Synchronize your Google Sheets with Postgres
Sync your Google Sheets Data with your Postgres database table, requiring minimal adjustments. Follow these steps: Retrieve Data: Pull data from Google Sheets and PostgreSQL. Compare Datasets: Identify differences, focusing on new or updated entries. Update PostgreSQL: Apply changes to ensure both platforms mirror each other. Automate this process to regularly synchronize data. Before starting, grant necessary access to both Google Sheets and PostgreSQL, and specify the data details for synchronization. This streamlined workflow enhances data consistency across platforms. This example is a one-way synchronization from Google Sheets into your Postgres. With small adjustments, you can make it the other way around, or 2-way.
By BelaGoogle Maps business scraper & lead enricher with Bright Data & Google Gemini
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: ranjancse@gmail.com 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
By Ranjan DailataTransforming emails into podcasts
Transforming Emails into Podcasts 🎙️ Check out this channel for example. The n8n workflow described here aims to revolutionize the way users engage with promotional emails by converting them into entertaining audio podcasts. This innovative project leverages automation through n8n to streamline tasks and enhance user experience. Project Benefit 🎧🌟 The primary goal of this project is to transform "CATEGORY_PROMOTIONS" emails into engaging audio content. By converting text into speech, users can enjoy promotional material hands-free, making it easier to consume information while on the go or relaxing. The workflow consists of several key steps orchestrated seamlessly to deliver a delightful experience to users. How to Use the Workflow: Gmail trigger Node: Initiates the workflow by fetching "CATEGORY_PROMOTIONS" emails at regular intervals. The Gmail Trigger node in your N8N workflow is set to poll for new emails every minute and is configured to filter emails with the label "CATEGORY_PROMOTIONS" before triggering the workflow. Steps to Use Filters Inside the Gmail Trigger Node: Configure Gmail Trigger Node: Set "Poll Times" to "Every Minute" to check for new emails at regular intervals. Enable the "Simple" toggle if you want to simplify the node interface. Under "Filters", specify the label IDs you want to filter by. In this case, it's set to "CATEGORY_PROMOTIONS". Adjust any additional options as needed. // Configure Gmail Trigger node pollTimes: { item: [ { mode: "everyMinute" } ] }, simple: false, filters: { labelIds: [ "CATEGORY_PROMOTIONS" ] }, options: {} Save and Execute: Save your workflow and execute it to start monitoring your Gmail account for new emails with the specified label filter. By following these steps, your workflow will effectively trigger based on new emails that match the "CATEGORY_PROMOTIONS" label in your Gmail account. Get message content Node: Extracts the email content for processing. Summarization Chain Node: Generates concise summaries using advanced methods for better readability. Delete the unnecessary items Node: Removes irrelevant details from the email content. Text to Free TTS Node: Converts the summary text into speech using Free TTS technology. Convert from base64 to File Node: Transforms the audio data into a compatible file format. Merge Text with Audio Node: Combines the text and audio components seamlessly. Aggregate in same cell Node: Gathers all processed data for finalization. Send Message to Telegram Node: Dispatches the audio message along with a caption to a designated Telegram chat ID. By automating these tasks, the workflow ensures efficient communication and delivers content in a more engaging format, fostering a positive user experience. Configuration Instructions: The configuration of this workflow involves setting up the necessary nodes and establishing connections between them. Each node performs a specific function crucial to the overall operation of the workflow. Additionally, credentials need to be provided for accessing Gmail and OpenAI services to enable seamless data processing and summarization. Utilizing Text-to-Speech API 🎧 In addition to n8n automation, an external Text-to-Speech API plays a pivotal role in generating audio content from text data. By sending a POST request with JSON data containing the text and voice preferences, users can quickly receive audio files of the converted content. The API offers a straightforward interface for text-to-speech conversion, making it ideal for creating audio clips efficiently. To access this API, simply submit the desired text and voice selection to receive the generated speech audio file. The API endpoint can be accessed at https://tiktok-tts.weilnet.workers.dev/api/generation or through https://tiktokvoicegenerator.com/. In conclusion, this n8n workflow coupled with a Text-to-Speech API presents a powerful solution for transforming emails into captivating podcasts, enhancing user engagement and communication effectiveness. By embracing automation and innovative technologies, this project aims to improve user experience and streamline content delivery processes. 🌈✨🚀
