Google Gemini Chat Model and HTTP Request integration

Youtube Video: https://youtu.be/dEtV7OYuMFQ?si=fOAlZWz4aDuFFovH Workflow Pre-requisites Step 1: Supabase Setup First, replace the keys in the "Save the embedding in DB" & "Search Embeddings" nodes with your new Supabase keys. After that, run the following code snippets in your Supabase SQL editor: Create the table to store chunks and embeddings: CREATE TABLE public."RAG" ( id bigserial PRIMARY KEY, chunk text NULL, embeddings vector(1024) NULL ) TABLESPACE pg_default; Create a function to match embeddings: DROP FUNCTION IF EXISTS public.matchembeddings1(integer, vector); CREATE OR REPLACE FUNCTION public.matchembeddings1( match_count integer, query_embedding vector ) RETURNS TABLE ( chunk text, similarity float ) LANGUAGE plpgsql AS $$ BEGIN RETURN QUERY SELECT R.chunk, 1 - (R.embeddings <=> query_embedding) AS similarity FROM public."RAG" AS R ORDER BY R.embeddings <=> query_embedding LIMIT match_count; END; $$; Step 2: Create Jotform with these fields Your full name email address Upload PDF Document [field where you upload the knowledgebase in PDF] Step 3: Get Together AI API Key Get a Together AI API key and paste it into the "Embedding Uploaded document" node and the "Embed User Message" node. Here is a detailed, node-by-node explanation of the n8n workflow, which is divided into two main parts. Part 1: Ingesting Knowledge from a PDF This first sequence of nodes runs when you submit a PDF through a Jotform. Its purpose is to read the document, process its content, and save it in a specialized database for the AI to use later. JotForm Trigger Type: Trigger What it does: This node starts the entire workflow. It's configured to listen for new submissions on a specific Jotform. When someone uploads a file and submits the form, this node activates and passes the submission data to the next step. Grab New knowledgebase Type: HTTP Request What it does: The initial trigger from Jotform only contains basic information. This node makes a follow-up call to the Jotform API using the submissionID to get the complete details of that submission, including the specific link to the uploaded file. Grab the uploaded knowledgebase file link Type: HTTP Request What it does: Using the file link obtained from the previous node, this step downloads the actual PDF file. It's set to receive the response as a file, not as text. Extract Text from PDF File Type: Extract From File What it does: This utility node takes the binary PDF file downloaded in the previous step and extracts all the readable text content from it. The output is a single block of plain text. Splitting into Chunks Type: Code What it does: This node runs a small JavaScript snippet. It takes the large block of text from the PDF and chops it into smaller, more manageable pieces, or "chunks," each of a predefined length. This is critical because AI models work more effectively with smaller, focused pieces of text. Embedding Uploaded document Type: HTTP Request What it does: This is a key AI step. It sends each individual text chunk to an embeddings API. A specified AI model converts the semantic meaning of the chunk into a numerical list called an embedding or vector. This vector is like a mathematical fingerprint of the text's meaning. Save the embedding in DB Type: Supabase What it does: This node connects to your Supabase database. For every chunk, it creates a new row in a specified table and stores two important pieces of information: the original text chunk and its corresponding numerical embedding (its "fingerprint") from the previous step. Part 2: Answering Questions via Chat This second sequence starts when a user sends a message. It uses the knowledge stored in the database to find relevant information and generate an intelligent answer. When chat message received Type: Chat Trigger What it does: This node starts the second part of the workflow. It listens for any incoming message from a user in a connected chat application. Embend User Message Type: HTTP Request What it does: This node takes the user's question and sends it to the exact same embeddings API and model used in Part 1. This converts the question's meaning into the same kind of numerical vector or "fingerprint." Search Embeddings Type: HTTP Request What it does: This is the "retrieval" step. It calls a custom database function in Supabase. It sends the question's embedding to this function and asks it to search the knowledge base table to find a specified number of top text chunks whose embeddings are mathematically most similar to the question's embedding. Aggregate Type: Aggregate What it does: The search from the previous step returns multiple separate items. This utility node simply bundles those items into a single, combined piece of data. This makes it easier to feed all the context into the final AI model at once. AI Agent & Google Gemini Chat Model Type: LangChain Agent & AI Model What it does: This is the "generation" step where the final answer is created. The AI Agent node is given a detailed set of instructions (a prompt). The prompt tells the Google Gemini Chat Model to act as a professional support agent. Crucially, it provides the AI with the user's original question and the aggregated text chunks from the Aggregate node as its only source of truth. It then instructs the AI to formulate an answer based only on that provided context, format it for a specific chat style, and to say "I don't know" if the answer cannot be found in the chunks. This prevents the AI from making things up.

Who Is This For? 🚘This workflow is designed for auto service / car repair businesses looking to streamline their social media marketing with Ai tools and automation via n8n. Whether you’re a small garage owner, a car repair shop, an automotive specialist or automechanic - this tool helps you maintain an active online presence without spending hours creating content. 💪🏼 Though this template is set up for Auto Service daily content uploads, but the underlying logic is universal. You can easily adapt it for any niche by editing prompts, adding nodes, and creating or uploading a variety of content to any platform. You can use any LLM and generative AI of your choice. Personally, I prefer the smooth and effective results from ChatGPT 4.1 combined with GPT Image 1. But you can generate videos instead of images for your posts as well 😉 What Problem Is This Workflow Solving? 🤦‍♂️ Many auto service businesses struggle with consistently posting engaging content due to time constraints or lack of marketing expertise. 💎This workflow solves that by automating the content creation and posting process, ensuring your social media channels stay fresh and active, ultimately attracting more customers. What This Workflow Does: Generates daily social media posts tailored specifically to the auto service niche using AI. Allows easy customization of post and image prompts. Integrates research links through the Tavily Internet Search tool for relevant content. Supports starting posts based on reference article links via Google Sheets. Automatically publishes posts to your connected social media platforms. Enables scheduled or trigger-based posting for maximum flexibility. How It Works? Easy, actually ☺️ AI creates daily social media content made just for Auto Service. You can simply edit prompts for both posts and images, set up news or articles research links via the Tavily Internet Search tool. You can also start the workflow with a reference article link through Google Sheets. 🎯 Consistently posting relevant and actual niche content helps attract new customers, all while leveraging AI and n8n tools to keep the process seamless and cost-effective. Set Up Steps: I kept it quick and simple for you ✨ If you’re happy with the current LLM and image model configurations, just connect your OpenAI API credentials to enable AI content generation. Link your social media accounts (Facebook, Telegram, X, etc.) for autoposting. Optionally connect Google Sheets if you want to trigger posts based on sheet updates with reference links. Customize prompts as needed to match your brand voice, style and marketing tasks. Choose between: 1) Scheduled automatic generation and posting at the same time as socials algorythms like it. 2) Google Sheets trigger with reference. 3) Manual start. How to Customize This Workflow to Your Needs? Switch AI models and edit prompts to better reflect your specific services or promotions. Add or modify research links in Tavily to keep your posts timely and relevant. Adjust posting schedules to match peak engagement times for your audience. Expand or reduce the number of social platforms integrated depending on your marketing strategy. Use Google Sheets to batch upload ideas or curate specific content topics. After adjusting a few settings, activate the workflow and let it run. 🤖 The system will then automatically publish your content across your selected social platforms — saving you time and effort. 📌 You’ll find more detailed tips and additional ai models for customizing ai generation process inside the workflow via sticky notes. 💬 Need help? For additional guidance, feel free to message me — here’s my profile in the n8n community for direct contact 👈 click!

Automate Multi-Platform Social Media Content Creation with AI Who is this for? Social Media Managers and Digital Marketers seeking to streamline content production across 7+ platforms (X/Twitter, Instagram, LinkedIn, Facebook, TikTok, Threads, YouTube Shorts) using AI-powered automation. What problem does this solve? Creating platform-optimized content at scale while maintaining brand consistency across multiple channels, reducing manual work by 80% through AI generation and automated publishing. What this workflow does AI Content Generation: Uses GPT-4/Gemini to create platform-specific posts Automatically generates hashtags, CTAs, and emoji placement Supports image/video suggestions and image creation using OpenAI or Pollinations.ai Uses SERP api to search for relavent content Approval Workflow: Sends formatted HTML emails for human review Implements double-approval system with Gmail integration Cross-Platform Publishing: One-click deployment to: Instagram/Facebook (via Graph API) X/Twitter (Official API) LinkedIn (Sales Navigator integration) Setup Credentials: OpenAI API key Google Gemini API Social media platform tokens (X, LinkedIn, Facebook) ImgBB for image hosting Gmail SERP API Telegram Configuration: Update all "your-unique-id" placeholders in API nodes Set email recipients in Gmail nodes Customize AI prompts Customization: Adjust character limits per platform Modify approval thresholds Add/remove social platforms as needed How to customize Content Style**: Edit prompt templates in the "Social Media Content Factory" agent node Approval Process**: Modify email templates Analytics**: Connect to Google Sheets for performance tracking Image Generation**: Switch between Pollinations.ai/DALL-E/Midjourney

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

🛒 Lead Workflow: Yelp & Trustpilot Scraping + OpenAI Analysis via BrightData > Description: Automated lead generation workflow that scrapes business data from Yelp and Trustpilot based on location and category, analyzes credibility, and sends personalized outreach emails using AI. > ⚠️ Important: This template requires a self-hosted n8n instance to run. 📋 Overview This workflow provides an automated lead generation solution that identifies high-quality prospects from Yelp and Trustpilot, analyzes their credibility through reviews, and sends personalized outreach emails. Perfect for digital marketing agencies, sales teams, and business development professionals. ✨ Key Features 🎯 Smart Location Analysis** AI breaks down cities into sub-locations for comprehensive coverage 🛍 Yelp Integration** Scrapes business details using BrightData's Yelp dataset ⭐ Trustpilot Verification** Validates business credibility through review analysis 📊 Data Storage** Automatically saves results to Google Sheets 🤖 AI-Powered Outreach** Generates personalized emails using Claude AI 📧 Automated Sending** Sends emails directly through Gmail integration 🔄 How It Works User Input: Submit location, country, and business category through a form AI Location Analysis: Gemini AI identifies sub-locations within the specified area Yelp Scraping: BrightData extracts business information from multiple locations Data Processing: Cleans and stores business details in Google Sheets Trustpilot Verification: Scrapes reviews and company details for credibility check Email Generation: Claude AI creates personalized outreach messages Automated Outreach: Sends emails to qualified prospects via Gmail 📊 Data Output | Field | Description | Example | |---------------|----------------------------------|----------------------------------| | Company Name | Business name from Yelp/Trustpilot | Best Local Restaurant | | Website | Company website URL | https://example-restaurant.com | | Phone Number | Business contact number | (555) 123-4567 | | Email | Business email address | [email protected] | | Address | Physical business location | 123 Main St, City, State | | Rating | Overall business rating | 4.5/5 | | Categories | Business categories/tags | Restaurant, Italian, Fine Dining | 🚀 Setup Instructions ⏱️ Estimated Setup Time: 10–15 minutes Prerequisites n8n instance (self-hosted or cloud) Google account with Sheets access BrightData account with Yelp and Trustpilot datasets Google Gemini API access Anthropic API key for Claude Gmail account for sending emails Step 1: Import the Workflow Copy the JSON workflow code In n8n: Workflows → + Add workflow → Import from JSON Paste JSON and click Import Step 2: Configure Google Sheets Integration Create two Google Sheets: Yelp data: Name, Categories, Website, Address, Phone, URL, Rating Trustpilot data: Company Name, Email, Phone Number, Address, Rating, Company About Copy Sheet IDs from URLs In n8n: Credentials → + Add credential → Google Sheets OAuth2 API Complete OAuth setup and test connection Update all Google Sheets nodes with your Sheet IDs Step 3: Configure BrightData Set up BrightData credentials in n8n Replace API token with: BRIGHT_DATA_API_KEY Verify dataset access: Yelp dataset: gd_lgugwl0519h1p14rwk Trustpilot dataset: gd_lm5zmhwd2sni130p Test connections Step 4: Configure AI Models Google Gemini (Location Analysis)** Add Google Gemini API credentials Configure model: models/gemini-1.5-flash Claude AI (Email Generation)** Add Anthropic API credentials Configure model: claude-sonnet-4-20250514 Step 5: Configure Gmail Integration Set up Gmail OAuth2 credentials in n8n Update "Send Outreach Email" node Test email sending Step 6: Test & Activate Activate the workflow Test with sample data: Country: United States Location: Dallas Category: Restaurants Verify data appears in Google Sheets Check that emails are generated and sent 📖 Usage Guide Starting a Lead Generation Campaign Access the form trigger URL Enter your target criteria: Country: Target country Location: City or region Category: Business type (e.g., restaurants) Submit the form to start the process Monitoring Results Yelp Data Sheet:** View scraped business information Trustpilot Sheet:** Review credibility data Gmail Sent Items:** Track outreach emails sent 🔧 Customization Options Modifying Email Templates Edit the "AI Generate Email Content" node to customize: Email tone and style Services mentioned Call-to-action messages Branding elements Adjusting Data Filters Modify rating thresholds Set minimum review counts Add geographic restrictions Filter by business size Scaling the Workflow Increase batch sizes Add delays between requests Use parallel processing Add error handling 🚨 Troubleshooting Common Issues & Solutions BrightData Connection Failed Cause: Invalid API credentials or dataset access Solution: Verify credentials and dataset permissions No Data Extracted Cause: Invalid location or changed page structure Solution: Verify location names and test other categories Gmail Authentication Issues Cause: Expired OAuth tokens Solution: Re-authenticate and check permissions AI Model Errors Cause: API quota exceeded or invalid keys Solution: Check usage limits and API key Performance Optimization Rate Limiting:** Add delays Error Handling:** Retry failed requests Data Validation:** Check for malformed data Memory Management:** Process in smaller batches 📈 Use Cases & Examples Digital Marketing Agency Lead Generation Goal:** Find businesses needing marketing Target:** Restaurants, retail stores Approach:** Focus on good-rated but low-online-presence businesses B2B Sales Prospecting Goal:** Find software solution clients Target:** Growing businesses Approach:** Focus on recent positive reviews Partnership Development Goal:** Find complementary businesses Target:** Established businesses Approach:** Focus on reputation and satisfaction scores ⚡ Performance & Limits Expected Performance Processing Time:** 5–10 minutes/location Data Accuracy:** 90%+ Success Rate:** 85%+ Daily Capacity:** 100–500 leads Resource Usage API Calls:** ~10–20 per business Storage:** Minimal (Google Sheets) Execution Time:** 3–8 minutes/10 businesses Network Usage:** ~5–10MB/business 🤝 Support & Community Getting Help n8n Community Forum:** community.n8n.io Docs:** docs.n8n.io BrightData Support:** Via dashboard Contributing Share improvements Report issues and suggestions Create industry-specific variations Document best practices > 🔒 Privacy & Compliance: Ensure GDPR/CCPA compliance. Always respect robots.txt and terms of service of scraped sites. 🎯 Ready to Generate Leads! This workflow provides a complete solution for automated lead generation and outreach. Customize it to fit your needs and start building your pipeline today! For any questions or support, please contact: 📧 [email protected] or fill out this form: Contact Us

