Image Hosting: Uses Cloudinary for reliable image hosting and delivery Instagram API Integration: Creates and publishes carousel posts via Facebook Graph API Google Drive Integration: Downloads images directly from Google Drive links Telegram Notifications: Sends success notifications after post publication Error Handling: Continues workflow execution even if individual images fail Technical Workflow Data Preparation: Structures input data with image links and post content Batch Processing: Loops through multiple image URLs from Google Drive Image Download: Downloads each image from Google Drive Cloud Upload: Uploads images to Cloudinary for public hosting Media Creation: Creates Instagram media objects for each image ID Collection: Collects all media IDs for carousel creation Carousel Assembly: Creates carousel post with all images and caption Publication: Publishes the complete carousel to Instagram Notification: Sends Telegram confirmation message Prerequisites Facebook Graph API credentials with Instagram Business permissions Google Drive API access for image downloads Cloudinary Account for image hosting Instagram Business Account connected to Facebook Telegram Bot for notifications Input Data Structure The workflow expects data with these fields: instagram_content: Caption text for the post Instagram Account ID: Target Instagram business account pose_X_drive_fotolink: Google Drive links for carousel images Image metadata for processing Configuration Options Wait Times: 20s between carousel creation and 15s before publishing for API rate limits Image Processing: Automatic upload to Cloudinary with preset configurations Error Handling: Individual image failures won't stop the entire carousel creation Batch Processing: Processes all images simultaneously for efficiency

This n8n workflow automatically finds apartments for rent in Germany, filters them by your city, rent budget, and number of rooms, and applies to them via email. Each application includes: A personalized German cover letter Schufa report (fetched dynamically from Google Drive) Recent salary slips (also fetched from Google Drive) The workflow runs daily at a scheduled time, emails landlords or agencies automatically, and logs every application into a Google Sheet for tracking. How It Works Scheduled Trigger – Runs every day at 9 AM (adjustable). Fetch Listings – Uses immobilienscout24 API (or similar) to pull rental listings for your selected city. Filter Listings – Keeps only listings matching your CITY, MAX_RENT, and ROOMS settings. Fetch Documents – Retrieves your Schufa report and salary slips from Google Drive (no need for local hosting). Generate Cover Letter – Creates a personalized German-language letter per apartment. Send Email Application – Sends the email to the landlord or agent with cover letter + documents attached. Log Applications – Saves each application (title, address, rent, date) in a Google Sheet. How to Use Import the workflow JSON into n8n. Set environment variables in n8n (for security): immobilienscout24_TOKEN: Your immobilienscout24 API token immobilienscout24_LISTING_ACTOR: Actor ID for your preferred rental listing scraper (or custom) MY_EMAIL: Your sender email address (SMTP configured in n8n) SCHUFA_FILE_ID: Google Drive File ID for your Schufa PDF SALARY_FILE_ID: Google Drive File ID for your Salary Slips PDF APPLICATION_SHEET_ID: Google Sheet ID to log applications Authenticate Google Drive and Google Sheets (OAuth2 in n8n). Customize search filters in the Set Config node: CITY (e.g., Berlin) MAX_RENT (e.g., 1200) ROOMS (e.g., 2) Activate the workflow – It will run daily at the configured time and send applications automatically. Check your Google Sheet – Every application will be logged for tracking. Requirements An immobilienscout24 account (or another apartment listing API, can be substituted). A Google account (for Drive and Sheets integration). A Schufa report (PDF) uploaded to Google Drive. Recent salary slips (PDF) uploaded to Google Drive. An SMTP-configured email account for sending applications. n8n instance (self-hosted or cloud) with: Google Drive and Google Sheets credentials configured Environment variables set for tokens and file IDs A working email SMTP setup

Auto-Generate Long Videos with AI, ElevenLabs,PIAPI,Shotstack/Creatomate & Post to Youtube Overview This n8n automation workflow automates the creation, scripting, production, and posting of YouTube videos. It leverages AI (OpenAI), image generation (PIAPI), video rendering (Shotstack), and platform integrations (Airtable, Google Sheets, YouTube) to streamline the process. Target Audience Content creators, video producers, and YouTubers** seeking to automate video content creation. Digital marketing teams** managing video campaigns for travel or history niches. Users familiar with n8n, Airtable, Google Sheets, YouTube, and API integrations**. Problem Solved Manually managing YouTube video production, from ideation to posting, is time-consuming and prone to errors. This workflow addresses: Content Sourcing**: Generates video ideas using AI based on "domain of choice". Content Formatting**: Automatically creates detailed scripts and scene structures. Visual Production**: Produces high-quality images and renders videos with minimal manual input. Multi-Platform Integration**: Publishes to YouTube with status tracking in Airtable and Google