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What it does The workflow is a simple yet efficient way to automate the process of indexing your website on Google using the Google Indexing API. How it works It works by extracting information from your sitemap, converting it into a JSON file, and looping through each URL to submit it for indexing. Here's a brief rundown of the workflow: The workflow can be triggered manually via the "Execute Workflow" button or scheduled to run at a specific time using the "Schedule Trigger" node. The sitemap of your website is fetched using the "sitemap_set" node with a HTTP Request to the sitemap URL. This XML sitemap is then converted into a JSON file using the "sitemap_convert" node. The "sitemap_parse" node splits the JSON file into individual URLs. The "url_set" node then prepares each URL to be sent to the Google Indexing API. A loop is created using the "loop" node to process each URL individually and make a POST request to Google Indexing API indicating that the URL has been updated. If the POST request is successful and the URL has been updated, the workflow waits for 2 seconds before moving to the next URL. In case the daily limit for the Google Indexing API is reached (200/day by default), an error message is triggered using the "Stop and Error" node. Before you use the workflow Activate the indexing API Create an account with Google Cloud Platform > Console and then create a new project Search for the Indexing API in the Library Activate the API Create a Service Account and get credentials Open the Service accounts page. If prompted, select a project. Click add Create Service Account, enter a name and description for the service account. You can use the default service account ID, or choose a different, unique one. When done click Create. On the Grant users access to this service account screen, scroll down to the Create key section. Click add Create key. In the side panel that appears, select the JSON format Click Create. Your new public/private key pair is generated and downloaded to your machine. Open the file and copy the private key. Add the credentials in the url_index node Add the user as owner of the site Beware, for each site you need to add the user as a owner like this: Set your sitemap Open the sitemap_set node and add the url to your sitemap. Now you should be able to ensure that Google is always up-to-date with the latest content on your website, improving your website's visibility and SEO rankings, have fun!

How it works It’s very important to come prepared to Sales calls. This often means a lot of manual research about the person you’re calling with. This workflow delivers the latest social media activity (LinkedIn + X) for businesses you are about to interact with each day. Scans Your Calendar**: Each morning, it reviews your Google Calendar for any scheduled meetings or calls with companies based on each attendee email address. Fetches Latest Posts**: For each identified company, it fetches recent LinkedIn and X posts Delivers Insight**s: You receive personalized emails via Gmail, each dedicated to a company you’re meeting with that day, containing a reminder of the meeting, list of posts categorized by the social media platform, and direct links to posts. Setup steps The workflow requires you to have the following accounts set up in their respective nodes: Google Calendar GMail Clearbit Besides those, you will need an account on the RapidAPI platform and subscribe to the following APIs: Fresh LinkedIn Profile Data Twitter Email example

How it works It’s very important to come prepared to Sales calls. This often means a lot of manual research about the person you’re calling with. This workflow delivers a summary of the latest social media activity (LinkedIn + X) for businesses you are about to interact with each day. Scans Your Calendar**: Each morning, it reviews your Google Calendar for any scheduled meetings or calls with companies based on each attendee email address. Fetches Latest Posts**: For each identified company, it fetches recent LinkedIn and X posts and summerizes them using AI to deliver a qucik overview for a busy sales rep. Delivers Insights**: You receive personalized emails via Gmail, each dedicated to a company you’re meeting with that day, containing a reminder of the meeting and a summary of company's recent social media activity. Setup steps The workflow requires you to have the following accounts set up in their respective nodes: Google Calendar GMail Clearbit OpenAI Besides those, you will need an account on the RapidAPI platform and subscribe to the following APIs: Fresh LinkedIn Profile Data Twitter Email example

Campaign tracking is pivotal; it enables marketers to evaluate the efficacy of various strategies and channels. UTM parameters are particularly essential as they provide granular details about the source, medium, and campaign effectiveness. However, when this data is not automatically integrated into a centralized system, it can become a tedious and error-prone process to manually collate and analyze it. Retrieving UTM data from Shopify and storing it in Baserow enables oy to do more with this data. For example you could build a campaign database in Baserow and automatically add campaign revenue to it using this workflow template. This template will help you: Automatically retrieve UTM parameters from Shopify orders using the Shopify Admin API Process marketing data through n8n Store this data into Baserow, providing you with a dynamic, responsive base for campaign tracking and decision-making This template will demonstrate the follwing concepts in n8n: use the Schedule trigger node use the GraphQL node to call the Shopify Admin API split larger incoming datasets into n8n items with the Split node transform the data structure with the Set node control flow with the If node store data in Baserow with the Baserow node How to get started? Create a custom app in Shopify get the credentials needed to connect n8n to Shopify This is needed for the Shopify Trigger Create Shopify Acces Token API credentials n n8n for the Shopify trigger node Create Header Auth credentials: Use X-Shopify-Access-Token as the name and the Acces-Token from the Shopify App you created as the value. The Header Auth is neccessary for the GraphQL nodes. You will need a running Baserow instance for this. You can also sign up for a free account at https://baserow.io/ Please make sure to read the notes in the template. For a detailed explanation please check the corresponding video: https://youtu.be/VBeN-3129RM

What is this workflow doing? This simple workflow is pulling the latest Euro foreign exchange reference rates from the European Central Bank and responding expected values to an incoming HTTP request (GET) via a Webhook trigger node. Setup no authentication** needed the workflow is ready to use test** the workflow template by hitting the test workflow button and calling the URL in the webhook node optional: choose your own Webhook listening path in the Webhook trigger node Usage There are two possible usage scenarios: get all Euro exchange rates as an array of objects get only a specific currency exchange rate as a single object All available rates Using the HTTP query ?foreign=USD (where USD is one of the available currency symbols) will provide only that specificly asked rate. Response example: {"currency":"USD","rate":"1.0852"} Single exchange rate If no query is provided, all available rates are returned. Response example: [{"currency":"USD","rate":"1.0852"},{"currency":"JPY","rate":"163.38"},{"currency":"BGN","rate":"1.9558"},{"currency":"CZK","rate":"25.367"},{"currency":"DKK","rate":"7.4542"},{"currency":"GBP","rate":"0.85495"},{"currency":"HUF","rate":"389.53"},{"currency":"PLN","rate":"4.3053"},{"currency":"RON","rate":"4.9722"},{"currency":"SEK","rate":"11.1675"},{"currency":"CHF","rate":"0.9546"},{"currency":"ISK","rate":"149.30"},{"currency":"NOK","rate":"11.4285"},{"currency":"TRY","rate":"33.7742"},{"currency":"AUD","rate":"1.6560"},{"currency":"BRL","rate":"5.4111"},{"currency":"CAD","rate":"1.4674"},{"currency":"CNY","rate":"7.8100"},{"currency":"HKD","rate":"8.4898"},{"currency":"IDR","rate":"16962.54"},{"currency":"ILS","rate":"3.9603"},{"currency":"INR","rate":"89.9375"},{"currency":"KRW","rate":"1444.46"},{"currency":"MXN","rate":"18.5473"},{"currency":"MYR","rate":"5.1840"},{"currency":"NZD","rate":"1.7560"},{"currency":"PHP","rate":"60.874"},{"currency":"SGD","rate":"1.4582"},{"currency":"THB","rate":"38.915"},{"currency":"ZAR","rate":"20.9499"}] Further info Read more about Euro foreign exchange reference rates here.

How to scrap emails from websites This workflow shows how to quickly build an Email scraping API using n8n. Email marketing is at the core of most marketing strategies, be it content marketing, sales, etc. As such, being able to find contacts in bulk for your business on a large scale is key. There are available tools available in the market that can do this, but most are premium; why not build a custom one with n8n? Usage The workflow gets the data from a website and performs an extraction based on the date around on the website Copy the webhook URL to your browser Add a query parameter eg ?Website=https://mailsafi.com . This should give you a URL like this {{$n8nhostingurl/webhook/ea568868-5770-4b2a-8893-700b344c995e?Website=https://mailsafi.com Click on the URL and wait for the extracted email to be displayed. This will return the email address on the website, or if there is no email, the response will be "workflow successfully executed." Make sure to use HTTP:// for your domains Otherwise, you may get an error.

Use Case This workflow is beneficial when you're automatically adding new leads to your Pipedrive CRM. Usually, you'd have to manually review each lead to determine if they're a good fit. This process is time-consuming and increases the chances of missing important leads. This workflow ensures every new lead is promptly evaluated upon addition. What this workflow does The workflow runs every 5 minutes. On every run, it checks your new Pipedrive leads and enriches them with Clearbit. It then marks items as enriched and checks if the company of the new lead matches certain criteria (in this case if they are B2B and have more than 100 employees) and sends a Slack alert to a channel for every match. Pre Conditions You must have Pipedrive, Clearbit, and Slack accounts. You also need to set up the custom fields Domain and Enriched at in Pipedrive. Setup Go to Company Settings -> Data fields -> Organization and add Domain as a custom field Go to Company Settings -> Data fields -> Leads and add Enriched at as a custom date field Add your Pipedrive, Clearbit and Slack credentials. Fill the setup node below. To get the ID of your custom domain fields, simply run the Show only custom organization fields and Show only custom lead fields nodes below and copy the keys of your domain, and enriched at fields. How to adjust this workflow to your needs Modify the criteria to suit your definition of an interesting lead. If you only want to focus on interesting leads in Pipedrive, add a node that archives all others. This workflow was built using n8n version 1.29.1

Use case This workflow automatically turns any RSS feed into a newsletter. It send an email every time a new post is published to an RSS feed in the last hour. I have been using this personally to follow Derek Sivers and Anil Dash, who don't have newsletters. Check them out 😉 How to setup Add your email and email creds Add the RSS feed URLs you want to follow How to adjust this template Add the feeds you want to follow. It does not have to be just email. Why not get a telegram message? Or Slack message? Ah the power of n8n 🚀

Use Case Track all Linear tickets in Google sheets. Useful if you want to do some custom analysis but don't want to pay for Linear's Plus features (Linear Insights) or that it does not cover. Setup Add Linear API header key Add Google sheets creds Update which teams to get tickets from in Graphql Nodes Update which Google Sheets page to write all the tickets to You only need to add one column, id, in the sheet. Google Sheets node in automatic mapping mode will handle adding the rest of the columns. Set any custom data on each ticket Activate workflow 🚀 How to adjust this template Set any custom fields you want to get out of this, that you can quickly do in n8n.

How it works This template takes a YouTube video ID and identifies potentially engaging moments based on the intensity of specific timestamps 👇 Ideal for vloggers and YouTube content creators, it serves as a foundation for various automations to streamline content calendars or highlight popular moments in your videos. You can leverage it for: Automatic processes to analyze YouTube videos and create sizzle reels or clips for social media, particularly effective for microcontent strategies like those endorsed by Gary Vee. Instant alerts via Slack, Telegram, Email, or WhatsApp when significant moments occur in your videos. Utilizing transcripts of these moments with AI to refine content ideas or brainstorm chatbots in your editorial workflow. Example response from the Workflow-as-an-API A GET request to {your instance URL}/webhook/youtube-engaging-moments-extractor?ytID=IZsQqarWXtYy returns 👇 The workflow generates multiple moments; the screenshot above shows a truncated version. Not all videos contain timestamp intensity data, the workflow handles this case as well 👇 How to use Import the template into your n8n workspace or self-hosted instance, then activate the workflow. Open the Webhook trigger node and copy the Production URL. In a web browser or any tool capable of consuming HTTP Requests (e.g., native code, Bubble app, n8n workflow, another automation tool, Postman, etc.), pass along the URL parameter ?ytID={youtube video ID} when invoking the API endpoint. Your URL should resemble something like https://acme.app.n8n.cloud/webhook/youtube-engaging-moments-extractor?ytID=IZsQqarWXtYy. Keep in mind This workflow relies on an unofficial YouTube API graciously hosted for free by the folks at lemnoslife.com. It's not recommended for high-volume production usecases.

This workflow is aimed at generating keywords for SEO and articles To get started, you need to use the workflow as it is. You just call the webhook URL with a query parameter as q={{ $keywords}} For example, you can call it using ?q=keyword research This will give you a list of keywords back as an array. This system can be used by SEO pros, content marketers and also social media marketers to generate relevant keywords for their user needs

With this workflow you get a fully automated AI powered Support-Agent for your WooCommerce webshop. It allows customers to request information about things like: the status of their order the ordered products shipping and billing address current DHL shipping status How it works The workflow receives chat messages from an in a website integrated chat. For security and data-privacy reasons, does the website transmit the email address of the user encrypted with the requests. That ensures that user can just request the information about their own orders. An AI agent with a custom tool supplies the needed information. The tool calls a sub-workflow (in this case, in the same workflow for convenience) to retrieve the required information. This includes the full information of past orders plus the shipping information from DHL. If otherr shipping providers are used it should be simple to adjust the workflow to query information from other APIs like UPS, Fedex or others.

Who this template is for This template is for every engineer who wants to automate their code reviews or just get a 2nd opinion on their PR. How it works This workflow will automatically review your changes in a Gitlab PR using the power of AI. It will trigger whenever you comment with +0 to a Gitlab PR, get the code changes, analyze them with GPT, and reply to the PR discussion. Set up Steps Set up webhook of note_events in Gitlab repository (see here on how to do it) Configure ChatGPT credentials Note "+0" in MergeRequest to trigger automatic review by ChatGPT

This n8n workflow template allows you to write WordPress posts by just providing a few keywords. It uses AI technology to write the text and to create the post's featured image. The text includes an introduction, chapters, and conclusions. Each chapter is written independently and this allows you to create also very long articles. The workflow uses technologies provided by Open AI: Chat GPT for the text and Dall-E for the image. I suggest reviewing the created posts before publishing them on your WordPress website. The article generation might take some minutes as each chapter is created independently. Features Easy to use:** Easy web interface to start the generation of the WordPress post AI-powered:** Text and image generation is done by artificial intelligence Long-text ready:** Possibility to create very long articles Configurable:** Possibility to provide as many keywords as you want, to choose the number of chapters and the length of the article Plugs into your WordPress:** Easily integrates with your WordPress website Tweak it as you want:** Fine-tune the Open AI prompts and the workflow as you want Workflow Steps User form:** An n8n form is used to trigger the post creation Settings:** This node is used to set your WordPress URL (which is used later in the workflow) Article structure:** First AI action that writes the introduction, the conclusions, and the chapter structure. Data check:** Check that the data provided by the AI is valid Chapters split/Chapters text:** Splits the data for each chapter in a separate item and generates each chapter's text with AI Content preparation:** Prepares the text for posting merging the introduction, the chapters, and the conclusions. Adds some basic HTML formatting Draft on WordPress:** Creates the draft post on WordPress Featured image:** Creates a featured image and adds it to the post on WordPress User feedback:** Sends a feedback to the user on the n8n form Getting Started To deploy and use this template: Import the workflow into your n8n workspace Set your WordPress URL in the wordpress_url field in the "Settings" node. Include the slash (/) at the end of the URL Set up your Open AI n8n credentials by following this guide. The Open AI credentials are used by the Open AI nodes ("Create post title and structure", "Create chapters text", and "Generate featured image") Set up your WordPress n8n credentials by following this guide. The WordPress credentials are used by the WordPress and HTTP Request nodes ("Post on Wordpress", "Upload media", and "Set image ID for the post"). Pay attention that the "Password" in the WordPress credentials is not the user's password by the Application Password How use the workflow to create a WordPress post Activate the workflow Open the "Form" node and copy the "Production URL". This is the public URL of the form to AI-write the post Open the URL in a browser and fill in the form Wait a few minutes till you get the feedback in the form that the post was created Go to WordPress and check the newly created draft post. Review and publish your post!

This workflow uses AI to analyze the content of every new message in Gmail and then assigns specific labels, according to the context of the email. Default configuration of the workflow includes 3 labels: „Partnership” - email about sponsored content or cooperation, „Inquiry” - email about products, services, „Notification” - email that doesn't require response. You can add or edit labels and descriptions according to your use case. 🎬 See this workflow in action in my YouTube video about automating Gmail. How it works? Gmail trigger performs polling every minute for new messages (you can change the trigger interval according to your needs). The email content is then downloaded and forwarded to an AI chain. 💡 The prompt in the AI chain node includes instructions for applying labels according to the email content - change label names and instructions to fit your use case. Next, the workflow retrieves all labels from the Gmail account and compares them with the label names returned from the AI chain. Label IDs are aggregated and applied to processed email messages. ⚠️ Label names in the Gmail account and workflow (prompt, JSON schema) must be the same. Set up steps Set credentials for Gmail and OpenAI. Add labels to your Gmail account (e.g. „Partnership”, „Inquiry” and „Notification”). Change prompt in AI chain node (update list of label names and instructions). Change list of available labels in JSON schema in parser node. Optionally: change polling interval in Gmail trigger (by default interval is 1 minute). If you like this workflow, please subscribe to my YouTube channel and/or my newsletter.

Introduction: Streamline your fundamental stock analysis process with AI-powered automation. By harnessing the power of SEC 10K reports - comprehensive documents required by the SEC containing vital company information - this template automates the analysis workflow. From planning by a Senior Research Analyst to execution by five Research Analysts and final review by a Senior Editor, this template takes an AI persona approach to compose the report that includes an overview of the business, strategy, SWOT (Strengths, Weaknesses, Opportunities, and Threads) analysis, near term catalysts, and top risks. Additionally, this template allows you to control the length and detail of the report generated. How it works There are three personas in the workflow: Senior Research Analyst** is the first part of the workflow. They are responsible for planning the work for the rest of the team. Squad of Research Analysts** is the second part of the workflow. They execute the plan created. Senior Editor** is the third part of the workflow. They polish the draft report and send it to publish This template uses a custom tool that is able to answer the SEC 10K questions from the Research team. Setup steps Setup the Stock Q&A Workflow for the company you want to analyze using this template Customize the setup node by specifying the company to analyze Customize the publish step by specifying the file name in the Google docs node Credit Inspired by Guilio's template

🚀 Supercharge Your Website Indexing with This Powerful n8n Workflow! 🌐 Google page indexing too slow? Tired of manually clicking through each page in the Google Search Console? 😴 Say goodbye to that tedious process and hello to automation with this n8n workflow! 🎉 **NB: this workflow was tested with sitemap.xml generated by Ghost CMS and WordPress. Reach out to Eduard if you need help adapting this workflow to your specific use-case!** ⚙️ How this automation works 📅 The workflow runs on a schedule or when you click "Test workflow". 🌐 It fetches the website's primary sitemap.xml and extracts all the content-specific sitemaps (this is a typical structure of the sitemap). 📑 Each content-specific sitemap is then parsed to retrieve the individual page data. 🔄 The extracted page data is converted to JSON format for easy manipulation. 🗃️ The lastmod (last modified date) and loc (page URL) fields are assigned to each page entry to ensure compliance with the Sitemap protocol. 🔀 The page entries are sorted by the lastmod field in descending order (newest to oldest). 🔁 The workflow then loops over each page entry and performs the following steps: 🔍 Checks the URL metadata in the Google Indexing API. ✅ If the page is new or has been updated since the last indexing request, it sends a request to the Google Indexing API to update the URL. ⏳ Wait a sec and move on with the next page. 🌟 Benefits ⏰ Save time by automating the indexing process. 🎯 Ensure all your website pages are consistently indexed by Google. 🚀 Improve your website's visibility and search engine rankings. 🛠️ Customize the workflow to fit your specific CMS and requirements. 🔧 Getting started To start using this powerful n8n workflow, follow these steps: ☑️ Make sure to verify the website ownership in the Google Search Console. 👨‍💻 Import the workflow JSON into your n8n instance. Edit the Get sitemap.xml node and update the URL with your website's valid sitemap.xml 🔑 Set up the necessary credentials for the Google Indexing API. 🎚️ Adjust the schedule trigger to run the workflow at your desired frequency. 🎉 Sit back and let the workflow handle the indexing process for you! Ready to take your website indexing to the next level? 🚀 Try this workflow now and see the difference it makes! 😊 ⚠️ IMPORTANT NOTE 1 Need help with connecting Google Cloud Platform to n8n? Check out our article on connecting Google Sheets to n8n. The process is mainly the same. When activating Google APIs, make sure to add Web Search Indexing API. Also, in the credential page of n8n, add the https://www.googleapis.com/auth/indexing scope: Check out Yulia's page for more n8n workflows! ⚠️ IMPORTANT NOTE 2 Free Google Cloud Platform account allows (re)indexing only 200 pages per day. If your website has more, then the workflow will automatically fail on quota limit ⛔. Next day it will skip the previously added items and continue with remaining pages. Example:* Assuming you have a free Google account, 500 pages on your website and they don't change for 3 days: On the first day 200 pages will be added for indexing and the workflow will fail due to quota limits. On the second day, the workflow will check 200 pages again and skip them (because the date of re-indexing is later then the page last modified date). The next 200 pages will be added to indexing. Workflow will fail again due to quota limits. On the third day 400 pages will be checked and skipped, the last 100 pages will be added for indexing and the workflow finishes successfully.