AI powered content creation and WordPress publishing workflow Summary This workflow automates the entire process of blog content creation, from idea generation and article writing using Google Gemini, to sourcing images from Pexels and publishing directly to your WordPress site. It uses Google Sheets as a central hub for managing content ideas and tracking their status, all orchestrated through interactive n8n forms. Key features AI driven content:** Leverages Google Gemini for generating: Full blog articles based on prompts. Relevant keywords for image searching. New blog topic ideas. Automated image sourcing:** Searches Pexels for suitable images based on AI generated keywords and downloads them. WordPress integration:** Creates new posts with AI generated title and content. Uploads sourced images to the WordPress media library. Sets the uploaded image as the featured image for the post. Google Sheets management:** Fetches content ideas (prompts) marked as "not generated". Updates the sheet after a post is generated with the post ID, title, and generation date. Adds newly AI generated blog topic ideas to the sheet. Interactive forms:** Main trigger form to choose between generating content or adding new ideas. Forms to input topics for idea generation. Confirmation forms at the end of processes. Structured output parsing:** Ensures AI responses for topic generation are correctly formatted as JSON. How it works The workflow is initiated via an n8n Form Trigger: Select Action, allowing the user to choose one of two main paths: Generate content path: Fetch idea: The Fetch unprocessed ideas (Google Sheets) node retrieves a row from your sheet where the "Generated" column is "no". Set prompt: The Set prompt node prepares the topic from the sheet for the AI. Generate article: The Generate article AI (Langchain Agent with Google Gemini) node takes the prompt and writes a full article. Generate image keyword: The Generate image keyword AI (Langchain Agent with Google Gemini) node creates a concise search term based on the article topic. Search image: The Search Pexels image (HTTP Request) node uses the generated keyword to find a relevant image via the Pexels API. Create WordPress post: The Create WordPress post node publishes the AI generated article and initial image metadata to your WordPress site. Download and upload image: The Download Pexels image (HTTP Request) node fetches the actual image file, and the Upload image (HTTP Request) node uploads it to your WordPress media library. Set featured image: The Set featured image (HTTP Request) node links the uploaded image as the featured image for the newly created post. Update sheet: The Update Google Sheet node marks the idea as "yes" in your Google Sheet and adds the WordPress post ID and title. Confirmation: A Form: End post generation node displays a completion message. Add ideas path: Input topic: The Form: Enter topic for ideas node prompts the user to enter a general subject. Generate topics: The Generate blog topics AI (Langchain Agent with Google Gemini and Structured Output Parser) node generates five SEO friendly blog topic ideas based on the user's input, formatted as JSON. Process topics: The Split topics node separates the generated list of topics into individual items. Add to sheet: For each topic, the Add ideas to sheet (Google Sheets) node appends it as a new row, marked with "Generated: no". Loop or end: The Form: Add more topics? node asks the user if they want to generate more ideas or end the process. If "NEXT", it loops back to the Form: Enter topic for ideas. If "END", a Form: End idea generation node displays a completion message with the list of added topics. Nodes used Form Trigger If Google Sheets Set Langchain Agent (with Google Gemini Chat Model) Structured Output Parser (Langchain) HTTP Request (for Pexels API and WordPress Media/Post updates) WordPress Split Out Form (for user interaction and completion messages) Sticky Note (for instructions within the workflow) Setup instructions Credentials: Google Sheets: Configure your Google Sheets OAuth2 credentials in the Fetch unprocessed ideas, Update Google Sheet, and Add ideas to sheet nodes. WordPress: Configure your WordPress API credentials in the Create WordPress post, Upload image, and Set featured image nodes. Google Gemini: Configure your Google Gemini (PaLM) API key in the Gemini model for article, Gemini model for image keyword, and Gemini model for topics nodes. API keys and URLs: Pexels: In the Search Pexels image node, replace <YOUR_PEXELS_API_KEY> in the Authorization header with your actual Pexels API key. WordPress URL: In the Upload image and Set featured image nodes, replace <YOUR_WORDPRESS_URL> in the URL field with your WordPress site's domain (e.g., yourblog.com). Google Sheet configuration: Ensure your Google Sheet (specified by Document ID in Google Sheets nodes) has a sheet named Sheet1 (or update the Sheet Name parameter). The sheet should have at least the following columns: Prompt (for the blog idea/topic), Generated (to track status, e.g., "no" or "yes"), row_number (automatically populated by n8n when reading), Date, Title (for the final WordPress post title), Post ID. Activate the workflow. The Form Trigger: Select Action will provide a webhook URL to initiate the process. Customization ideas Modify the AI prompts in the Langchain Agent nodes for different tones, styles, or content structures. Change the Google Gemini models used for different cost/performance balances. Integrate other image sources instead of or in addition to Pexels. Add steps for social media sharing after a post is published. Extend the Google Sheet to track more metrics like word count or target keywords. Implement more sophisticated error handling. Use cases Automating blog content generation for personal or company blogs. Streamlining content marketing efforts. Quickly populating new websites with initial content. Assisting SEO agencies in creating draft content for clients. Helping solo bloggers maintain a consistent publishing schedule.

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.

AI-Powered Product Research & SEO Content Automation Skip the guesswork and manual effort — this n8n flow automates the entire process of researching your product's online competition and generating high-quality SEO content. Whether you're launching a new product or optimizing existing listings, this workflow leverages real-time web data and AI-driven copywriting to deliver: 📈 Search-optimized metadata (Title, Description, Keywords) 🛍️ Engaging product descriptions tailored for marketing 📊 Auto-organized output ready for use in your content or e-commerce platform All of this happens with just one product title input! 🧠 How It Works • User submits a product title via a form. • The workflow uses Google Custom Search to gather real-time competitor content based on that title. • Titles, snippets, and keywords are extracted from the search results. • This information is sent to a language model (Google Gemini via LangChain) to generate: SEO-optimized metadata (Title, Description, Keywords) A compelling product description tailored for marketing • The AI-generated content is then parsed and organized into two categories: SEO data and product content. • The structured output is saved automatically into a connected Google Sheet for easy access or further automation. 🛠️ What Problems Does This Solve? Manual competitor research and writing SEO content from scratch can be: Time-consuming** Inconsistent in quality** Not optimized for search engines** Hard to scale for multiple products** This workflow automates the entire research + writing + structuring process. ✅ Key Benefits Instant Content Creation**: Generate polished SEO content in seconds. Competitor-Aware**: Pulls in real-time data from the web for relevant, market-aligned content. Scalable**: Easily repeat the process for multiple product titles with minimal effort. Data Centralization**: Stores everything in Google Sheets—great for collaboration or syncing with other tools. Customizable**: Easily extend or modify the workflow to include translations, publishing, or social media automation. ⚙️ Set-Up Steps • Connect Google Custom Search API with a valid API key and search engine ID (CX). • Connect and configure Google Gemini or LangChain with access credentials. • Provide access to a Google Sheet with columns for storing SEO and product data. • Estimated setup time: ~15–25 minutes depending on API access and sheet setup. 🚀 Let’s Get You Started with Automating Your LinkedIn Posts! Create your free n8n account and set up the workflow in just a few minutes using the link below: 👉 Start Automating with n8n Save time, stay consistent, and grow your LinkedIn presence effortlessly!

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:

WhatsApp RAG Chatbot with Supabase, Gemini 2.5 Flash, and OpenAI Embeddings This n8n template demonstrates how to build a WhatsApp-based AI chatbot that answers user questions using document retrieval (RAG) powered by Supabase for storage, OpenAI embeddings for semantic search, and Gemini 2.5 Flash LLM for generating high-quality responses. Use cases are many: Turn your WhatsApp into a knowledge assistant for FAQs, customer support, or internal company documents — all without coding. Good to know The workflow uses OpenAI embeddings for both document embeddings and query embeddings, ensuring accurate semantic search. Gemini 2.5 Flash LLM** is used to generate user-friendly answers from the retrieved context. Messages are processed in real-time and sent back directly to WhatsApp. Workflow is modular — you can split document ingestion and query handling for large-scale setups. Supabase and WhatsApp API credentials must be configured before running. How it works Trigger: A new WhatsApp message triggers the workflow via webhook. Message Check: Determines if the message is a query or a document upload. Document Handling: Fetch file URL from WhatsApp. Convert binary to text. Generate embeddings with OpenAI and store them in Supabase. Query Handling: Generate query embeddings with OpenAI. Retrieve relevant context from Supabase. Pass context to Gemini 2.5 Flash LLM to compose a response. Response: Send the answer back to the user on WhatsApp. Optional: Add Gmail node to forward chat logs or daily summaries. How to use Configure WhatsApp Business API webhook for incoming messages. Add your Supabase and OpenAI credentials in n8n’s credentials manager. Upload documents via WhatsApp to populate the Supabase vector store. Ask queries — the bot retrieves context and answers using Gemini 2.5 Flash. Requirements WhatsApp Business API** (or Twilio WhatsApp Sandbox) Supabase account** (vector storage for embeddings) OpenAI API key** (for generating embeddings) Gemini API access** (for LLM responses) Customising this workflow Swap WhatsApp with Telegram, Slack, or email for different chat channels. Extend ingestion to other sources like Google Drive or Notion. Adjust the number of retrieved documents or prompt style in Gemini for tone control. Add a Gmail output node to send logs or alerts automatically.