Sheets. Status Tracking**: Monitors progress (Generated, Scripted, Produced, Published) across platforms. Prerequisites Before setting up, ensure you have: An n8n instance (self-hosted or cloud) API credentials for: OpenAI (for idea generation) PIAPI.ai (for image and video generation) ElevenLabs (for audio generation) Shotstack (for video rendering) Creatomate (for video rendering) Airtable & Google Sheets and Drive (for storage and tracking) Gmail (for notifications) YouTube API (for posting to YouTube) How the Automation Works (Step by Step) Trigger (Schedule Trigger) Initiates the workflow daily Connects to "Generate Idea" Generate Idea Uses OpenAI to create a unique 4-minute video idea with a title, description, keywords, scene structure, and intrigue note Checks Airtable "Ideas" table via searchAirtable to avoid duplicates Connects to "Parse Ideas" Parse Ideas Extracts title, description, and notes from the OpenAI output using JavaScript Connects to "Add Ideas" Add Ideas Stores the initial idea in Google Sheets "Ideas" sheet with fields like "Idea", "Description", and "Progress" (set to "Generated") Connects to "Store in Airtable" Store in Airtable Saves the idea to Airtable "Ideas" table with mapped fields and typecast enabled Connects to "Generate Script" Generate Script Creates a 500-600 word script with 8-10 scenes using OpenAI, based on the latest "Generated" idea Uses Structured Output Parser to format output Connects to "Parse Script Output" Parse Script Output Formats the script into readable text and JSON, extracting scenes and closing question Connects to "Store Script" Store Script Saves the script to Google Sheets "Production" sheet with "Script", "Scenes", and "Status" (set to "Scripted") Connects to "Store Script in Airtable" Store Script in Airtable Saves the script to Airtable "Production" table with mapped fields and typecast enabled Connects to "Updated Idea to Scripted" Updated Idea to Scripted Updates the idea status to "Scripted" in Google Sheets "Ideas" sheet Connects to "Update Status Ideas Table" Update Status Ideas Table Updates the idea status to "Scripted" in Airtable "Ideas" table, matching by "Idea ID" Connects to "Extract Scenes" Extract Scenes Parses scene data from Airtable "Production" table for image generation Connects to "Text-to-Image" Text-to-Image Generates images for each scene using PIAPI Connects to "Wait for 4 Min" Wait for 4 Min Waits 3 minutes to allow image generation to complete Connects to "Get Images" Trigger (Schedule Trigger1) Initiates the posting process daily Connects to "Search for Latest Ready Video" Search for Latest Ready Video Searches Airtable "Production" table for the latest video with "Status" = "Ready" Connects to "If Ready?" If Ready? Checks if a video is ready (condition: Status contains Ready) If true, connects to "Download Video" and "Update Production Table" Download Video Downloads the video file using the VideoURL from Airtable Connects to "Post YouTube" Post YouTube Uploads the video to YouTube with title and description, using YouTube OAuth2 Update Production Table Updates the "Production" sheet in Google Sheets, setting "Status" to "Published" and matching by "Production ID" Additional Nodes and Processes OpenAI Chat Model**: Powers "Generate Idea" and "Generate Script" with GPT Structured Output Parser**: Ensures proper JSON output for scripts Get Images**: Retrieves generated images Extract Narration**: Prepares narration for voice generation Voice Generation**: Generates voiceovers Generate Music Prompt**: Creates music prompts using OpenAI Text-to-Music**: Generates music Build Shotstack Timeline**: Constructs video timeline ShotStack Render Video**: Renders the final video Poll Rendered Videos**: Checks video rendering status Final Video**: Updates Airtable "Production" with final video details Final Video Update**: Updates Google Sheets "Production" with video URL Music Urls**: Adds music URLs to the process Setup Requirements Before starting, ensure you have the following 1 n8n Instance A self-hosted or cloud-based n8n instance to run the workflow 2 API Credentials OpenAI: API key Airtable: Personal Access Token (e.g, "Airtable Personal Access Token Google Sheets: OAuth2 credentials PIAPI: HTTP Header Auth key YouTube: OAuth2 credentials 3 Airtable Configuration Base: "Youtube Videos" Tables: "Ideas" "Production" Share with the Airtable token 4 Google Sheets Configuration Document: "Youtube Videos" Sheets: "Ideas" "Production" Share with the Google Sheets credential email Shotstack Configuration (Assumed) API key and endpoint for video rendering (not specified in JSON) Setup Instructions Import the Workflow Import the provided JSON file into your n8n instance Configure Credentials Add OpenAI, Airtable, Google Sheets, PIAPI, and YouTube credentials in n8n’s credential manager Set Up Airtable Create or update the "Ideas" and "Production" tables with the specified fields Ensure proper permissions with the Airtable token Configure Google Sheets Create or update the "Ideas" and "Production" sheets with the specified columns Share the document with the Google Sheets credential email Schedule Triggers Set "Schedule Trigger" to trigger Test the Workflow Run manually to verify each node’s functionality Check Airtable, Google Sheets, and YouTube for updates Ensure PIAPI image generation completes (wait 4 minutes) Monitor and Adjust