By AlQaisiWordPress auto-blogging pro - content automation machine for SEO topics
The best content automation in the market! This advanced workflow not only creates and publishes SEO-optimized blog posts to your WordPress website but also backs up all content and images to a designated folder in your Google Drive. In addition, It generates a unique image for each chapter and a featured image for the overall article, and it automatically collects internal website links—seamlessly inserting them throughout each chapter and the entire article. This integrated approach enhances on-page SEO, improves navigation, and streamlines your content creation process, saving you time while ensuring your work is securely stored. How it works Triggers upon adding a new row to a Google Sheets. Generates a full blog post by writing content based on customizable parameters such as topic, target audience, length, style, and seed keyword. Generates and adds images for each chapter as well as a featured image for the article. Gathers internal website links and strategically embeds them within each chapter and throughout the article, boosting SEO and enhancing user navigation. Publishes the blog post directly to your WordPress website. Saves all content (blog post and images) to Google Drive, organizing them in a folder named after the blog post title. Unique features Full Automation: The workflow is designed to be 100% automated. Once imported and configured, it can run without manual intervention. Simple Activation: It can be easily triggered through the Google Spreadsheets interface. You simply add a new row to a Google Sheet. Customization Options: Offers a wide array of customization options, including topic, category, target audience, word count, number of chapters, length of introduction and conclusion, and writing style. It also allows for the inclusion of calls-to-action (CTAs) and company/product introductions. Automatic Content Saving: After writing a blog post, all content and images are automatically saved to Google Drive, preventing data loss. The folder is even named after the title of the blog post. SEO-Optimized Content: It's designed to create content optimized for SEO using seed keywords. AI Model Flexibility: It’s super easy to switch between different AI models through the Open Router node. Rate Limit Handling: Includes "Wait" nodes to avoid rate limits. Internal Link Limit: Limits the number of internal links to 20 by default. Set up steps Install the workflow template: Import the JSON file into your n8n instance. Connect the workflow to your accounts: This includes linking your WordPress website, Google Drive, and AI models (such as OpenAI GPT-4o). Configure the Google Sheet: Ensure your Google Sheet is set up to trigger the workflow upon adding a new row and that the input data is correctly formatted. Customize the workflow: Adjust parameters like topic, target audience, and writing style to match your specific content needs. Optimize prompts for best results. Test the workflow: Use low-cost AI models and image settings initially to ensure everything runs smoothly. Tailor Further as Needed: Modify workflow elements to align perfectly with your needs and content strategy.
By Daniel NgMedical Q&A chatbot for urology using RAG with Pinecone and GPT-4o
Medical Q&A Chatbot for Urology using RAG with Pinecone and GPT-4o This template provides an AI-powered Q&A assistant for the Urology domain using Retrieval-Augmented Generation (RAG). It uses Pinecone for vector search and GPT-4o for conversational responses. 🧠 Use Case This chatbot is designed for clinics or medical pages that want to automate question answering for Urology-related conditions. It uses a vector store of domain knowledge to return verified responses. 🔧 Requirements ✅ OpenAI API key (GPT-4o or GPT-4o-mini) ✅ Pinecone account with an active index ✅ Verified Urology documents embedded into Pinecone ⚙️ Setup Instructions Create a Pinecone vector index and connect it using the Pinecone credentials node. Upload Urology-related documents to embed using the Create Embeddings for Urology Docs node. Customize the chatbot system message to reflect your medical specialty. Deploy this chatbot on your website or link it with Telegram via the chat trigger node. 🛠️ Components chatTrigger: Listens for user messages and starts the workflow. Medical AI Agent: GPT-based agent guided by domain-specific instructions. RAG Tool Vector Store: Fetches relevant documents from Pinecone using vector search. Memory Buffer: Maintains conversation context. Create Embeddings for Urology Docs: Encodes documents into vector format. 📝 Customization You can replace the knowledge base with any other medical domain by: Updating the documents stored in Pinecone. Modifying the system prompt in the AI Agent node. 📣 CTA This chatbot is ideal for clinics, medical consultants, or educational websites wanting a reliable AI assistant in Urology.