The template allows to make Dropcontact batch requests up to 250 requests every 10 minutes (1500/hour). Valuable if high volume email enrichment is expected. Dropcontact will look for email & basic email qualification if first_name, last_name, company_name is provided. +++++++++++++++++++++++++++++++++++++++++ Step 1: Node "Profiles Query" Connect your own source (Airtable, Google Sheets, Supabase,...) the template is using Postgres by default. Note I: Be careful your source is only returning a maximum of 250 items. Note II: The next node uses the next variables, make sure you can map these from your source file: first_name last_name website (company_name would work too) full_name (see note) Note III: This template is using the Dropcontact Batch API, which works in a POST & GET setup. Not a GET request only to retrieve data, as Dropcontact needs to process the batch data load properly. +++++++++++++++++++++++++++++++++++++++++ Step 2: Node "Data Transformation" Will transform the input variables in the proper json format. This json format is expected from the Dropcontact API to make a batch request. "full_name" is being used as a custom identifier to update the returned email to the proper contact in your source database. To make things easy, use a unique identiefer in the full_name variable. +++++++++++++++++++++++++++++++++++++++++ Step3: Node: "Bulk Dropcontact Requests". Enter your Dropcontact credentials in the node: Bulk Dropcontact Requests. +++++++++++++++++++++++++++++++++++++++++ Step4: Connect your output source by mapping the data you like to use. +++++++++++++++++++++++++++++++++++++++++ Step5: Node: "Slack" (OPTIONAL) Connect your slack account, if an error occur, you will be notified. TIP: Try to run the workflow with a batch of 10 (not 250) as it might need to run initially before you will be able to map the data to your final destination. Once the data fields are properly mapped, adjust back to 250.

How it works: The workflow starts by sending a request to a website to retrieve its HTML content. It then parses the HTML extracting the relevant information The extracted data is storted and converted into a CSV file. The CSV file is attached to an email and sent to your specified address. The data is simultaneously saved to both Google Sheets and Microsoft Excel for further analysis or use. Set-up steps: Change the website to scrape in the "Fetch website content" node Configure Microsoft Azure credentials with Microsoft Graph permissions (required for the Save to Microsoft Excel 365 node) Configure Google Cloud credentials with access to Google Drive, Google Sheets and Gmail APIs (the latter is required for the Send CSV via e-mail node).

How it works This workflow reads a list of URLs every 15 minutes, and sends an HTTP request to every URL on the list. Set up steps Schedule the workflow to run at your desired frequency (default is every 15 minutes). Add your desired URLs to the list. The list should be in the same format as the image below (Don't forget to have single quotes around every URL in the list, and separate each one with a comma!): Turn the workflow ON. Ideas to customize the workflow for your own use cases: Change the HTTP method Add headers Add a request body

This is a very simple workflow that lets you subscribe to any github repository for the latest release (using n8n as example). How it works: daily poll to Github repository for release for latest (stable) version of n8n parses the content to HTML sends a gmail Setup steps: add your gmail credentials (or use other email node of choice) change the url to the right Github repository you want to check regularly change the To email address to the email that you want to receive the updates for Feedback & Questions If you have any questions or feedback about this workflow - Feel free to get in touch at ria@n8n.io

Who is this template for? This workflow template is designed for everyone with a Gmail address, who wants to forward all Netflix emails, including temporary login codes, to friends and family effortlessly. How it works Scans your Gmail inbox every minute for new e-mails from Netflix Forwards all Netflix e-mails to all desired e-mail addresses via the e-mail provider Mailjet Setup Steps Connect your Google Mail Account to n8n following the official n8n instructions Add all recipients you want to the recipients array at the "Set all recipients" node. Create and connect your Mailjet Account to n8n following the official n8n instructions. Note: You cannot use an Gmail e-mail address as the sender address, as mailjet does not support this. I recommend using your own email address from a custom domain. This works perfectly.

Purpose This workflow enables you to listen to your recent favorites in very hight quality offline without sacrificing all of your storage. How it works This workflow automatically creates a playlist in Spotify named "Downloads" which periodically gets updated so it always contains only a defined amount of the latest liked songs. This enables only the Downloads playlist to set for automatic downloading and thus free up space on the device. Setup The workflow is ready to go. Just select your Spotify credentials and activate the workflow. In Spotify just enable automatic downloads on the automatically created Downloads folder after the first workflow run. Current limitations This setup currently supports a maximum of 50 songs in the Downloads Playlist. This is due to the paylod limits defined by Spotify encountered in the Get liked songs node. Implementing batching would solve the issue.

How it works it will return workflows that have buil-in nodes not of latest version with information of node name, type, current version and latest version for that type Set up steps: You need to have n8n credentials set, you can get n8n API key under settings set your instance base URL in "instance base url" node Disclaimar: Only check build-in nodes, community nodes are not supported

This workflow with AI agent is designed to navigate through the page to retrieve specific type of information (in this example: social media profile links). The agent is equipped with 2 tools: text tool:** to retrieve all the text from the page, URLs tool:** to extract all possible links from the page. 💡 You can edit prompt and JSON schema connected to the agent in order to return other data then social media profile links. 👉 This workflow uses Supabase as storage (input/output). Feel free to change it to any other database of your choice. 🎬 See this workflow in action in my YouTube video. How it works? The workflow uses the input URL (website) as a starting point to retrieve the data (e.g. example.com). Using the "URLs tool", the agent is able to retrieve all links from the page and navigate to them. For example, if you want to retrieve contact information, agent will try to find a subpage that might contain this information (e.g. example.com/contact) and extract the information using the text tool. Set up steps Connect database with input data (website addresses) or pin sample data to trigger node. Configure the crawling agent to retrieve the desired data (e.g. modify prompt and/or parsing schema). Set credentials for OpenAI. Optionally: split agent tools to separate workflows. If you like this workflow, please subscribe to my YouTube channel and/or my newsletter.

This n8n workflow automates the process of parsing and extracting data from PDF invoices. With this workflow, accounts and finance people can realise huge time and cost savings in their busy schedules. Read the Blog: https://blog.n8n.io/how-to-extract-data-from-pdf-to-excel-spreadsheet-advance-parsing-with-n8n-io-and-llamaparse/ How it works This workflow will watch an email inbox for incoming invoices from suppliers It will download the attached PDFs and processing them through a third party service called LlamaParse. LlamaParse is specifically designed to handle and convert complex PDF data structures such as tables to markdown. Markdown is easily to process for LLM models and so the data extraction by our AI agent is more accurate and reliable. The workflow exports the extracted data from the AI agent to Google Sheets once the job complete. Requirements The criteria of the email trigger must be configured to capture emails with attachments. The gmail label "invoice synced" must be created before using this workflow. A LlamaIndex.ai account to use the LlamaParse service. An OpenAI account to use GPT for AI work. Google Sheets to save the output of the data extraction process although this can be replaced for whatever your needs. Customizing this workflow This workflow uses Gmail and Google Sheets but these can easily be swapped out for equivalent services such as Outlook and Excel. Not using Excel? Simple redirect the output of the AI agent to your accounting software of choice.

This n8n workflow takes Slack conversations and turns them into Calendar events complete with accurate date and times and location information. Adding and removing attendees are also managed automatically. How it works Workflow monitors a Slack channel for invite messages with a "📅" reaction and sends this to the AI agent. AI agent parses the message determining the time, date and location. Using its Location tool, the AI agent searches for the precise location address from Google Maps. Using its Calendar tool, the AI agent creates a Google Calendar invite with the title, description and location address for the user. Back in the Slack channel, others can RSVP to the invite by reacting with the "✅" emjoi. The workflow polls the message after a while and adds the users who have reacted to the Calendar Invite as attendees. Conversely, removing any attendees who have since removed their reaction. Examples Jill: "Hey team, I'm organising a round of Laser Tag (Bunker 51) next Thursday around 6pm. Please RSVP with a ✅" AI: "I've helped you create an event in your calendar https://cal.google.com/..." Jack: "✅" AI: "I've added Jack to the event as an attendee". Requirements Slack channel to attach the workflow OpenAI account to use a GPT model Google Calendar to create and update events Customising the Workflow This workflow can work with other messaging platforms that support reactions or tagging like features such as discord. Don't use Google Calendar? Swap it out for Outlook or your own. Use any combinations of emjoi reactions and add new rules like "RSVP maybe" which could send reminder updates nearer the event date.

This n8n workflow demonstrates how you can summarise and automate post-meeting actions from video transcripts fed into an AI Agent. Save time between meetings by allowing AI handle the chores of organising follow-up meetings and invites. How it works This workflow scans for the calendar for client or team meetings which were held online. * Attempts will be made to fetch any recorded transcripts which are then sent to the AI agent. The AI agent summarises and identifies if any follow-on meetings are required. If found, the Agent will use its Calendar Tool to to create the event for the time, date and place for the next meeting as well as add known attendees. Requirements Google Calendar and the ability to fetch Meeting Transcripts (There is a special OAuth permission for this action!) OpenAI account for access to the LLM. Customising the workflow This example only books follow-on meetings but could be extended to generate reports or send emails.

This n8n workflow demonstrates how to automate indexing of images to build a object-based image search. By utilising a Detr-Resnet-50 Object Classification model, we can identify objects within an image and store these associations in Elasticsearch along with a reference to the image. How it works An image is imported into the workflow via HTTP request node. The image is then sent to Cloudflare's Worker AI API where the service runs the image through the Detr-Resnet-50 object classification model. The API returns the object associations with their positions in the image, labels and confidence score of the classification. Confidence scores of less the 0.9 are discarded for brevity. The image's URL and its associations are then index in an ElasticSearch server ready for searching. Requirements A Cloudflare account with Workers AI enabled to access the object classification model. An ElasticSearch instance to store the image url and related associations. Extending this workflow Further enrich your indexed data with additional attributes or metrics relevant to your users. Use a vectorstore to provide similarity search over the images.

If you have a shared or personal drive location with a high frequency of files created by humans, it can become difficult to organise. This may not matter... until you need to search for something! This n8n workflow works with the local filesystem to target the messy folder and categorise as well as organise its files into sub directories automatically. Disclaimer Unfortunately due to the intended use-case, this workflow will not work on n8n Cloud and a self-hosted version of n8n is required. How it works Uses the local file trigger to activate once a new file is introduced to the directory The new file's filename and filetype are analysed using AI to determine the best location to move this file. The AI assess the current subdirectories as to not create duplicates. If a relevant subdirectory is not found, a new subdirectory is suggested. Finally, an Execute Command node uses the AI's suggestions to move the new file into the correct location. Requirements Self-hosted version of n8n. The nodes used in this workflow only work in the self-hosted version. If you are using docker, you must create a bind mount to a host directory. Mistral.ai account for LLM model Customise this workflow If the frequency of files created is high enough, you may not want the trigger to active on every new file created event. Switch to a timer to avoid concurrency issues. Want to go fully local? A version of this workflow is available which uses Ollama instead. You can download this template here: https://drive.google.com/file/d/1iqJ_zCGussXpfaUBYGrN5opziEFAEQMu/view?usp=sharing

This n8n workflow is designed to work on the local network and assists with reconciling downloaded bank statements with internal tenant records to quickly highlight any issues with payments such as missed or late payments or those of incorrect amounts. This assistant can then generate a report to quick flag attention to ensure remedial action is taken. How it works The workflow monitors a local network drive to watch for new bank statements that are added. This bank statement is then imported into the n8n workflow, its contents extracted and sent to the AI Agent. The AI Agent analyses the line items to identify the dates and any incoming payments from tenants. The AI agent then uses an locally-hosted Excel ("XLSX") spreadsheet to get both tenant records and property records. From this data, it can determine for each active tenant when payment is due, the amount and the tenancy duration. Comparing to the bank statement, the AI Agent can now report on where tenants have missed their payments, made late payments or are paying the incorrect amounts. The final report is generated and logged in the same XLSX for a human to check and action. Requirements A self-hosted version of n8n is required. OpenAI account for the AI model Customising this workflow If you organisation has a Slack or Teams account, consider sending reports to a channel for increased productivity. Email may be a good choice too. Want to go fully local? A version of this workflow is available which uses Ollama instead. You can download this template here: https://drive.google.com/file/d/1YRKjfakpInm23F_g8AHupKPBN-fphWgK/view?usp=sharing

This n8n workflow takes in a document such as a research paper, marketing or sales deck or company filings, and breaks them down into 3 templates: study guide, briefing doc and timeline. These templates are designed to help a student, associate or clerk quickly summarise, learn and understand the contents to be more productive. Study guide - a short quiz of questions and answered generated by the AI Agent using the contents of the document. Briefing Doc - key information and insights are extracted by the AI into a digestable form. Timeline - key events, durations and people are identified and listed into a simple to understand timeline by the AI How it works A local file trigger watches a local network directory for new documents. New documents are imported into the workflow, its contents extracted and vectorised into a Qdrant vector store to build a mini-knowledgebase. The document then passes through a series of template generating prompts where the AI will perform "research" on the knowledgebase to generate the template contents. Generated study guide, briefing and timeline documents are exported to a designated folder for the user. Requirements Self-hosted version of n8n. Qdrant instance for knowledgebase. Mistral.ai account for embeddings and AI model. Customising your workflow Try adding your own templates or adjusting the existing templates to suit your unique use-case. Anything is quite possible and limited only by your imagination! Want to go fully local? A version of this workflow is available which uses Ollama instead. You can download this template here: https://drive.google.com/file/d/1VV5R2nW-IhVcFP_k8uEks4LsLRZrHSNG/view?usp=sharing

This n8n workflows builds another example of creating a knowledgebase assistant but demonstrates how a more deliberate and targeted approach to ingesting the data can produce much better results for your chatbot. In this example, a government tax code policy document is used. Whilst we could split the document into chunks by content length, we often lose the context of chapters and sections which may be required by the user. Our approach then is to first split the document into chapters and sections before importing into our vector store. Additionally, using metadata correctly is key to allow filtering and scoped queries. Example Human: "Tell me about what the tax code says about cargo for intentional commerce?" AI: "Section 11.25 of the Texas Property Tax Code pertains to "MARINE CARGO CONTAINERS USED EXCLUSIVELY IN INTERNATIONAL COMMERCE." In this section, a person who is a citizen of a foreign country or an en..." How it works The tax code policy document is downloaded as a zip file from the government website and its pages are extracted as separate chapters. Each chapter is then parsed and split into its sections using data manipulation expressions. Each section is then inserted into our Qdrant vector store tagged with its source, chapter and section numbers as metadata. When our AI Agent needs to retrieve data from our vector store, we use a custom workflow tool to perform the query to Qdrant. Because we're relying on Qdrant's advanced filtering capabilities, we perform the search using the Qdrant API rather than the Qdrant node. When the AI Agent, needs to pull full wording or extracts, we can use Qdrant's scroll API and metadata filtering to do so. This makes Qdrant behave like a key-value store for our document. Requirements A Qdrant instance is required for the vector store and specifically for it's filtering functionality. Mistral.ai account for Embeddings and AI models. Customising this workflow Depending on your use-case, consider returning actual PDF pages (or links) to the user for the extra confirmation and to build trust. Not using Mistral? You are able to replace but note to match the distance and dimension size of Qdrant collection to your chosen embedding model.

This workflow syncs multiple Notion databases to your Google Calendar. And it works both ways. What events are supported? Everything except recurring events. All day events, multiple day events, start and end date… these are all supported. You set them in Notion and they stay in sync with Google. And vice versa. Why doesn’t it support recurring events? Notion doesn’t support recurring events yet. So when you create a recurring event in Google, it will only consider the first date, ignoring future occurrences of the event. Can I connect more than one Notion database? Yes. You can have many Notion databases synced to one Google Calendar account. You can see how to do it in the workflow instructions. It is recommended that you create more calendars in your account, so that you can link each calendar to a different database in Notion. But that’s a choice. What happens if I delete an event or page? Notion page deleted → Deletes event in Google Notion date property cleared → Deletes event in Google Google event deleted → Clears the date property in Notion, but keeps the page, so you don’t lose your work. Does it update the events? Yes. When you update the event in Google or in Notion it syncs both ways. How can I know what Notion item was linked to an event? Either by the name or by clicking the hyperlink in the event description that says: 👉 View in Notion. When I create a new event in Google, does it add an item to Notion? Yes. When you create an event inside one of your calendars, the item is synced to the corresponding Notion database. Does it sync event descriptions? No. The event description will always be “View in Notion”. Even if you change it in Google Calendar it will be overwritten when you make a change to the Notion page. 🎉 When you buy this template you receive step-by-step instructions on how to set it up. Check out my other templates 👉 https://n8n.io/creators/solomon/

This n8n workflow demonstrates a simple multi-agent setup to perform the task of competitor research. It showcases how using the HTTP request tool could reduce the number of nodes needed to achieve a workflow like this. How it works For this template, a source company is defined by the user which is sent to Exa.ai to find competitors. Each competitor is then funnelled through 3 AI agents that will go out onto the internet and retrieve specific datapoints about the competitor; company overview, product offering and customer reviews. Once the agents are finished, the results are compiled into a report which is then inserted in a notion database. Check out an example output here: https://jimleuk.notion.site/2d1c3c726e8e42f3aecec6338fd24333?v=de020fa196f34cdeb676daaeae44e110&pvs=4 Requirements An OpenAI account for the LLM. Exa.ai account for access to their AI search engine. SerpAPI account for Google search. Firecrawl.dev account for webscraping. Notion.com account for database to save final reports. Customising the workflow Add additional agents to gather more datapoints such as SEO keywords and metrics. Not using notion? Feel free to swap this out for your own database.

The Stripe API does not provide custom fields in invoice or charge data. So you have to get it from the Checkout Sessions endpoint. But that endpoint is not easy for begginners. It has dictionary parameters and pagination settings. This workflows solves that problem by having a preconfigured GET request that gets all the checkout sessions from the last 7 days. It then transforms the data to make it easier to work with and allows you to filter by the custom_fields you want to get. Want to generate Stripe invoices automatically? Open 👉 this workflow . Check out my other templates https://n8n.io/creators/solomon/

Using the Systeme API can be challenging due to its pagination settings and low rate limit. This requires a bit more knowledge about API requests than a beginner might have. This template provides preconfigured HTTP Request nodes to help you work more efficiently. Pagination settings, item limits, and rate limits are all configured for you, making it easier to get started. How to configure Systeme.io credentials The Systeme API uses the Header Auth method. So create a Header Auth credential in your n8n with the name "X-API-Key". . Check out my other templates 👉 https://n8n.io/creators/solomon/

Who is it for If you are a postmaster or you manage email server, you can set up DKIM and SPF records to ensure that spoofing your email address is hard. On your domain you can also set up DMARC record to receive XML reports from email providers (rua tag). Those reports contain data if email they received passed DKIM and SPF verifications. Since DMARC email is public, you will receive a lot of emails from email providers, not only if DKIM/SPF fail. There is no need for it - you probably only need to know if SPF/DKIM failed. So this script is intended to automatically parse all DMARC reports that come from email providers, but ONLY send you notification if SPF or DKIM failed - meaning that either someone tries to spoof your email or your DKIM/SPF is improperly set up. How it works script monitors postmaster email for DMARC reprots (rua) unpacks report and parses XML into JSON maps JSON and formats fields for MySQL/MariaDB input inputs into database sends notification on DKIM or SPF failure Remember to set up email input mailbox notification channels for slack for email

This n8n template is one of a 3-part series exploring use-cases for clustering vector embeddings: Survey Insights Customer Insights Community Insights This template demonstrates the Survey Insights scenario where survey participant responses can be quickly grouped by similarity and an AI agent can generate insights on those groupings. With this workflow, researchers can save days and even weeks of work breaking down cohorts of participants and identify frequently mentioned positives and negatives. Sample Output: https://docs.google.com/spreadsheets/d/e/2PACX-1vT6m8XH8JWJTUAfwojc68NAUGC7q0lO7iV738J7aO5fuVjiVzdTRRPkMmT1C4N8TwejaiT0XrmF1Q48/pubhtml# How it works All survey questions and responses are imported from a Google Sheet. Responses are then inserted into a Qdrant collection carefully tagged with the question and survey metadata. For each question, all relevant response are put through a clustering algorithm using the Python Code node. The Qdrant points are returned in clustered groups. Each group is looped to fetch the payloads of the points and feed them to the AI agent to summarise and generate insights for. The resulting insights and raw responses are then saved to the Google Spreadsheet for further analysis by the researcher. Requirements Survey data and format as shown in the attached google sheet. Qdrant Vectorstore for storing embeddings. OpenAI account for embeddings and LLM. Customising the Template Adjust clustering parameters which make sense for your data. Add more clusters for open-ended questions and less clusters when responses are multiple choice.

This n8n template is one of a 3-part series exploring use-cases for clustering vector embeddings: Survey Insights Customer Insights Community Insights This template demonstrates the Customer Insights scenario where Trustpilot reviews can be quickly grouped by similarity and an AI agent can generate insights on those groupings. With this workflow, marketers can save days and even weeks of work breaking down their own or competitor reviews and identify frequently mentioned positives and negatives. Sample Output: https://docs.google.com/spreadsheets/d/e/2PACX-1vQ6ipJnXWXgr5wlUJnhioNpeYrxaIpsRYZCwN3C-fFXumkbh9TAsA_JzE0kbv7DcGAVIP7az0L46_2P/pubhtml How it works Trustpilot reviews are scraped for a particular company using the HTTP request node. Reviews are then inserted into a Qdrant collection carefully tagged with the question and Trustpilot metadata. Reviews are fetched and put through a clustering algorithm using the Python Code node. The Qdrant points are returned in clustered groups. Each group is looped to fetch the payloads of the points and feed them to the AI agent to summarise and generate insights for. The resulting insights and raw responses are then saved to the Google Spreadsheet for further analysis by the marketer. Requirements Qdrant Vectorstore for storing embeddings. OpenAI account for embeddings and LLM. Customising the Template Adjust clustering parameters which make sense for your data. Consider expanding date range of reviews for insights over common intervals: 3mth, 6mth and YTD.