Monitor API rate limits (e.g, PIAPI, YouTube) Adjust wait times if image or video generation delays occur Verify connections for unlinked nodes Benefits Efficiency**: Automates the entire process from idea to posting Scalability**: Handles daily video production Quality**: Ensures cinematic scripts and visuals Tracking**: Provides detailed progress monitoring Notes Rate Limits**: Be aware of PIAPI (150,000 units per task) and YouTube API limits Timing**: Adjust wait nodes (e.g, "Wait for 4 Min") based on API response times Conclusion and Suggestions to Improve the Automation Conclusion This workflow streamlines YouTube video production, making it ideal for busy content creators, video producers, and marketing teams. Customize it by adding more platforms, adjusting wait delays for image/video generation, or enhancing notifications for status updates. Share your feedback in the n8n community to help others benefit from this automation. Suggestions to Improve Customization**: Adjust prompts, timings, and API parameters based on your needs Expand "Text-to-Music**" with multiple music styles or integrate a royalty-free music API for variety. Improve Video Rendering**: Optimize "Build Shotstack Timeline" and "ShotStack Render Video" with predefined templates to reduce rendering time. Add Analytics Tracking**: Include a node to fetch YouTube Analytics post-upload for performance monitoring. Error Handling**: Add error-catching nodes (e.g., "If" nodes) to retry failed image or video generations. Notification System**: Incorporate email or Slack notifications for key milestones (e.g., script completion, video upload).

This workflow demonstrates how to create viral AI-generated selfie videos featuring famous characters using a fully automated and platform-independent approach. The process is designed to replicate the kind of celebrity selfie videos that are currently going viral on social media and YouTube, where a realistic selfie-style video appears to show the creator together with a well-known public figure. Instead of relying on a proprietary or closed platform, the workflow explains how to build the entire pipeline using direct access to Google Veo 3.1 APIs, giving full control over generation, orchestration, and distribution. Key Advantages ✅ Fully automated video pipeline From prompt to final published video, the entire process runs without manual intervention. ✅ Spreadsheet-driven control Non-technical users can manage video production simply by editing Google Sheets: Add new prompts Adjust duration Control merge logic ✅ Scalable and modular Supports batch processing of many videos Easy to extend with new AI models, platforms, or output formats ✅ Reliable async handling Built-in wait and status-check logic ensures robustness Prevents failures caused by long-running AI jobs ✅ Centralized asset management Automatically stores video URLs and statuses Keeps production data organized and auditable ✅ Multi-platform ready One generated video can be reused for: YouTube TikTok Instagram Other social channels ✅ Cost and time efficiency Eliminates repetitive manual video editing Reduces production time from hours to minutes Ideal Use Cases AI-generated storytelling videos Social media content automation Marketing video campaigns Short-form video experiments at scale Faceless or semi-automated content channels How it Works This workflow automates the generation of short video clips using AI, merges them into a final video, and optionally uploads the result to multiple platforms. Trigger & Data Fetching The workflow starts with a manual trigger. It reads a Google Sheet containing prompts, image URLs (first and last frames), and duration settings for each video clip to be generated. Video Clip Generation For each row in the sheet, the workflow calls the fal.ai VEO 3.1 API to generate a video clip based on the provided prompt, start image, end image, and duration. The clip is created asynchronously, so the workflow polls the API for status until completion. Status Polling & URL Retrieval Once a clip is marked as COMPLETED, its video URL is fetched and written back to the Google Sheet in the corresponding row. Video Merging After all clips are generated, the workflow collects the video URLs from rows marked for merging and sends them to the fal.ai FFmpeg API to be combined into a single video. Final Video Processing The merged video is polled until ready, then its final URL is retrieved. The video file is downloaded via HTTP request. Upload & Distribution The final video can be uploaded to: Google Drive YouTube (via upload-post.com API) Postiz (for multi-platform social media posting) Each upload step is currently disabled and requires configuration (usernames, titles, platform settings). WARNING It may happen that the workflow stops at the video generation node with the following message: > Your request is invalid or could not be processed by the service [item 0] > The content could not be processed because it contained material flagged by a content checker. This occurs because images are checked both before and after the video generation process. If this happens, you can either use less restrictive video models while keeping the same workflow structure, or change the source images in the Google Sheets file. Set Up Steps Google Sheets Setup Prepare a Google Sheet with columns: START, LAST, PROMPT, DURATION, VIDEO URL, MERGE