Automated AI Content Creation & Instagram Publishing from Google Sheets This n8n workflow automates the creation and publishing of social media content directly to Instagram, using ideas stored in a Google Sheet. It leverages AI (Google Gemini and Replicate Flux) to generate concepts, image prompts, captions, and the final image, turning your content plan into reality with minimal manual intervention. Think of this as the execution engine for your content strategy. It assumes you have a separate process (whether manual entry, another workflow, or a different tool) for populating the Google Sheet with initial post ideas (including Topic, Audience, Voice, and Platform). This workflow takes those ideas and handles the rest, from AI generation to final publication. What does this workflow do? This workflow streamlines the content execution process by: Automatically fetching** unprocessed content ideas from a designated Google Sheet based on a schedule. Using Google Gemini to generate a platform-specific content concept (specifically for a 'Single Image' format). Generating two distinct AI image prompt options based on the concept using Gemini. Writing an engaging, platform-tailored caption (including hashtags) using Gemini, based on the first prompt option. Generating a visual image using the first prompt option via the Replicate API (using the Flux model). Publishing* the generated image and caption directly to a connected Instagram Business account*. Updating the status** in the Google Sheet to mark the idea as completed, preventing reprocessing. Who is this for? Social Media Managers & Agencies:** Automate the execution of your content calendar stored in Google Sheets. Marketing Teams:** Streamline content production from planned ideas and ensure consistent posting schedules. Content Creators & Solopreneurs:** Save significant time by automating the generation and publishing process based on your pre-defined ideas. Anyone** using Google Sheets to plan social media content and wanting to automate the creative generation and posting steps with AI. Benefits Full Automation:** From fetching planned ideas to Instagram publishing, automate the entire content execution pipeline. AI-Powered Generation:** Leverage Google Gemini for creative concepts, prompts, and captions, and Replicate for image generation based on your initial topic. Content Calendar Execution:** Directly turn your Google Sheet plan into published posts. Time Savings:** Drastically reduce the manual effort involved in creating visuals and text for each planned post. Consistency:** Maintain a regular posting schedule by automatically processing your queue of ideas. Platform-Specific Content:** AI prompts are designed to tailor concepts, prompts, and captions for the platform specified in your sheet (e.g., Instagram or LinkedIn). How it Works Scheduled Trigger: The workflow starts automatically based on the schedule you set (e.g., every hour, daily). Fetch Idea: Reads the next row from your Google Sheet where the 'Status' column indicates it's pending (e.g., '0'). It only fetches one idea per run. Prepare Inputs: Extracts Topic, Audience, Voice, and Platform from the sheet data. AI Concept Generation (Gemini): Creates a single content concept suitable for a 'Single Image' post on the target platform. AI Prompt Generation (Gemini): Develops two detailed, distinct image prompt options based on the concept. AI Caption Generation (Gemini): Writes a caption tailored to the platform, using the first image prompt and other context. Image Generation (Replicate): Sends the first prompt to the Replicate API (Flux model) to generate the image. Prepare for Instagram: Formats the generated image URL and caption. Publish to Instagram: Uses the Facebook Graph API in three steps: Creates a media container by uploading the image URL and caption. Waits for Instagram to process the container. Publishes the processed container to your feed. Update Sheet: Changes the 'Status' in the Google Sheet for the processed row (e.g., to '1') to mark it as complete. n8n Nodes Used Schedule Trigger Google Sheets (Read & Update operations) Set (Multiple instances for data preparation) Langchain Chain - LLM (Multiple instances for Gemini calls) Langchain Chat Model - Google Gemini (Multiple instances) Langchain Output Parser - Structured (Multiple instances) HTTP Request (for Replicate API call) Wait Facebook Graph API (Multiple instances for Instagram publishing steps) Prerequisites Active n8n instance (Cloud or Self-Hosted). Google Account** with access to Google Sheets. Google Sheets API Credentials (OAuth2):** Configured in n8n. A Google Sheet** structured with columns like Topic, Audience, Voice, Platform, Status (or similar). Ensure your 'pending' and 'completed' statuses are defined (e.g., '0' and '1'). Google Cloud Project** with the Vertex AI API enabled. Google Gemini API Credentials:** Configured in n8n (usually via Google Vertex AI credentials). Replicate Account** and API Token. Replicate API Credentials (Header Auth):** Configured in n8n. Facebook Developer Account**. Instagram Business Account** connected to a Facebook Page. Facebook App** with necessary permissions: instagram_basic, instagram_content_publish, pages_read_engagement, pages_show_list. Facebook Graph API Credentials (OAuth2):** Configured in n8n with the required permissions. Setup Import the workflow JSON into your n8n instance. Configure Schedule Trigger: Set the desired frequency (e.g., every 30 minutes, every 4 hours) for checking new ideas in the sheet. Configure Google Sheets Nodes: Select your Google Sheets OAuth2 credentials for both Google Sheets nodes. In 1. Get Next Post Idea..., enter your Spreadsheet ID and Sheet Name. Verify the Status filter matches your 'pending' value (e.g., 0). In 7. Update Post Status..., enter the same Spreadsheet ID and Sheet Name. Ensure the Matching Columns (e.g., Topic) and the Status value to update match your 'completed' value (e.g., 1). Configure Google Gemini Nodes: Select your configured Google Vertex AI / Gemini credentials in all Google Gemini Chat Model nodes. Configure Replicate Node (4. Generate Image...): Select your Replicate Header Auth credentials. The workflow uses black-forest-labs/flux-1.1-pro-ultra by default; you can change this if needed. Configure Facebook Graph API Nodes (6a, 6c): Select your Facebook Graph API OAuth2 credentials. Crucially, update the Instagram Account ID in the Node parameter of both Facebook Graph API nodes (6a and 6c). The template uses a placeholder (17841473009917118); replace this with your actual Instagram Business Account ID. Adjust Wait Node (6b): The default wait time might be sufficient, but if you encounter errors during publishing (especially with larger images/videos in the future), you might need to increase the wait duration. Activate the workflow. Populate your Google Sheet: Ensure you have rows with your content ideas and the correct 'pending' status (e.g., '0'). The workflow will pick them up on its next scheduled run. This workflow transforms your Google Sheet content plan into a fully automated AI-powered Instagram publishing engine. Start automating your social media presence today!

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!

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.

🚀 AI-Powered LinkedIn Post Automation 🧩 How It Works This workflow automatically generates LinkedIn posts based on a user-submitted topic, including both content creation and image generation, then publishes the post to LinkedIn. Ideal for marketers, content creators, or businesses looking to streamline their social media activity, without the need for manual post creation. High-Level Workflow: Trigger: The workflow is triggered when a user submits a form with a topic for the LinkedIn post. Data Mapping: The topic is mapped and prepared for the AI model. AI Content Generation: Calls the Google Gemini AI model to generate engaging post content and a visual image prompt. Image Creation: Sends the image prompt to the external API, gen-imager, to generate a professional image matching the topic. Post Creation: Publishes the text and image to LinkedIn, automatically updating the user's feed. ⚙️ Set Up Steps (Quick Overview) 🕐 Estimated Setup Time: ~10–20 minutes Connect Google Gemini: Set up your Google Gemini API credentials to interact with the AI model for content creation. Set Up External Image API: Configure the external image generation API (gen-imager API) for visual creation based on the post prompt. Connect LinkedIn: Set up OAuth2 credentials to authenticate your LinkedIn account and allow publishing posts. Form Submission Setup: Create a simple web form for users to submit the topic for LinkedIn posts. Activate the Workflow: Once everything is connected, activate the workflow. It will trigger automatically upon receiving form submissions. 💡 Important Notes: The flow uses Google Gemini (PaLM) for generating content based on the user's topic. Text to Image: The image generation process involves creating a professional, LinkedIn-appropriate image based on the post’s topic using the **gen-imager API. You can customize the visual elements of the posts and adjust the tone of the generated content based on preferences. 🛠 Detailed Node Breakdown: On Form Submission Trigger: Captures the user-submitted topic and initializes the workflow. Action: Start the process by gathering the topic information. Mapper (Field Mapping) Action: Maps the captured topic to a variable that is passed along for content generation. AI Agent (Content Generation) Action: Calls Google Gemini to generate professional LinkedIn post content and an image prompt based on the submitted topic. Key: Outputs content in a structured form — post text and image prompt. Google Gemini Chat Model Action: AI model that generates actionable insights, engaging copy, and an image prompt for LinkedIn post. Normalizer (Data Cleanup) Action: Cleans the output from the AI model to ensure the content and image prompt are correctly formatted for use in the next steps. Text to Image (Image Generation) Action: Sends the image prompt to the gen-imager API, which returns a custom image based on the post's topic. Decoder (Base64 Decoding) Action: Decodes the image from base64 format for easier uploading to LinkedIn. LinkedIn (Post Creation) Action: Publishes the generated text and image to LinkedIn, automatically creating a polished post for the user’s feed. ⏱ Execution Time Breakdown: Total Estimated Execution Time**: ~15–40 seconds per workflow run. On Form Submission: Instant (Trigger) Mapper (Field Mapping): ~1–2 seconds AI Content Generation: ~5–10 seconds (depending on server load) Text to Image: ~5–15 seconds (depends on external API) LinkedIn Post Creation: ~2–5 seconds 🚀 Ready to Get Started? Let’s get you started with automating your LinkedIn posts! Create your free n8n account and set up the workflow using this link. 📝 Notes & Customizations Form Fields**: Customize the form to gather more specific information for the LinkedIn posts (like audience targeting, post category, etc.). Image API Customization**: Adjust the image generation prompt to fit your brand’s style, or change the color palette as needed. Content Tone**: The tone can be adjusted by modifying the system message sent to Google Gemini for content generation.

This n8n workflow automates lead extraction from Google Maps, enriches data with AI, and stores results for cold outreach. It uses the Bright Data community node and Bright Data MCP for scraping and AI message generation. How it works Form Submission User provides Google Maps starting location, keyword and country. Bright Data Scraping Bright Data community node triggers a Maps scraping job, monitors progress, and downloads results. AI Message Generation Uses Bright Data MCP with LLMs to create a personalized cold call script and talking points for each lead. Database Storage Enriched leads and scripts are upserted to Supabase. How to use Set up all the credentials, create your Postgres table and submit the form. The rest happens automatically. Requirements LLM account (OpenAI, Gemini…) for API usage. Bright Data account for API and MCP usage. Supabase account (or other Postgres database) to store information.

🤖💬 Conversational AI Chatbot with Google Gemini for Text & Image | Telegram Overview 📋 Flexible and scalable chatbot template, designed mainly for Spanish conversations but capable of handling English and other languages. Integrates Google Gemini API for text and image generation, and Telegram for messaging. Supports multiple output types with potential for video, audio, and more. How It Works Modular Architecture & Extensibility ⚙️ Separate modules for data extraction, intent analysis, and adaptive response generation. Easily extendable with additional tools, databases, or APIs. Context & Memory Handling 🧠 Session-based volatile memory maintains conversation coherence. Allows updates or modifications to previous images based on new requests (e.g., add a hat to a dog 🐶). Intent Detection & Classification 🔍 Google Gemini accurately classifies user intent. Two-step validation ensures context-aware, precise replies. Content Generation & Output ✍️🖼️ Generates text and images based on intent and context. Designed for Telegram but adaptable to other platforms and media types (audio, video). Key Benefits ✅ Scalable, customizable, and production-ready architecture. Supports multiple content formats: text, images, audio, and video. Dynamic context and memory management for smooth, coherent conversations. Native integration with Google Gemini and Telegram ensures reliable and seamless operation. Suitable for diverse use cases and easy to extend with new tools or platforms. Use Cases 💼 Customer support virtual assistants. On-demand multimedia content creation. Marketing and user engagement bots. AI conversational prototypes and pilots. Requirements 👨‍💻 n8n instance (self-hosted or cloud) Google Gemini API credentials Telegram bot setup (optional but recommended) Active member of the Polytechnic Artificial Intelligence Club (CIAP) at ESPOL.