By HoangSPScrape Web Data with Bright Data, Google Gemini and MCP Automated AI Agent
Disclaimer This template is only available on n8n self-hosted as it's making use of the community node for MCP Client. Who this is for? The Scrape Web Data with Bright Data and MCP Automated AI Agent workflow is built for professionals who need to automate large-scale, intelligent data extraction by utilizing the Bright Data MCP Server and Google Gemini. This solution is ideal for: Data Analysts - Who require structured, enriched datasets for analysis and reporting. Marketing Researchers - Seeking fresh market intelligence from dynamic web sources. Product Managers - Who want competitive product and feature insights from various websites. AI Developers - Aiming to feed web data into downstream machine learning models. Growth Hackers - Looking for high-quality data to fuel campaigns, research, or strategic targeting. What problem is this workflow solving? Manually scraping websites, cleaning raw HTML data, and generating useful insights from it can be slow, error-prone, and non-scalable. This workflow solves these problems by: Automating complex web data extraction through Bright Data’s MCP Server. Reducing the human effort needed for cleaning, parsing, and analyzing unstructured web content. Allowing seamless integration into further automation processes. What this workflow does? This n8n workflow performs the following steps: Trigger: Start manually. Input URL(s): Specify the URL to perform the web scrapping. Web Scraping (Bright Data): Use Bright Data’s MCP Server tools to accomplish the web data scrapping with markdown and html format. Store / Output: Save results into disk and also performs a Webhook notification. Setup Please make sure to setup n8n locally with MCP Servers by navigating to n8n-nodes-mcp Please make sure to install the Bright Data MCP Server @brightdata/mcp on your local machine. Sign up at Bright Data. Create a Web Unlocker proxy zone called mcp_unlocker on Bright Data control panel. Navigate to Proxies & Scraping and create a new Web Unlocker zone by selecting Web Unlocker API under Scraping Solutions. In n8n, configure the Google Gemini(PaLM) Api account with the Google Gemini API key (or access through Vertex AI or proxy). In n8n, configure the credentials to connect with MCP Client (STDIO) account with the Bright Data MCP Server as shown below. Make sure to copy the Bright Data APITOKEN within the Environments textbox above as APITOKEN=<your-token>. Update the LinkedIn URL person and company workflow. Update the Webhook HTTP Request node with the Webhook endpoint of your choice. Update the file name and path to persist on disk. How to customize this workflow to your needs Different Inputs: Instead of static URLs, accept URLs dynamically via webhook or form submissions. Outputs: Update the Webhook endpoints to send the response to Slack channels, Airtable, Notion, CRM systems, etc.
By Ranjan DailataNotify on Telegram when a new order is created in WooCommerce 📦
📦 Send Telegram Notifications for New WooCommerce Orders This workflow automatically sends a Telegram notification when an order status in WooCommerce changes to "Processing." Perfect for online store owners who want instant updates on order fulfillment. ⚙️ Set Up Telegram Alerts for WooCommerce Orders Configure WooCommerce Webhook to trigger on order updates. Create a Telegram Bot and obtain the API token. Set Up Telegram Credentials in n8n. Configure the Telegram Node with your chat ID. Activate and Test the workflow by placing a new order. 💡 Notes You can customize the message format in the 🖋️ Design Message Template node to include additional order details. Contact me on [Telegram]: https://t.me/amir676080 Message structure includes the following details 🆔 Order Number: 11234 👦🏻 Customer Name: John Doe 💵 Amount: 299.99 USD 📅 Order Date: ➖ 25th November 2024 at 14:42 🏙 City: New York 📞 Phone: +1 555-1234 ✍🏻 Order Note: Fast delivery requested 📦 Ordered Products: 🔹 Wireless Earbuds (2 items) 📝 Type: Premium Sound Edition Contact me on [Telegram]: https://t.me/amir676080
By AmirHossein MnasouriZadeCreate a private document Q&A system with Llama3, Postgres, Qdrant and Google Drive
