Workflow Templates

Automates the process of generating, storing, and publishing engaging LinkedIn posts derived from books (PDFs) using AI and vector search. 🧠 Overview This workflow: Watches a Google Drive folder for new or updated book PDFs. Extracts and embeds the content using OpenAI. Stores the data in a Pinecone vector database. Uses a LangChain agent to generate post ideas. Creates concise LinkedIn posts with hook, insight, CTA. Updates a Google Sheet and posts to LinkedIn. 🛠 Workflow Breakdown 📥 1. Google Drive Trigger Trigger:** Watches a folder for new or updated PDF files. Action:** Downloads the updated PDF. 📄 2. Extract and Embed Content Extract from File:** Parses PDF to extract text. Text Splitter:** Breaks text into chunks. Embeddings (OpenAI):** Converts chunks into vector embeddings. Pinecone Vector Store:** Saves the embeddings with the book name as namespace. 🧠 3. Post Idea Generation (LangChain Agent) Uses a prompt to: Search Pinecone DB Extract insights Format into 5 LinkedIn post ideas with: Hook Insight CTA Memory buffer** and structured output parser are used for clean AI interaction. ✍️ 4. Post Creation Each idea is: Split Rewritten with a GPT model prompt to match LinkedIn tone Styled for under 600 characters Includes emojis, hashtags, and tone guidelines 📊 5. Google Sheet Integration Saves all generated posts to a Google Sheet. Marks status: "published" or "no". 🔁 6. Scheduled Publishing Every day: Pulls an unpublished post Publishes it to LinkedIn Updates the post's status and timestamp in the Google Sheet ⚙️ Setup Guide 📂 Google Drive Create a folder for book PDFs Connect your Google Drive account to n8n Provide access token with file read permission 📊 Google Sheets Create a Google Sheet with columns: bookname, hook, insight, cta, postContent, published, date Add credentials in n8n with read/write permission 🧠 Pinecone Set up a Pinecone project and index (linkdenpost) Namespace will be auto-named using the book filename 🔑 API Credentials Required OpenAI API** (for embeddings and post generation) Pinecone API** (for vector storage and retrieval) LinkedIn OAuth2** (to publish posts) Google Drive & Sheets** credentials 🔁 Flow Summary graph TD A[Google Drive Trigger] --> B[Download PDF] B --> C[Extract Text] C --> D[Text Splitter] D --> E[Create Embeddings] E --> F[Pinecone Vector Store] F --> G[LangChain Agent] G --> H[Structured Output (5 Post Ideas)] H --> I[Split Ideas] I --> J[Format as LinkedIn Post (GPT)] J --> K[Store in Google Sheet] L[Schedule Trigger] --> M[Get Unpublished Post] M --> N[Post to LinkedIn] N --> O[Mark as Published] 🧪 Prompt Example (Used in LangChain Agent) You are a content strategist. Search the Pinecone vector DB containing a book. Generate 5 unique LinkedIn post ideas with: A Hook (curiosity driven) Insight (summary < 100 words) CTA ("Agree or disagree?", etc.) Respond in structured JSON: [ { "Hook": "...", "Insight": "...", "CTA": "..." }, ... ] ✅ Output Sample { "Hook": "Why your lab's results might be invalid 😱", "Insight": "ISO/IEC 17025 stresses that labs must plan and address risks to impartiality and validity.", "CTA": "Does your lab audit for these risks?" } 📆 Schedule Control Uses Schedule Trigger to post daily at a set time. Ensures automation with LinkedIn and accurate Google Sheet syncing. 📝 Notes Posts remain professional and concise for a LinkedIn audience Works with any PDF book Supports multi-book pipelines You can filter and tag books by filename or folder for segmenting post styles