This n8n template is one of a 3-part series exploring use-cases for clustering vector embeddings: Survey Insights Customer Insights Community Insights This template demonstrates the Community Insights scenario where HN commments can be quickly grouped by similarity and an AI agent can generate insights on those groupings. With this workflow, Researchers or HN users can quickly breakdown community consensus on a particular topic and identify frequently mentioned positives and negatives. Sample Output: https://docs.google.com/spreadsheets/d/e/2PACX-1vQXaQU9XxsxnUIIeqmmf1PuYRuYtwviVXTv6Mz9Vo6_a4ty-XaJHSeZsptjWXS3wGGDG8Z4u16rvE7l/pubhtml How it works HN comments are imported via the Hacknews API node. Comments are then inserted into a Qdrant collection carefully tagged with the Hackernews API metadata. Comments are then fetched and are put through a clustering algorithm using the Python Code node. The Qdrant points are returned in clustered groups. Each group is looped to fetch the payloads of the points and feed them to the AI agent to summarise and generate insights for. The resulting insights and raw responses are then saved to the Google Spreadsheet for further analysis by the researcher or the HN user. Requirements Works best with lots of comments! Qdrant Vectorstore for storing embeddings. OpenAI account for embeddings and LLM. Customising the Template Adjust clustering parameters which make sense for your data. Adjust sentimentality setting if comments are overwhelmingly negative at times.

Overview This template integrates an IOT multi-button switch (meant for controlling a dimmable light) with Spotify playback functions, via MQTT messages. This isn't likely to work without some tinkering, but should be a good head start on receiving/routing IOT/MQTT messages and hooking up to a Spotify-like API. Requirements An IOT device capable of generating events that can be delivered as MQTT messages through an MQTT Broker e.g. Ikea Strybar remote An MQTT Broker to which n8n can connect and consume messages e.g. Zigbee2MQTT in HomeAssistant A Spotify developer-account (which provides access to API functions via OAuth2 authorization) A Spotify user-account (which provides access to Spotify streamed content, user settings, etc.) Setup Create an MQTT Credential item in n8n and assign it to the MQTT Trigger node Modify the MQTT trigger node to match the topic for your IOT device messages Modify the switch/router nodes to map to the message text from your IOT button (e.g. arrow_left_click, brightness_up_click, etc.) Create a Spotify developer-account (or use the login for a user-account) Create an "App" in the developer-account to represent the n8n workflow Chicken/Egg ALERT: The n8n Spotify Credentials dialog box will display the "OAuth Redirect URL" required to create the App in Spotify, but the n8n Credential item itself cannot be created until AFTER the App has been created. Create a Spotify Credentials item in n8n Open the Settings on the Spotify App to find the required Client ID and Client Secret information. ALERT: Save this before proceeding to the Connect step. Connect the n8n Spotify Credential item to the Spotify user-account ALERT: Expect n8n to open a separate OAuth2 window on authorization.spotify.com here, which may require a login to the Spotify user-account Open each of the HTTP and Spotify nodes, one by one, and re-assign to your Spotify Credential (try not to miss any). (Then, probably, upvote this feature request: https://community.n8n.io/t/select-credentials-via-expression/5150 Modify the variable values in the Globals node to match your own environment. target_spotify_playback_device_name - The name of a playback device available to the Spotify user-account favorite_playlist_name - The name of a playlist to start when one of the button actions is indicated in the MQTT message. Used in example "Custom Function 2" sequence. Notes You're on your own for getting the multi-button remote switch talking to MQTT, figuring out what the exact MQTT topic name is, and mapping the message parts to the workflow (actions, etc.). The next / previous actions are wired up to not transfer control to the target device. This alternative routing just illustrates a different behavior than the remaining actions/functions, which include activation of the target device when required. Some of the Spotify API interactions use the Spotify node in n8n, but many of the available Spotify API functions are limited or not implemented at all in the Spotify node. So, in other cases, a regular HTTP node is used with the Spotify OAuth2 API credential instead. By modifying one of the examples included in the template, it should be possible to call nearly anything the Spotify API has to offer. Spotify+n8n OAuth Mini-Tutorial Definitions The developer-account is the Spotify login for creating a spotify-app which will be associated with a client id and client secret. The user-account is the Spotify login that has permission to stream songs, set up playback devices, etc. ++A spotify-login allows access to a Spotify user-account, or a Spotify developer-account, OR BOTH++ The spotify-app, which has a client id and client secret, is an object created in the developer-account. The app-implementation (in this case, an ++n8n workflow++) uses the spotify-app's credentials (client id / client secret) to call Spotify API endpoints on behalf of a user-account. Using One Spotify Login as Both User and Developer When an n8n Spotify-node or HTTP-node (i.e. an app-implementation) calls a Spotify API endpoint, the Credentials item may be using the client id and client secret from a spotify-app, which was created in a developer-account that is ++one and the same spotify-login as the user-account++. However, it helps to remind yourself that from the Spotify API server's perspective, the developer-account + spotify-app, and the user-account, are ++two independent entities++. n8n Spotify-OAuth2-API Credential Authorization Process The 2 layers/steps, in the process of authorizing an n8n Spotify-OAuth2-API credential to make API calls, are: n8n must identify itself to Spotify as the app-implementation associated with the developer-account/spotify-app by sending the app's credentials (client id and client secret) to Spotify. The Client ID and Client Secret are supplied in the n8n Spotify OAuth2 Credentials UI/dialog-box Separately, n8n must obtain an authorization token from Spotify to represent the permissions granted by the user to execute actions (call API endpoints) on behalf of the user (i.e. access things that belong to the user-account). This authorization for the user-account access is obtained when the "Connect" or "Reconnect" button is clicked in the n8n Spotify Credentials UI/dialog-box (which pops up a separate authorization UI/browser-window managed by Spotify). The Authorization for a given spotify-app stays "registered" in the user-account until revoked. See: https://support.spotify.com/us/article/spotify-on-other-apps/ Direct Link: https://www.spotify.com/account/apps/ More than one user-account can be authorized for a given spotify-app. A particular n8n Spotify-OAuth2-API credential item appears to cache an authorization token for the user-account that was most recently authorized. Up to 25 users can be allowed access to a spotify-app in Developer-Mode, but any user-account other than the one associated with the developer-account must be added by email address at https://developer.spotify.com/dashboard/{{app-credential-id}}/users ALERT: IF the browser running the n8n UI is ALSO logged into a Spotify account, and the spotify-app is already authorized for that Spotify account, the "reconnect" button in the Spotify-OAuth2-API credential dialog may automatically grab a token for that logged in user-account, offering no opportunity to select a different user-account. This can be managed somewhat by using "incognito" browser windows for n8n, Spotify, or both. References n8n Spotify Credentials Docs Spotify Authorization Docs

Who this is for This template is for everyone that wants to download their n8n Cloud invoices automatically as a PDF instead of downloading them manually. How it works This workflow checks your Gmail inbox for new n8n invoice emails from n8n's payment provider Paddle. Once it finds something, it converts the URL into a PDF using pdflayer and saves it in Google Drive. Setup Setup your Gmail and Google Drive credentials Create a free account at https://pdflayer.com/ Insert your pdflayer API key into the Setup node Insert the URL to the wanted drive folder into the setup node (make sure to remove everything after the ?) How to adjust it to your need Instead of saving the PDF in Google drive, you could also save it in your local system, any other storage provider or send the PDF automatically to the right person in your company.

Workflow: Snapshot Contabo How it Works This workflow automates daily backups (snapshots) of VPS instances hosted on Contabo. Each day at midnight, it checks for existing snapshots and ensures that only the latest backups are retained by removing older ones. It provides a seamless, hands-off backup process to keep your data secure. Setup Steps Setting up this workflow is quick, typically taking about 10-15 minutes. The essential part of the setup is providing the necessary credentials, which you can easily retrieve from your Contabo control panel. Import the Workflow: Download and upload the workflow JSON into n8n. Configure Credentials: Add CLIENT_ID, CLIENT_SECRET, API_USER, and API_PASSWORD in the credential node. Activate the Workflow: Enable it to run automatically at midnight every day. Flow Overview Schedule Trigger (00:00 daily):** Automatically initiates the workflow. Formatted Date:** Prepares a timestamp for naming the snapshot. List Snapshots:** Verifies if an existing snapshot is available for each VPS. Conditional Logic:** No Snapshot? Proceeds to create a new one. Snapshot Found? Deletes the old snapshot before creating a new one. Key Points Snapshot Retention:** Old snapshots are deleted to ensure only the latest backups are stored. Unique Identifiers:** UUIDs are used to track and guarantee unique operations.

How it works Fetch transaction notification emails (including attachments) Clean up data Let AI (Basic LLM Chain node) generate bookkeeping item Send to Google sheet Details The example fetch email from Gmail lables, suggested using filters to automatically orgianize email into the labels Data will send to "raw data" sheet Example google sheet: https://docs.google.com/spreadsheets/d/1_IhdHj8bxtsfH2MRqKuU2LzJuzm4DaeKSw46eFcyYts/edit?gid=1617968863#gid=1617968863

This n8n workflow shows how using multimodal LLMs with AI vision can tackle tricky image validation tasks which are near impossible to achieve with code and often impractical to be done by humans at scale. You may need image validation when users submitted photos or images are required to meet certain criteria before being accepted. A wine review website may require users only submit photos of wine with labels, a bank may require account holders to submit scanned documents for verification etc. In this demonstration, our scenario will be to analyse a set of portraits to verify if they meet the criteria for valid passport photos according to the UK government website (https://www.gov.uk/photos-for-passports). How it works Our set of portaits are jpg files downloaded from our Google Drive using the Google Drive node. Each image is resized using the Edit Image node to ensure a balance between resolution and processing speed. Using the Basic LLM node, we'll define a "user message" option with the type of binary (data). This will allow us to pass our portrait to the LLM as an input. With our prompt containing the criteria pulled off the passport photo requirements webpage, the LLM is able to validate the photo does or doesn't meet its criteria. A structured output parser is used to structure the LLM's response to a JSON object which has the "is_valid" boolean property. This can be useful to further extend the workflow. Requirements Google Gemini API key Google Drive account Customising this workflow Not using Gemini? n8n's LLM node works with any compatible multimodal LLM so feel free to swap Gemini out for OpenAI's GPT4o or Antrophic's Claude Sonnet. Don't need to validate portraits? Try other use cases such as document classification, security footage analysis, people tagging in photos and more.

What this workflow does Downloads the daily top podcasts of a selected genre Summarizes the content of each podcast in a few paragraphs Sends the summaries and the direct link to each podcast in a formatted email Setup Create a free API key on Taddy here: https://taddy.org/signup/developers Input your user number and API key into the TaddyTopDaily node in the header parameters X-USER-ID and X-API-KEY respectively. Create access credentials for your Gmail as described here: https://developers.google.com/workspace/guides/create-credentials. Use the credentials from your client_secret.json in the Gmail node. In the Genre node, set the genre of podcasts you want a summary for. Valid values are: TECHNOLOGY, NEWS, ARTS, COMEDY, SPORTS, FICTION, etc. Look at api.taddy.org for the full list (they will be displayed in the help docs as PODCASTSERIES_TECHNOLOGY, PODCASTSERIES_NEWS, etc.) Enter your email address in the Gmail node. Change the schedule time for sending email from Schedule to whichever time you want to receive the email. Test: Hit Test Workflow. Check your email for the results. That's it! It should take less than 5 minutes total.

This n8n workflow template lets you easily generate comprehensive FAQ (Frequently Asked Questions) content for multiple services (or any items or pages you need to add the FAQs to). Simply provide the Google Sheets document containing the items to scrape, and the workflow automatically creates detailed, AI-enhanced FAQ documents. How it works The workflow reads data from a Google Sheets document containing information about different services and categories (again, in your case - whatever objects you need). For each service and category, it generates a set of standard questions and answers covering setup, permissions, integrations, use cases, and pricing benefits. An AI model (OpenAI's GPT) is used to enhance or complete some of the answers, making the content more comprehensive and natural-sounding. The workflow formats the Q&A pairs, combining AI-generated content with predefined answers where applicable. It creates a text file (JSON) for each service or category, containing the formatted Q&A pairs. The generated files are saved to specific folders in Google Drive, organized by the type of integration (native, credential-only, non-native) or category. After processing each service or category, it updates the status in the original Google Sheets document to mark it as completed. Ideal for: Marketing teams: Rapidly create comprehensive FAQ documents for multiple products or services. Customer support: Generate consistent and detailed answers for common customer queries. Product managers: Easily maintain up-to-date documentation as products evolve. Content creators: Streamline the process of creating informative content about various offerings. Accounts required Google account (for Google Sheets and Google Drive) OpenAI API account (for AI-enhanced content generation) n8n.io account (for workflow execution) Set up instructions Set up the required credentials for Google Sheets, Google Drive, and OpenAI when you first open the workflow. Prepare your Google Sheets document with the service/category information. Here's an example of Google Sheet. Fill the "Define Sheets" node with your sheets Adjust the folder IDs in the "Prepare Job" node to match your Google Drive structure. Configure the OpenAI model settings in the "OpenAI Chat Model" node if needed. Test the workflow with a small subset of data before running it on your entire dataset. Adjust the questions asked in the "Create your Q&A templates" section After testing, activate your workflow for automated FAQ generation. 🙏 Big, big kudos to Jim Le for his ideas, input and support when building this workflow. Your approach to AI workflows is always super helpful!

What this workflow does This workflow allows you to monitor multiple Github repos simultaneously without polling due to use of Webhooks. It programmatically allows for adding and deleting of repos to your watchlist to make management convenient. Description Can monitor multiple repos simultaneously. Programmatically register or unregister repos from a list. No need for manual work. Webhook notification means no constant polling necessary. Setup 1. Creating Credentials on Github Generate a personal access token on github by following these esteps; Right hand side of page -> Settings -> scroll to bottom -> Developer Settings > Personal Access Token > Tokens (classic) > Generate New Token Give scopes: admin:repo_hook repo (if you want to use it for your own private repo) if you need more help, see here: https://docs.github.com/en/authentication/keeping-your-account-and-data-secure/managing-your-personal-access-tokens 2. Setting Credentials in n8n In Register Github Webhook Authenticaion > Generic Credential Type Generic Auth Type > Header Auth Header Auth > Create New Credential with Name set to 'Authorization' and Value set to 'Bearer '. (You can reuse this for Delete Github Webhook and Get Existing Webhooks). Now in Register Github Webhook, scroll down to Send Body > JSON and inside the JSON, change the value of "url" to the webhook address given as Production URL in the node Webhook Trigger. 3. Notification settings In the third row, link up the Webhook Trigger to any API of your choice. Slack and Telegram are given as examples. You can also format the notification message as you wish. Setup time: roughly 10 minutes. Instructions Video: https://vimeo.com/1013473758 Test 1. Register Webhooks In Repos to Monitor, add any repo you want to monitor changes for. Disable Webhook Trigger, Click Test Workflow and if your Github credentials were set correctly, it will automatically register the webhooks. - You can test this by running the single node Get Existing Webhook and confirming it outputs the repo addresses. 2. Handle Github Events Now that you have registered the webhooks, re-enable Webhook Trigger and activate the workflow. Make a commit to any of the registered repos. Confirm that the notification went through. That's it!

Create a recommendation tool without hallucinations based on RAG with the Qdrant Vector database. This example is based on movie recommendations on the IMDB-top1000 dataset. You can provide your wishes and your "big no's" to the chatbot, for example: "A movie about wizards but not Harry Potter", and get top-3 recommendations. How it works a video with the full design process Upload IMDB-1000 dataset to Qdrant Vector Store, embedding movie descriptions with OpenAI; Set up an AI agent with a chat. This agent will call a workflow tool to get movie recommendations based on a request written in the chat; Create a workflow which calls Qdrant's Recommendation API to retrieve top-3 recommendations of movies based on your positive and negative examples. Set Up Steps You'll need to create a free tier Qdrant Cluster (Qdrant can also be used locally; it's open-sourced) and set up API credentials You'll OpenAI credentials You'll need GitHub credentials & to upload the IMDB Kaggle dataset to your GitHub.

Workflow Description: This n8n workflow automates the drafting of email replies for Fastmail using OpenAI's GPT-4 model. Here’s the overall process: Email Monitoring: The workflow continuously monitors a specified IMAP inbox for new, unread emails. Email Data Extraction: When a new email is detected, it extracts relevant details such as the sender, subject, email body, and metadata. AI Response Generation: The extracted email content is sent to OpenAI's GPT-4, which generates a personalized draft response. Get Fastmail Session and Mailbox IDs: Connects to the Fastmail API to retrieve necessary session details and mailbox IDs. Draft Identification: Identifies the "Drafts" folder in the mailbox. Draft Preparation: Compiles all the necessary information to create the draft, including the generated response, original email details, and specified recipient. Draft Uploading: Uploads the prepared draft email to the "Drafts" folder in the Fastmail mailbox. Prerequisites: IMAP Email Account: You need to configure an IMAP email account in n8n to monitor incoming emails. Fastmail API Credentials: A Fastmail account with JMAP API enabled. You should set up HTTP Header authentication in n8n with your Fastmail API credentials. OpenAI API Key: An API key from OpenAI to access GPT-4. Make sure to configure the OpenAI credentials in n8n. Configuration Steps: Email Trigger (IMAP) Node: Provide your email server settings and credentials to monitor emails. HTTP Request Nodes for Fastmail: Set up HTTP Header authentication in n8n using your Fastmail API credentials. Replace the httpHeaderAuth credential IDs with your configured credential IDs. OpenAI Node: Configure the OpenAI API key in n8n. Replace the openAiApi credential ID with your configured credential ID. By following these steps and setting up the necessary credentials, you can seamlessly automate the creation of email drafts in response to new emails using AI-generated content. This workflow helps improve productivity and ensures timely, personalized communication.

🚀 Local Multi-LLM Testing & Performance Tracker This workflow is perfect for developers, researchers, and data scientists benchmarking multiple LLMs with LM Studio. It dynamically fetches active models, tests prompts, and tracks metrics like word count, readability, and response time, logging results into Google Sheets. Easily adjust temperature 🔥 and top P 🎯 for flexible model testing. Level of Effort: 🟢 Easy – Minimal setup with customizable options. Setup Steps: Install LM Studio and configure models. Update IP to connect to LM Studio. Create a Google Sheet for result tracking. Key Outcomes: Benchmark LLM performance. Automate results in Google Sheets for easy comparison. Version 1.0

This automation syncs your Invoice PDFs from Stripe to a (AWS) S3 Bucket each month, in a folder of your choice, with the following subPath: yourFolder/invoiceYear/invoiceMonth/fileName Fill in your Credentials and Settings in the Nodes marked with "*". You can adjust this Workflow to your needs. You can also override the yearand month in the ENV* Node for manual syncs. It will sync every Invoice PDF which created-date is greater then the provided year and month. It will automatically set the day to the first day of the desired month. Enjoy the Workflow! ❤️ https://let-the-work-flow.com Workflow Automation & Development

Purpose of workflow: The purpose of this workflow is to automatically transform complex, lengthy PDFs into concise, insightful blog posts. This process aims to make dense information more accessible and understandable to a broader audience. How it works: Multi-agent team: Working together to transform PDF to insightful blog Content Analyst: Extracts key information and structure from the PDF. Project Planner: Organizes the workflow and ensures efficient processing. Writers: Multiple agents that craft engaging content based on the analyzed information. Editor: Polishes the final output for accuracy, reliability, and readability. Step by step User inputs parameters via a n8n form (tone, word count, sections, PDF file). System extracts text from the PDF. Content Analyst AI agent analyzes the extracted text, identifying main topics and key points. Project Planner AI agent organizes the workflow, creating a structure for the blog post. Multiple Writer AI agents (based on the number of sections specified) each write a portion of the blog post. Editor AI agent combines all sections and polishes the final draft. Generates a title for the blog post. Final content is uploaded to a publishing Ghost platform

This n8n template demonstrates the beginnings of building your own n8n-powered WhatsApp chatbot! Under the hood, utilise n8n's powerful AI features to handle different message types and use an AI agent to respond to the user. A powerful tool for any use-case! How it works Incoming WhatsApp Trigger provides a way to get messages into the workflow. The message received is extracted and sent through 1 of 4 branches for processing. Each processing branch uses AI to analyse, summarize or transcribe the message so that the AI agent can understand it. The supported types are text, image, audio (voice notes) and video. The AI Agent is used to generate a response generally and uses a wikipedia tool for more complex queries. Finally, the response message is sent back to the WhatsApp user using the WhatsApp node. How to use Once you have setup and configured your WhatsApp account, you'll need to activate your workflow to start processing messages. Good to know: Large media files may negatively impact workflow performance. Requirements WhatsApp Buisness account Google Gemini for LLM. Gemini is used specifically because it can accept audio and video files whereas at time of writing, many other providers like OpenAI's GPT, do not. Customising this workflow For performance reasons, consider detecting large audio and video before sending to the LLM. Pre-processing such files may allow your agent to perform better. Go beyond and create rich and engagement customer experiences by responding using images, audio and video instead of just text!

This n8n template takes a video and extracts frames from it which are used with a multimodal LLM to generate a script. The script is then passed to the same multimodal LLM to generate a voiceover clip. This template was inspired by Processing and narrating a video with GPT's visual capabilities and the TTS API How it works Video is downloaded using the HTTP node. Python code node is used to extract the frames using OpenCV. Loop node is used o batch the frames for the LLM to generate partial scripts. All partial scripts are combined to form the full script which is then sent to OpenAI to generate audio from it. The finished voiceover clip is uploaded to Google Drive. Sample the finished product here: https://drive.google.com/file/d/1-XCoii0leGB2MffBMPpCZoxboVyeyeIX/view?usp=sharing Requirements OpenAI for LLM Ideally, a mid-range (16GB RAM) machine for acceptable performance! Customising this workflow For larger videos, consider splitting into smaller clips for better performance Use a multimodal LLM which supports fully video such as Google's Gemini.