⚙️ How It Works: LocalRAG.AI ⚠️ Note: This system only works for self-hosted n8n instances. It will not function on n8n.cloud or other remote setups. LocalRAG.AI is a private, on-prem AI assistant that uses your own documents to answer questions intelligently. It combines LangChain, Ollama, Qdrant, and Postgres into a powerful AI pipeline — all running locally for maximum data privacy. 🔄 What It Does Monitors Your Google Drive Folders for new or updated files. Downloads the file, extracts the text, and prepares it. Generates Embeddings using your local Ollama model (e.g., LLaMA 3). Stores them in Qdrant, your local vector database. During a chat, it: Uses vector search to retrieve relevant chunks. Combines them with chat history stored in Postgres. Responds via a LangChain AI agent using your local model. 🛠️ Setup Steps (Self-hosted Only) Install and Self-host n8n (e.g., via Docker). Set up your Ollama instance locally and load your desired LLM (e.g., llama3). Deploy Qdrant locally for vector storage. Connect a Postgres DB to store chat history. Create and import the workflow in n8n. Authenticate Google Drive to monitor folders. Connect credentials for Ollama, Qdrant, Postgres in the n8n workflow. Start chatting through the Webhook Trigger or custom UI. 🧠 Perfect For: Research teams handling confidential data Internal documentation Q&A AI chatbots that don’t rely on OpenAI or cloud
By David OlusolaConversational travel booker: Automate flight & hotel reservations with GPT-3.5
This guide walks you through setting up an AI-driven workflow to automate flight and hotel reservation processes using a conversational travel booking system. The workflow accepts booking requests, processes them via APIs, and sends confirmations, enabling a seamless travel booking experience. What’s the Goal? Automatically accept and process booking requests for flights and hotels via HTTP POST. Use AI to understand natural language requests and route them to appropriate data processors. Search for flights and hotels using external APIs and process booking confirmations. Send confirmation emails and return structured booking data to users. Enable an automated system for efficient travel reservations. By the end, you’ll have a self-running system that handles travel bookings effortlessly. Why Does It Matter? Manual booking processes are time-consuming and prone to errors. This workflow offers: Zero Human Error: AI ensures accurate request parsing and booking processing. Time-Saving Automation: Automates the entire booking lifecycle, boosting efficiency. Seamless Confirmation: Sends automated emails and responses without manual intervention. Enhanced User Experience: Provides a conversational interface for bookings. Think of it as your reliable travel booking assistant that keeps the process smooth and efficient. How It Works Here’s the step-by-step flow of the automation: Step 1: Trigger the Workflow Webhook Trigger: Accepts incoming booking requests via HTTP POST, initiating the workflow. Step 2: Parse the Request AI Request Parser: Uses AI to understand natural language booking requests (e.g., flight or hotel) and extracts relevant details. Step 3: Route Booking Type Booking Type Router: Determines whether the request is for a flight or hotel and routes it to the respective data processor. Step 4: Process Flight Data Flight Data Processor: Handles flight-specific data and prepares it for the search API. Step 5: Search Flight API Flight Search API: Searches for available flights based on parameters (e.g., https://api.aviationstack.com) and returns results. Step 6: Process Hotel Data Hotel Data Processor: Handles hotel-specific data and prepares it for the search API. Step 7: Search Hotel API Hotel Search API: Searches for available hotels based on parameters (e.g., https://api.booking.com) and returns results. Step 8: Process Flight Booking Flight Booking Processor: Processes flight bookings and generates confirmation details. Step 9: Process Hotel Booking Hotel Booking Processor: Processes hotel bookings and generates confirmation details. Step 10: Generate Confirmation Message Confirmation Message Generator: Creates structured confirmation messages for the user. Step 11: Send Confirmation Email Send Confirmation Email: Sends booking confirmation via email to the user. Step 12: Send Response Send Response: Returns structured booking data to the user, completing the workflow. How to Use the Workflow? Importing the workflow in n8n is a straightforward process. Follow these steps to import the Conversational Travel Booker workflow: Download the Workflow: Obtain the workflow file (e.g., JSON export from n8n). Open n8n: Log in to your n8n instance. Import Workflow: Navigate to the workflows section, click "Import," and upload the workflow file. Configure Nodes: Adjust settings (e.g., API keys, webhook URLs) as needed. Execute Workflow: Test and activate the workflow to start processing bookings. Requirements n8n account and instance setup. Access to flight and hotel search APIs (e.g., Aviationstack, Booking.com). Email service integration for sending confirmations. Webhook URL for receiving booking requests. Customizing this Workflow Modify the AI Request Parser to handle additional languages or booking types. Update API endpoints in Flight Search API and Hotel Search API nodes to match your preferred providers. Adjust the Send Confirmation Email node to include custom email templates or additional recipients. Schedule the Webhook Trigger to align with your business hours or demand peaks.