Stay ahead of trends by automating your content research. This workflow fetches trending keywords from Google Trends RSS, extracts key insights from top articles, and saves structured summaries in Google Sheets—helping you build a data-driven editorial plan effortlessly. How it works Fetch Google Trends RSS – The workflow retrieves trending keywords along with three related article links. Extract & Process Content – It fetches the content of these articles, cleans the HTML, and generates a concise summary using Jina AI. Store in Google Sheets – The processed insights, including the trending keyword and summary, are saved in a pre-configured Google Sheet. Setup Steps Prepare a Google Sheet – Ensure you have a Google Sheet ready to store the extracted data. Configure API Access – Set up Google Sheets API and any required authentication. Get Jina.ai API key Adjust Workflow Settings – A dedicated configuration node allows you to fine-tune how data is processed and stored. Customization Modify the RSS source to focus on specific Google Trends regions or categories. Adjust the content processing logic to refine how article summaries are created. Expand the workflow to integrate with CMS (e.g., WordPress) for automated content planning. This workflow is ideal for content strategists, SEO professionals, and news publishers who want to quickly identify and act on trending topics without manual research. 🚀 Google Sheets Fields Copy and paste these column headers into your Google Sheet: | Column Name | Description | |------------------------|-------------| | status | Initial status of the keyword (e.g., "idea") | | trending_keyword | Trending keyword extracted from Google Trends | | approx_traffic | Estimated traffic for the trending keyword | | pubDate | Date when the keyword was fetched | | news_item_url1 | URL of the first related news article | | news_item_title1 | Title of the first news article | | news_item_url2 | URL of the second related news article | | news_item_title2 | Title of the second news article | | news_item_url3 | URL of the third related news article | | news_item_title3 | Title of the third news article | | news_item_picture1 | Image URL from the first news article | | news_item_source1 | Source of the first news article | | news_item_picture2 | Image URL from the second news article | | news_item_source2 | Source of the second news article | | news_item_picture3 | Image URL from the third news article | | news_item_source3 | Source of the third news article | | abstract | AI-generated summary of the articles (limited to 49,999 characters) | Instructions Open Google Sheets and create a new spreadsheet. Copy the column names from the table above. Paste them into the first row of your Google Sheet.

🔧 Workflow Summary This system automates LinkedIn lead generation and enrichment in six clear stages: 1. Lead Collection (via Apollo.io) Automatically pulls leads based on keywords, roles, or industries using Apollo’s API. Captures name, job title, company, and LinkedIn profile URL. You can kick off the workflow via form, webhook, WhatsApp, Telegram, or any other custom trigger that passes search parameters. 2. LinkedIn Username Extraction Extracts usernames from LinkedIn profile URLs using a script step. These usernames are required for further enrichment using RapidAPI. 3. Email Retrieval (via Apollo.io User ID) Fetches verified work email using the Apollo User ID. Email validity is double-checked using www.mails.so filtering out undeliverable or inactive emails by checking MX records and deliverability. 4. Profile Summary (via LinkedIn API on RapidAPI) Enriches lead data by pulling bio/summary details to understand their background and expertise. 5. Activity Insights (Posts & Reposts) Collects recent posts or reposts to help craft personalised messages based on what they’re currently engaging with. 6. Leads Sheet Update All data is written into a Google Sheet. New columns are populated dynamically without erasing existing data. ⸻ ✅ Smart Retry Logic Each workflow is equipped with a fail-safe system: Tracks status per row: ✅ done, ❌ failed, ⏳ pending Failed rows are automatically retried after a custom delay (e.g., 2 weeks). Ensures minimal drop-offs and complete data coverage. 📊 Google Sheets Setup Make a copy of the following: Template 1: Apollo Leads Scraper & Enrichment Template 2: Final Enriched Leads The system appends data (like emails, bios, activity) step by step. 🔐 API Credentials Needed 1. Apollo API Sign up and generate API key at Apollo Developer Portal Be sure to enable the “Master API Key” toggle so the same key works for all endpoints. 2. LinkedIn Data API (via RapidAPI) Subscribe at RapidAPI - LinkedIn Data Use your key in the x-rapidapi-key header. 3. Mails.so API Get your API Key from mails.so dashboard 🛠️ Troubleshooting – LinkedIn Lead Machine ✅ Common Mistakes & Fixes 1. API Keys Not Working Make sure API keys for Apollo, RapidAPI, and mails.so are correct. Apollo “Master API Key” must be enabled. Keys should be saved as Generic Credentials in n8n. 2. Leads Not Found Check if the search query (keyword/job title) is too narrow. Apollo might return empty results if the filters are incorrect. 3. LinkedIn URLs Missing or Invalid Ensure Apollo is returning valid LinkedIn URLs. Improper URLs will cause username extraction and enrichment steps to fail. 4. Emails Not Coming Through Apollo may not have verified emails for all leads. mails.so might reject invalid or expired email addresses. 5. Google Sheet Not Updating Make sure the Google Sheet is shared with the right Google account (linked to n8n). Check if the column names match and data isn’t blocked due to formatting. 6. Status Columns Not Changing Each row must have done, failed, or pending in the status column. If the status doesn’t update, the retry logic won’t trigger. 7. RapidAPI Not Returning Data Double-check if username is present and valid. Make sure the RapidAPI plan is active and within limits. 8. Workflow Not Running Check if the trigger node (form, webhook, etc.) is connected and active. Make sure you’re passing the required inputs (keyword, role, etc.). Need Help? Contact www.KrupalPatel.com for support and custom workflow development