What this workflow does: This flow uses an AI node to generate Seed Keywords to focus SEO efforts on based on your ideal customer profile. You can use these keywords to form part of your SEO strategy. Outputs: List of 20 Seed Keywords Setup Fill the Set Ideal Customer Profile (ICP) Connect with your credentials Replace the Connect to your own database with your own database Pre-requisites / Dependencies You know your ideal customer profile (ICP) An AI API account (either OpenAI or Anthropic recommended) More templates and n8n workflows >>> @simonscrapes

Use Case Research search engine rankings for SEO analysis: You need to track keyword rankings for your website You want to analyze competitor positions in search results You need data for SEO competition analysis You want to monitor SERP changes over time What this Workflow Does The workflow uses ScrapingRobot API to fetch Google search results: Retrieves SERP data for your target keywords Captures URL rankings and page titles Processes up to 5000 searches with free account Organizes results for SEO analysis Setup Create a ScrapingRobot account and get your API key Add your ScrapingRobot API key to the HTTP Request node's GET SERP token parameter Either connect your keyword database (column name "Keyword") or use the "Set Keywords" node Configure your preferred output database connection How to Adjust it to Your Needs Modify keyword source to pull from different databases Adjust the number of SERP results to capture Customize output format for your reporting needs More templates and n8n workflows >>> @simonscrapes

Use Case Transform web pages into AI-friendly markdown format: You need to process webpage content for LLM analysis You want to extract both content and links from web pages You need clean, formatted text without HTML markup You want to respect API rate limits while crawling pages What this Workflow Does The workflow uses Firecrawl.dev API to process webpages: Converts HTML content to markdown format Extracts all links from each webpage Handles API rate limiting automatically Processes URLs in batches from your database Setup Create a Firecrawl.dev account and get your API key Add your Firecrawl API key to the HTTP Request node's Authorization header Connect your URL database to the input node (column name must be "Page") or edit the array in Example fields from data source Configure your preferred output database connection How to Adjust it to Your Needs Modify input source to pull URLs from different databases Adjust rate limiting parameters if needed Customize output format for your specific use case More templates and n8n workflows >>> @simonscrapes

This workflow automates the process of gathering LinkedIn advice articles, extracting their content, and generating unique contributions for each article using an AI model. The contributions are then posted to a Slack channel and a NocoDB database for record-keeping. The workflow is triggered weekly to ensure new articles are continuously collected and responded to. Who is this for? This workflow is designed for professionals, marketers, and content creators looking to boost their LinkedIn presence by regularly engaging with LinkedIn advice articles. It’s especially useful for those who want to be seen as a "thought leader" or "top voice" in their niche by contributing relevant and unique advice to trending topics. What problem is this workflow solving? Manually searching for relevant LinkedIn articles, reading through them, and crafting thoughtful contributions can be time-consuming. This workflow solves that by automating the process of finding new articles, extracting key content, and generating AI-powered contributions. It helps users stay consistently active on LinkedIn, contributing value to trending discussions. What this workflow does Triggers Weekly: The workflow is set to run every Monday at 8:00 AM. Search Google for LinkedIn Advice Articles: Uses a predefined Google search URL to find the latest LinkedIn advice articles based on the user's area of expertise. Extract LinkedIn Article Links: A code node extracts all LinkedIn advice article links from the search results. Retrieve Article Content: For each article link, the workflow retrieves the HTML content and extracts the article title, topics, and existing contributions. Generate AI-Powered Contributions: The workflow sends the extracted article content to an AI model, which generates unique, helpful advice for each topic within the article. Post to Slack & NocoDB: The AI-generated contributions, along with the article links, are posted to a designated Slack channel and stored in a NocoDB database for future reference. Setup Google Search URL: Update the Google search URL with the relevant LinkedIn advice query for your field (e.g., "site:linkedin.com/advice 'marketing automation'"). Slack Integration: Connect your Slack account and specify the Slack channel where you want the contributions to be posted. NocoDB Integration: Set up your NocoDB project to store the generated contributions along with the article titles and links. How to customize this workflow Change Search Terms**: Modify the Google search URL to focus on a different LinkedIn topic or expertise area. Adjust Trigger Frequency**: The workflow is set to run weekly, but you can adjust the frequency by changing the schedule trigger. Enhance Contribution Quality**: Customize the AI model's prompt to generate contributions that align with your brand voice or content strategy. Workflow Summary This workflow helps users maintain a consistent presence on LinkedIn by automating the discovery of new advice articles and generating unique contributions using AI. It is ideal for professionals who want to engage with LinkedIn content regularly without spending too much time manually searching and drafting responses.

Use Case Generate accurate search volume data for SEO keyword research: You have a list of potential keywords to target for your website SEO but don't know their actual search volume You need historical data to identify seasonal trends in keyword popularity You want to assess keyword difficulty to prioritize your content strategy You need data-driven insights for planning your SEO campaigns What this Workflow Does The workflow connects to Google's Keyword Planner API to retrieve keyword metrics for your SEO research: Fetches monthly search volume for each keyword Provides historical trends data for the past 12 months Calculates keyword difficulty scores Delivers competition metrics from Google Ads Setup Fill the Set 20 Keywords with up to 20 Keywords of your choosing in an array e.g. ["keyword 1", "keyword 2",...] Create a Google Ads API account and add credentials to Get Search Data node Replace the Connect to your own database with your own database for the output How to Adjust it to Your Needs Change the Set 20 Keywords node input to a source of your choosing e.g. Airtable database with 20 keywords Connect to output source of your choosing More templates and n8n workflows >>> @simonscrapes

Monthly Spotify Track Archiving and Playlist Classification This n8n workflow allows you to automatically archive your monthly Spotify liked tracks in a Google Sheet, along with playlist details and descriptions. Based on this data, Claude 3.5 is used to classify each track into multiple playlists and add them in bulk. Who is this template for? This workflow template is perfect for Spotify users who want to systematically archive their listening history and organize their tracks into custom playlists. What problem does this workflow solve? It automates the monthly process of tracking, storing, and categorizing Spotify tracks into relevant playlists, helping users maintain well-organized music collections and keep a historical record of their listening habits. Workflow Overview Trigger Options**: Can be initiated manually or on a set schedule. Spotify Playlists Retrieval**: Fetches the current playlists and filters them by owner. Track Details Collection**: Retrieves information such as track ID and popularity from the user’s library. Audio Features Fetching**: Uses Spotify's API to get audio features for each track. Data Merging**: Combines track information with their audio features. Duplicate Checking**: Filters out tracks that have already been logged in Google Sheets. Data Logging**: Archives new tracks into a Google Sheet. AI Classification**: Uses an AI model to classify tracks into suitable playlists. Playlist Updates**: Adds classified tracks to the corresponding playlists. Setup Instructions Credentials Setup: Make sure you have valid Spotify OAuth2 and Google Sheets access credentials. Trigger Configuration: Choose between manual or scheduled triggers to start the workflow. Google Sheets Preparation: Set up a Google Sheet with the necessary structure for logging track details. Spotify Playlists Setup: Have a diverse range of playlists and exhaustive description (see example) ready to accommodate different music genres and moods. Customization Options Adjust Playlist Conditions**: Modify the AI model’s classification criteria to align with your personal music preferences. Enhance Track Analysis**: Incorporate additional audio features or external data sources for more refined track categorization. Personalize Data Logging**: Customize which track attributes to log in Google Sheets based on your archival preferences. Configure Scheduling**: Set a preferred schedule for periodic track archiving, e.g., monthly or weekly. Cost Estimate For 300 tracks, the token usage amounts to approximately 60,000 tokens (58,000 for input and 2,000 for completion), costing around 20 cents with Claude 3.5 Sonnet (as of October 2024). Playlists' Description Examples | Playlist Name | Playlist Description | |-------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------| | Classique | Indulge in the timeless beauty of classical music with this refined playlist. From baroque to romantic periods, this collection showcases renowned compositions. | | Poi | Find your flow with this dynamic playlist tailored for poi, staff, and ball juggling. Featuring rhythmic tracks that complement your movements. | | Pro Sound | Boost your productivity and focus with this carefully selected mix of concentration-enhancing music. Ideal for work or study sessions. | | ChillySleep | Drift off to dreamland with this soothing playlist of sleep-inducing tracks. Gentle melodies and ambient sounds create a peaceful atmosphere for restful sleep. | | To Sing | Warm up your vocal cords and sing your heart out with karaoke-friendly tracks. Featuring popular songs, perfect for solo performances or group sing-alongs. | | 1990s | Relive the diverse musical landscape of the 90s with this eclectic mix. From grunge to pop, hip-hop to electronic, this playlist showcases defining genres. | | 1980s | Take a nostalgic trip back to the era of big hair and neon with this 80s playlist. Packed with iconic hits and forgotten gems, capturing the energy of the decade.| | Groove Up | Elevate your mood and energy with this upbeat playlist. Featuring a mix of feel-good tracks across various genres to lift your spirits and get you moving. | | Reggae & Dub | Relax and unwind with the laid-back vibes of reggae and dub. This playlist combines classic reggae tunes with deep, spacious dub tracks for a chilled-out vibe. | | Psytrance | Embark on a mind-bending journey with this collection of psychedelic trance tracks. Ideal for late-night dance sessions or intense focus. | | Cumbia | Sway to the infectious rhythms of Cumbia with this lively playlist. Blending traditional Latin American sounds with modern interpretations for a danceable mix. | | Funky Groove | Get your body moving with this collection of funk and disco tracks. Featuring irresistible basslines and catchy rhythms, perfect for dance parties. | | French Chanson | Experience the romance and charm of France with this mix of classic and modern French songs, capturing the essence of French musical culture. | | Workout Motivation | Push your limits and power through your exercise routine with this high-energy playlist. From warm-up to cool-down, these tracks will keep you motivated. | | Cinematic Instrumentals | Immerse yourself in a world of atmospheric sounds with this collection of cinematic instrumental tracks, perfect for focus, relaxation, or contemplation. |

Purpose This workflow allows you to import any workflow from a file or another n8n instance and map the credentials easily. How it works A multi-form setup guides you through the entire process At the beginning you have two options: Upload a workflow file (JSON) Copy workflow from a remote n8n instance If you choose the second option, you get to choose one of your predefined (in the Settings node) remote instances first, then it retrieves a list of all the workflows using the n8n API which you then can choose a workflow from. Now both initial options come together - the workflow file is being processed In parallel all credentials of the current instance are being retrieved using the Execute Command node The next form page enables a mapping of all the credentials used in the workflow. The matching happens between the names (because one workflow can contain different credentials of the same type) of the original credentials and the ones available on the current instance. Every option then shows all available credentials of the same type. In addition the user has always the choice to create a new credential on the fly. For every option which was set to create a new credential, an empty credential is being created on the current instance using the n8n API. An emoji is being appended to the name, which indicates that it needs to be populated. Finally the workflow gets updated with the new credential ID’s and created on the current instance using the n8n API. Then the user gets a message, if the process has succeeded or not. Setup Select your credentials in the nodes which require those Configure your remote instance(s) in the Settings node. (You can skip this step, if you only want to use the File Upload feature) Every instance is defined as object with the keys name, apiKey and baseUrl. Those instances are then wrapped inside an array. You can find an example described within a note on the workflow canvas. How to use Grab the (production) URL of the Form from the first node Open the URL and follow the instructions given in the multi-form Disclaimer Security: Beware, that all credentials are being decrypted and processed within the workflow. Also the API keys to other n8n instances are stored within the workflow. This solution is primarily meant for transferring data between testing environments. For production use consider the n8n enterprise edition which provides a reliable way to deploy workflows between different environments without the need of manual credential mapping.

AI Content Generator Workflow Introduction This workflow automates the process of creating high-quality articles using AI, organizing them in Google Drive, and tracking their progress in Google Sheets. It's perfect for marketers, bloggers, and businesses looking to streamline content creation. With minimal setup, you can have a fully operational system to generate, save, and manage your articles in one cohesive workflow. How It Works Collect Inputs: Users fill out a form with details like article title, keywords, and instructions. Generate Content: AI creates an outline and writes the article based on user inputs. Organize Files: Saves the outline and final article in Google Drive for easy access. Track Progress: Updates Google Sheets with links to the generated content for tracking. Set Up Steps Time Required**: Approximately 15–20 minutes to connect all integrations and test the workflow. Steps**: Connect Google Drive and Google Sheets: Authorize access to store files and update the spreadsheet. Set Up OpenAI Integration: Add your OpenAI API key for generating the outline and article content. Customize the Form: Modify the form fields to match the details you want to collect for each article. Test the Workflow: Run the workflow with sample inputs to ensure everything works smoothly. This workflow not only simplifies the process of article creation but also sets a foundation for expanding into additional automations, like posting to social media platforms.

This n8n workflow simplifies the process of removing backgrounds from images stored in Google Drive. By leveraging the PhotoRoom API, this template enables automatic background removal, padding adjustments, and output formatting, all while storing the updated images back in a designated Google Drive folder. This workflow is very useful for companies or individuals that are spending a lot of time into removing the background from product images. How it Works The workflow begins with a Google Drive Trigger node that monitors a specific folder for new image uploads. Upon detecting a new image, the workflow downloads the file and extracts essential metadata, such as the file size. Configurations are set for background color, padding, output size, and more, which are all customizable to match specific requirements. The PhotoRoom API is called to process the image by removing its background and adding padding based on the settings. The processed image is saved back to Google Drive in the specified output folder with an updated name indicating the background has been removed. Requirements PhotoRoom API Key Google Drive API Access Customizing the Workflow Easily adjust the background color, padding, and output size using the configuration node. Modify the output folder path in Google Drive or replace Google Drive with another storage service if needed. For advanced use cases, integrate further image processing steps, such as adding captions or analyzing content using AI.

Automate Report Generation with n8n & Qualys Introducing the Save Qualys Reports to TheHive Workflow—a robust solution designed to automate the retrieval and storage of Qualys reports in TheHive. This workflow fetches reports from Qualys, filters out already processed reports, and creates cases in TheHive for the new reports. It runs every hour to ensure continuous monitoring and up-to-date vulnerability management, making it ideal for Security Operations Centers (SOCs). How It Works: Set Global Variables:** Initializes necessary global variables like base_url and newtimestamp. This step ensures that the workflow operates with the correct configuration and up-to-date timestamps. Ensure to change the Global Variables to match your environment. Fetch Reports from Qualys:** Sends a GET request to the Qualys API to retrieve finished reports. Automating this step ensures timely updates and consistent data retrieval. Convert XML to JSON:** Converts the XML response to JSON format for easier data manipulation. This transformation simplifies further processing and integration into TheHive. Filter Reports:** Checks if the reports have already been processed using their creation timestamps. This filtering ensures that only new reports are handled, avoiding duplicates. Process Each Report:** Loops through the list of new reports, ensuring each is processed individually. This step-by-step handling prevents issues related to bulk processing and improves reliability. Create Case in TheHive:** Generates a new case in TheHive for each report, serving as a container for the report data. Automating case creation improves efficiency and ensures that all relevant data is captured. Download and Attach Report:** Downloads the report from Qualys and attaches it to the respective case in TheHive. This automation ensures that all data is properly archived and easily accessible for review. Get Started: Ensure your Qualys and TheHive integrations are properly set up. Customize the workflow to fit your specific vulnerability management needs. Need Help? Join the discussion on our Forum or check out resources on Discord! Deploy this workflow to streamline your vulnerability management process, improve response times, and enhance the efficiency of your security operations.

This workflow automates the collection of comments from posts on a Facebook Page. Providing clean, structured data for analysis or further automation. What this workflow does Fetches recent posts from a Facebook Page. Retrieves comments for each post. Outputs structured data of Comments and Posts for further use. Setup Facebook Graph API: Connect your Access Token with the required permissions (pages_read_engagement, pages_read_user_content). Workflow: Set the Page ID and the number of posts to fetch in the "Set Number of Latest Posts to Fetch" node.

Purpose of workflow: The purpose of this workflow is to automate scraping of a website, transforming it into a structured format, and loading it directly into a Google Sheets spreadsheet. How it works: Web Scraping: Uses the Jina AI service to scrape website data and convert it into LLM-friendly text. Information Extraction: Employs an AI node to extract specific book details (title, price, availability, image URL, product URL) from the scraped data. Data Splitting: Splits the extracted information into individual book entries. Google Sheets Integration: Automatically populates a Google Sheets spreadsheet with the structured book data. Step by step setup: Set up Jina AI service: Sign up for a Jina AI account and obtain an API key. Configure the HTTP Request node: Enter the Jina AI URL with the target website. Add the API key to the request headers for authentication. Set up the Information Extractor node: Use Claude AI to generate a JSON schema for data extraction. Upload a screenshot of the target website to Claude AI. Ask Claude AI to suggest a JSON schema for extracting required information. Copy the generated schema into the Information Extractor node. Configure the Split node: Set it up to separate the extracted data into individual book entries. Set up the Google Sheets node: Create a Google Sheets spreadsheet with columns for title, price, availability, image URL, and product URL. Configure the node to map the extracted data to the appropriate columns.

Who is this workflow for? This workflow is the baseline workflow for anyone who needs to automate the process of posting 1-4 images to Bluesky using the Bluesky API. It is ideal for anyone looking to streamline their social media posting process, saving time and ensuring consistent content delivery. Use Case / Problem Solved Manually posting images and captions on Instagram can be time-consuming, especially for businesses and content creators managing multiple accounts. This workflow automates the process from image preparation to publishing, reducing manual effort and increasing efficiency. What this workflow does Trigger Initialization: The workflow starts with a manual trigger that can be adapted to other triggers (e.g., HTTP webhook or schedule). Set Parameters: The workflow includes a node that sets essential parameters, such as the Bluesky account ID, image URLs, and caption. Prepare Bluesky Session: A node creates the authenticated session data used by the upload and post operations later in the workflow. Publish Media: Nodes retrieve image files from the specified URLS and uploads them as blobs to Bluesky, a necessary pre-requisite for a Bluesky post to have images attached. Post text caption + images: A node does the final call to the Bluesky API, including the text caption and relevant image references. Setup Sign-in to Bluesky and create an App Password Add your username and App Password to the Define Credentials node. Set the caption (text content) of your post in the Set Caption node. Set 1-4 image URLs in the Set Images node Adapt the initial trigger as needed to fit your workflow's requirements (e.g., schedule, webhook). Adapt the caption and images nodes to accept dynamic parameters. Limitations This workflow assumes a minimum of 1 image URL to function. If you want a text-only post, remove the whole embed section from the JSON in last Post to Bluesky node, as well as relevant image attachment nodes. The 300-character limit in Bluesky includes the caption + hashtags + image alt text. Going over 300 will return a Record/description must not be longer than 300 graphemes error.

Important Notes: Check Legal Regulations: This workflow involves scraping, so ensure you comply with the legal regulations in your country before getting started. Better safe than sorry! Workflow Description: 😮‍💨 Tired of struggling with XPath, CSS selectors, or DOM specificity when scraping ? This AI-powered solution is here to simplify your workflow! With a vision-based AI Agent, you can extract data effortlessly without worrying about how the DOM is structured. This workflow leverages a vision-based AI Agent, integrated with Google Sheets, ScrapingBee, and the Gemini-1.5-Pro model, to extract structured data from webpages. The AI Agent primarily uses screenshots for data extraction but switches to HTML scraping when necessary, ensuring high accuracy. Key Features: Google Sheets Integration**: Manage URLs to scrape and store structured results. ScrapingBee**: Capture full-page screenshots and retrieve HTML data for fallback extraction. AI-Powered Data Parsing**: Use Gemini-1.5-Pro for vision-based scraping and a Structured Output Parser to format extracted data into JSON. Token Efficiency**: HTML is converted to Markdown to optimize processing costs. This template is designed for e-commerce scraping but can be customized for various use cases.

This n8n template combines an AI agent with n8n's multi-page forms to create a novel interaction which allows automated question-and-answer sessions. One of the more obvious use-cases of this interaction is what I'm calling the AI interviewer. You can read the full post here: https://community.n8n.io/t/build-your-own-ai-interview-agents-with-n8n-forms/62312 Live demo here: https://jimleuk.app.n8n.cloud/form/driving-lessons-survey How it works A form trigger is used to start the interview and a new session is created in redis to capture the transcript. An AI agent is then tasked to ask questions to the user regarding the topic of the interview. This is setup as a loop so the questions never stop unless the user wishes to end the interview. Each answer is recorded in our session set up earlier between questions. When the user requests to end the interview we break the loop and show the interview completion screen. Finally, the session is then saved in a Google Sheet which can then be shared with team members and for the purpose of data analysis. How to use You'll need to be on a n8n instance that is accessible to your target audience. Not technical enough to setup your own server? Try out n8n cloud and instantly deploy template! Remember to activate the workflow so the form trigger is published and available for users to use. Requirements Groq LLM for AI agent. Feel free to swap this out for any other LLM. Redis(-compatible) storage for capturing sessions Customising this workflow The next step would be adding tools! AI interviews with knowledge retrieval could definitely open up other possibilities. Eg. An onboarding wizard generating questions by pulling facts from internal knowledgebase.