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

Notice Community nodes can only be installed on self-hosted instances of n8n. Description This workflow automates the process of scraping local business data from Google Maps and enriching it using AI to generate lead profiles. It's designed to help sales, marketing, and outreach teams collect high-quality B2B leads from Google Maps and enrich them with contextual insights without manual data entry. Overview This workflow scrapes business listings from Google Maps, extracts critical information like name, category, phone, address, and website using Bright Data, and passes the results to Google Gemini to generate enriched summaries and lead insights such as company description, potential services offered, and engagement score. The data is then structured and stored in spreadsheets for outreach. Tools Used n8n: The core automation engine to manage flow and trigger actions. Bright Data: Scrapes business information from Google Maps at scale with proxy rotation and CAPTCHA-solving. Google Gemini: Enriches the raw scraped data with smart business summaries, categorization, and lead scoring. Google Sheets : For storing and acting upon the enriched leads. How to Install Import the Workflow: Download the .json file and import it into your n8n instance. Set Up Bright Data: Insert your Bright Data credentials and configure the Google Maps scraping proxy endpoint. Configure Gemini API: Add your Google Gemini API key (or use via Make.com plugin). Customize the Inputs: Choose your target location, business category, and number of results per query. Choose Storage: Connect to your preferred storage like Google Sheets. Test and Deploy: Run a test scrape and enrichment before deploying for bulk runs. Use Cases Sales Teams: Auto-generate warm B2B lead lists with company summaries and relevance scores. Marketing Agencies: Identify local business prospects for SEO, web development, or ads services. Freelancers: Find high-potential clients in specific niches or cities. Business Consultants: Collect and categorize local businesses for competitive analysis or partnerships. Recruitment Firms: Identify and score potential company clients for talent acquisition. Connect with Me Email: [email protected] LinkedIn: https://www.linkedin.com/in/ranjan-dailata/ Get Bright Data: Bright Data (Supports free workflows with a small commission) #n8n #automation #leadscraping #googlemaps #brightdata #leadgen #b2bleads #salesautomation #nocode #leadprospecting #marketingautomation #googlemapsdata #geminiapi #googlegemini #aiworkflow #scrapingworkflow #businessleads #datadrivenoutreach #crm #workflowautomation #salesintelligence #b2bmarketing

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. 🤖 AI Image Generator Telegram Bot Transform simple text descriptions into stunning AI-generated images through a Telegram bot powered by Google's Gemini 2.0 Flash image. This workflow automatically enhances user prompts with professional prompt engineering techniques and delivers high-quality images directly to your Telegram chat. 🎯 What This Workflow Does This automation creates an intelligent Telegram bot that: Receives text messages** from users describing what image they want Enhances prompts** using AI-powered prompt engineering to add artistic details, lighting, composition, and style specifications Generates images** using Google's Gemini 2.0 Flash image generation model Delivers results** instantly back to the user's Telegram chat ⚡️ Key Features Smart Prompt Enhancement**: Automatically transforms basic requests like "a cat on a windowsill" into detailed, professional prompts with lighting, composition, and style details Professional Image Quality**: Leverages Google's latest Gemini 2.0 Flash model for high-quality image generation Instant Delivery**: Images are generated and sent back to users within seconds User-Friendly**: Simple text-to-image conversion through familiar Telegram interface Structured Output**: Uses JSON schema to ensure consistent prompt formatting 🛠️ How It Works Telegram Trigger: Listens for incoming messages from users AI Prompt Enhancement: Uses Gemini 2.5 Flash Lite to analyze and expand user requests into detailed prompts Structured Processing: Formats the enhanced prompt using JSON schema for consistency Image Generation: Sends the enhanced prompt to Gemini 2.0 Flash image generation API File Conversion: Converts the generated image data to a file format Delivery: Sends the generated image back to the user via Telegram 🎭 Use Cases Creative Content Creation**: Generate artwork, illustrations, and visual concepts Social Media Content**: Create unique images for posts and stories Concept Visualization**: Turn ideas into visual representations Educational Materials**: Generate images for presentations and learning materials Personal Projects**: Create custom artwork for personal use 📋 Prerequisites Before setting up this workflow, you'll need: Required Accounts & APIs: Telegram Bot Token**: Create a bot via @BotFather Google AI Studio Account**: Access to Gemini API services Required Credentials: Telegram Bot API credentials Google Gemini API key with access to: Gemini 2.5 Pro (for prompt enhancement) Gemini 2.0 Flash Preview (for image generation) 🚀 Setup Instructions Import the Workflow: Copy the workflow JSON into your n8n instance Configure Telegram Bot: Create a new bot using @BotFather Add your bot token to the Telegram credentials in n8n Set Up Google Gemini API: Create API key from Google AI Studio and add to n8n credentials Activate the Workflow: Enable the workflow to start receiving messages 💡 Customization Options Prompt Templates**: Modify the prompt enhancement instructions for different artistic styles Image Parameters**: Adjust generation settings for different image formats and qualities Response Formats**: Customize how images are delivered (with captions, multiple formats, etc.) 📊 Example Interaction User Input: "Generate a beautiful image of a dragon from game of thrones" Enhanced Prompt: "A majestic, formidable dragon, reminiscent of those from Game of Thrones, perched atop a jagged, snow-capped mountain peak. The dragon is depicted with immense, leathery wings unfurled, scales glinting with iridescent blues and deep charcoals under the harsh, cold light. Its eyes glow with an inner, fiery amber. The scene is captured with a dramatic, low-angle wide shot, emphasizing the dragon's sheer scale against a turbulent, stormy sky filled with dark, bruised clouds and streaks of lightning. The atmosphere is oppressive and foreboding, with biting wind and swirling snow creating a sense of raw power and danger. The color palette is dominated by icy blues, stark greys, deep blacks, and the contrasting fiery glow of the dragon's eyes and perhaps a hint of internal fire. Rendered in a hyperrealistic, cinematic digital art style, with exceptional attention to detail on the scales, musculature, and the texture of the rocky environment. Lighting is dramatic and high-contrast, with sharp highlights on the dragon's form and deep, impenetrable shadows. Quality specifications include ultra-high detail, 8K resolution, photorealistic rendering, and an epic, awe-inspiring mood, evoking the grandeur and terror of powerful fantasy creatures." Result: 🔧 Technical Details AI Models**: Google Gemini 2.5 Pro (prompt enhancement) + Gemini 2.0 Flash Preview (image generation) Messaging**: Telegram Bot API Output Format**: High-quality images in standard formats Processing Time**: Typically 10-15 seconds per image for Gemini 2.5 Flash and 25-30 seconds Gemini for 2.5 Pro

This workflow makes it easier to keep track of the stocks market and get an email with a summary of the daily highlights on what happened, key insights and trends Setup Guide Define the schedule (days, times, intervals). Replace sample stock data with your desired stock list (ticker, name, etc.) in JSON format. Split Out the fields to have a clean list of the stocks to monitor set keyword node Extracts the stock ticker from each item and sets it to the keyword property. Financial times scraper Triggers the Bright Data Datasets API to scrape financial data. Set the node as below Method: POST URL: https://api.brightdata.com/datasets/v3/trigger Query Parameters: dataset_id: Replace with your Bright Data dataset ID. include_errors: true type: discover_new discover_by: keyword Headers: Authorization: Bearer YOUR_BRIGHTDATA_API_KEY Replace with your Bright Data API key. Body: JSON, ={{ $('set keyword').all().map(item => item.json)}} Execute Once: Checked. Get progress node Checks the status of the Bright Data scraping job if complete, or running Setup: URL: https://api.brightdata.com/datasets/v3/progress/{{ $json.snapshot_id }} Headers: Authorization: Bearer YOUR_BRIGHTDATA_API_KEY Replace with your Bright Data API key. Get snapshot + data retrieves the scraped data from the Bright Data API. Pass the request as URL: https://api.brightdata.com/datasets/v3/snapshot/{{ $json.snapshot_id }} Query Parameters: format: json Headers: Authorization: Bearer YOUR_BRIGHTDATA_API_KEY Replace with your Bright Data API key. Aggregate. Combines the data from each stock item into a single object Update to sheet and add all items to This sheet. Make a copy before you can map the data create summary node generates a summary of the scraped stock data using the Google Gemini AI model and notifies you via Gmail. Setup: Prompt Type: define Text: Customize the prompt to define the AI's role, input format, tasks, output format (HTML email), and constraints. Google Sheets. Appends the scraped data to a Google Sheet. This should be set to automap so as to adjust to the results found in the request Important Notes: Remember to replace placeholder values (API keys, dataset IDs, email addresses, Google Sheet IDs) with your actual values. Review and customize the AI prompt for the "create summary" node to achieve the desired email summary output. Consider adding error handling for a more robust workflow. Monitor API usage to avoid rate limits.

👥 Who Is This For? Content creators, marketing teams, and channel managers who need to streamline video publishing with optimized metadata and scheduled releases across multiple videos. 🛠 What Problem Does This Solve? Manual YouTube video publishing is time-consuming and often results in inconsistent descriptions, tags, and scheduling. This workflow fully automates: Extracting video transcripts via Apify for metadata generation Creating SEO-optimized descriptions and tags for each video Setting videos to private during initial upload (critical for scheduling) Implementing scheduled publishing at strategic times Maintaining consistent branding and formatting across all content 🔄 Node-by-Node Breakdown | Step | Node Purpose | |------|--------------| | 1 | Every Day (Scheduler) | Trigger workflow on a regular schedule | | 2 | Get Videos to Harmonize | Retrieve videos requiring metadata enhancement | | 3 | Get Video IDs (Unpublished) | Filter for videos that need publishing | | 4 | Loop over Video IDs | Process each video individually | | 5 | Get Video Data | Retrieve metadata for the current video | | 6 | Loop over Videos with Parameter IS | Set parameters for processing | | 7 | Set Videos to Private | Ensure videos are private (required for scheduling) | | 8 | Apify: Get Transcript | Extract video transcript via Apify | | 9 | Fetch Latest Videos | Get most recent channel content | | 10 | Loop Over Items | Process each video item | | 11 | Generate Description, Tags, etc. | Create optimized metadata from transcript | | 12 | AP Clean ID | Format identifiers | | 13 | Retrieve Generated Data | Collect the enhanced metadata | | 14 | Adjust Transcript Format | Format transcript for better processing | | 15 | Update Video's Metadata | Apply generated description and tags to video | ⚙️ Pre-conditions / Requirements n8n with YouTube API credentials configured Apify account with API access for transcript extraction YouTube channel with upload permissions Master templates for description formatting Videos must be initially set to private for scheduling to work ⚙️ Setup Instructions Import this workflow into your n8n instance. Configure YouTube API credentials with proper channel access. Set up Apify integration with appropriate actor for transcript extraction. Define scheduling parameters in the Every Day node. Configure description templates with placeholders for dynamic content. Set default tags and customize tag generation rules. Test with a single video before batch processing. 🎨 How to Customize Adjust prompt templates for description generation to match your brand voice. Modify tag selection algorithms based on your channel's SEO strategy. Create multiple publishing schedules for different content categories. Integrate with analytics tools to optimize publishing times. Add notification nodes to alert when videos are successfully scheduled. ⚠️ Important Notes Videos MUST be uploaded as private initially - the Publish At logic only works for private videos that haven't been published before. Publishing schedules require videos to remain private until their scheduled time. Transcript quality affects metadata generation results. Consider YouTube API quotas when scheduling large batches of videos. 🔐 Security and Privacy API credentials are stored securely within n8n. Transcripts are processed temporarily and not stored permanently. Webhook URLs should be protected to prevent unauthorized triggering. Access to the workflow should be limited to authorized team members only.