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. CAD-BIM Multi-Format Validation Pipeline This workflow enables automated validation of CAD and BIM files in multiple formats (Revit, IFC, DWG, DGN) for compliance with project standards and requirements. Key Features Converts Revit, IFC, DWG, and DGN models into open data tables Runs automated validation checks on model naming, structure, attributes, and completeness Generates error reports and QTO (Quantity Take-Off) tables for all processed files How it works Upload one or more project files in Revit (.rvt), IFC (.ifc), DWG, or DGN formats The pipeline automatically processes each file and validates against configurable rules in Excel form Error summaries and QTO tables are generated All outputs are available for download as Excel Converter Path:** Make sure the converter executable (e.g. RvtExporter.exe) is placed in DDC Exporter\datadrivenlibs\. Specify the full path in the workflow settings if required. Troubleshooting:** If conversion fails, double-check the path to the executable. Only supported formats can be processed (see GitHub Readme). Review logs in /output for error details. Docs & Issues:** Full Readme on GitHub

Complete MCP server exposing all Mandrill Tool operations to AI agents. Zero configuration needed - all 2 operations pre-built. ⚡ Quick Setup Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free? Join the community Import this workflow into your n8n instance Activate the workflow to start your MCP server Copy the webhook URL from the MCP trigger node Connect AI agents using the MCP URL 🔧 How it Works • MCP Trigger: Serves as your server endpoint for AI agent requests • Tool Nodes: Pre-configured for every Mandrill Tool operation • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Uses official n8n Mandrill Tool tool with full error handling 📋 Available Operations (2 total) Every possible Mandrill Tool operation is included: 💬 Message (2 operations) • Send a message based on a template • Send a message based on HTML 🤖 AI Integration Parameter Handling: AI agents automatically provide values for: • Resource IDs and identifiers • Search queries and filters • Content and data payloads • Configuration options Response Format: Native Mandrill Tool API responses with full data structure Error Handling: Built-in n8n error management and retry logic 💡 Usage Examples Connect this MCP server to any AI agent or workflow: • Claude Desktop: Add MCP server URL to configuration • Custom AI Apps: Use MCP URL as tool endpoint • Other n8n Workflows: Call MCP tools from any workflow • API Integration: Direct HTTP calls to MCP endpoints ✨ Benefits • Complete Coverage: Every Mandrill Tool operation available • Zero Setup: No parameter mapping or configuration needed • AI-Ready: Built-in $fromAI() expressions for all parameters • Production Ready: Native n8n error handling and logging • Extensible: Easily modify or add custom logic > 🆓 Free for community use! Ready to deploy in under 2 minutes.

Multi-AI Agent Chatbot for Postgres/Supabase Databases and QuickChart Generation Who is this for? This workflow is ideal for data analysts, developers, and business intelligence teams who need an AI-powered chatbot to query Postgres/Supabase databases and generate dynamic charts for data visualization. What problem does this solve? It simplifies data exploration by combining conversational AI with database querying and chart generation. Users can interact with their database using natural language, retrieve insights, and visualize data without manual SQL queries or chart configuration. What this workflow does AI-Powered Chat Interface: Accepts natural language prompts to query databases or generate charts. Routes user requests through a tool agent system to determine the appropriate action (query or chart). Database Querying: Executes SQL queries on Postgres/Supabase databases based on user input. Retrieves schema information, table definitions, and specific data records. Dynamic Chart Generation: Uses QuickChart to create bar charts, line charts, or other visualizations from database records. Outputs a shareable chart URL or JSON configuration for further customization. Memory Integration: Maintains chat history using Postgres memory nodes, enabling context-aware interactions. Workflow diagram showcasing AI agents, database querying, and chart generation paths. Setup Prerequisites: A Postgres-compatible database (e.g., Supabase). API credentials for OpenAI. Configuration Steps: Add your database connection credentials in the Postgres nodes. Set up OpenAI credentials for GPT-4o-mini in the language model nodes. Adjust the QuickChart schema in the "QuickChart Object Schema" node to fit your use case. Testing: Trigger the chat workflow via the "When chat message received" node. Test with prompts like "Generate a bar chart of sales data" or "Show me all users in the database." How to customize this workflow Modify AI Prompts** Add Chart Types** Integrate Other Tools**