Who is this template for? This workflow template is designed for sales, marketing, and business development professionals who want a cost-effective and efficient way to generate leads. By leveraging n8n core nodes, it scrapes business emails from Google Maps without relying on third-party APIs or paid services, ensuring there are no additional costs involved. Ideal for small business owners, freelancers, and agencies, this template automates the process of collecting contact information for targeted outreach, making it a powerful tool for anyone looking to scale their lead generation efforts without incurring extra expenses. You can watch the video tutorial here: https://youtu.be/HaiO-UeiKBA How it works This template streamlines email scraping from Google Maps using only n8n core nodes, ensuring a completely free and self-contained solution. Here’s how it operates: Input Queries You provide a list of queries, each consisting of keywords related to the type of business you want to target and the specific region or subregion you’re interested in. Iterates through Queries The workflow processes each query one at a time. For each query, it triggers a sub-workflow dedicated to handling the scraping tasks. Scrapes Google Maps for URLs Using these queries, the workflow scrapes Google Maps to collect URLs of business listings matching the provided criteria. Fetches HTML Content The workflow then fetches the HTML pages of the collected URLs for further processing. Extracts Emails Using a Code Node with custom JavaScript, the workflow runs regular expressions on the HTML content to extract business email addresses. Setup Add Queries: Open the first node, "Run Workflow" and input a list of queries, each containing the business keywords and the target region. Configure the Google Sheets Node: Open the Google Sheets node and select a document and specific sheet where the scraped results will be saved. Run the workflow: Click on "Test workflow" and watch your Google Sheets document gradually receive business email addresses. Customize as Needed: You can adjust the regular expressions in the Code Node to refine the email extraction logic or add logic to extract other kinds of information.

Who is this for? BlueSky users who are looking to send a "welcome message" to their new followers as a private message. What this workflow does This worflow will check for new followers on BlueSky every 60 minutes and send a private message to the new ones. Setup You need to create a BlueSky app password with private messages access. Fill your credentials and the message text on the corresponding nodes (see sticky notes). Manually run once the `Save followers to file` node to generate your initial followers list. Enable the workflow How to customize this workflow to your needs You can adjust the check frecuency, but be careful to avoid hitting the 100 createSession per day rate limit Feedback or comments You can leave comments, feedback or improvements about this workflow on the n8n forums

This workflow imports Productboard data into Snowflake, automating data extraction, mapping, and updates for features, companies, and notes. It supports scheduled weekly updates, data cleansing, and Slack notifications summarizing the latest insights. Features Fetches data from Productboard (features, companies, notes). Maps and processes data for Snowflake tables. Automates table creation, truncation, and updates. Summarizes new and unprocessed notes. Sends weekly Slack notifications with key insights. Setup Configure Productboard and Snowflake credentials in n8n. Update Snowflake table schemas to match your setup. Replace Slack channel ID and dashboard URL in the notification node. Activate the workflow and set the desired schedule.

Linear Project Status and End Date to Productboard feature Sync Sync project data between Linear and Productboard to keep teams aligned. This workflow updates Productboard features with the status and end date from Linear projects. It ensures consistent data and sends a Slack notification whenever changes are made. Features Listens for updates in Linear projects. Maps Linear statuses to Productboard feature statuses. Updates Productboard feature details including timeframe. Sends a Slack notification summarizing the updates. Setup Linear Credentials: Add your Linear API credentials in n8n. Productboard Credentials: Configure the Productboard API credentials in n8n. Linear Projects: Select the Linear project(s) you want to monitor for updates. Productboard Custom Field: Create a custom field in Productboard named "Linear Project". This field should store the URL of the Linear project you want to sync. Retrieve the UUID of the custom field in Productboard and set it up in the "Get Productboard Feature ID" node. Slack Notification: Update the Slack node with the desired Slack channel ID. Activate the Workflow: Enable the workflow to automatically sync data when triggered by updates in Linear.

This n8n template builds a meeting assistant that compiles timely reminders of upcoming meetings filled with email history and recent LinkedIn activity of other people on the invite. This is then discreetly sent via WhatsApp ensuring the user is always prepared, informed and ready to impress! How it works A scheduled trigger fires hourly to check for upcoming personal meetings. When found, the invite is analysed by an AI agent to pull email and LinkedIn details of the other invitees. 2 subworkflows are then triggered for each invitee to (1) search for last email correspondence with them and (2) scrape their LinkedIn profile + recent activity for social updates. Using both available sources, another AI agent is used to summarise this information and generate a short meeting prep message for the user. The notification is finally sent to the user's WhatsApp, allowing them ample time to review. How to use There are a lot of moving parts in this template so in it's current form, it's best to use this for personal rather than team calendars. The LinkedIn scraping method used in this workflow requires you to paste in your LinkedIn cookies from your browser which essentially let's n8n impersonate you. You can retrieve this from dev console or ask someone technical for help! Note: It may be wise to switch to other LinkedIn scraping approaches which do not impersonate your own account for production. Requirements OpenAI for LLM Gmail for Email Google Calendar for upcoming events WhatsApp Business account for notifications Customising this workflow Try adding information sources which are relevant to you and your invitees. Such as company search, other social media sites etc. Create an on-demand version which doesn't rely on the scheduled trigger. Sometimes you want to know prepare for meetings hours or days in advance where this could help immensely.

Printify Automation - Update Title and Description Workflow This n8n workflow automates the process of retrieving products from Printify, generating optimized product titles and descriptions, and updating them back to the platform. It leverages OpenAI for content generation and integrates with Google Sheets for tracking and managing updates. Features Integration with Printify**: Fetch shops and products through Printify's API. AI-Powered Optimization**: Generate engaging product titles and descriptions using OpenAI's GPT model. Google Sheets Tracking**: Log and manage updates in Google Sheets. Custom Brand Guidelines**: Ensure consistent tone by incorporating brand-specific instructions. Loop Processing**: Iteratively process each product in batches. Workflow Structure Nodes Overview Manual Trigger: Manually start the workflow for testing purposes. Printify - Get Shops: Retrieves the list of shops from Printify. Printify - Get Products: Fetches product details for each shop. Split Out: Breaks down the product list into individual items for processing. Loop Over Items: Iteratively processes products in manageable batches. Generate Title and Desc: Uses OpenAI GPT to create optimized product titles and descriptions. Google Sheets Integration: Trigger: Monitors Google Sheets for changes. Log Updates: Records product updates, including old and new titles/descriptions. Conditional Logic: If Nodes: Ensure products are ready for updates and stop processing once completed. Printify - Update Product: Sends updated titles and descriptions back to Printify. Brand Guidelines + Custom Instructions: Sets brand tone and seasonal instructions. Setup Instructions Prerequisites n8n Instance: Ensure n8n is installed and configured. Printify API Key: Obtain an API key from your Printify account. Add it to n8n under HTTP Header Auth. OpenAI API Key: Obtain an API key from OpenAI. Add it to n8n under OpenAI API. Google Sheets Integration: Share your Google Sheets with the Google API service account. Configure Google Sheets credentials in n8n. Workflow Configuration Set Brand Guidelines: Update the Brand Guidelines + Custom Instructions node with your brand name, tone, and seasonal instructions. Batch Size: Configure the Loop Over Items node for optimal batch sizes. Google Sheets Configuration: Set the correct Google Sheets document and sheet names in the integration nodes. Run the Workflow: Start manually or configure the workflow to trigger automatically. Key Notes Customization**: Modify API calls to support other platforms like Printful or Vistaprint. Scalability**: Use batch processing for efficient handling of large product catalogs. Error Handling**: Configure retries or logging for any failed nodes. Output Examples Optimized Content Example Input Title**: "Classic White T-Shirt" Generated Title**: "Stylish Classic White Tee for Everyday Wear" Input Description**: "Plain white T-shirt made of cotton." Generated Description**: "Discover comfort and style with our classic white tee, crafted from premium cotton for all-day wear. Perfect for casual outings or layering." Next Steps Monitor Updates: Use Google Sheets to review logs of updated products. Expand Integration: Add support for more Printify shops or integrate with other platforms. Enhance AI Prompts: Customize prompts for different product categories or seasonal needs. Feel free to reach out for additional guidance or troubleshooting!

Upload Public-Facing Images to an S3 Cloudflare Bucket via Slack Modal 🛠 Who is this for? This workflow is for teams that use Slack for internal communication and need a streamlined way to upload public-facing images to an S3 Cloudflare bucket. It's especially beneficial for DevOps, marketing, or content management teams who frequently share assets and require efficient cloud storage integration. 💡 What problem does this workflow solve? Manually uploading images to cloud storage can be time-consuming and disruptive, especially if you're already working in Slack. This workflow automates the process, allowing you to upload images directly from Slack via a modal popup. It reduces friction and keeps your workflow within a single platform. 🔍 What does this workflow do? This workflow connects Slack with an S3 Cloudflare bucket to simplify the image-uploading process: Slack Modal Interaction**: Users trigger a Slack modal to select images for upload. Dynamic Folder Management**: Choose to create a new folder or use an existing one for uploads. S3 Integration**: Automatically uploads the images to a specified S3 Cloudflare bucket. Slack Confirmation**: After upload, Slack sends a confirmation with the uploaded file URLs. 🚀 Setup Instructions Prerequisites Slack Bot with the following permissions: commands files:write files:read chat:write Cloudflare S3 Credentials: Create an API token with write access to your S3 bucket. n8n Instance: Ensure n8n is properly set up with webhook capabilities. Steps Configure Slack Bot: Set up a Slack app and enable the Events API. Add your n8n webhook URL to the Events Subscription section. Add Credentials: Add your Slack API and S3 Cloudflare credentials to n8n. Customize the Workflow: Open the Idea Selector Modal node and update folder options to suit your needs. Update the Post Image to Channel node with your Slack channel ID. Deploy the Workflow: Activate the workflow and test by triggering the Slack modal. 🛠 How to Customize This Workflow Adjust the Slack Modal You can modify the modal layout in the Idea Selector Modal node to add additional fields or adjust the styling. Change the Bucket Structure Update the Upload to S3 Bucket node to customize the folder paths or change naming conventions. 🔗 References and Helpful Links Slack API Documentation Cloudflare S3 Setup n8n Documentation 📓 Workflow Notes Key Features: Slack Integration**: Uses Slack modal interactions to streamline the upload process. Cloud Storage**: Automatically uploads to a Cloudflare S3 bucket. User Feedback**: Sends a Slack message with file URLs upon successful upload. Setup Dependencies: Slack API token Cloudflare S3 credentials n8n webhook configuration Sticky Notes Included Sticky notes are embedded within the workflow to guide you through configuration and explain node functionality. 🌟 Why Use This Workflow? This workflow keeps your image-uploading process intuitive, efficient, and fully integrated with tools you already use. By leveraging n8n's flexibility, you can ensure smooth collaboration and quick sharing of public-facing assets without switching contexts.

This workflow facilitates seamless synchronization between Entra (Microsoft Azure AD) and Zammad. It automates the following processes: Fetch Entra Group Members: Retrieves users from a designated Entra group. These users are candidates for synchronization. Create Universal User Object: Extracts key user information, such as email, phone, and name, and formats it for Zammad compatibility. Synchronize with Zammad: Identifies users in Zammad who need updates based on Entra data. Adds new users from Entra to Zammad. Deactivates users in Zammad if they are no longer in the Entra group. Key Features Dynamic Matching**: Compares users from Entra with existing Zammad users based on email and updates records accordingly. Efficient Management**: Automatically creates, updates, or deactivates Zammad users based on their status in Entra. Custom Fields**: Supports custom field mapping, ensuring enriched user profiles in Zammad. Setup Instructions Microsoft Entra Integration: Ensure proper API permissions for accessing Entra groups and members. Configure Microsoft OAuth2 credentials in n8n. Zammad Integration: Set up Zammad API credentials with appropriate access rights. Customize the workflow to include additional fields or map existing fields as needed. Run Workflow: Trigger the workflow manually or set up an automation schedule (e.g., daily sync). Review created/updated/deactivated users in Zammad. Use Cases IT Administration**: Keep your support system in sync with the organization’s Entra data. User Onboarding**: Automatically onboard new hires into Zammad based on Entra groups. Access Management**: Ensure accurate and up-to-date user records in Zammad. Prerequisites Access to an Entra (Azure AD) environment with group data. A Zammad instance with API credentials for user management. A custom field in Zammad User Object (entra_key) of type String. A custom field in Zammad User Object (entra_object_type) of type `Single selection field with two key value pairs user = User contact = Contact` This workflow is fully customizable and can be adapted to your organization’s specific needs. Save time and reduce manual errors by automating your user sync process with this template! If you have found an error or have any suggestions, please report them here on Github.

Automating daily notifications of the latest releases from a GitHub repository. This template is ideal for developers and project managers looking to stay up-to-date with software updates. How it Works: Daily Trigger: The workflow initiates daily using the Schedule Trigger node. Fetch Repository Data: The HTTP Request node retrieves the latest release details from the specified GitHub repository. Check if new: The IF node check if the release was done in the last 24 hours. Split Content: The Split Out node processes the JSON response to extract and structure relevant data. Convert Markdown: The Markdown node converts release notes from Markdown format to HTML, making them ready to use in emails. Send a notification by email Key Features: Simple to customize by modifying the GitHub URL. Automatically processes and formats release notes for better readability. Modular design, allowing integration with other workflows like Gmail or Slack notifications. Setup Steps: Modify Repository URL: Update the Sticky Note node with the URL of the repository you want to monitor. Modify SMTP details: Update the Send Email node with your SMTP details.

How it Works This n8n template makes it possible to send emails directly from your Obsidian notes. It leverages the power of the Obsidian Post Webhook plugin, allowing seamless integration between your notes and the email workflow. What it does: Receives note content and metadata from Obsidian via a Webhook. Parses YAML frontmatter to define email recipients, subject, and more. Automatically processes attachments, encoding them into an email-friendly format. Sends emails via Gmail and confirms the status back to Obsidian. Includes a testing feature to verify everything works before going live. Set-up Steps Webhook Configuration: Set your n8n POST Webhook URL in the Obsidian Obsidian Post Webhook plugin settings. Email Integration: Submit the Gmail credentials in n8n email nodes. Test the Workflow: Run a test from Obsidian to ensure the template functions correctly. Activate and Enjoy: Start sending customized emails with attachments from your notes in no time!

This workflow facilitates seamless synchronization between Entra (Microsoft Azure AD) and Zammad. It automates the following processes: Fetch Entra Contacts: Create Universal User Object: Extracts key user information, such as email, phone, and name, and formats it for Zammad compatibility. Synchronize with Zammad: Identifies users in Zammad who need updates based on Entra data. Adds new users from Entra to Zammad. Deactivates users in Zammad if they are no longer in Entra. Key Features Dynamic Matching**: Compares contacts from Entra with existing Zammad users based on email and updates records accordingly. Efficient Management**: Automatically creates, updates, or deactivates Zammad users based on their status in Entra. Custom Fields**: Supports custom field mapping, ensuring enriched user profiles in Zammad. Setup Instructions Microsoft Entra Integration: Ensure proper API permissions for accessing Entra contacts. Configure Microsoft OAuth2 credentials in n8n. Zammad Integration: Set up Zammad API credentials with appropriate access rights. Customize the workflow to include additional fields or map existing fields as needed. Run Workflow: Trigger the workflow manually or set up an automation schedule (e.g., daily sync). Review created/updated/deactivated users in Zammad. Use Cases IT Administration**: Keep your support system in sync with the organization’s Entra data. Customer Management**: Ensure accurate and up-to-date user records in Zammad. Prerequisites Access to an Entra (Azure AD) environment with contacts data. A Zammad instance with API credentials for user management. A custom field in Zammad User Object (entra_key) of type String. A custom field in Zammad User Object (entra_object_type) of type `Single selection field with two key value pairs user = User contact = Contact` This workflow is fully customizable and can be adapted to your organization’s specific needs. Save time and reduce manual errors by automating your user sync process with this template! If you have found an error or have any suggestions, please report them here on Github.

This n8n template showcases a cool feature of n8n Forms where the form itself can be defined dynamically using the form fields schema. It may be debateable how useful this template actually is since both Airtable and Baserow provide form interfaces already but still a great exercise and demonstration if ever the use-case comes around. How it works A form trigger is used to dynamically select a database/table from which to build the n8n form from. the table's schema is imported into the workflow and using the code node, is converted into the n8n form fields schema. This let's us dynamically build the fields in our n8n form when we choose to define the form using the JSON option. Once the n8n form submits, we convert the values back into our table's API schema so that we can create a new row. Note any files/attachments fields are removed as they need to be handled separately. Files are processed separately as they may first need to be stored. Once complete, the reference is saved into the newly created row. Check out the example Airtable here - https://airtable.com/appfP15Xd0aVZR9xV/shrGFgXLyQ4Jg58SU How to use The n8n form is autogenerated which means you only need provide access to the table. Using this approach, this template can be reused for any number of Airtable and/or Baserow tables. Requirements You'll need either an Airtable account or a Baserow account to use this template. Accessible n8n instance to your users Customising this workflow Not using either Airtable or Baserow? Theoretically any datastore which provides a fields schema can be used with this template. If you're feeling creative, split the table into multiple forms for a better user experience.

This workflow leverages n8n to perform automated Google Maps API queries and manage data efficiently in Google Sheets. It's designed to extract specific location data based on a given list of ZIP codes and categories. Features Queries the Google Maps API for location data using predefined ZIP codes and subcategories. Filters, de-duplicates, and organizes data into structured rows in Google Sheets. Implements exponential backoff retries to handle API rate limits. Logs and updates statuses directly in Google Sheets for easy tracking. Prerequisites Google OAuth Credentials: A configured Google Cloud project for Google Maps API and Sheets API access. Google Sheets: A sheet with ZIP codes and categories defined (e.g., "AZ Zips"). n8n Setup: A running instance of n8n with credentials configured for Google OAuth. Setup Instructions 1. Prepare Google Sheets Add the ZIP codes to the "AZ Zips" sheet. Define subcategories in another sheet (e.g., "Google Maps Categories"). Provide the sheet's URL in the Settings node of the workflow. 2. Configure API Access Set up Google OAuth credentials for Maps and Sheets APIs in n8n. Ensure your API key has access to the places.searchText endpoint. 3. Workflow Customization Modify textQuery parameters in the GMaps API node to match your query needs. Adjust trigger intervals as required (e.g., manual or scheduled execution). 4. Run the Workflow Execute the workflow manually or schedule periodic runs to keep your data updated. Notes This workflow includes robust error handling to retry failed API calls with exponential backoff. All data is organized and logged directly in Google Sheets for easy reference and updates. For more information or issues, feel free to reach out!

Purpose of workflow: This AI-powered workflow is designed to automatically generate comprehensive, well-researched articles on any given topic. It utilizes a team of AI agents to streamline the research and writing process, producing high-quality content with proper citations and credible sources. How it works Multi-agent team: Research Leader: Plans and conducts initial research, creating a table of contents. Project Planner: Breaks down the table of contents into manageable sections. Research Assistants: Multiple agents that conduct in-depth research on assigned sections. Editor: Compiles and refines the final article, ensuring coherence and proper citations. Key features: Utilizes Perplexity AI for internet search and citation capabilities Produces well-structured articles with proper citations Customizable parameters (topic, tone, word count, number of sections) Step by step setup: Get account from OpenRouter.ai to access Perplexity API Set API key in the Perplexity API node Credential key name : Authorization and key value Bearer <api-key value>

Address Validation Workflow About This workflow automates the process of validating and correcting client shipping addresses in Billbee, ensuring accurate delivery information. It's ideal for e-commerce businesses looking to save time and reduce errors in their order fulfillment process. The workflow uses Billbee, an order management platform for small to medium-sized online retailers, and the Endereco API for address validation. Who Is This For? E-Commerce Businesses**: Streamline order fulfillment by automatically correcting common shipping address errors. Warehouse Teams**: Reduce manual work and ensure packages are shipped to the correct address. Small to Medium-Sized Retailers**: Businesses using Billbee to manage orders and requiring efficient, automated solutions for address validation. How it Works Trigger: Workflow starts via a Billbee Webhook when an order is imported. Fetch Data: Retrieve the client's shipping address using the Order ID. Validate Address: Send the address to the Endereco API for validation and correction (e.g., house number errors). Conditional Actions: Valid Address: Update the address in Billbee. Invalid Address: Tag the order with "Validation Error." Track Status: Add tags in Billbee for processed orders. Setup Steps API Keys: Obtain Billbee Developer/User API Keys and Endereco API Key. Billbee Rule: Create an automation rule: Trigger: Order imported. Action: Call External URL with OrderId to trigger n8n workflow. Optional: Use a secondary trigger (e.g., order state changes to "gepackt") for manual corrections. Customization Options Filter Delivery Addresses: Customize filters to exclude specific delivery types, such as pickup shops ("Postfiliale," "Paketshop," or "Packstation"). Filters can be adjusted within Billbee or in the workflow. Error Handling: Configure additional actions for orders that fail validation, such as notifying your team or flagging orders for manual review. Order Tags: Define custom tags in Billbee to better track order statuses (e.g., "Address Corrected," "Validation Error"). Trigger Types: Use additional triggers such as changes to order states (e.g., "gepackt" or "In Fulfillment") for manual corrections or validations. Address Fields: Modify the workflow to focus on specific address components, such as postal codes, city names, or country codes. Validation Rules: Adjust Endereco API settings or add custom logic to refine validation criteria based on your business needs. API Documentation Endereco**: Endereco API Docs Billbee**: Billbee API Docs

How it works This workflow gets the search console results data and exports this to google sheets. This makes it easier to visualize and do other SEO related tasks and activities without having to log into Search Console Setup and use Set your desired schedule Enter your desired domain Connect to your Google sheets or make a copy of this sheet. Detailed Setup Inputs and Outputs:** Input: API response from Google Search Console regarding keywords, page data, and date data. Output: Entries written to Google Sheets containing keyword data, clicks, impressions, CTR, and positions. Setup Instructions: Prerequisites:** An n8n instance set up and running. Active Google Account with access to Google Search Console and Google Sheets. Google OAuth 2.0 credentials for API access. Step-by-Step Setup:** Open n8n and create a new workflow. Add the nodes as described in the JSON. Configure the Google OAuth2 credentials in n8n to enable API access. Set your domain in the Set your domain node. Customize the Google Sheets document URLs to your personal sheets. Adjust the schedule in the Schedule Trigger node as per your requirements. Save the workflow. Configuration Options:** You can customize the date ranges in the body of the HttpRequest nodes. Adjust any fields in the Edit Fields nodes based on different data requirements. Use Case Examples: Useful in tracking website performance over time using Search Console metrics. Ideal for digital marketers, SEO specialists, and web analytics professionals. Offers value in compiling performance reports for stakeholders or team reviews. Running and Troubleshooting: Running the Workflow:** Trigger the workflow manually or wait for the schedule to run it automatically. Monitoring Execution:** Check the execution logs in n8n's dashboard to ensure all nodes complete successfully. Common Issues:** Invalid OAuth credentials – ensure credentials are set up correctly. Incorrect Google Sheets URLs – double-check document links and permissions. Scheduling conflicts – make sure the schedule set does not overlap with other workflows.