What this workflow does This workflow creates an automated web scraper that accepts form submissions, extracts specific data from any website using AI, and emails the results back to you. Step by step: Web Scraper Form Submission provides a web form interface where users submit a URL and specify what data to extract Get HTML from Source URL fetches the complete HTML content from the provided website HTML Extractor processes the raw HTML and extracts the body content for analysis Data Extractor LLM Chain uses Google Gemini AI to intelligently analyze the content and extract only the specific data requested by the user Structured Output Parser formats the AI response into clean JSON structure with standardized format Gmail Send Result delivers the extraction results via email including the source URL, extraction request details, and clean extracted results How to set up Connect your Google Gemini API to the Google Gemini Chat Model node for AI-powered data extraction Connect your Gmail account to the Gmail node for sending result emails Update the recipient email in the Gmail node Customize the extraction prompt in the Data Extractor LLM Chain node based on your specific requirements How to customize this workflow to your needs Switch AI models**: Replace Google Gemini with OpenAI, Claude, or other LLM providers in the Chat Model node based on your accuracy requirements and budget preferences Change result delivery**: Replace Gmail with Google Sheets for data storage, Outlook for corporate email, Slack for team notifications, or webhook integrations for custom applications Customize extraction prompts**: Modify the LLM prompt in the Data Extractor Chain to handle specific data types, extraction formats, or industry-specific terminology for your use case Need help customizing? Contact me for consulting and support: 📧 [email protected]

🤖 Interactive Academic Chatbot (Telegram + MongoDB) Overview 📋 This project is a template for building a complete academic virtual assistant using n8n. It connects to Telegram, answers frequently asked questions by querying MongoDB, keeps the community informed about key dates (via web scraping), and collects user feedback for continuous improvement. How It Works Architecture and Workflow ⚙️ n8n: Orchestration of 3 workflows (chatbot, scraping worker, announcer). Telegram: Frontend for user interaction and sending announcements. MongoDB: Centralized database for FAQs, academic calendar, and feedback logs. Web Scraping: HTTP Request and HTML Extract nodes to read the university's web calendar. Cron: For automatic periodic executions (daily and weekly). Core Processes 🧠 Real-time reception of user queries via Telegram. Querying MongoDB collections for FAQ answers and calendar dates. Daily scraping of the university website to keep the calendar updated. Instant logging of user feedback (👍/👎) in MongoDB. Proactive sending of weekly announcements to the Telegram channel. Key Benefits ✅ Complete automation of student communication 24/7. An always-accurate academic calendar database without manual intervention. A built-in continuous improvement system through user feedback. Proactive communication of important events to the entire community. Use Cases 💼 Automation of student support in universities, colleges, and institutions. A virtual assistant for any organization needing to manage FAQs and a dynamic calendar. An automated announcements channel to keep a community informed. Requirements 👨‍💻 n8n instance (self-hosted or cloud). Credentials for a Telegram Bot (obtained from @BotFather). Credentials for a MongoDB database (Connection URI). URL of the academic calendar to be scraped. Authors 👥 Doménica Amores Nicole Guevara Adrián Villamar Mentor: Jaren Pazmiño Applicants to the CIAP Polytechnic Artificial Intelligence Club

📱🤖 Create Stunning AI Images Directly from WhatsApp with Gemini This workflow transforms your WhatsApp into a personal AI image generation studio. Simply send a text message with your idea, and this bot will use the advanced prompt engineering capabilities of Gemini 2.5 Pro to craft a detailed, artistic prompt. It then uses Gemini 2.0 Flash to generate a high-quality image from that prompt and sends it right back to your chat. It's a powerful yet simple way to bring your creative ideas to life, all from the convenience of your favorite messaging app\! What this workflow does Listens for WhatsApp Messages: The workflow starts automatically when you send a message to your connected WhatsApp number. Enhances Your Idea with AI: It takes your basic text (e.g., "a knight on a horse") and uses Gemini 2.5 Pro to expand it into a rich, detailed prompt perfect for image generation (e.g., "A cinematic, full-body shot of a stoic knight in gleaming, ornate silver armor, riding a powerful black warhorse through a misty, ancient forest. The scene is lit by ethereal morning sunbeams piercing the canopy, creating dramatic volumetric lighting and long shadows. Photorealistic, 8K, ultra-detailed, award-winning fantasy concept art."). Generates a Unique Image: It sends this enhanced prompt to the Google Gemini 2.0 Flash image generation API. Prepares the Image: The API returns the image in Base64 format, and the workflow instantly converts it into a binary file. Sends it Back to You: The final, high-quality image is sent directly back to you in the same WhatsApp chat. Nodes Used 🟢 WhatsApp Trigger: The entry point that listens for incoming messages. 🧠 LangChain Chain (LLM): Uses Gemini 2.5 Pro for advanced prompt engineering. ➡️ HTTP Request: Calls the Google Gemini 2.0 Flash API to generate the image. 🔄 Convert to File: Converts the Base64 image data into a sendable file format. 💬 WhatsApp: Sends the final image back to the user. Prerequisites To use this workflow, you will need: An n8n instance. A WhatsApp Business Account connected to n8n. You can find instructions on how to set this up in the n8n docs. A Google Gemini API Key. You can get one for free from Google AI Studio. How to use this workflow Get your Google Gemini API Key: Visit the Google AI Studio and create a new API key. Configure the Gemini 2.5 Pro Node: In the n8n workflow, select the Gemini 2.5 Pro node. Under 'Connect your account', click 'Create New' to add a new credential. Paste your Gemini API key from the previous step and save. Configure the Generate Image (HTTP Request) Node: Select the Generate Image node. In the properties panel on the right, find the Query Parameters section. In the 'Value' field for the key parameter, replace "Your API Key" with your actual Google Gemini API Key. Connect WhatsApp: Select the WhatsApp Trigger node. Follow the instructions to connect your WhatsApp Business Account credential. If you haven't created one, the node will guide you through the process. Activate and Test: Save the workflow using the button at the top right. Activate the workflow using the toggle switch. Send a message to your connected WhatsApp number (e.g., "A futuristic city in the style of Van Gogh"). The bot will process your request and send a stunning AI-generated image right back to you\!

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.

Translating your YouTube video titles and descriptions into multiple languages is one of the simplest ways to expand your channel's global reach. But doing it manually is super tedious and time-consuming. This n8n workflow automates the entire process: from detecting your latest video, translating its metadata into multiple languages using AI, to publishing the translated versions directly to YouTube - all managed and tracked through a connected Google Sheet only. What Problem Is This Workflow Solving? Manually translating YouTube metadata—titles, descriptions, and tags—is both time-consuming and costly, especially as your video library grows. For example, let's say you want to translate the metadata of 50 videos into 5 languages, and if you spend 10 minutes on each video, it could take over 40 hours of manual work. This workflow automates the localization of your YouTube metadata, making it fast and efficient to translate large volumes of content. Instead of spending days on translations, you can handle bulk updates in minutes: Save Time and Resources**: Instantly translate metadata for dozens or hundreds of videos, freeing you from repetitive, manual tasks. Expand Your Global Reach**: Enable your videos to appear in search results across multiple languages, reaching new audiences worldwide. Boost Engagement and SEO**: Localized metadata helps your videos get discovered and increases viewer engagement, leading to higher watch times and better performance. Make Content More Accessible**: Welcome viewers from different linguistic backgrounds, making your channel inclusive and inviting. Who Is This For? Use cases are many: This workflow is perfect for YouTubers who want to automate multilingual metadata updates and eliminate repetitive manual tasks. It’s especially useful for creators whose content is visually driven and easy to follow, such as: DIY and How-to Channels Travel and Nature Channels Fitness and Workout Channels Cooking Channels Art and Craft Channels How It Works Phase 1: Prepare Values & Auto Crawl Mode Set up a Schedule Trigger: In the **Schedule Trigger node in n8n, define your preferred interval to automatically run the workflow on a recurring schedule; no manual execution needed. Set Required Parameters: In the **Prepare Values node in n8n, you must enter the following: spreadsheet_id: to link the workflow to your connected Google Sheet channel_name: to specify which tab of the Google Sheet contains the video URLs to process channel_id: to define the YouTube channel the workflow will act upon Set Target Languages: In the **Languages tab of your connected Google Sheet, list all languages you'd like to generate translated titles and descriptions for. These will be used later during the translation phase. Choose Crawling Mode: In the **Auto tab of your Google Sheet, configure the Auto Crawl setting in Column B based on your preferred method: Select No (Turn off Auto Crawl): You must manually input the video URL(s) in the channel_name tab and set the status to Ready for 1 video only. Select Yes (Turn on Auto Crawl): The workflow will automatically fetch one of the latest videos from your connected YouTube channel (based on channel_id) into the channel_name tab in your Google Sheet. Phase 2: Trigger The Process Once everything is properly set up, the workflow in n8n can be activated - either manually or automatically via the Schedule Trigger, which runs based on the interval you’ve configured earlier. The tool then checks the Auto Crawl status in Column B in the Auto tab of your connected Google Sheet to determine the route: If Auto Crawl = No: The workflow skips auto-fetching and proceeds directly to the next phase, expecting that the video URL is already entered manually and marked as Ready in its status. If Auto Crawl = Yes: The tool connects to your YouTube channel using the predefined channel_id. It fetches one of the latest videos and checks whether that video’s ID already exists in the list of processed videos. If the video has not been processed yet, its URL will be inserted into the channel_name tab, and its status in Column A will automatically be set to Ready, ensuring it proceeds to the next step. If it already exists, the video is skipped to avoid reprocessing. ⚠️ Important: When Auto Crawl = Yes, do not manually add another URL and set its status to Ready in the channel_name tab in the Google Sheet. Doing so may trigger the same video twice, causing data conflicts and redundant processing. Phase 3: Collect Video Information Once a new video URL appears in your connected Google Sheet and its status is set Ready in Column A (under the specified channel_name tab), the workflow picks it up automatically. Then, it extracts the Video ID from the URL and sends a GET request to the YouTube API to retrieve that video’s title and description in your channel’s default language for the next steps. Phase 4: Generate Translated Metadata In Preset Languages The tool reads your target languages from the Languages tab in your connected Google Sheet. A loop runs through each language code one at a time. For each language, the tool sends your original title and description to Google Gemini’s Chat Model. Then, the AI returns the content translated into the target language. The output is returned in JSON data, then restructured to ensure each language’s data is clearly separated and ready for the next step. Phase 5: Update Translated Metadata On YouTube & Log Status All translated titles and descriptions from previous steps are combined into one structured format. The tool sends a PUT request to the YouTube API to update the video’s metadata directly with the new multilingual-translated content. If the update is successful, the video's status in Column A in the channel_name tab in the connected Google Sheet is marked as Success. If the update fails, the video’s status is marked as Error for later review or retry. How To Set Up Download the working package. Import the package into your n8n interface. Duplicate the Youtube - Update Video Metadata in Multi-Languages Google Sheet template into your Google Sheets account. For the channel_name tab in the template, you can rename it with your actual YouTube channel's name for easier tracking. Set up necessary credentials in Google Cloud Console for tools access and usability: For Google Sheets access, please ensure connection in the following nodes: Node Get Auto Crawl Status → connected to the Auto tab Node Check Latest Video ID → connected to the channel_name tab Node Insert Video Info → connected to the channel_name tab Node Get Video URL → connected to the channel_name tab Node Get Language List → connected to the Languages tab Node Update Status - Success → connected to the channel_name tab Node Update Status - Error → connected to the channel_name tab For YouTube access, ensure connection to YouTube API in the following nodes: Node YouTube - Get Latest Video Node Get Video Info Node Update Video Metadata with Selected Languages For Google Gemini access, ensure connection to Google Gemini API in the following node: Node Google Gemini’s Chat Model Set a Schedule Trigger in n8n to run the workflow automatically at your preferred interval. Define necessary parameters in Node Prepare Values in your n8n workflow: spreadsheet_id: your connected Google Sheet ID channel_name: the tab in your connected Google Sheet contains the video URLs and receives process updates (should be renamed with your actual YouTube channel’s name for easy tracking) channel_id: your YouTube channel ID Check the status of the Auto Crawl function in the Auto tab in your connected Google Sheet: By default, its status is No: You’ll manually insert a video URL and mark its row as Ready. In case you want to turn it on, please change it to Yes: The tool will automatically fetch the latest video(s) from your channel. Activate the workflow in n8n. To manually update a video: Set Auto Crawl to No Insert the video URL into the channel_name tab Set the status to Ready To automate with Auto Crawl: Set Auto Crawl to Yes The tool will auto-fetch one of the new videos and set its status to Ready Track results of the original row in the channel_name tab of your Google Sheet and YouTube: If the row’s status is Success, the metadata is updated on YouTube with all the set languages and you can check things out on the platform directly. If the row’s status is Error, you can do manual review or retry. Requirements Basic setup in Google Cloud Console with OAuth2 credentials in the following configurations: Google Sheets API enabled, with edit permissions on the connected spreadsheet YouTube API enabled, with an account that has Owner or Editor role on the target channel API access to Google Gemini for generating multilingual translated content via AI. How To Customize Adjust the trigger interval: Change the schedule in the **Schedule Trigger node to fit your needs (e.g. every 10 minutes, hourly, etc.). Add or remove target languages: Simply update the **Languages tab in your connected Google Sheet. No changes in n8n are required. Customize the translation style: You can edit the prompt inside the **AI node to change the tone, format, or style of the translations. However, do not modify the output structure format - doing so will break the workflow. Add alerts or notifications when finished**: Feel free to integrate additional nodes (like Telegram or Email) to notify you and your team when updates succeed or fail. FAQs: Can I use this workflow for more than one YouTube channel? Not directly. This workflow is currently designed to connect to a single YouTube channel ID at a time. However, if you’d like to manage multiple YouTube channels within one Google Sheet and a unified n8n interface, we can customize the setup for you. Feel free to reach out to Agent Circle for a tailored setup and guidance. What happens if I manually enter a video URL while Auto Crawl is ON? Avoid this. Manually adding a URL with status Ready in the channel_name tab while Auto Crawl = Yes may cause duplicate processing, API conflicts, or data overwrites. How many languages can I translate into at once? There's no strict limit. You can list as many languages as needed in the Languages tab in your connected Google Sheet. Refer to the All Languages tab in the Google Sheet template for valid languages and language codes (e.g., en, fr, es, de). Do I need to change anything in n8n when I add more languages? No - simply update the Languages tab in your connected Google Sheet. No work in n8n is needed for this. Can I change the AI model from Google Gemini to something else? Yes. You can replace the Google Gemini Chat Model node with another chat model, such as OpenAI GPT-4, or any compatible LLM provider. What happens if the metadata update to YouTube fails? The video's status in Column A of the channel_name tab in your connected Google Sheet will be marked Error. You can then review, fix, and re-run the process. Can I edit the translation prompt in the AI node for my own brand tone? Absolutely. You can customize the translation prompt in the AI node to adjust tone, format, or even brand voice. Just make sure the structure of the returned JSON remains intact. Is the workflow GDPR or YouTube policy-compliant? Yes - as long as you're the owner or have editor access to the YouTube channel and use the official YouTube API with proper OAuth2 authentication. Can I schedule this workflow to run every day? Yes. In the Schedule Trigger node in n8n, set your preferred interval - e.g., daily, every 12 hours, etc. Does this work with unlisted or private videos? No - YouTube API typically returns data only for public videos. For private/unlisted videos, additional permissions and scopes are required. If you need support for this case, feel free to contact Agent Circle for personalized consultation and setup assistance. Need Help? If you need a step-by-step guide to set up this workflow or want it customized for your specific business needs, feel free to reach out to Agent Circle. We’re always here to support and help you to bring automation ideas to life. Join our community on different platforms for assistance, inspiration and tips from others. Website: https://www.agentcircle.ai/ Etsy: https://www.etsy.com/shop/AgentCircle Gumroad: http://agentcircle.gumroad.com/ Discord Global: https://discord.gg/d8SkCzKwnP FB Page Global: https://www.facebook.com/agentcircle/ FB Group Global: https://www.facebook.com/groups/aiagentcircle/ X: https://x.com/agent_circle YouTube: https://www.youtube.com/@agentcircle LinkedIn: https://www.linkedin.com/company/agentcircle