🛠️ Pushover Tool MCP Server Complete MCP server exposing all Pushover Tool operations to AI agents. Zero configuration needed - 1 operation pre-built. ⚡ Quick Setup Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free? Join the community Import this workflow into your n8n instance Activate the workflow to start your MCP server Copy the webhook URL from the MCP trigger node Connect AI agents using the MCP URL 🔧 How it Works • MCP Trigger: Serves as your server endpoint for AI agent requests • Tool Nodes: Pre-configured for every Pushover Tool operation • AI Expressions: Automatically populate parameters via $fromAI() placeholders • Native Integration: Uses official n8n Pushover Tool tool with full error handling 📋 Available Operations (1 total) Every possible Pushover Tool operation is included: 💬 Message (1 operations) • Push a message 🤖 AI Integration Parameter Handling: AI agents automatically provide values for: • Resource IDs and identifiers • Search queries and filters • Content and data payloads • Configuration options Response Format: Native Pushover Tool API responses with full data structure Error Handling: Built-in n8n error management and retry logic 💡 Usage Examples Connect this MCP server to any AI agent or workflow: • Claude Desktop: Add MCP server URL to configuration • Custom AI Apps: Use MCP URL as tool endpoint • Other n8n Workflows: Call MCP tools from any workflow • API Integration: Direct HTTP calls to MCP endpoints ✨ Benefits • Complete Coverage: Every Pushover Tool operation available • Zero Setup: No parameter mapping or configuration needed • AI-Ready: Built-in $fromAI() expressions for all parameters • Production Ready: Native n8n error handling and logging • Extensible: Easily modify or add custom logic > 🆓 Free for community use! Ready to deploy in under 2 minutes.

Submission Overview for Voiceflow Demo Workflow View the YouTube video for this workflow here. Who is this for? This workflow is ideal for businesses and developers using Voiceflow to power AI voice chatbots. It benefits teams that want to enhance chatbot functionality through integrations with platforms like Zendesk, Google Calendar, and Airtable. What problem is this workflow solving? The workflow addresses the need for seamless integration of chatbot interactions with backend systems. It automates customer service tasks such as ticket creation, meeting scheduling, and data reporting, reducing manual effort and enhancing efficiency. What does this workflow do? Customer Lookup:** Checks the database for existing customers and returns relevant details or a "NOT_FOUND" status. Zendesk Ticket Creation:** Automates the creation of support tickets for customer issues. Meeting Scheduling:** Integrates with Google Calendar to provide availability and schedule meetings. Transcript Reporting:** Aggregates interaction data and sends it to Airtable for analysis by the product team. Setup Configure your Voiceflow chatbot to connect to this workflow via a webhook. Set up the required integrations: Zendesk API: For ticket creation. Google Calendar API: For scheduling. Airtable API: For storing transcripts. Customize the workflow's nodes to match your use case, such as database fields or API endpoints. Deploy the workflow on your n8n instance and test the integrations. How to customize this workflow to your needs Adjust database queries to match your customer data schema. Modify the Zendesk ticket payload to include additional fields or custom formats. Update Google Calendar configurations for different scheduling requirements. Add or remove Airtable fields based on the product team's analysis needs. This template adheres to n8n’s submission guidelines, ensuring clarity, relevance, and broad applicability for users in customer service, product development, and automation.

📈 How it works This n8n workflow allows you to interact with Binance Spot Trading API directly to: Place Limit Buy and Limit Sell orders Place Market Buy and Market Sell orders Query account info* and *open orders** Cancel all open orders** for a specific symbol All requests are signed using Binance's HMAC SHA256 signature method for secure trading. ⚙️ Setup Steps Create Binance API Credentials in n8n: Go to Credentials > New Choose Binance API Add api_key and api_secret Save as Binance API Import this workflow into your n8n instance. Update default values: In Set Parameter nodes like LimitBuy Parameter, change: symbol (e.g. BTCUSDT) quantity, price as needed Run the workflow manually via the Execute workflow trigger. ✅ Notes Credential node is marked with instructions. HMAC signatures are automatically calculated before making each request. HTTP nodes are preconfigured for Binance API v3. 🔒 No API key or secret is included.