This n8n template scrapes a list of AI grants from grants.gov and qualifies them using AI; determining interest and eligibility for the business. It then sends an email alert of interesting items to team members in an email. The template also shows how you can use the "Remove Duplicates" node to simplify deduplication of external listings without the need to manage this yourself. Not particularly interested in AI Grants? This template works for other tender websites as long as you're able to scrape them. How it works A scheduled trigger is set to fetch a list of AI grants listed on the grants.gov website in the past day. A Remove Duplicates node is used to track Grant IDs to filter out those already processed by the workflow. New grants are summarized and analysed by AI nodes to determine eligibility and interest which is then saved to an Airtable database. Another scheduled trigger starts a little later than the first to collect and summarize the new grants The results are then compiled into an email template using the HTML node, in the form of a newsletter designed to alert and brief team members of new AI grants. This email is then sent to a list of subscribers using the gmail node. How to use Make a copy of sample Airtable here: https://airtable.com/appiNoPRvhJxz9crl/shrRdP6zstgsxjDKL The filters for fetching the grants is currently set to the "AI" category. Feel free to change this to include more categories. Not interested in grants, this template can works for other sources of leads just change the endpoint and how you're defining the item ID to track. Requirements Airtable for database OpenAI for LLM Note: These are not hard requirements and can be exchanged for services available to you. customising the workflow "Eligibility" criteria at this stage may be better served by identifying hard blockers instead ie. certifications, geographical considerations or certain legal checks. Be sure to mention any hard blockers into the Eligibility prompt. Not particularly interested in AI prompts? This template works for other tender websites as long as you're able to scrape them.

Community Node Disclaimer: This workflow uses community nodes and is compatible only with self-hosted n8n environments. How It Works Enhanced Calendly Integration: This workflow processes bookings and cancellations in Calendly, dynamically managing invitee and guest data with KlickTipp. Data Transformation: Dates and times are converted into formats (UNIX timestamps) compatible with KlickTipp’s API, ensuring seamless data integration. Key Features Calendly Trigger: Captures new bookings or cancellations of events, including participant details. Invitee and Guest Subscription in KlickTipp: Adds or updates invitees and guests in KlickTipp based on booking details (event name, time, join link, reschedule link, cancel link, etc.). Tracks and processes cancellations for both invitees and guests. Handles rescheduling intelligently to avoid redundant operations. Guest-Specific Operations: Processes guests individually for bookings and cancellations using dynamic arrays of email addresses. Recovers guest data from invitee records for cancellations since Calendly does not provide guest data upon cancellation. Data Processing: Standardizes and validates input fields Converts phone numbers to numeric-only format with international prefixes. Transforms dates into UNIX timestamps. Reads out the name of the invitee based on both possible input fields for name (name vs. firstname and lastname field setup). Error Handling: Validates critical fields like phone numbers, URLs, and dates to prevent incorrect data submissions. Setup Instructions Authentication: Set up the Calendly and KlickTipp nodes in your n8n instance. Configure authentication for both Calendly and KlickTipp nodes. Custom Field Preparation in KlickTipp: Create the following custom fields in KlickTipp to align with workflow requirements: | Feld-Name | Feld-Typ | |----------------------------------|------------------| | Calendly_event_name | Zeile | | Calendly_join_url | URL | | Calendly_reschedule_url | URL | | Calendly_cancel_url | URL | | Calendly_event_start_datetime | Datum & Zeit | | Calendly_event_end_datetime | Datum & Zeit | | Calendly_invitee_start_date | Datum | | Calendly_invitee_end_date | Datum | | Calendly_invitee_start_time | Zeit | | Calendly_invitee_end_time | Zeit | | Calendly_invitee_timezone | Zeile | | Calendly_invitee_guests_adresses| Zeile | After creating fields, allow 10-15 minutes for them to sync. If fields don’t appear, reconnect your KlickTipp credentials. Field Mapping and Adjustments: Open each KlickTipp node and map fields to match your setup. The workflow includes placeholders for: Invitee details (first name, last name, email, and phone). Event details (start/end times, timezone, etc.). Workflow Logic Trigger via Calendly event Booking: A new form event booking or cancellation from Calendly initiates the workflow Data Transformation: Processes raw Calendly event data to ensure compatibility with KlickTipp’s API. Add to KlickTipp Subscriber List: Adds invitees and guests to the designated KlickTipp list, including event-specific details. Benefits Efficient lead generation: Contacts from event bookings are automatically imported into KlickTipp and can be used immediately, saving time and increasing the conversion rate. Automated processes: Experts can start workflows directly, such as reminder emails or course admissions, reducing administrative effort. Error-free data management: The template ensures precise data mapping, avoids manual corrections and reinforces a professional appearance. Testing and Deployment Test the workflow by triggering a Calendly event and verifying data updates in KlickTipp. Notes: Customization: Update field mappings within the KlickTipp nodes to align with your account setup. This ensures accurate data syncing.

Use Case Generate keywords for your Amazon product. You want to find more keywords for advertising your product on Amazon. What this Workflow Does The workflow connects to Amazon's completion API to retrieve keywords for your advertising campaigns Use Airtable to send the workflow your keywords. Download airtable here. It sends the keyword to Amazon and returns keywords related to your keyword. It stores the results back into Airtable. How to Adjust it to Your Needs You can modify the Amazon Completion API URL to get more data back from Amazon. Made by Rumjahn

This n8n template monitors active support issues in Linear.app to track the mood of their ongoing conversation between reporter and assignee using Sentiment Analysis. When sentiment dips into the negative, a notification is sent via Slack to alert the team. How it works A scheduled trigger is used to fetch recently updated issues in Linear using the GraphQL node. Each issue's comments thread is passed into a simple Information Extractor node to identify the overall sentiment. The resulting sentiment analysis combined with the some issue details are uploaded to Airtable for review. When the template is re-run at a later date, each issue is re-analysed for sentiment Each issue's new sentiment state is saved to the airtable whilst its previous state is moved to the "previous sentiment" column. An Airtable trigger is used to watch for recently updated rows Each matching Airtable row is filtered to check if it has a previous non-negative state but now has a negative state in its current sentiment. The results are sent via notification to a team slack channel for priority. Check out the sample Airtable here: https://airtable.com/appViDaeaFw4qv9La/shrq6HgeYzpW6uwXL How to use Modify the GraphQL filter to fetch issues to a relevant issue type, team or person. Update the Slack channel to ensure messages are sent to the correct location or persons. The Airtable also serves to give a snapshot of Sentiment across support tickets for a given period. It's possible to use this to assess the daily operations. Requirements Linear for issue tracking (but feel free to use another system if preferred) Airtable for Database OpenAI for LLM and Sentiment Analysis Customising the workflow Add more granular levels of sentiment to reduce the number of alerts. Explore different types of sentiment based on issue types and customer types. This may help prioritise alerts and response. Run across teams or categories of issues to get an overview of sentiment across the support organisation.

This n8n template demonstrates a simple approach to using AI to automate the generation of blog content which aligns to your organisation's brand voice and style by using examples of previously published articles. In a way, it's quick and dirty "training" which can get your automated content generation strategy up and running for very little effort and cost whilst you evaluate our AI content pipeline. How it works In this demonstration, the n8n.io blog is used as the source of existing published content and 5 of the latest articles are imported via the HTTP node. The HTML node is extract the article bodies which are then converted to markdown for our LLMs. We use LLM nodes to (1) understand the article structure and writing style and (2) identify the brand voice characteristics used in the posts. These are then used as guidelines in our final LLM node when generating new articles. Finally, a draft is saved to Wordpress for human editors to review or use as starting point for their own articles. How to use Update Step 1 to fetch data from your desired blog or change to fetch existing content in a different way. Update Step 5 to provide your new article instruction. For optimal output, theme topics relevant to your brand. Requirements A source of text-heavy content is required to accurately breakdown the brand voice and article style. Don't have your own? Maybe try your competitors? OpenAI for LLM - though I recommend exploring other models which may give subjectively better results. Wordpress for blog but feel free to use other preferred publishing platforms. Customising this workflow Ideally, you'd want to "train" your agent on material which is similar to your output ie. your social media post may not get the best results from your blog content due to differing formats. Typically, this brand voice extraction exercise should run once and then be cached somewhere for reuse later. This would save on generation time and overall cost of the workflow.

Instructions This automation enables you to just upload any Image (via Form) of a Logo Sheet, containing multiple Images of Product Logos (most likely) which brings them in some context to one another. After submitting an AI-Agent eats that Logo Sheet, turning it into an List of "Productname" and "Attributes", also checks if Tools are kind of similar to another, given the Context of the Image. We utilize AI Vision capabilities for that. NOTE: It might not be able to extract all informations. For a "upload and forget it" Workflow it works for me. You can even run it multiple times, to be sure. But if you need to make sure it extracts everything you might need to think about an Multi-Agent Setup with Validation-Agent Steps. Once the Agent finishes the extraction, it will traditionally and deterministicly add those Attributes to Airtable (Creates those, if not already existing.) and also Upserts the Tool Informations. It uses MD5 Hashes for turning Product Names into.. something fancy really, you could also use it without that, but I wanted to have something that looks atleast like an ID. Setup Set Up the Airtable like shown below. Update and set Credentials for all Airtable Nodes. Check or Adjust the Prompt of the Agent matching your use-case. Activate the Workflow. Open the Form (default: https://your-n8n.io/form/logo-sheet-feeder) Enjoy growing your Airtable. Enjoy the workflow! ❤️ let the work flow — Workflow Automation & Development

Vector Database as a Big Data Analysis Tool for AI Agents Workflows from the webinar "Build production-ready AI Agents with Qdrant and n8n". This series of workflows shows how to build big data analysis tools for production-ready AI agents with the help of vector databases. These pipelines are adaptable to any dataset of images, hence, many production use cases. Uploading (image) datasets to Qdrant Set up meta-variables for anomaly detection in Qdrant Anomaly detection tool KNN classifier tool For anomaly detection The first pipeline to upload an image dataset to Qdrant. 2. This is the second pipeline to set up cluster (class) centres & cluster (class) threshold scores needed for anomaly detection. The third is the anomaly detection tool, which takes any image as input and uses all preparatory work done with Qdrant to detect if it's an anomaly to the uploaded dataset. For KNN (k nearest neighbours) classification The first pipeline to upload an image dataset to Qdrant. The second is the KNN classifier tool, which takes any image as input and classifies it on the uploaded to Qdrant dataset. To recreate both You'll have to upload crops and lands datasets from Kaggle to your own Google Storage bucket, and re-create APIs/connections to Qdrant Cloud (you can use Free Tier cluster), Voyage AI API & Google Cloud Storage. [This workflow] Setting Up Cluster (Class) Centres & Cluster (Class) Threshold Scores for Anomaly Detection Preparatory workflow to set cluster centres and cluster threshold scores so anomalies can be detected based on these thresholds. Here, we're using two approaches to set up these centres: the "distance matrix approach" and the "multimodal embedding model approach".

This workflow automates the process of discovering and extracting APIs from various services, followed by generating custom schemas. It works in three distinct stages: research, extraction, and schema generation, with each stage tracking progress in a Google Sheet. 🙏 Jim Le deserves major kudos for helping to build this sophisticated three-stage workflow that cleverly automates API documentation processing using a smart combination of web scraping, vector search, and LLM technologies. How it works Stage 1 - Research: Fetches pending services from a Google Sheet Uses Google search to find API documentation Employs Apify for web scraping to filter relevant pages Stores webpage contents and metadata in Qdrant (vector database) Updates progress status in Google Sheet (pending, ok, or error) Stage 2 - Extraction: Processes services that completed research successfully Queries vector store to identify products and offerings Further queries for relevant API documentation Uses Gemini (LLM) to extract API operations Records extracted operations in Google Sheet Updates progress status (pending, ok, or error) Stage 3 - Generation: Takes services with successful extraction Retrieves all API operations from the database Combines and groups operations into a custom schema Uploads final schema to Google Drive Updates final status in sheet with file location Ideal for: Development teams needing to catalog multiple APIs API documentation initiatives Creating standardized API schema collections Automating API discovery and documentation Accounts required: Google account (for Sheets and Drive access) Apify account (for web scraping) Qdrant database Gemini API access Set up instructions: Prepare your Google Sheets document with the services information. Here's an example of a Google Sheet – you can copy it and change or remove the values under the columns. Also, make sure to update Google Sheets nodes with the correct Google Sheet ID. Configure Google Sheets OAuth2 credentials, required third-party services (Apify, Qdrant) and Gemini. Ensure proper permissions for Google Drive access.

Overview This n8n workflow automates the creation of 9:16 aspect ratio images optimized for short-form video content and thumbnails. It integrates multiple tools to retrieve content, generate scripts, and create AI-generated imagery. Key Features Trigger Workflow Manually The workflow starts when triggered manually in n8n. Retrieve Brand Guidelines Fetch brand elements like style, tone, and guidelines from Airtable. SEO Keywords and Blog Post Retrieval Retrieves blog posts and associated SEO keywords from Airtable to form the basis of image content. Content Preparation Uses GPT-4 to prepare a 4-scene script and thumbnail prompts for short-form videos. AI Image Generation Uses Leonardo.ai API to generate: Thumbnail Images Scene-specific Images (9:16 Aspect Ratio) Airtable Asset Management Generated assets (images) are saved back into Airtable with metadata like URLs and file sizes. Tools and Integrations n8n**: Workflow automation platform. OpenAI**: Generates scripts and prompts (GPT-4O-MINI). Leonardo.ai**: AI tool for improving prompts and generating high-quality images. Airtable**: Used as a data source for brand guidelines, blog posts, and to store generated assets. Workflow Steps Manual Trigger Initiate the workflow. Retrieve Brand and SEO Guidelines Fetch essential brand elements like tone, style, and keywords. Filter and Fetch Blog Content Search for blog posts relevant to selected SEO keywords. Script Preparation Use GPT-4 to generate a script with image prompts for scenes and thumbnails. Image Generation Call Leonardo.ai to create: Scene Images in 9:16 Aspect Ratio. A Thumbnail Image with an improved prompt. Store Assets Save generated assets (images) to Airtable for future use. Workflow Structure Nodes Breakdown: Manual Trigger**: Start the workflow. Get Brand Guidelines**: Pull brand-related information (style, tagline, tone, etc.) from Airtable. Set Guidelines**: Prepare fetched data. Get SEO Keywords**: Retrieve keywords to filter relevant content. Keyword Filter*: Filter results for specified keywords (e.g., *"AI Automation"). Script Prep**: Generate 4-scene scripts and prompts with GPT-4. Leo - Improve Prompt**: Improve image prompts for clarity and detail. Leo - Generate Image**: Create AI-generated images for scenes and thumbnails. Wait Nodes**: Ensures Leonardo image generation is complete. Add Asset Info**: Store the generated images back into Airtable with metadata. API Credentials Required Ensure the following credentials are configured in n8n: OpenAI API Key Leonardo.ai API Key Airtable API Token Output Generated Images**: High-quality AI-generated images with a 9:16 aspect ratio. Saved Metadata**: Asset details (URLs, sizes, types) stored in Airtable. Usage Import this workflow into n8n. Set up your Airtable API, Leonardo.ai API, and OpenAI API credentials. Run the workflow manually. Monitor image generation and check the Airtable output for results. Tags OpenAI** RunwayML** Leonardo** Airtable** Video Automation** Author AlexK1919 AI-Native Workflow Architect More Workflow Templates YouTube Channel Connect with Alex

-- Disclaimer: This workflow uses a community node and therefore only works for self-hosted n8n users -- Transform YouTube videos into comprehensive summaries and structured analysis instantly. This n8n workflow automatically extracts, processes, and analyzes video transcripts to deliver clear, organized insights without watching the entire video. Time-Saving Features 🚀 Instant Processing Simply provide a YouTube URL and receive a structured summary within seconds, eliminating the need to watch lengthy videos. Perfect for research, learning, or content analysis. 🤖 AI-Powered Analysis Leverages GPT-4o-mini to analyze video transcripts, organizing key concepts and insights into a clear, hierarchical structure with main topics and essential points. Smart Processing Pipeline 📝 Automated Transcript Extraction Supports public YouTube video Handles multiple URL formats Extracts complete video transcripts automatically 🧠 Intelligent Content Organization Breaks down content into main topics Highlights key concepts and terminology Maintains technical accuracy while improving clarity Structures information logically with markdown formatting Perfect For 📚 Researchers & Students Quick comprehension of educational content and lectures without watching entire videos. 💼 Business Professionals Efficient analysis of industry talks, presentations, and training materials. 🎯 Content Creators Rapid research and competitive analysis of video content in your niche. Technical Implementation 🔄 Workflow Components Webhook endpoint for URL submission YouTube API integration for video details Transcript extraction system GPT-4 powered analysis engine Telegram notification system (optional) Transform your video content consumption with an intelligent system that delivers structured, comprehensive summaries while saving hours of viewing time.

Video Guide I prepared a comprehensive guide detailing how to create a Smart Agent that automates meeting task management by analyzing transcripts, generating tasks in Airtable, and scheduling follow-ups when necessary. Youtube Link Who is this for? This workflow is ideal for project managers, team leaders, and business owners looking to enhance productivity during meetings. It is particularly helpful for those who need to convert discussions into actionable items swiftly and effectively. What problem does this workflow solve? Managing action items from meetings can often lead to missed tasks and poor follow-up. This automation alleviates that issue by automatically generating tasks from meeting transcripts, keeping everyone informed about their responsibilities and streamlining communication. What this workflow does The workflow leverages n8n to create a Smart Agent that listens for completed meeting transcripts, processes them using AI, and generates tasks in Airtable. Key functionalities include: Capturing completed meeting events through webhooks. Extracting relevant meeting details such as transcripts and participants using API calls. Generating structured tasks from meeting discussions and sending notifications to clients. Webhook Integration: Listens for meeting completion events to trigger subsequent actions. API Requests for Data: Pulls necessary details like transcripts and participant information from Fireflies. Task and Notification Generation: Automatically creates tasks in Airtable and notifies clients of their responsibilities. Setup N8N Workflow Configure the Webhook: Set up a webhook to capture meeting completion events and integrate it with Fireflies. Retrieve Meeting Content: Use GraphQL API requests to extract meeting details and transcripts, ensuring appropriate authentication through Bearer tokens. AI Processing Setup: Define system messages for AI tasks and configure connections to the AI chat model (e.g., OpenAI's GPT) to process transcripts. Task Creation Logic: Create structured tasks based on AI output, ensuring necessary details are captured and records are created in Airtable. Client Notifications: Use an email node to notify clients about their tasks, ensuring communications are client-specific. Scheduling Follow-Up Calls: Set up Google Calendar events if follow-up meetings are required, populating details from the original meeting context.