This workflow is designed for content creators or AI artists who want to automate posting unique AI-generated images to their Facebook Page multiple times a day. It uses Google Gemini via LangChain to generate imaginative image prompts, and Pollinations AI to generate the images. Posts are published with hashtags and a clean caption. Who Is It For AI artists Facebook page managers Digital marketers looking for automated creative content What It Does Triggers 3x daily at 7:00, 11:00, and 17:00 (local time) Generates random AI image prompts in a retro-futuristic, cinematic, or surreal style using Google Gemini Fetches images from Pollinations AI using custom prompts Posts images automatically to your Facebook Page with hashtags Requirements n8n self-hosted or desktop (workflow uses schedule trigger) Pollinations API (no auth needed) Facebook Page with Facebook Graph API token: Required scopes: pages_manage_posts, pages_read_engagement, pages_show_list Google Gemini API Key (used via LangChain node) How to Customize Change the prompt style in the Basic LLM Chain node (promptType: define) to suit your theme. Adjust Set The Generator Image node if you want: Different image sizes (width / height) Different seed randomness Other Pollinations models (&model=kontext) Add Telegram/Twitter nodes if you want cross-posting Use Set node to allow easy user-level configuration of models, hashtags, times, etc.

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.

How it works: This project creates a personal AI knowledge assistant that operates through Telegram. The assistant can extract summaries from YouTube videos or online articles, store them in Google Sheets for later reference, and retrieve stored summaries when requested by the user. Step-by-step: Google Sheets Trigger:* The workflow starts by detecting a new YouTube or article URL added to a dedicated sheet (Sheet2*). It checks whether the link is already processed. Link Type Detection:** The system identifies if the URL is from YouTube or a standard article. Data Retrieval:** If it’s YouTube: Uses Apify to fetch the transcript. If it’s an article: Uses an HTTP Request node to fetch the webpage content. AI Summarization:* The transcript or article content is passed to Google Gemini* for refined summarization. Google Sheets Storage:* The summary and title are appended to another sheet (Sheet1*) for long-term storage, along with a “Stored” status update in Sheet2. Telegram Assistant:** A Telegram Trigger listens for messages from the user. The assistant searches stored summaries in Google Sheets. If a match is found, it returns the result to the user on Telegram; otherwise, it politely apologizes.

AI-Powered Automated Outreach Scheduling with Gemini, Gmail & Google Sheets Automate your lead generation and outreach process seamlessly using AI, Gmail, and Google Sheets—all within n8n. No complicated setup—just import, activate, and start reaching prospects with personalized messages generated by Google Gemini’s AI model. Quick Setup Import the Workflow Download and import the provided workflow into your n8n instance. Connect Your Accounts Authenticate your Google Sheets account. Connect your Gmail account for sending emails. Prepare the Spreadsheet Use this template to set up your leads and tracking sheet. Configure the Gemini API Obtain your Gemini API key. Here Add it to the Gemini API credentials within n8n. Set Scheduling Preferences Customize the Schedule Trigger node to control when the workflow runs. Edit Email Prompts Update the initial and follow-up email prompts to match your outreach tone and goals. Set Rate Limits Configure the rate limiting settings to comply with Gmail sending limits and avoid spam filters. Activate the Workflow Enable the workflow to begin automated outreach to your leads. Track and Manage Leads Monitor responses and update lead statuses directly in your Google Sheet. How It Works Schedule Trigger:** Automatically starts outreach based on your defined schedule Google Sheets Integration:** Fetches leads and updates their status after outreach Email Validation:** Checks if lead emails are valid before sending Website Scraper:** Gathers info from lead websites to personalize messages Google Gemini AI:** Generates tailored cold outreach messages optimized for high response Gmail Node:** Sends personalized emails directly from your Gmail account Core Features Pull leads automatically from Google Sheets Validate emails to avoid bounces Scrape lead websites for custom messaging context Generate AI-crafted outreach emails with dynamic personalization Send emails on schedule without manual intervention Update lead status to track outreach progress AI Integration Uses Google Gemini AI to create professional, friendly, and engaging outreach emails Dynamic prompt templates tailored to each lead’s company and website content Structured JSON output to easily map subject, greeting, and body content 💡 Usage Examples B2B cold outreach campaigns with personalized emails Automated follow-ups based on lead engagement Lead nurturing with context-aware messaging Sales prospecting workflows integrated into your CRM ✨ Benefits Save hours by automating personalized outreach Increase response rates with AI-optimized messaging Keep lead data organized and updated in Google Sheets Fully scalable and customizable n8n workflow Minimal setup, ready to run out-of-the-box

Description This workflow provides a powerful AI assistant for content creators, book editors, and marketers. It automates the collection and analysis of trending discussions from Reddit, YouTube, and X (Twitter), generating insightful topic reports. This frees you from hours of tedious data compilation, allowing you to make faster, more accurate topic decisions based on deep AI analysis. How it works This workflow simulates the complete research process of a strategic editor: Initiate & Collect: A user submits a keyword via a public Form Trigger. The workflow then automatically fetches relevant, trending content in parallel from the official APIs of Reddit, YouTube, and X (Twitter). Multi-stage AI Processing & Analysis: The workflow utilizes a layered AI pipeline to process the data. First, a lightweight Gemini model in the AI Pre-filter Content node rapidly screens the vast amount of content to filter out noise. Next, a more powerful Gemini Pro model in the AI Deep Analysis node performs a detailed, structured analysis on each high-value item, extracting summaries, sentiment, and key arguments. Finally, a "strategist" AI model in the AI Synthesize Final Report node aggregates all analyses to generate the comprehensive final topic report in HTML. Multi-Channel Report Distribution: The workflow distributes the final report to multiple channels based on pre-defined templates. The Send Gmail Report node sends the complete HTML report. The Send Feishu Notification node sends a concise summary card to a group chat. Meanwhile, the Archive to Google Sheets node archives key data. Setup Steps This workflow takes approximately 20-30 minutes to set up, with most of the time spent connecting your accounts. Connect Your API Accounts: In the n8n Credentials section, you will need to prepare and connect credentials for the following services: Google: For the Gemini AI model, Gmail sending, and Google Sheets archiving. This requires a Google Cloud API Key and OAuth2 credentials. Reddit: For fetching Reddit posts. This requires a Reddit account with OAuth2 configured in n8n to allow searches. YouTube: For collecting YouTube videos. You'll need to enable the YouTube Data API v3 in your Google Cloud Console and get an API Key. Twitter: For the official Twitter node, requiring a free developer account and an App with v2 API access. Configure Output Channels: In the final nodes (Send Gmail Report, Send Feishu Notification, Archive to Google Sheets), update the recipient email address, the Feishu bot's Webhook URL, and the target spreadsheet ID to match your own. Activate and Share the Trigger: Activate the workflow. The first Form Trigger node will automatically generate a public URL. Share this link with your team members to let them start using the tool.

This template attempts to replicate OpenAI's DeepResearch feature which, at time of writing, is only available to their pro subscribers. > An agent that uses reasoning to synthesize large amount of online information and complete multi-step research tasks for you. Source Though the inner workings of DeepResearch have not been made public, it is presumed the feature relies on the ability to deep search the web, scrape web content and invoking reasoning models to generate reports. All of which n8n is really good at! Using this workflow, n8n users can enjoy a variation of the Deep Research experience for themselves and their teams at a fraction of the cost. Better yet, learn and customise this Deep Research template for their businesses and/or organisations. Check out the generated reports here: https://jimleuk.notion.site/19486dd60c0c80da9cb7eb1468ea9afd?v=19486dd60c0c805c8e0c000ce8c87acf How it works A form is used to first capture the user's research query and how deep they'd like the researcher to go. Once submitted, a blank Notion page is created which will later hold the final report and the researcher gets to work. The user's query goes through a recursive series of web serches and web scraping to collect data on the research topic to generate partial learnings. Once complete, all learnings are combined and given to a reasoning LLM to generate the final report. The report is then written to the placeholder Notion page created earlier. How to use Duplicate this Notion database template and make sure all Notion related nodes point to it. Sign-up for APIFY.com API Key for web search and scraping services. Ensure you have access to OpenAI's o3-mini model. Alternatively, switch this out for o1 series. You must publish this workflow and ensure the form url is publically accessible. On depth & breadth configuration For more detailed reports, increase depth and breadth but be warned the workflow will take exponentially longer and cost more to complete. The recommended defaults are usually good enough. Depth=1 & Breadth=2 - will take about 5 - 10mins. Depth=1 & Breadth=3 - will take about 15 - 20mins. Dpeth=3 & Breadth=5 - will take about 2+ hours! Customising this workflow I deliberately chose not to use AI-powered scrapers like Firecrawl as I felt these were quite costly and quotas would be quickly exhausted. However, feel free to switch web search and scraping services which suit your environment. Maybe you don't decide to source the web and instead, data collection comes from internal documents instead. This template gives you freedom to change this. Experiment with different Reasoning/Thinking models such as Deepseek and Google's Gemini 2.0. Finally, the LLM prompts could definitely be improved. Refine them to fit your use-case. Credits This template is largely based off the work by David Zhang (dzhng) and his open source implementation of Deep Research: https://github.com/dzhng/deep-research

Who’s it for This workflow is ideal for: Content creators producing daily historical or educational videos YouTube automation enthusiasts building AI-driven channels Educators sharing engaging historical facts in short-form video format Anyone creating an automated AI video pipeline with human approval How it works This workflow automates the full pipeline of generating and publishing historical videos: Triggers daily at 1 AM and initializes retry tracking (maximum 3 attempts) Fetches historical events for the current date and selects one randomly Uses Google Gemini to generate a cinematic text-to-video script Sends the prompt to fal.ai (Hunyuan LoRA) to generate a short video Polls the generation status every 30 seconds until the video is ready Downloads the generated video and sends it to Telegram with context Waits for manual approval via Telegram If approved → uploads the video to YouTube and sends a confirmation message If declined → retries with a new event (up to 3 attempts total) How to set up Import the workflow into n8n Configure your Telegram credentials Set your Telegram Chat ID using a variable or Set node (avoid hardcoding) Configure HTTP Header Auth credentials for fal.ai (API key required) Set up Google Gemini API credentials Connect your YouTube account using OAuth2 (Optional) Adjust the schedule time in the trigger node Activate the workflow Requirements n8n (cloud or self-hosted) fal.ai account and API key (for video generation) Google Gemini API access YouTube account with upload permissions Telegram account for approval notifications How to customize the workflow Adjust retry limits in the retry logic node Modify video parameters (resolution, frames, aspect ratio) in the fal.ai request Change the script style by editing the Gemini prompt Replace the historical events API with another content source Customize Telegram messages or approval flow