By Oneclick AI SquadAuto-generate tech news blog posts with NewsAPI & Google Gemini to WordPress
WordPress Daily News Digest Generator Overview: This automation automatically fetches trending tech news every morning, uses AI to create engaging blog posts from each article, and publishes them directly to your WordPress site. What it does: Fetches top 10 US technology news stories every day at 8 AM via NewsAPI Splits articles into individual items for processing Processes each article through a loop system AI creates expanded, engaging blog posts (600-800 words) from each news article Parses AI response to extract clean titles and content Publishes individual blog posts to WordPress automatically Setup Required: NewsAPI Configuration Get free API key from newsapi.org (1,000 requests/day free) Replace YOURAPIKEY in the HTTP Request URL with your actual key Customize country/category parameters in URL if needed WordPress Connection Configure WordPress credentials in the "Publish to WordPress" node Enter your WordPress site URL, username, and password/app password AI Configuration Set up Google Gemini API credentials Connect the Gemini model to the "AI News Summarizer" node Customization Options Publishing Schedule: Modify schedule trigger (default: daily 8 AM) News Sources: Change country, category, or pageSize in NewsAPI URL Content Style: Adjust AI system message for different writing tones Post Status: Change from "publish" to "draft" for manual review Testing Run workflow manually to test all connections Verify news articles are fetched correctly Check that blog posts appear properly on your WordPress site Features: Automatic daily content creation AI-generated unique titles and expanded content Loop processing for multiple articles per day Duplicate content filtering (removes incomplete articles) SEO-optimized blog post formatting Automatic tagging and categorization Customization: Change news categories (technology, business, science, etc.) Adjust posting frequency (hourly, twice daily, etc.) Modify AI prompts for different writing styles Add custom categories and tags Change article limits (currently 5 articles max) Need Help? For n8n coaching or one-on-one consultation
By David OlusolaReceive updates on an order created in Shopify
Companion workflow for Shopify Trigger node docs
By amudhanBulk resume screening & JD matching with GPT-4 for HR teams
TalentFlow AI – Bulk Resume Screening with JD Matching [](https://www.youtube.com/watch?v=MD1krFvVKdU) Automatically extract, evaluate, and shortlist multiple resumes against a selected job description using GPT-4. This smart, scalable n8n workflow helps HR/TA teams streamline hiring decisions while keeping results structured, auditable, and easy to share. --- 👤 Who’s it for This workflow is designed for: HR or Talent Acquisition (TA) teams handling multiple candidates per role Recruiters who want AI-assisted resume screening to save time and reduce bias Organizations that want to automatically log evaluations and keep stakeholders updated in real-time via Slack or Sheets --- ⚙️ How it works / What it does HR/TA uploads multiple candidate resumes and selects a job role Each resume is: Uploaded to Google Drive Parsed with GPT-4 to extract structured profile data The job description for the selected role is: Retrieved from Google Sheets Downloaded from Drive and parsed The profile + JD are sent to an AI agent to generate: Fit score Strengths & gaps Final recommendation Results are: Appended to the evaluation tracking sheet Optionally shared with the hiring team on Slack Used to trigger emails to qualified or unqualified candidates --- 🛠️ How to set up Clone or import the workflow into your n8n instance Connect your integrations: Google Sheets (positions & evaluation form) Google Drive (CV & JD folders) OpenAI API (GPT-4) Slack (for notifications) (Optional) SendGrid or SMTP for email notifications Update Google Sheets structure: Positions sheet: maps Job Role → JD file link Evaluation form: stores evaluation results Prepare Drive folders: /cv folder for uploaded resumes /jd folder for job description PDFs --- 📋 Requirements ✅ n8n (hosted or self-hosted) ✅ OpenAI GPT-4 account (used in Profile & JD evaluator agents) ✅ Google Drive + Google Sheets access ✅ Slack workspace + bot token (Optional) SendGrid or email credentials for candidate follow-up --- 🎨 How to customize the workflow Change the fit score threshold in the Candidate qualified? node Edit Slack message content/formatting to match your company tone Add additional candidate metadata to Sheets or Slack messages Use a webhook trigger to integrate with your ATS or job board Swap GPT-4 with Claude or Gemini if you prefer other AI services Expand to include multi-position batch screening logic --- Happy Hiring! 🚀 Automated with love using n8n
By Trung Tran