This workflow automates the process of fetching agricultural transaction data from the Taiwan Agricultural Products Open Data Platform and storing it in a Google Sheets document for further analysis. Key Features Manual Trigger: Allows manual execution of the workflow to control when data is fetched. HTTP Request: Sends a request to the Open Data Platform's API to retrieve detailed transaction data, including: Pricing (Upper, Middle, Lower, Average) Transaction quantities Crop and market details Split Out Node: Processes each record individually, ensuring accurate handling of every data entry. Google Sheets Integration: Appends the data into a structured Google Sheets document for easy access and analysis. Node Configurations 1. Manual Trigger Purpose**: Start the workflow manually. Configuration**: No setup needed. 2. HTTP Request Purpose**: Fetch agricultural data. Configuration**: URL: https://data.moa.gov.tw/api/v1/SheepQuotation Query Parameters: Start_time: 2024/12/01 End_time: 2024/12/31 MarketName: 台北二 api_key: <your_api_key> Headers: accept: application/json 3. Split Out Purpose**: Split the API response data array into individual items. Configuration**: Field to Split Out: Data 4. Google Sheets Purpose**: Append the data to Google Sheets. Configuration**: Operation: Append Document ID: <your_document_id> Sheet Name: Sheet1 Mapped Fields: TransDate, TcType, CropCode, CropName, MarketCode, MarketName Upper_Price, Middle_Price, Lower_Price, Avg_Price, Trans_Quantity 此 Workflow 從 台灣農業產品開放資料平臺 獲取農產品交易數據，並將其儲存到 Google Sheets 文件 中進行進一步分析。 主要功能 Manual Trigger：允許手動執行工作流程，以控制數據獲取的時間。 HTTP Request：向開放資料平臺的 API 發送請求，獲取詳細的交易數據，包括： 價格 (Upper, Middle, Lower, Average) 交易數量 作物和市場詳細資料 Split Out Node：逐筆處理每一筆記錄，確保數據準確無誤。 Google Sheets Integration：將數據追加到結構化的 Google Sheets 文件中，方便存取和分析。 節點設定 1. Manual Trigger 用途**：手動啟動工作流程。 設定**：無需額外設定。 2. HTTP Request 用途**：抓取農產品數據。 設定**： URL: https://data.moa.gov.tw/api/v1/SheepQuotation 查詢參數 (Query Parameters)： Start_time: 2024/12/01 End_time: 2024/12/31 MarketName: 台北二 api_key: <your_api_key> 標頭 (Headers)： accept: application/json 3. Split Out 用途**：將 API 回應的數據陣列分解為個別項目。 設定**： Field to Split Out: Data 4. Google Sheets 用途**：將數據追加至 Google Sheets。 設定**： Operation：Append Document ID：<your_document_id> Sheet Name：Sheet1 映射欄位 (Mapped Fields)： TransDate, TcType, CropCode, CropName, MarketCode, MarketName Upper_Price, Middle_Price, Lower_Price, Avg_Price, Trans_Quantity 請多利用 Curl Import 功能 例如 curl -X GET "https://data.moa.gov.tw/api/v1/AgriProductsTransType/?Start_time=114.01.01&End_time=114.01.01&MarketName=%E5%8F%B0%E5%8C%97%E4%BA%8C" -H "accept: application/json" 農業資料開放平台 文件

This is a simple workflow that grabs HackerNews front-page headlines from today's date across every year since 2007 and uses a little AI magic (Google Gemini) to sort 'em into themes, sends a neat Markdown summary on Telegram. How it works Runs daily, grabs Hacker News front page for this day across every year since 2007. Pulls headlines & dates. Uses Google Gemini to sort headlines into topics & spot trends. Sends a Markdown summary to Telegram. Set up steps Clone the workflow. Add your Google Gemini API key. Add your Telegram bot token and chat ID. **Built on Day-01 as part of the #100DaysOfAgenticAi Fork it, tweak it, have fun!**

Make OpenAI Citation for File Retrieval RAG Use case In this example, we will ensure that all texts from the OpenAI assistant search for citations and sources in the vector store files. We can also format the output for Markdown or HTML tags. This is necessary because the assistant sometimes generates strange characters, and we can also use dynamic references such as citations 1, 2, 3, for example. What this workflow does In this workflow, we will use an OpenAI assistant created within their interface, equipped with a vector store containing some files for file retrieval. The assistant will perform the file search within the OpenAI infrastructure and will return the content with citations. We will make an HTTP request to retrieve all the details we need to format the text output. Setup Insert an OpenAI Key How to adjust it to your needs At the end of the workflow, we have a block of code that will format the output, and there we can add Markdown tags to create links. Optionally, we can transform the Markdown formatting into HTML.

Generate new keywords for SEO with the monthly Search volumes This workflow is an improvement on the workflows below. It can be used to generate new keywords that you can use for your SEO campaigns or Google ads campaigns Generate SEO Keyword Search Volume Data using Google API and Generating Keywords using Google Autosuggest Usage Send the keywords you need as an array to this workflow Pin the data and map it to the set Keywords node Map the keywords to the Google ads API with the location and Language of your choice Split the results and set them data Pass this to the next nodes as needed for storage Make a copy of this spreedsheet and update the data accordingly Having challenges with the google Ads API? Read this blog Setup Replace the trigger with your desired trigger eg a webhook or manual trigger Map the data correctly to the set Keywords node On the Generate new keywords, Update the {customer_id} on the url and login-customer-id with your actual one. Update the developer-token` also with your values. The url should be corrected as below https://googleads.googleapis.com/v18/customers/{customer-id}:generateKeywordIdeas You should send the headers as below { "name": "content-type", "value": "application/json" }, { "name": "developer-token", "value": "5j-tyzivCNmiCcoW-xkaxw" }, { "name": "login-customer-id", "value": "513554 " } and the json body should take the following format { "geoTargetConstants": ["geoTargetConstants/2840"], "includeAdultKeywords": false, "pageToken": "", "pageSize": 2, "keywordPlanNetwork": "GOOGLE_SEARCH", "language": "languageConstants/1000", "keywordSeed": { "keywords": {{ $json.Keyword }} } } Troubleshooting If you get an error with the workflow, check the credentials you are using Check the account you are using eg the right customer id and developer token Follow the guide on the blog to set up your Google ads account Made by @Imperol

Learning something new? Endlessly searching to find the best resources? This workflow finds top community-recommended learning resources on any topic from Hacker News, delivered to your inbox. How it works User submits a topic they want to learn via a simple form. The workflow searches for relevant "Ask HN" posts on Hacker News and extracts top-level comments. An LLM analyzes the comments and identifies the best learning resources. A personalized email is sent to the user with a Markdown formatted list of top recommendations, categorized by resource type (e.g., book, course, article) and difficulty level. Set up steps Add your Google Gemini API credentials. You'll need to create a project and enable the Generative Language API. Add your SMTP credentials for sending emails. Customize the Form and email subject (optional) Activate the workflow Screenshots for Workflow, Form and Email Built on Day-03 as part of the #100DaysOfAgenticAi Fork it, tweak it, have fun!

Pull data using the Facebook Graph API and get your Meta Ads insights into your Google Sheets for analysis. Get metrics like impressions, spend, reach, conversions, CTR, and CPC. Automate your data collection. Who is this template for? Marketing professionals looking to analyze Meta Ads data. You can also replace the Google Sheets node for a database node like MySQL or Postgres, and then use your BI tool (Power BI, Looker Studio, Tableau) to analyze the data. How it works Every day the flow gets Meta Ads insights from the previous day and saves them to Google Sheets. How to set up All information you need to set up this workflow is already inside the template. Check out my other templates 👉 https://n8n.io/creators/solomon/

Overview This workflow automates the end-to-end process of creating, optimizing, and publishing content on WordPress. It integrates AI-powered tools, Airtable, and WordPress plugins to generate high-quality, on-brand posts effortlessly. Perfect for content creators, marketers, and business owners looking to save time and scale their content strategy. Features Content Creation: AI-Powered Content:** Generates SEO-friendly blog posts with structured headings, relevant keywords, and meta descriptions. Custom Prompts:** Tailor the AI-generated content to match your brand’s tone and voice. SEO Optimization: RankMath Plugin Integration:** Updates RankMath SEO with focus keywords and meta descriptions, ensuring your content is search-engine optimized. Content Management: Airtable Integration:** Organizes content ideas, drafts, and publishing schedules in one place. Easily scalable for teams or solo creators. Visuals: Branded Featured Images:** Automatically generates on-brand images for every post. Publishing: Effortless Formatting:** Adapts content to fit your WordPress theme and schedules it for publication. Workflow Steps Trigger: Initiated manually or on a schedule. Content Management: Retrieves and organizes ideas from Airtable. Content Generation: Generates AI-driven blog content tailored to your audience. SEO Optimization: Automatically updates RankMath with SEO details. Featured Image Creation: Produces on-brand images for the post. Publishing: Formats and schedules the post on WordPress. Prerequisites API Keys: OpenAI Airtable WordPress REST API RankMath SEO Plugin Custom Code: Add a small update to your WordPress theme’s functions.php file to enable seamless automation. Customization Replace Airtable with another content management system if preferred. Adjust AI prompts to reflect different tones, styles, or industries. Add integrations for additional plugins, analytics, or storage services. Usage Import the workflow into your n8n instance. Configure API credentials for WordPress, Airtable, OpenAI, and RankMath. Update your functions.php file with the provided code snippet. Customize prompts and Airtable structure for your content needs. Trigger the workflow manually or set it on a schedule. Notes Experiment with Airtable views or add filters for more granular control over your content pipeline. Extend the workflow to include social media posting or analytics tracking. For questions, refer to n8n documentation or reach out to the creator. Tools Used Airtable OpenAI GPT WordPress REST API RankMath SEO Plugin Feel free to adapt and extend this workflow to meet your specific needs! 🎉

Community Node Disclaimer: As this workflow relies on a community node, it is limited to self-hosted environments. How It Works: Jotform Webinar Registry Integration: This workflow streamlines the process of handling webinar registrations submitted via JotForm. It ensures the data is correctly formatted and seamlessly integrates with KlickTipp. Data Transformation: Input data is validated and transformed to meet KlickTipp’s API requirements, including formatting phone numbers, converting dates, and validating URLs. Key Features JotForm Trigger: Captures new form submissions, including participant details and webinar preferences. Data Processing: Standardizes and validates input fields Converts phone numbers to numeric-only format with international prefixes. Transforms dates into UNIX timestamps. Validates LinkedIn URLs and applies fallback URLs if validation fails. Scales numerical fields, such as work experience, for specific use cases. Subscriber Management in KlickTipp: Adds or updates participants as subscribers in KlickTipp. Includes custom field mappings, such as: Personal information (name, email, phone number). Webinar details (chosen webinar, start date/time). Preferences (reminder intervals, questions for presenters). Tags contacts for segmentation: Adds fixed and dynamic tags to contacts. Error Handling: Validates critical fields like phone numbers, URLs, and dates to prevent incorrect data submissions. Setup Instructions Install and Configure Nodes: Set up the JotForm and KlickTipp nodes in your n8n instance. Authenticate your JotForm and KlickTipp accounts. Custom Field Preparation in KlickTipp: Create the necessary custom fields to match the data structure: | Name | Datentyp | | - | - | | Jotform_URL_Linkedin | URL | | Jotform_Workexperience_in_Years | Dezimalzahl | | Jotform_Webinar_start_timestamp | Datum & Zeit | | Jotform_Questions/Notes | Absatz | | Jotform_webinar | Zeile | | Jotform_reminder | Zeile | After creating fields, allow 10-15 minutes for them to sync. If fields don’t appear, reconnect your KlickTipp credentials. Field Mapping and Adjustments: Verify and customize field assignments in the workflow to align with your specific form and subscriber list setup. Workflow Logic Trigger via JotForm Submission: A new form submission from JotForm initiates the workflow Data Transformation: Processes raw form data to ensure compatibility with KlickTipp’s API. Add to KlickTipp Subscriber List: Adds participants to the designated KlickTipp list, including webinar-specific details. Get all tags from KlickTipp and create a list: Fetches all existing Tags and turns them into an array Define tags to dynamically set for contacts: Definiton of variables that are received from the form submission and should be converted into tags Merge tags of both lists: Checks whether the list of existing tags in KlickTipp contains the tags which should be dynamically set based on the form submission Tag creation and tagging contacts: Creates new tags if it previously did not exist and then tags the contact Benefits Efficient lead generation: Contacts from forms are automatically imported into KlickTipp and can be used immediately, saving time and increasing the conversion rate. Automated processes: Experts can start workflows directly, such as welcome emails or course admissions, reducing administrative effort. Error-free data management: The template ensures precise data mapping, avoids manual corrections and reinforces a professional appearance. Testing and Deployment: Test the workflow by filling the form on Jotform and verifying data updates in KlickTipp. Notes: Customization: Update field mappings within the KlickTipp nodes to align with your account setup. This ensures accurate data syncing.

How the Automated Workflow Works Scheduled Fetching from Hugging Face ⏰ The workflow triggers every weekday at 8 AM, automatically fetching the latest papers from Hugging Face for easy access. Duplication Check to Avoid Redundant Entries 🔍 It ensures the paper's summary is not already stored in your Notion workspace, preventing duplicate records and keeping your database organized. Content Analysis with OpenAI 🧠 Using OpenAI's powerful capabilities, the workflow analyzes the fetched paper summary, extracts key insights, and categorizes the content for easier understanding. Data Storage and Notification Integration 📥🔔 Once the summary is processed, it's automatically stored in your Notion workspace, and a notification containing the paper details is sent to your designated Slack channel for quick reference. Set Up Your Automated Workflow Create Your n8n Account 📝 Start by registering for an n8n account and logging into the n8n cloud service. Connect OpenAI, Notion, and Slack 🔗 Link your OpenAI, Notion, and Slack accounts by entering the appropriate tokens. This step will take approximately 10–15 minutes to complete. Import the Workflow Template 📥 Import the provided workflow template into your n8n instance to streamline the setup process. Activate the Workflow for Daily Summaries 🚀 After importing, simply enable the workflow, and you’re all set to receive daily paper summaries automatically. Setup Time ⏳: Approximately 15–20 minutes. Why Use This Automated Workflow? This automated workflow not only saves you time by fetching and categorizing the latest research papers but also helps streamline your Notion workspace and Slack notifications, allowing you to stay organized and efficient without manual intervention. Results Presentation

Community Node Disclaimer: As this workflow relies on a community node, it is limited to self-hosted environments. How It Works Gravity Forms Customer Feedback Form Integration: This workflow streamlines the process of handling customer feedback submitted via Gravity Forms. It ensures the data is correctly formatted and seamlessly integrates with KlickTipp. Data Transformation: Input data is validated and transformed to meet KlickTipp’s API requirements, including formatting phone numbers and converting dates. Key Features Gravity Forms Trigger Captures new form submissions from Gravity Forms via a webhook and initiates the workflow. Data Processing and Transformation Formats and validates essential data: Converts phone numbers to numeric-only format with international prefixes. Transforms dates (e.g., birthdays) to UNIX timestamps. Calculates and scales numeric responses (e.g., webinar ratings). Parses webinar selections into timestamps for structured scheduling. Subscriber Management in KlickTipp Adds or updates contacts in a KlickTipp subscriber list. Includes custom field mappings such as: Personal details (name, email, birthday, phone number). Feedback and preferences (e.g., webinar ratings, chosen sessions). Structured answers from form responses. Tags contacts for segmentation: Adds fixed and dynamic tags to contacts. Error Handling Ensures invalid or empty data is handled gracefully, preventing workflow interruptions. Setup Instructions Install and Configure Nodes: Set up the Webhook, Set, and KlickTipp nodes in your n8n instance. Authenticate your Gravity Forms and KlickTipp accounts. Prepare Custom Fields in KlickTipp: Create fields in KlickTipp to align with the form submission data, such as: | Name | Datentyp | |-----------------------------------|----------------| | Gravityforms_URL_Linkedin | URL | | Gravityforms_kurs/webinar_zeitpunkt | Datum & Zeit | | Gravityforms_kurs/webinar_bewertung | Dezimalzahl | | Gravityforms_feedback | Absatz | | Gravityforms_kontaktaufnahme | Zeile | After creating fields, allow 10-15 minutes for them to sync. If fields don’t appear, reconnect your KlickTipp credentials. Field Mapping and Adjustments: Verify and customize field assignments in the workflow to align with your specific form and subscriber list setup. Workflow Logic Trigger via Gravity Forms Submission: The workflow begins when a new form submission is received through the webhook. Transform Data for KlickTipp: Formats and validates raw form data for compatibility with KlickTipp’s API. Add to KlickTipp Subscriber List: Adds processed data as a new subscriber or updates an existing one. Get all tags from KlickTipp and create a list: Fetches all existing Tags and turns them into an array Define tags to dynamically set for contacts: Definiton of variables that are received from the form submission and should be converted into tags Merge tags of both lists: Checks whether the list of existing tags in KlickTipp contains the tags which should be dynamically set based on the form submission Tag creation and tagging contacts: Creates new tags if it previously did not exist and then tags the contact Benefits Efficient lead generation: Contacts from forms are automatically imported into KlickTipp and can be used immediately, saving time and increasing the conversion rate. Automated processes: Experts can start workflows directly, such as welcome emails or course admissions, reducing administrative effort. Error-free data management: The template ensures precise data mapping, avoids manual corrections and reinforces a professional appearance. Testing and Deployment Test the workflow by filling the form on Gravity Forms and verifying data updates in KlickTipp. Notes Customization: Update field mappings within the KlickTipp nodes to align with your account setup. This ensures accurate data syncing.

Purpose This solution enables you to manage all your Notion and Todoist tasks from different workspaces as well as your calendar events in a single place. All tasks can be managed in Todoist and additionally Fantastical can be used to manage scheduled tasks & events all together. Demo & Explanation How it works The realtime sync consists of two workflows, both triggered by a registered webhook from either Notion or Todoist To avoid overwrites by lately arriving webhook calls, every time the current task is retrieved from both sides. Redis is used to prevent from endless loops, since an update in one system triggers another webhook call again. Using the ID of the task, the trigger is being locked down for 15 seconds. Depending on the detected changes, the other side is updated accordingly. Generally Notion is treaded as the main source. Using an "Obsolete" Status, it is guaranteed, that tasks never get deleted entirely by accident. The Todoist ID is stored in the Notion task, so they stay linked together An additional full sync workflow daily fixes inconsistencies, if any of them occurred, since webhooks cannot be trusted entirely. Since Todoist requires a more complex setup, a tiny workflow helps with activating the webhook. Another tiny workflow helps generating a global config, which is used by all workflows for mapping purposes. Mapping (Notion >> Todoist) Name: Task Name Priority: Priority (1: do first, 2: urgent, 3: important, 4: unset) Due: Date Status: Section (Done: completed, Obsolete: deleted) <page_link>: Description (read-only) Todoist ID: <task_id> Current limitations Changes on the same task cannot be made simultaneously in both systems within a 15-20 second time frame Subtasks are not linked automatically to their parent yet Recurring tasks are not supported yet Tasks names do not support URL’s yet Prerequisites Notion A database must already exist (get a basic template here) with the following properties (case matters!): Text: "Name" Status: "Status", containing at least the options "Backlog", "In progress", "Done", "Obsolete" Select: "Priority", containing the options "do first", "urgent", "important" Date: "Due" Checkbox: "Focus" Text: "Todoist ID" Todoist A project must already exist with the same sections like defined as Status in Notion (except Done and Obsolete) Redis Create a Free Redis Cloud instance or self-host Setup The setup involves quite a lot of steps, yet many of them can be automated for business internal purposes. Just follow the video or do the following steps: Setup credentials for Notion (access token), Todoist (access token) and Redis - you can also create empty credentials and populate these later during further setup Clone this workflow by clicking the "Use workflow" button and then choosing your n8n instance - otherwise you need to map the credentials of many nodes. Follow the instructions described within the bundle of sticky notes on the top left of the workflow How to use You can apply changes (create, update, delete) to tasks both in Notion and Todoist which then get synced over within a couple of seconds (this is handled by the differential realtime sync) The daily running full sync, resolves possible discrepancies in Todoist and sends a summary via email, if anything needed to be updated. In case that contains an unintended change, you can jump to the Task from the email directly to fix it manually.

Community Node Disclaimer: As this workflow relies on a community node, it is limited to self-hosted environments. How It Works: Typeform Quiz Integration: This workflow streamlines the process of handling quiz answers submitted via Typeform. It ensures the data is correctly formatted and seamlessly integrates with KlickTipp. Data Transformation: Input data is validated and transformed to meet KlickTipp’s API requirements, including formatting phone numbers and converting dates. Key Features Typeform Trigger: Captures new quiz submissions from Typeform, including user details and quiz responses. Data Processing and Transformation: Formats phone numbers to numeric-only format with international prefixes. Converts dates (e.g., birthdays) to UNIX timestamps. Maps multiple-choice quiz answers to string values for API compatibility. Scales numeric quiz responses for tailored use cases. Subscriber Management in KlickTipp: Adds participants as subscribers to a designated KlickTipp list, with custom field mappings for: Personal details (e.g., name, email, phone number, birthday). Quiz responses (e.g., intended usage of KlickTipp, company location, and team size). Tags contacts for segmentation: Adds fixed and dynamic tags to contacts. Error Handling: Handles empty or malformed data gracefully, ensuring clean submissions to KlickTipp. Setup Instructions Install and Configure Nodes: Set up the Typeform and KlickTipp nodes in your n8n instance. Authenticate your Typeform and KlickTipp accounts. Prepare Custom Fields in KlickTipp: Create custom fields to store quiz answers and personal details, such as: | Name | Datentyp | |----------------------------------|-----------------| | Typeform_URL_Linkedin | URL | | Typeform_Frage1_klicktipp_nutzen | Zeile | | Typeform_Frage2_klicktipp_sitz | Zeile | | Typeform_Frage3_mitglieder_CHT | Dezimalzahl | After creating fields, allow 10-15 minutes for them to sync. If fields don’t appear, reconnect your KlickTipp credentials. Field Mapping and Adjustments: Verify and customize field assignments in the workflow to align with your specific form and subscriber list setup. Workflow Logic Trigger via Typeform Submission: The workflow initiates upon receiving a new quiz submission. Transform Data for KlickTipp: Converts and validates data from Typeform to match KlickTipp’s API requirements. Add to KlickTipp Subscriber List: Submits the cleaned data to KlickTipp, including all relevant quiz answers. Get all tags from KlickTipp and create a list: Fetches all existing Tags and turns them into an array Define tags to dynamically set for contacts: Definiton of variables that are received from the form submission and should be converted into tags Merge tags of both lists: Checks whether the list of existing tags in KlickTipp contains the tags which should be dynamically set based on the form submission Tag creation and tagging contacts: Creates new tags if it previously did not exist and then tags the contact Benefits Efficient lead generation: Contacts from forms are automatically imported into KlickTipp and can be used immediately, saving time and increasing the conversion rate. Automated processes: Experts can start workflows directly, such as welcome emails or course admissions, reducing administrative effort. Error-free data management: The template ensures precise data mapping, avoids manual corrections and reinforces a professional appearance. Testing and Deployment Test the workflow by filling the form on Typeform and verifying data updates in KlickTipp. Notes Customization: Update field mappings within the KlickTipp nodes to align with your account setup. This ensures accurate data syncing.