Generate visual resumes from Telegram inputs using Google Gemini This workflow transforms text-based resume data into visually stunning images by leveraging Google Gemini's reasoning and vision capabilities. It autonomously analyzes the candidate's profile, selects an appropriate design template based on their industry, and renders a high-quality resume image directly in Telegram. Target Audience Job seekers, career coaches, resume writers, and recruitment agencies looking to automate design generation. How it works Classify Input: The workflow starts with a Telegram trigger. A Google Gemini agent analyzes the incoming message to determine if it is a casual chat or a resume generation request. Fetch Context: If it is a resume request, a BrowserAct node triggers a workflow (using the "AI Resume Replicant" template) to fetch necessary external context or data. Ingest Designs (Optional): If a reference image is provided, CloudConvert standardizes the file, and Google Gemini Vision reverse-engineers the layout and style, saving the "Visual DNA" to Google Sheets. Draft Blueprint: The "Resume Writer" AI agent selects a stored design template that matches the candidate's industry (e.g., "Corporate" for Finance, "Creative" for Design) and maps the text content to the layout. Generate Prompt: A "Visualizer" AI agent converts the structured blueprint into a highly detailed natural language prompt for image generation. Render & Deliver: Google Gemini generates the final resume image, which is then sent back to the user via Telegram. How to set up Configure Credentials: Connect your Telegram, Google Gemini, Google Sheets, CloudConvert, and BrowserAct accounts in n8n. Prepare BrowserAct: Ensure the AI Resume Replicant template is saved in your BrowserAct account. Setup Google Sheet: Create a new Google Sheet with the required header (listed below). Connect Sheet: Open the Google Sheets nodes (Clear, Get, Append) and select your new spreadsheet. Configure Telegram: Ensure your Telegram Bot is connected to the Trigger and Message nodes. Google Sheet Headers To use this workflow, create a Google Sheet with the following header: Resume Details Requirements BrowserAct* account (Template: AI Resume Replicant*). Google Gemini** account. Telegram** account (Bot Token). CloudConvert** account. Google Sheets** account. How to customize the workflow Refine Design Logic: Modify the system prompt in the "Resume Writer" agent to change how the AI matches industries to design styles (e.g., force specific colors for specific roles). Change Output Format: Replace the Telegram response node with a Google Drive node to save the generated images as PDF or PNG files instead of sending them. Switch Image Model: Update the "Generate an image" node to use a different image generation model if preferred (e.g., OpenAI DALL-E). Need Help? How to Find Your BrowserAct API Key & Workflow ID How to Connect n8n to BrowserAct How to Use & Customize BrowserAct Templates Workflow Guidance and Showcase Video I Built a Resume Bot that CLONES Any Template! 🤖 (BrowserAct + n8n + Gemini Tutorial)

Zoho CRM - Smart Meeting Scheduler This workflow automatically schedules meetings for new Zoho CRM leads by detecting their timezone, checking the sales rep’s Google Calendar, generating conflict-free time slots, creating a Zoom meeting and sending a personalized AI-generated email to the lead. If no slots are available, it sends a fallback message to the lead without updating Zoho CRM. When a meeting is created, all details are logged inside Zoho CRM for visibility. ⚡ Quick Implementation Steps (Fast Start Guide) Import the workflow JSON into n8n. Configure Zoho CRM, Google Calendar, Gmail, Zoom OAuth and Gemini AI credentials. Update meeting duration, working hours, buffer time and search window. Set email recipient to the lead’s email instead of test/static values. Add the webhook URL to Zoho CRM → Automation → Webhooks. Test with a new lead and activate the workflow. 📘 What It Does This workflow automates scheduling for new Zoho CRM leads. As soon as a lead is created, it retrieves full lead and owner details, detects the lead’s timezone and checks the assigned sales rep’s upcoming Google Calendar events. This helps identify when the rep is available. Using your settings—working hours, meeting duration, buffer before/after and days to evaluate—the system generates valid meeting time slots with no conflicts. If suitable slots exist, it authenticates with Zoom and creates a meeting for the earliest option, then generates a polished HTML invitation using Gemini AI and emails it to the lead. This ensures a fast, smart and personalized lead engagement process. If no slots exist, the workflow sends a fallback email informing the lead that no availability is open in the next few days. In this branch, Zoho CRM is not updated, because no meeting was scheduled. 🎯 Who’s It For This workflow is perfect for: Sales teams managing high inbound volume CRM managers automating lead qualification & engagement SaaS companies scheduling demos automatically Agencies booking consultation calls Any team struggling with timezone-based scheduling manually 🔧 Requirements to Use This Workflow Platform Requirements n8n (Cloud or self-hosted) Required Integrations Zoho CRM OAuth2 Google Calendar OAuth2 Gmail OAuth2 Zoom OAuth (account-level) Gemini AI / Google PaLM API Required Lead Fields Email (mandatory for sending the invite) Country / State (for timezone detection) Lead Owner (to fetch rep details) 🔄 How It Works Zoho CRM Webhook triggers when a new lead is created. Workflow fetches full lead and owner details. Detects the lead’s timezone using country/state mapping. Fetches the sales rep’s availability from Google Calendar. Generates valid time slots based on working hours, buffers and meeting duration. If slots exist: Authenticate with Zoom Create a Zoom meeting Generate personalized HTML invite using Gemini AI Send email to the lead Log meeting details in Zoho CRM If no slots exist: Generate fallback message Send fallback email to the lead (Zoho CRM is NOT updated in this path) 🛠️ Setup Steps (Configuration Guide) Import Workflow Go to: n8n → Workflows → Import and upload the JSON file. Add Required Credentials Configure the following inside n8n: Zoho CRM OAuth Google Calendar OAuth Gmail OAuth Zoom OAuth Gemini AI API key Update Workflow Configuration Node Set: Meeting duration Buffer before/after Working hours Days to look ahead Default meeting provider (Zoom) Fix Email Recipient In Send Meeting Invite node, set: sendTo = {{$('Detect Lead Timezone').item.json.Email}} yaml Copy code Update Google Calendar Email/ID Ensure the calendar ID matches the sales rep’s Google Calendar. Add Webhook in Zoho CRM Navigate to: Setup → Automation → Webhooks → Create Webhook → Lead Created Paste the webhook URL from n8n. Test the Automation Verify: Correct timezone detection Calendar availability check Zoom meeting creation AI email sent to the lead Zoho CRM updated only when meeting is created Activate Workflow Enable the workflow for live operation. 🧩 How To Customize Nodes Adjust Meeting Logic Modify the Workflow Configuration node to change: Slot duration Buffer time Working hour ranges Days to consider Expand Timezone Detection Edit the Detect Lead Timezone node to add new countries/states. Personalize Email Content Update the prompt inside the Generate Personalized Invite node. Add New Regions Duplicate timezone logic for new regions (Australia, Middle East, etc.) Replace Zoom Swap Zoom with Google Meet, Microsoft Teams or Zoho Meeting. ➕ Add-Ons (Optional Enhancements) Auto-book calendar events when lead confirms a slot WhatsApp notifications via Twilio or Gupshup Slack/Email internal alerts for reps Follow-up reminder emails Log lead activity to Google Sheets Attach downloadable ICS calendar file 💼 Use Case Examples SaaS demo scheduling Consultation & discovery calls Global timezone-based sales teams Onboarding/support calls Event follow-up scheduling (And many more…) 🩻 Troubleshooting Guide | Issue | Possible Cause | Solution | |-------|----------------|----------| | Lead not receiving email | Gmail OAuth expired / wrong email field | Reconnect Gmail OAuth & fix sendTo value | | Wrong time slots | Incorrect timezone detection | Update mapping in Detect Lead Timezone | | Zoom meeting not created | Invalid/expired Zoom OAuth | Reconnect Zoom credentials | | CRM not updated after fallback email | Expected behavior | No CRM update when slots don’t exist | | Workflow not triggering | Missing Zoho webhook | Re-add webhook | | Empty AI email | Gemini key incorrect | Reconfigure Gemini credentials | 🤝 Need Help? If you want assistance setting up, customizing or extending this workflow, the n8n automation team at WeblineIndia is here to help. We specialize in: Advanced automation workflows Multi-timezone scheduling systems CRM-integrated AI communication Custom Zoho + n8n development End-to-end automation architecture 👉 Contact WeblineIndia for expert workflow development and enhancements.

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

Overview & Setup This n8n template demonstrates how to automatically generate authentic User-Generated Content (UGC) style marketing videos for eCommerce products using AI. Simply upload a product image, and the workflow creates multiple realistic influencer-style video ads complete with scripts, personas, and video generation. Use cases Generate multiple UGC video variations for A/B testing Create authentic-looking product demonstrations for social media Produce influencer-style content without hiring creators Quickly test different marketing angles for new products Scale video content creation for eCommerce catalogs Good to know Sora 2 video generation takes approximately 2-3 minutes per 12-second video Each video generation costs approximately $0.50-1.00 USD (check OpenAI pricing for current rates) The workflow generates multiple video variations from a single product image Videos are automatically uploaded to Google Drive upon completion Generated videos are in 720x1280 (9:16) format optimized for social media How it works Product Analysis: OpenAI's vision API analyzes the uploaded product image to understand its features, benefits, and target audience Persona Creation: The system generates a detailed profile of the ideal influencer/creator who would authentically promote this product Script Generation: Gemini 2.5 Pro creates multiple authentic UGC video scripts (12 seconds each) with frame-by-frame breakdowns, natural dialogue, and camera movements Frame Generation: For each script, Gemini generates a custom first frame that adapts the product image to match UGC aesthetic and aspect ratio Video Production: Sora 2 API generates the actual video using the script and custom first frame as reference Status Monitoring: The workflow polls the video generation status every 15 seconds until completion Upload & Storage: Completed videos are automatically uploaded to Google Drive with organized naming How to use Click the form trigger URL to access the submission form Upload your product image (works best with clean product shots on white/neutral backgrounds) Enter the product name Submit the form and wait for the workflow to complete Find your generated UGC videos in the specified Google Drive folder Each run produces multiple video variations you can test Requirements OpenAI API** account with Sora 2 access for video generation and GPT-4 Vision Google Gemini API** account for script generation and image adaptation Google Drive** account for video storage Sufficient API credits for video generation (budget accordingly) Customizing this workflow Adjust the video duration in the generate_video node (currently set to 12 seconds) Modify the persona prompt in analyze_product node to target different audience demographics Change the script style in set_build_video_prompts node for different UGC aesthetics (excited discovery, casual recommendation, etc.) Update the Google Drive folder in upload_video node to organize videos by campaign Add additional processing nodes for video editing, subtitle generation, or thumbnail creation Modify the aspect ratio in resize_image node for different platforms (1:1 for Instagram feed, 16:9 for YouTube, etc.)

💼 LinkedIn Content Machine – AI-Powered Post Generator & Scheduler for X and LinkedIn How it works: This end-to-end workflow automates your personal or brand content strategy by: 🧠 Using Google Gemini or OpenAI to generate engaging LinkedIn/X content from a title or trending posts. 🗓️ Posting directly to LinkedIn and X (formerly Twitter). 📊 Pulling high-performing LinkedIn posts to inspire new ideas. ✍️ Saving AI-generated drafts to Google Sheets for review. 🔔 Notifying your team on Slack when drafts are ready. Steps to set up: Add your API keys for Google Gemini or OpenAI. Set up your LinkedIn, X (Twitter), Google Sheets, and Slack credentials. Customize prompt logic or post filters if needed. Schedule the idea generation module or trigger it manually. Start generating and posting consistent, high-quality content with zero manual effort!