Description: The closest definition to this workflow is a cheaper Modular Version of Perplexity online API empowered by LLM models that outperform the Perplexity Lama Model. This flow provides a seamless way to conduct detailed web searches, extract data, and generate insightful reports based on real-time information. It provides a webhook-based flow that gets any search question and reports back the results via a multi-level web search analysis and domain-specific emulation of an agent to deliver an unbiased expert report. This Flow is Ideal for market research, competitive analysis, or any scenario where actionable, structured insights are needed. A more complete, step-by-step guide is provided within the workflow, ensuring you have all the details to set up and customize each component. This tool is designed to function similarly to Perplexity by performing semantic search, reranking, and follow-up queries. However, it offers a unique advantage—complete customization at every stage. Modify any part of the process, from query refinement to data extraction, allowing you to tailor the workflow to your specific needs. Key Features: AI-Powered Query Generation and Expert Emulation**: Uses Google Gemini to transform user queries into expert-level searches, providing accurate and context-aware results. Dual-Stage Semantic Search with Intelligent Reranking**: Performs an initial search, reranks results, and refines the query based on findings to conduct a second, more targeted search. Top-Result Data Extraction**: Extracts content from the top three results of each search, capturing relevant insights from six total sources. Customizable API Options**: Pre-configured with free APIs (Google Gemini, DuckDuckGo, and Article Extraction APIs) but easily adaptable to other APIs if preferred. Automated, Insightful Reporting**: Synthesizes data into a cohesive report, providing expert-level insights tailored to the user’s query. Instructions for API Setup: This workflow is designed to work with free-tier APIs, offering a cost-effective way to retrieve high-quality data. Here’s how to set up each API, with detailed instructions included in the workflow: Google Gemini API (for Query Generation and Analysis): Visit Google AI Studio and log in. Create a free API key under "Get API Key" → "Create API Key in New Project." The free tier includes up to 15 requests per minute, 1 million tokens per minute, and up to 1,500 requests per day. Brave Search API (for Web Search): To attain the free web search API tier from Brave, follow these steps: Visit api.search.brave.com Create an account Subscribe to the free plan (no charge) Navigate to the API Keys section Generate an API key. For the subscription type, choose "Free". Article Extraction API (for Content Extraction): Register on RapidAPI.com and subscribe to the Article Extraction API. The free plan allows up to 300 extractions per month. Enter your API key in each of the 6 extraction nodes for content retrieval. Alternative: In the workflow, we have provided the full instructions on how to replace the current flow with alternative API Keys and provided suggestions such as Scraper Tech API. Additional Tip: To use other APIs, you can generate a cURL request in RapidAPI’s playground, and then paste it into the HTTP Request node in n8n. This approach streamlines integration by automatically filling in headers and request details. Why Choose This Workflow? The Intelligent Online Web Researcher offers an all-in-one solution for complex, customizable online research. Unlike other tools that provide automated semantic search, this workflow is fully modifiable, allowing you to tailor each step, from the initial query and reranking to data extraction and reporting. With built-in instructions and a structure that’s easy to adapt, it’s ideal for commercial applications that require real-time, high-quality insights. Tags: Online Research, Web Search, Market Analysis, Web Search Automation, Data Extraction, Semantic Search, API Integration, Competitive Intelligence, Business Intelligence, Real-Time Reporting, Web Scrape, Data Crawler, Perplexity

🎶 Add liked songs to a monthly playlist > This Workflow is a port of Add saved songs to a monthly playlist from IFTTT. When you like a song, the workflow will save this song in a monthly playlist. E.g.: It's June 2024, I liked a song. The workflow will save this song in a playlist called June '24. If this playlist does not exist, the workflow will create it for me. ⚙ How it works Each 5 minutes, the workflow will start automatically. He will do 3 things : Get the last 10 songs you saved in the "Liked song" playlist (by clicking on the heart in the app) and save them in a NocoDB table (of course, the workflow avoid to create duplicates). Check if the monthly playlist is already created. Otherwise, the playlist is created. The created playlist is also saved in NocoDB to avoid any problems. Check if the monthly playlist contains all the song liked this month by getting them from NocoDB. If they are not present, add them one by one in the playlist. You may have a question regarding the need of NocoDB. Over the last few weeks/months, I've had duplication problems in my playlists and some playlists have been created twice because Spotify wasn't returning all the information but only partial information. Having the database means I don't have to rely on Spotify's data but on my own, which is accurate and represents reality. 📝 Prerequisites You need to have : Spotify API keys, which you can obtain by creating a Spotify application here: https://developer.spotify.com/dashboard. Create a NocoDB API token 📚 Instructions Follow the instructions below Create your Spotify API credential Create your NocoDB credential Populate all Spotify nodes with your credentials Populate all Spotify nodes with your credentials Enjoy ! If you need help, feel free to ping me on the N8N Discord server or send me a DM at "LucasAlt" Show your support Share your workflow on X and mention @LucasCtrlAlt Consider buying me a coffee 😉

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: 1. 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. 2. 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.