Connect n8n to Google Sheets using OAuth2 credentials. Fal.ai API Configuration Obtain an API key from fal.ai. Set up HTTP Header Auth credentials in n8n with the key. Upload Services Configuration Google Drive: Configure OAuth2 credentials and specify the target folder ID. YouTube/upload-post.com: Enter your username and title in the respective node. Postiz: Set up Postiz API credentials and configure platform channels. Enable Required Nodes Enable the upload nodes (Upload Video, Upload to Youtube, Upload to Postiz, Upload to Social) once credentials are configured. Adjust Polling Intervals Modify wait times (Wait 30 sec., Wait 60 sec.) as needed based on video processing times. Test Execution Start the workflow manually via the trigger node. Monitor execution in n8n’s editor and check the Google Sheet for updated video URLs. This workflow is designed for batch video creation and merging, ideal for content pipelines involving AI-generated media. 👉 Subscribe to my new YouTube channel. Here I’ll share videos and Shorts with practical tutorials and FREE templates for n8n. Need help customizing? Contact me for consulting and support or add me on Linkedin.

This workflow implements a complete Voice AI Chatbot system for Wordress that integrates speech recognition, guardrails for safety, retrieval-augmented generation (RAG), Qdrant vector search, and audio responses. It is designed to be connected to a WordPress Voicebot AI plugin through a webhook endpoint. Key Advantages ✅ Complete Voice AI Pipeline** The workflow handles: audio input STT intelligent processing TTS output All within a single automated process. ✅ Safe and Policy-Compliant Thanks to the Guardrails module, the system automatically: detects harmful or disallowed requests blocks them responds safely This protects both the user and the business. ✅ Contextual and Memory-Based Conversations The Window Buffer Memory tied to unique session IDs enables: continuous conversation flow natural dialogue better understanding of context ✅ Company-Specific Knowledge via RAG By integrating Qdrant as a vector store, the system can: retrieve business documentation give accurate and up-to-date answers support personalized content This makes the chatbot far more powerful than a standard LLM. ✅ Modular and Extensible Architecture Because everything is modular inside n8n, you can: swap OpenAI with other models add new tools or knowledge sources change prompts or capabilities without redesigning the entire workflow. ✅ **Easy WordPress Integration The workflow connects directly to a WordPress Voicebot plugin, meaning: no custom backend development simple deployment fast integration for websites ✅ Automatic Indexing of Documents The second workflow section: fetches Google Drive files converts them into embeddings indexes them into Qdrant This lets you maintain your knowledge base with almost no manual work. How It Works This workflow creates a Wordpress voice-enabled AI chatbot that processes audio inputs and provides contextual responses using RAG (Retrieval-Augmented Generation) from a Qdrant vector database. The system operates as follows: Audio Processing Pipeline: Receives audio input via webhook and converts speech to text using OpenAI's STT (Speech-to-Text) Applies guardrails to detect inappropriate content or jailbreak attempts using a separate GPT-4.1-mini model Routes safe queries to the AI agent and blocks unsafe content with a default response AI Agent with Contextual Memory: Uses OpenAI Chat Model with window buffer memory to maintain conversation context Equips the agent with two tools: Calculator for computations and RAG tool for business knowledge retrieval The RAG system queries Qdrant vector store containing company documents using OpenAI embeddings Response Generation: Generates appropriate text responses based on query type and available knowledge Converts approved responses to audio using OpenAI's TTS (Text-to-Speech) with "onyx" voice Returns binary audio responses to the webhook caller Set Up Steps Vector Database Preparation: Create Qdrant collection via HTTP request with specified vector configuration Clear existing collection data before adding new documents Set up Google Drive integration to source documents from specific folders Document Processing Pipeline: Search and retrieve files from Google Drive folder "Test Negozio" Process documents through recursive text splitting (500 chunk size, 50 overlap) Generate embeddings using OpenAI and store in Qdrant vector store Implement batch processing with 5-second delays between operations System Configuration: Configure webhook endpoint for receiving audio inputs Set up multiple OpenAI accounts for different functions (STT, TTS, guardrails, main agent) Establish Qdrant API connections for vector storage and retrieval Implement session-based memory management using session IDs from webhook headers WordPress Integration: Install the provided Voicebot AI Agent WordPress plugin Configure the plugin with the webhook URL to connect to this n8n workflow The system is now ready to receive audio queries and respond with voice answers The workflow handles both real-time voice queries and background document processing, creating a comprehensive voice assistant solution with business-specific knowledge retrieval capabilities. Need help customizing? Contact me for consulting and support or add me on Linkedin.