YouTube Transcript Summarization in Any Language for Social Media This n8n workflow automates the process of: Retrieving YouTube Video Transcripts: It fetches the transcript for any YouTube video URL provided using the YouTube Transcript API from RapidAPI. Generating a Concise Summary in Any Language: The workflow uses Google Gemini (PaLM) to create a concise summary of the transcript in the language specified by the user (e.g., English, Spanish, etc.). Storing the Summary in Google Docs: The generated summary is inserted into a predefined Google Document, making it easy for users to share or edit. Features: Language Flexibility:** Summaries are created in the desired language. Fully Automated:** From fetching the transcript to updating Google Docs, the process is fully automated. Social Media Ready:** The summary is formatted and stored in a Google Doc, ready for use in social media posts. This workflow integrates with YouTube Transcript API via RapidAPI, allowing you to easily fetch video transcripts and summarize them with AI. The entire process is automated and seamless. Powered by RapidAPI: API Used:* YouTube Transcript API via RapidAPI* to get the transcript data. Benefits: Saves Time:** Automates the transcript summarization process, eliminating the need for manual content extraction and summarization. Customizable Language Support:** Provides summaries in any language, enabling accessibility and engagement for a global audience. Streamlined Content Creation:** Automatically generates concise, engaging summaries that are ready for social media use. Google Docs Integration:** Saves summaries directly into a Google Doc for easy sharing, editing, and content management. Challenges Addressed: Manual Transcript Extraction:** Problem: Manually transcribing and summarizing YouTube videos for social media can be time-consuming and error-prone. Solution: This workflow fully automates the process, saving hours of manual work using the YouTube Transcript API. Lack of Language Support in Summaries:** Problem: Many automated tools only summarize content in a single language, limiting their accessibility. Solution: With language flexibility, the workflow creates summaries in the language of your choice, helping you cater to diverse audiences. Inconsistent Video Quality & Transcript Accuracy:** Problem: Not all YouTube videos have well-structured or accurate transcripts, leading to incomplete or inaccurate summaries. Solution: The workflow can process and format even imperfect transcripts, ensuring that the generated summaries are still accurate and useful. Managing Content Across Platforms:** Problem: Transcripts and summaries often need to be stored in multiple locations for social media posts, which can be cumbersome. Solution: The workflow integrates with Google Docs to automatically store and manage summaries in one place, making it easier to share and reuse content.

AI-Powered Social Media Content Generator & Publisher 🚀 This AI-driven n8n workflow automates social media content creation and publishing across LinkedIn, Instagram, Facebook, and Twitter (X). It generates engaging, platform-optimized posts using Google Gemini AI, based on user inputs such as a post title, keywords, and an uploaded image. The workflow ensures seamless content generation and publishing, making it a perfect tool for marketers, business owners, influencers, and content creators. 🌟 Features & Benefits ✅ AI-Generated Social Media Posts – Uses Google Gemini AI to create high-quality, optimized content. ✅ Multi-Platform Support – Automatically generates posts for LinkedIn, Instagram, Facebook, and Twitter (X). ✅ Hashtag & SEO Optimization – Includes trending hashtags to enhance visibility and engagement. ✅ Image Upload & Processing – Allows image uploads for Instagram and Facebook using imgbb and Facebook Graph API. ✅ Automated Publishing – Posts are automatically published on all selected platforms. ✅ Custom Call-to-Action – Each platform's post is optimized with CTAs for better engagement. ✅ User-Friendly Form Submission – Easy-to-use form where users can enter post titles, keywords, links, and images. ✅ Performance Tracking – Provides confirmation and tracking links for published posts. 📌 How It Works 1️⃣ User Submission Form Fill out the form with Post Title, Keywords, and an Optional Link. Upload an image for Instagram & Facebook posts. 2️⃣ AI Content Generation Google Gemini AI generates optimized content for each platform. The AI ensures professional, engaging, and audience-specific content. 3️⃣ Content Review Users review and approve the AI-generated content before publishing. 4️⃣ Automated Publishing Posts are automatically published on LinkedIn, Facebook, Instagram, and Twitter (X). Uses Facebook Graph API, LinkedIn API, Twitter API, and Instagram API. 5️⃣ Post Confirmation & Tracking Get links to track published posts on each platform. 🛠️ Prerequisites Before using this workflow, ensure you have: ✅ n8n Instance (Cloud or Self-Hosted) ✅ Social Media API Credentials (Facebook, Instagram, LinkedIn, Twitter API) ✅ Google Gemini AI API Key ✅ imgbb API Key (for image hosting) Get N8n My Affiliate Link Buy My Book: Mastering n8n on Amazon Full Courses & Tutorials: http://lms.syncbricks.com 📺 YouTube Video Tutorial 🎥 Watch the step-by-step tutorial on how to set up and use this n8n workflow template: 🔗 YouTube Tutorial - AI-Powered Social Media Posting in n8n 🎯 Use Cases 📌 Marketing Agencies – Automate client content scheduling. 📌 Businesses & Brands – Maintain a consistent brand presence on social media. 📌 Content Creators & Influencers – Generate high-quality posts quickly. 📌 E-commerce & Startups – Promote products and services effortlessly. 📌 Corporate & Enterprise Teams – Streamline internal and external communications. Important Start with n8n Learn n8n with Amjid Get n8n Book 👨‍💻 Creator Information 👤 Developed by: Amjid Ali 🌐 Website: SyncBricks 📧 Email: [email protected] 💼 LinkedIn: Amjid Ali 📺 YouTube: SyncBricks 💡 Support & Contributions If you find this workflow helpful, consider supporting my work: 👉 Donate via PayPal For full courses on * AI Automation*, visit: 📚 SyncBricks LMS 📚 AI and Auotmation Course 👉 Get Started with N8N

Stay ahead of the market with this powerful, automated workflow that performs real-time sentiment analysis on stock market news. By leveraging the advanced capabilities of Google Gemini, this solution provides you with actionable insights to make informed investment decisions. This workflow is designed for investors, traders, and financial analysts who want to automate the process of monitoring news and gauging market sentiment for specific stocks. It seamlessly integrates with Google Sheets for input and output, making it easy to track a portfolio of stocks. Key Features & Benefits Automated Daily Analysis: The workflow is triggered daily, providing you with fresh sentiment analysis just in time for the market open. Dynamic Stock Tracking: Easily manage your list of tracked stocks from a simple Google Sheet. AI-Powered Insights: Utilizes Google Gemini's sophisticated language model to analyze news content for its potential impact on stock prices, including a sentiment score and a detailed rationale. Comprehensive News Aggregation: Fetches the latest news articles from EODHD for each of your specified stock tickers. Error Handling & Validation: Includes built-in checks for invalid stock tickers and formats the AI output for reliable data logging. Centralized Reporting: Automatically logs the sentiment score, rationale, and date into a Google Sheet for easy tracking and historical analysis. How It Works This workflow follows a systematic process to deliver automated sentiment analysis: Scheduled Trigger: The workflow begins each day at a specified time. Fetch Stock Tickers: It reads a list of stock tickers from your designated Google Sheet. Loop and Fetch News: For each ticker, it retrieves the latest news articles using the EODHD API. AI Sentiment Analysis: The collected news articles are then passed to a Google Gemini-powered AI agent. The agent is prompted to act as a stock sentiment analyzer, evaluating the news and generating: A sentiment score from -1 (strong negative) to 1 (strong positive). A detailed rationale explaining the basis for the score. Data Formatting & Validation: The AI's output is parsed and validated to ensure it is in the correct JSON format. Log to Google Sheets: The final sentiment score and rationale are appended to your Google Sheet, alongside the corresponding stock ticker and the current date. Nodes Used Schedule Trigger Google Sheets SplitInBatches HttpRequest (EODHD) If Code (JavaScript) AI Agent (LangChain) Google Gemini Chat Model This workflow is a valuable tool for anyone looking to harness the power of AI for financial market analysis. Deploy this automated solution to save time, gain a competitive edge, and make more data-driven trading decisions.

Who this is for? The LinkedIn Profile Extract and JSON Resume Builder is a powerful workflow that scrapes professional profile data from LinkedIn using Bright Data's infrastructure, then transforms that data into a clean, structured JSON resume using Google Gemini. The workflow is ideal for automating resume parsing, candidate profiling, or integrating into recruiting platforms. This workflow is tailored for: HR professionals & recruiters automating resume screening Talent acquisition platforms enriching candidate profiles Developers & AI builders creating resume-parsing AI pipelines Data scientists working on labor market analytics Growth hackers profiling prospects via public data What problem is this workflow solving? Parsing resumes or LinkedIn profiles into machine-readable formats is often a manual, error-prone process. Most scraping tools either fail due to anti-bot protections or return unstructured HTML that's hard to work with. This workflow solves that by: Using Bright Data's Web Unlocker for reliable, CAPTCHA-free LinkedIn scraping Extracting clean text and structured profile data via Google Gemini LLM Automatically generating a standards-compliant JSON Resume and Skills Sending the resume to webhooks or storing it for downstream usage What this workflow does Accepts LinkedIn Profile URL and required metadata (Bright Data zone, webhook) Scrapes LinkedIn profile using Bright Data Web Unlocker Extracts clean content and skills using Google Gemini LLM Builds a JSON-formatted resume following the JSON resume schema Sends the JSON resume via Webhook Notification Persists the output by saving the file to disk Setup Sign up at Bright Data. Navigate to Proxies & Scraping and create a new Web Unlocker zone by selecting Web Unlocker API under Scraping Solutions. In n8n, configure the Header Auth account under Credentials (Generic Auth Type: Header Authentication). The Value field should be set with the Bearer XXXXXXXXXXXXXX. The XXXXXXXXXXXXXX should be replaced by the Web Unlocker Token. In n8n, configure the Google Gemini(PaLM) Api account with the Google Gemini API key (or access through Vertex AI or proxy). Update the Set URL and Bright Data Zone node with the LinkedIn profile, Bright Data Zone and the Webhook notification URL. For testing purposes, you can obtain a webhook url using https://webhook.site/ How to customize this workflow to your needs Add Language Translation Insert a translation LLM node to support multilingual profiles. Generate PDF Resumes Convert JSON to formatted PDF resumes using an HTML-to-PDF module. Push to ATS or CRM Add integration nodes to pipe data into applicant tracking systems (ATS), CRMs, or databases. Use Alternative LLMs Swap Gemini with OpenAI or Anthropic Claude if preferred.

🎥 YouTube Video Summarizer for Social Media Turn any YouTube video into a short, structured summary using AI — perfect for content creators, marketers, or social media managers. 🔧 What We Built We created a no-code automation in n8n that: Accepts a YouTube Video ID via a form Fetches the video transcript using an external API Summarizes the transcript using AI (Google Gemini) Automatically saves the summary to Google Docs for team use 🧩 Flow Overview | Step | Description | |------|-------------| | ✅ Form Trigger | User submits a YouTube video ID using an n8n form | | 🔁 Set Node | Maps the YouTube video ID for use in the API request | | 🌐 HTTP Request (External API) | Calls the YouTube Transcriptor AI API via RapidAPI to fetch transcript | | 🧹 Formatter (Code Node) | Joins transcript lines into a readable text block | | 🧠 AI Agent + Google Gemini (via Langchain) | Summarizes the full transcript into bullet points and tone | | 🧽 Optimizer (Code Node) | Extracts just the summary from the AI response | | 📝 Google Docs Node | Appends the clean summary to a shared Google Doc | 🌍 Real-World Problem Solved ❌ The Challenge Creators and marketers waste hours watching full videos just to extract the key points. Manual summarization is inconsistent, repetitive, and delays content planning. ✅ Our Solution ⏱️ Reduces time spent watching videos 🧠 AI-powered summaries keep tone consistent and structured 📄 Auto-sync with Google Docs makes summaries instantly available for teams 🔥 Bonus: This uses the YouTube Transcriptor AI API, so no need to manually scrape captions or use browser extensions. 🚀 Ideal Use Cases Repurpose YouTube content into Instagram Reels, LinkedIn posts, or blog content Build a video summary library for your editorial team Quickly extract talking points from podcast episodes 🛠️ Tech Stack n8n** – workflow automation engine YouTube Transcriptor AI API** – via RapidAPI Google Gemini (via Langchain)** – AI summarization Google Docs** – stores the final summary JavaScript nodes** – custom text parsing & formatting 💡 Want to customize it? Add Slack, Airtable, Notion, or Tweet auto-posting to expand the flow. Create your free n8n account and set up the workflow in just a few minutes using the link below: 👉 Start Automating with n8n Save time, stay consistent, and grow your LinkedIn presence effortlessly!