💥 Automate YouTube thumbnail creation from video links (with templated.io) Who is this for? This workflow is designed for content creators, YouTubers, and automation enthusiasts who want to automatically generate stunning YouTube thumbnails and streamline their publishing workflow — all within n8n. If you regularly post videos and spend hours designing thumbnails manually, this automation is built for you. What problem is this workflow solving? Creating thumbnails is time-consuming — yet crucial for video performance. This workflow completely automates that process: No more manual design. No more downloading screenshots. No more repetitive uploads. In less than 2 minutes, you can refresh your entire YouTube thumbnail library and make your channel look brand new. What this workflow does Once activated, this workflow can: ✅ Receive YouTube video links via Telegram ✅ Extract metadata (title, description, channel info) via YouTube API ✅ Generate a custom thumbnail automatically using Templated.io ✅ Upload the new thumbnail to Google Drive ✅ Log data in Google Sheets ✅ Send email and Telegram notifications when ready ✅ Create and publish AI-generated social posts on LinkedIn, Facebook, and Twitter via Blotato Bonus: You can re-create dozens of YouTube covers in minutes — saving up to 5 hours per week and around $500/month in manual design effort. Setup 1️⃣ Get a YouTube Data API v3 key from Google Cloud Console 2️⃣ Create a Templated.io account and get your API key + template ID 3️⃣ Set up a Telegram bot using @BotFather 4️⃣ Create a Google Drive folder and copy the folder ID 5️⃣ Create a Google Sheet with columns: Date, Video ID, Video URL, Title, Thumbnail Link, Status 6️⃣ Get your Blotato API key from the dashboard 7️⃣ Connect your social media accounts to Blotato 8️⃣ Fill all credentials in the Workflow Configuration node 9️⃣ Test by sending a YouTube URL to your Telegram bot How to customize this workflow Replace the Templated.io template ID with your own custom thumbnail layout Modify the OpenAI node prompts to change text tone or style Add or remove social platforms in the Blotato section Adjust the wait time (default: 5 minutes) based on template complexity Localize or translate the generated captions as needed Expected Outcome With one Telegram message, you’ll receive: A professional custom thumbnail An instant email + Telegram notification A Google Drive link with your ready-to-use design And your social networks will be automatically updated — no manual uploads. Credits Thumbnail generation powered by Templated.io Social publishing powered by Blotato Automation orchestrated via n8n 👋 Need help or want to customize this? 📩 Contact: LinkedIn 📺 YouTube: @DRFIRASS 🚀 Workshops: Mes Ateliers n8n 🎥 Watch This Tutorial 📄 Documentation: Notion Guide Need help customizing? Contact me for consulting and support : Linkedin / Youtube / 🚀 Mes Ateliers n8n

LinkedIn URL → Scrape → Match → Screen → Decide, all automated This workflow automatically processes candidate LinkedIn profiles shared via Telegram, intelligently matches them to job descriptions, performs AI-powered screening analysis, and sends actionable summaries to your team in Telegram. Good to know Handles LinkedIn profile scraping via Apify API (extracts full profile data including experience, education, skills) Built-in spam prevention: limits users to 3 LinkedIn profile submissions Two-stage JD matching: prioritizes role mentioned in candidate's Telegram message, falls back to LinkedIn profile analysis if needed Uses Google Gemini API for AI screening (generous free tier and rate limits, typically enough to avoid paying for API requests - check latest pricing at Google AI Pricing and rate limits documentation) Automatic polling mechanism checks Apify extraction status up to 10 times (15-second intervals) Complete audit trail logged in Google Sheets with unique submission IDs Who's it for Hiring teams and recruiters who want to streamline first-round screening for candidates who share LinkedIn profiles directly. Perfect for companies accepting applications via messaging platforms (Telegram, WhatsApp, etc.), especially useful fortech-savvy audiences and remote/global hiring. How it works Telegram bot receives message containing LinkedIn profile URL from candidate Validates URL format and checks spam prevention (max 3 submissions per Telegram username) Sends confirmation message to candidate and notifies internal talent team via Telegram group Extracts clean LinkedIn URL and initiates Apify scraping job Polls Apify API up to 10 times (15-second intervals) until profile extraction completes AI agent matches candidate to best-fit job description by analyzing Telegram message context first (if candidate mentioned a role), or LinkedIn profile content as fallback (selects up to 3 potential JD matches) If multiple JDs matched, second AI agent selects the single best fit based on detailed profile analysis AI recruiter agent analyzes LinkedIn profile against selected JD and generates structured screening report (strengths, weaknesses, risk/reward factors, overall fit score 0-10 with justification) Logs complete analysis to Google Sheets tracker with unique submission ID Sends formatted summary to Telegram group with candidate details, matched JD, and overall fit score Requirements Telegram Bot Token (Create bot via @BotFather) Apify account with API token (Sign up for free tier) Google Drive account (OAuth2) Google Sheets account (OAuth2) Google Gemini API key (Get free key here) Google Drive folder for Job Descriptions (as PDFs or Google Docs) Telegram group for internal talent team notifications How to set up Create Telegram bot and internal Telegram chat group with new bot: Message @BotFather on Telegram Send /newbot and follow instructions to create your bot Save the API token provided Create Telegram group chat and invite your new bot + invite the @GetIDs bot Note down the group chat ID (How to get group chat ID) Setup Apify: Sign up at Apify Get your API token from Settings Note: Free tier includes sufficient scraping credits for testing and production ($0.01 per successful LinkedIn profile enriched, a free monthly limit of $5.00) - LinkedIn profile scraper "actor" details Create Google Sheet: Create new sheet named "LinkedIn Profile AI Candidate Screening" Add columns: Submission ID, Date, LinkedIn Profile URL, First Name, Last Name, Email (if known), Telegram Username, Strengths, Weaknesses, Risk Factor, Reward Factor, JD Match, Overall Fit, Justification Copy the spreadsheet ID from URL Setup Google Drive folder: Create folder named "Job Descriptions" Upload your JD files (PDFs or Google Docs) with clear, descriptive filenames Copy the folder ID from URL Configure workflow nodes: In "Receive Telegram Msg to Recruiter Bot" node: Add Telegram API credentials In "Extract LinkedIn Profile Information" node: Replace YOUR_APIFY_API_TOKEN with your Apify token In "Check LinkedIn Profile Extraction Status" node: Replace YOUR_APIFY_API_TOKEN with your Apify token In "Get Fully Extracted LinkedIn Profile Data" node: Replace YOUR_APIFY_API_TOKEN with your Apify token In "Access JD Files" node: Update folder ID to your "Job Descriptions" folder In "Get All Rows Matching Telegram Username" node: Select your Google Sheet In "Add Candidate Analysis in GSheet" node: Select your Google Sheet and verify column mappings In "Send Msg to Internal Talent Group" node: Update chat ID to your Telegram group chat ID In "Send Review Completed Msg to Talent Group" node: Update chat ID and Google Sheet URL Add your company description: In "JD Matching Agent" system message: Replace company description with your details In "Detailed JD Matching Agent" system message: Replace company description with your details In "Recruiter Scoring Agent" system message: Update company description Test the workflow: Send a LinkedIn profile URL to your bot from Telegram Monitor execution to ensure all nodes run successfully Check Google Sheets for logged results Activate workflow Customizing this workflow Change spam limits: Edit "Spam Check: Sent <4 LinkedIn Profiles?" node to adjust maximum submissions (currently 3) Adjust polling attempts: Edit "Checked 10x for LinkedIn Profile Data?" node to change maximum polling attempts (currently 10) or modify wait time in "Wait for LinkedIn Profile" node (currently 15 seconds) Change JD matching logic: Edit "JD Matching Agent" node prompt to adjust how LinkedIn profiles are matched to roles (e.g., weight current role vs. overall experience) Modify screening criteria: Edit "Recruiter Scoring Agent" node system message to focus on specific qualities (culture fit, leadership potential, technical depth, industry experience, etc.) Add more messaging platforms: Add nodes to support WhatsApp, Discord, or other messaging platforms using similar URL-based triggers Customize Telegram messages: Edit notification nodes to change formatting, add emojis, or include additional candidate data Auto-proceed logic: Add IF node after screening to auto-proceed candidates with fit score above threshold (e.g., 8+/10) and trigger different notification paths Add candidate responses: Connect nodes to automatically message candidates back via Telegram (confirmation, rejection, interview invite) Add interview scheduling: For approved candidates, send Telegram message with Cal.com or Calendly link so they can book their interview Enrich with additional data: Add nodes to cross-reference candidate data with other sources (GitHub, Twitter/X, company websites) Multi-language support: Add translation nodes to support candidates submitting profiles in different languages Add human approval step: Create buttons in Telegram group messages for instant Approve/Reject decisions that update Google Sheets Pro tip: Add your Telegram bot to your company's careers page with instructions like: "Want fast-track screening? Share your LinkedIn profile with our AI recruiter: @YourBotName" Troubleshooting Telegram bot not responding: Ensure bot token is correct in "Receive Telegram Msg to Recruiter Bot" node, and users have sent /start to your bot at least once "LinkedIn profile URL invalid" error: Check that candidates are sending full URLs in format https://www.linkedin.com/in/username (not shortened links or text without URL) Apify extraction failing: Verify Apify API token is correctly set in all three HTTP Request nodes ("Extract LinkedIn Profile Information", "Check LinkedIn Profile Extraction Status", "Get Fully Extracted LinkedIn Profile Data") LinkedIn extraction timeout: Increase polling attempts in "Checked 10x for LinkedIn Profile Data?" node (currently 10) or increase wait time in "Wait for LinkedIn Profile" node (currently 15 seconds) Spam check blocking valid users: Check "Get All Rows Matching Telegram Username" node is pointing to correct Google Sheet, and adjust limit in "Spam Check: Sent <4 LinkedIn Profiles?" node if needed JD matching returns no results: Check "Access JD Files" node folder ID points to your Job Descriptions folder, and JD files are named clearly (e.g., "Marketing Director JD.pdf") JD matching is not relevant for my company: Update the "Company Description" in the System Messages in all three AI agent nodes ("JD Matching Agent", "Detailed JD Matching Agent", "Recruiter Scoring Agent") "Can't find matching JD": Ensure candidate's Telegram message mentions role name OR their LinkedIn profile clearly indicates relevant experience for available JDs Google Sheets errors: Verify sheet name is "LinkedIn Profile AI Candidate Screening" and column headers exactly match workflow expectations (Submission ID, Date, LinkedIn Profile URL, First Name, Last Name, etc.) Telegram group notifications not appearing: Verify chat ID is correct in "Send Msg to Internal Talent Group" and "Send Review Completed Msg to Talent Group" nodes (use negative number for group chats, e.g., -4954246611) Missing candidate data in Google Sheets: LinkedIn profile may be incomplete - verify Apify successfully extracted data by checking "Get Fully Extracted LinkedIn Profile Data" node output Loop counter not working: Check "Restore Loop Counter" code node references correct node names ("Checked 10x for LinkedIn Profile Data?" and "Initialize Loop Counter to Poll for Completion") 401/403 API errors: Re-authorize all OAuth2 credentials (Google Drive, Google Sheets) and verify Apify and Telegram API tokens are valid AI analysis quality issues: Edit system prompts in "JD Matching Agent", "Detailed JD Matching Agent", and "Recruiter Scoring Agent" nodes to refine screening criteria and provide more context about your hiring needs Gemini API rate limit errors: Check your usage at Google AI Studio and consider upgrading to paid tier if exceeding free tier limits (see rate limits documentation) Sample Outputs Google Sheets - LinkedIn AI Candidate Screening - sample Telegram messages between AI recruiter bot and job applicant Telegram messages from AI recruiter bot in internal group chat