Purpose of workflow: This AI-powered workflow automatically generates detailed, well-researched newsletters by monitoring and analyzing specified news topics (like Bitcoin, Nvidia, etc.). It uses a team of AI research agents to gather, analyze, and compile information with automatic citations, saving significant time in newsletter creation. How it works: Multi-agent system: Research Leader: Analyzes topics and creates content outline Project Planner: Breaks down research into specific tasks Research Assistants: Conduct detailed research on assigned subtopics Editor: Combines research and polishes final output Key features: Automated daily monitoring of specified news topics Real-time information gathering using Perplexity AI Auto-citation functionality for source verification Flexible time window filtering (day/week/month) Options for detailed or simple reports Direct email delivery of completed newsletters Step-by-step setup: Perplexity API Setup: Create account at perplexity.ai Navigate to API tab Generate API key Set up credentials with 'Bearer' authentication Workflow Configuration: Connect Google Sheets containing news monitoring topics Configure schedule trigger for daily execution Set up email delivery settings Define report type preferences (detailed/simple) Specify time window for news gathering Integration: Connect with newsletter tools like Kit Import generated content as starting point Edit and customize as needed before publishing

What this workflow does Monitors Google Drive: The workflow triggers whenever a new CSV file is uploaded. Uses AI to Identify PII Columns: The OpenAI node analyzes the data and identifies PII-containing columns (e.g., name, email, phone). Removes PII: The workflow filters out these columns from the dataset. Uploads Cleaned File: The sanitized file is renamed and re-uploaded to Google Drive, ensuring the original data remains intact. How to customize this workflow to your needs Adjust PII Identification: Modify the prompt in the OpenAI node to align with your specific data compliance requirements. Include/Exclude File Types: Adjust the Google Drive Trigger settings to monitor specific file types (e.g., CSV only). Output Destination: Change the folder in Google Drive where the sanitized file is uploaded. Setup Prerequisites: A Google Drive account. An OpenAI API key. Workflow Configuration: Configure the Google Drive Trigger to monitor a folder for new files. Configure the OpenAI Node to connect with your API Set the Google Drive Upload folder to a different location than the Trigger folder to prevent workflow loops.

This n8n template introduces the Dynamic Prompts AI workflow pattern which are incredible for certain types of data extraction tasks where attributes are unknown or need to remain flexible. The general idea behind this pattern is that the prompts for requested attributes to be extracted live outside the template and so can be changed at any time - without needing to edit the template. This seriously cuts down on maintainance requirements and is reusable for any number of tables at little cost. Check out the n8n Studio Episode here: https://www.youtube.com/watch?v=_fNAD1u8BZw Community post here: https://community.n8n.io/t/dynamic-prompts-with-n8n-baserow-and-airtable/72052 Looking for the Airtable Version? https://n8n.io/workflows/2771-ai-data-extraction-with-dynamic-prompts-and-airtable/ How it works Given we have an "input" field for context and a number of fields for the data we want to extract, this template will run in the background to react to any changes to either the "input" or fields and automatically update the rows accordingly. The key is that Baserow fields have a special property called the "field description". In this pattern, we use this property to allow the user to store a simple prompt describing the data that should exist in the column. Our n8n template reads these column descriptions aka "prompts" to use as instructions to perform tasks on the "input". In this template, the "input" is a PDF of a resume/CV and the columns are attributes a HR person would want to extract from it - such as full name, address, last position, years of experience etc. How to use First publish this template and ensure it's accessible via webhook URL. You then have to complete the "create Baserow webhooks" steps to configure your baserow to send change events to the n8n template. Baserow webhooks are created in the Baserow web interface. Check the template for more instructions. Requirements Baserow for Tables/Database OpenAI for LLM and extraction. Feel free to choose another LLM if preferred. Customising this workflow If you're not using files, you can replace the "input" field with anything you like. For example, the "input" could be single line text.

Workflow Overview This workflow automates the process of scraping Trustpilot reviews, extracting key details, analyzing sentiment, and saving the results to Google Sheets. It uses OpenAI for sentiment analysis and HTML parsing for review extraction. How It Works 1. Scrape Trustpilot Reviews HTTP Request**: Fetches review pages from Trustpilot (https://it.trustpilot.com/review/{{company_id}}). Paginates through pages (up to max_page limit). HTML Parsing**: Extracts review URLs using CSS selectors Splits the URLs into individual review links. 2. Extract Review Details Information Extractor**: Uses DeepSeek to extract structured data from the review: Author: Name of the reviewer. Rating: Numeric rating (1-5). Date: Review date in YYYY-MM-DD format. Title: Review title. Text: Full review text. Total Reviews: Number of reviews by the user. Country: Reviewer’s country (2-letter code). 3. Sentiment Analysis Sentiment Analysis Node**: Uses OpenAI to classify the review text as Positive, Neutral, or Negative. Example output: { "category": "Positive", "confidence": 0.95 } 4. Save to Google Sheets Google Sheets Node**: Appends or updates the extracted data to a Google Sheet Set Up Steps 1. Configure Trustpilot Scraping Edit Fields1 Node**: Set company_id to the Trustpilot company name Set max_page to limit the number of pages scraped. 2. Configure Google Sheets Google Sheets Node**: Update the documentId with your Google Sheet ID Ensure the sheet has the required columns (Id, Data, Nome, etc.). 3. Configure OpenAI OpenAI Chat Model Node**: Add your OpenAI API key. Sentiment Analysis Node**: Ensure the categories match your desired sentiment labels (Positive, Neutral, Negative). Key Components Nodes**: HTTP Request/HTML: Scrape and parse Trustpilot reviews. Information Extractor: Extract structured review data using DeepSeek. Sentiment Analysis: Classify review sentiment. Google Sheets: Save and update review data. Credentials**: OpenAI API key. DeepSeek API key. Google Sheets OAuth2.

What this workflow does This workflow retrieves the Zoom meeting data from the last 24 hours. The transcript of the last meeting is then retrieved, processed, a summary is created using AI and sent to all participants by email. AI is then used to create tasks and follow-up appointments based on the content of the meeting. Important: You need a Zoom Workspace Pro account and must have activated Cloud Recording/Transcripts! This workflow has the following sequence: manual trigger (Can be replaced by a scheduled trigger or a webhook) retrieval of of Zoom meeting data filter the events of the last 24 hours retrieval of transcripts and extract of the text creating a meeting summary, format to html and send per mail create tasks and follow-up call (if discussed in the meeting) in ClickUp/Outlook (can be replaced by Gmail, Airtable, and so forth) via sub workflow Requirements: Zoom Workspace (via API and HTTP Request): Documentation Microsoft Outlook: Documentation ClickUp: Documentation AI API access (e.g. via OpenAI, Anthropic, Google or Ollama) SMTP access data (for sending the mail) You must set up the individual sub-workflows as separate workflows. Then set the “Execute workflow trigger” here. Then select the corresponding sub-workflow in the AI Agent Tools. You can select the number of domains yourself. If the data queries are not required, simply delete the corresponding tool (e.g. “Analytics_Domain_5). Feel free to contact me via LinkedIn, if you have any questions!

This workflow automates the process of retrieving Hugging Face paper summaries, analyzing them with OpenAI, and storing the results in Notion. Here’s a breakdown of how it works: ⏰ Scheduled Trigger: The flow is set to run automatically at 8 AM on weekdays. 📄 Fetching Paper Data: It fetches Hugging Face paper summaries using their API. 🔍 Data Check: Before processing, the workflow checks if the paper already exists in Notion to avoid duplicates. 🤖 Content Analysis with OpenAI: If the paper is new, it extracts the summary and uses OpenAI to analyze the content. 📥 Store Results in Notion: After analysis, the summarized data is saved in Notion for easy reference. ⚙️ Set Up Steps for Automation Follow these steps to set up this automated workflow with Hugging Face, OpenAI, and Notion integration: 🔑 Obtain API Tokens: You’ll need the Notion and OpenAI API tokens to authenticate and connect these services with n8n. 🔗 Integration in n8n: Link Hugging Face, OpenAI, and Notion by configuring the appropriate nodes in n8n. 🔧 Configure Workflow Logic: Set up a cron trigger for automatic execution at 8 AM on weekdays. Use an HTTP request node to fetch Hugging Face paper data. Add logic to check if the data already exists in Notion. Set up the OpenAI integration to analyze the paper’s summary. Store the results in Notion for easy access and reference. Result:

Sync your Google Contacts with your Notion database. You can filter contacts by label or sync all contacts. All contact information is kept in sync between Google and Notion. What happens if I delete a contact? It gets deleted on the other end. Google Contact deleted → Notion page deleted Notion page deleted → Google contact deleted But you can easily change this behavior by disabling the respective deletion nodes. Who is this template for? Service providers looking to keep track of client information Organized individuals who like to centralize their lives in Notion Automation nerds who enjoy creating interesting projects How it works First, you perform an initial import to bring your contacts from Google to Notion. After that, the workflow listens for changes in both Notion and Google and keeps everything in sync. How to set up Instructions are included within the workflow itself. Check out my other templates 👉 https://n8n.io/creators/solomon/

How it works: This workflow automates tagging for WordPress posts using AI: Fetch blog post content and metadata. Generate contextually relevant tags using AI. Verify existing tags in WordPress and create new ones if necessary. Automatically update posts with accurate and optimized tags. Set up steps: Estimated time: ~15 minutes. Configure the workflow with your WordPress API credentials. Connect your content source (e.g., RSS feed or manual input). Adjust tag formatting preferences in the workflow settings. Run the workflow to ensure proper tag creation and assignment. This workflow is perfect for marketers and content managers looking to streamline their content categorization and improve SEO efficiency.

Domain Outbound Machine: Automate Lead Generation, Email Extraction, and Targeted Outreach with n8n Description Domain Outbound Machine is an n8n workflow designed to fully automate the domain sales process: lead generation, email extraction, personalized outreach, and automated email sending. It also stores extracted email addresses and sent emails in an Excel file for tracking and follow-up. How It Works? 1. Domain Input You provide the domain name you want to sell. The workflow takes this domain as the starting point. 2. Google Maps Query Generation The workflow automatically generates 100 Google Maps queries based on the domain's niche or industry. This ensures you target businesses or individuals who might be interested in acquiring the domain. 3. Web Scraping for Emails Using the generated queries, the workflow scrapes relevant websites to extract email addresses. This step ensures you have a targeted list of potential buyers. 4. Email Enrichment For each extracted email, the workflow gathers publicly available information (e.g., LinkedIn, company websites) to enhance personalization. 5. Personalized Email Creation Based on the enriched data, the workflow crafts a custom email for each lead, emphasizing the domain’s value, its relevance to their business, and a compelling call-to-action. 6. Email Sending via Gmail The workflow sends the personalized emails directly through your Gmail account, ensuring timely and professional outreach. 7. Email & Lead Tracking in Excel All extracted email addresses and sent messages are automatically stored in an Excel file, allowing you to track responses and manage follow-ups efficiently. Key Features ✅ Automated Lead Generation – Saves time by automatically finding and extracting potential leads. ✅ Personalized Outreach – Boosts engagement by tailoring each email to the recipient. ✅ Seamless Integration – Uses n8n’s automation to connect Google Maps, web scraping tools, and Gmail in one workflow. ✅ Scalable & Trackable – Adjust the number of queries or emails as needed, while keeping track of everything in Excel. Domain Outbound Machine is perfect for domain investors, digital marketers, and anyone looking to sell domains efficiently. By automating the tedious tasks, you can focus on closing deals and growing your business.

Retrieve 20 Latest TechCrunch Articles Who is this for? This workflow is designed for developers, content creators, and data analysts who need to scrape recent articles from TechCrunch. It’s perfect for anyone looking to aggregate news articles or create custom feeds for analysis, reporting, or integration into other systems. What problem is this workflow solving? This workflow automates the process of scraping recent articles from TechCrunch. Manually collecting article data can be time-consuming and inefficient, but with this workflow, you can quickly gather up-to-date news articles with relevant metadata, saving time and effort. What this workflow does This workflow retrieves the latest 20 news articles from TechCrunch’s “Recent” page. It extracts the article URLs, metadata (such as titles and publication dates), and main content for each article, allowing you to access the information you need without any manual effort. Setup Clone or download the workflow template. Ensure you have a working n8n environment. Configure the HTTP Request nodes with your desired parameters to connect to the TechCrunch API. (Optional) Customize the workflow to target specific sections or topics of interest. Run the workflow to retrieve the latest 20 articles. How to customize this workflow to your needs Modify the HTTP request to pull articles from different pages or sections of TechCrunch. Adjust the number of articles to retrieve by changing the selection criteria. Add additional processing steps to further filter or analyze the article data. Workflow Steps Send an HTTP request to the TechCrunch "Recent" page. Parse a posts box that holds the list of articles. Parse all posts to extract all articles. spilt out posts for each article. Extract the URL and metadata from each article. Send an HTTP request for each article using its URL. Locate and parse the main content of each article. Note: Be sure to update the HTTP Request nodes with any necessary headers or authentication to work with TechCrunch’s website.

Docker Registry Cleanup Template This template is designed to automatically clean up old image tags in the Docker registry and perform garbage collection. Features List all images in the registry Preserve the last 10 tags for each image (latest tag is always preserved) Delete old tags Email notification for Successful/Excused cancellation Registry garbage collection automation Failure notification in error conditions Prerequisites Docker Registry v2 API access Basic Authentication credentials SMTP email settings (for notifications) SSH node installed on n8n (for garbage collection) Installation 1. Identity Information Add the following credentials in n8n: HTTP Basic Auth**: For Registry access SSH Private Key**: For Garbage collection command Email SMTP**: For notifications 2. Set Variables Replace your-registry-url with your actual registry URL on all nodes: ‘url": ‘https://your.registry.com/v2/_catalog’. Customisation Retention Policy: Set the number of tags to be retained by changing the slice(0, 10) value in the Identify Tags to Remove node Schedule: Change the frequency of operation at the Trigger node Notification Content: Customise email templates according to your needs Notes Check DELETE operations before running in a test environment Make sure that the registry is not in read-only mode The registry may need to be put into maintenance mode for garbage collection Step Details: Retrieving image information:** The workflow starts by fetching a list of images and their associated tags from the Docker registry. Filtering and sorting:** The retrieved tags are then filtered and sorted based on specific criteria, such as creation date and tag name. Deleting old tags:** The workflow identifies old or unused tags and attempts to delete them from the registry. Sending notifications:** The workflow sends email notifications to inform the user about the status of the cleanup process, including any errors or successes. Executing additional cleanup tasks:** Finally, the workflow executes an SSH command on the Docker registry server to perform additional cleanup tasks, such as garbage collection. TL;DR In summary, this n8n template provides a robust and automated solution for managing and cleaning up Docker registries. By regularly running this workflow, users can ensure that their registry remains organized and efficient, and avoid running out of storage space.-

n8n Workflow: Automate SIEM Alert Enrichment with MITRE ATT&CK & Qdrant Who is this for? This workflow is ideal for: Cybersecurity teams & SOC analysts* who want to automate *SIEM alert enrichment**. IT security professionals* looking to integrate *MITRE ATT&CK intelligence** into their ticketing system. Organizations using Zendesk for security incidents* who need enhanced *contextual threat data**. Anyone using n8n and Qdrant* to build *AI-powered security workflows**. What problem does this workflow solve? Security teams receive large volumes of raw SIEM alerts that lack actionable context. Investigating every alert manually is time-consuming and can lead to delayed response times. This workflow solves this problem by: ✔ Automatically enriching SIEM alerts with MITRE ATT&CK TTPs. ✔ Tagging & classifying alerts based on known attack techniques. ✔ Providing remediation steps to guide the response team. ✔ Enhancing security tickets in Zendesk with relevant threat intelligence. What this workflow does 1️⃣ Ingests SIEM alerts (via chatbot or ticketing system like Zendesk). 2️⃣ Queries a Qdrant vector store containing MITRE ATT&CK techniques. 3️⃣ Extracts relevant TTPs (Tactics, Techniques, & Procedures) from the alert. 4️⃣ Generates remediation steps using AI-powered enrichment. 5️⃣ Updates Zendesk tickets with threat intelligence & recommended actions. 6️⃣ Provides structured alert data for further automation or reporting. Setup Guide Prerequisites n8n instance** (Cloud or Self-hosted). Qdrant vector store** with MITRE ATT&CK data embedded. OpenAI API key** (for AI-based threat processing). Zendesk account** (for ticket enrichment, if applicable). Clean Mitre Data Python Script Cleaned Mitre Data Full Mitre Data Steps to Set Up 1️⃣ Embed MITRE ATT&CK data into Qdrant This workflow pulls MITRE ATT&CK data from Google Drive and loads it into Qdrant. The data is vectorized using OpenAI embeddings for fast retrieval. 2️⃣ Deploy the n8n Chatbot The chatbot listens for SIEM alerts and sends them to the AI processing pipeline. Alerts are analyzed using an AI agent trained on MITRE ATT&CK. 3️⃣ Enrich Zendesk Tickets The workflow extracts MITRE ATT&CK techniques from alerts. It updates Zendesk tickets with contextual threat intelligence. The remediation steps are included as internal notes for SOC teams. How to Customize This Workflow 🔧 Modify the chatbot trigger: Adapt the chatbot node to receive alerts from Slack, Microsoft Teams, or any other tool. 🔧 Change the SIEM input source: Connect your workflow to Splunk, Elastic SIEM, or Chronicle Security. 🔧 Customize remediation steps: Use a custom AI model to tailor remediation responses based on organization-specific security policies. 🔧 Extend ticketing integration: Modify the Zendesk node to also work with Jira, ServiceNow, or another ITSM platform. Why This Workflow is Powerful ✅ Saves time: Automates alert triage & classification. ✅ Improves security posture: Helps SOC teams act faster on threats. ✅ Leverages AI & vector search: Uses LLM-powered enrichment for real-time context. ✅ Works across platforms: Supports n8n Cloud, Self-hosted, and Qdrant. 🚀 Get Started Now! 📖 Watch the Setup Video 💬 Have Questions? Join the Discussion in the YouTube Comments!

UPDATE This is an updated version of the previous Ultimate Content Generator for WordPress v2. https://n8n.io/workflows/2737-ultimate-content-generator-for-wordpress/ It includes an additional workflow to generate content using Anthropic Claude in addition to OpenAI 4o. I also mofidied it to use the AI Agent Tool node with structured output for more consistent outputs. Lastly, the workflow updates a new table in AirTable with the published blog post url and featured image url. Overview- This workflow automates the end-to-end process of creating, optimizing, and publishing content on WordPress. It integrates AI-powered tools, Airtable, and WordPress plugins to generate high-quality, on-brand posts effortlessly. Perfect for content creators, marketers, and business owners looking to save time and scale their content strategy. Features Content Creation: AI-Powered Content: Generates SEO-friendly blog posts with structured headings, relevant keywords, and meta descriptions. Custom Prompts: Tailor the AI-generated content to match your brand’s tone and voice. SEO Optimization: RankMath Plugin Integration: Updates RankMath SEO with focus keywords and meta descriptions, ensuring your content is search-engine optimized. Content Management: Airtable Integration: Organizes content ideas, drafts, and publishing schedules in one place. Easily scalable for teams or solo creators. Visuals: Branded Featured Images: Automatically generates on-brand images for every post. Publishing: Effortless Formatting: Adapts content to fit your WordPress theme and schedules it for publication. Workflow Steps Trigger: Initiated manually or on a schedule. Content Management: Retrieves and organizes ideas from Airtable. Content Generation: Generates AI-driven blog content tailored to your audience. SEO Optimization: Automatically updates RankMath with SEO details. Featured Image Creation: Produces on-brand images for the post. Publishing: Formats and schedules the post on WordPress. Prerequisites API Keys: OpenAI Claude Airtable WordPress REST API Custom Code: Add a small update to your WordPress theme’s functions.php file to enable seamless automation. Customization Replace Airtable with another content management system if preferred. Adjust AI prompts to reflect different tones, styles, or industries. Add integrations for additional plugins, analytics, or storage services. Usage Import the workflow into your n8n instance. Configure API credentials for WordPress, Airtable, OpenAI, Claude and Slack. Update your functions.php file with the provided code snippet. Customize prompts and Airtable structure for your content needs. Trigger the workflow manually or set it on a schedule. Notes Experiment with Airtable views or add filters for more granular control over your content pipeline. Extend the workflow to include social media posting or analytics tracking. Feel free to adapt and extend this workflow to meet your specific needs! 🎉

How it works This workflow enables companies to provide instant HR support by automating responses to employee queries about policies and benefits: Retrieves company policies, benefits, and HR documents from BambooHR. Uses AI to analyze and answer employee questions based on company records. Identifies the most relevant contact person for escalations. Seamlessly integrates with company systems to provide real-time HR assistance. Set up steps: Estimated time: ~20 minutes Connect your BambooHR account to allow policy retrieval. Configure AI parameters and access control settings. (Optional) Set up the employee lookup tool for personalized responses. Test the chatbot to ensure accurate responses and seamless integration. Benefits This workflow is perfect for HR teams looking to enhance employee support while reducing manual inquiries. Outperform BambooHR's "Ask BambooHR" Chatbot #1. Superior specificity of replies to general inquiries #2. More appropriate escalations when responding to sensitive employee concerns

Automated YouTube Shorts Creator from Google News Trends Transform trending Google News articles into engaging YouTube Shorts with this fully automated workflow. Save time and effort while creating dynamic, eye-catching videos that are perfect for content creators, journalists, and digital marketers. Key Features Trend Analysis: Automatically fetch Google News articles and entertainment trends every 24 hours. AI-Powered Video Creation: Generate accurate transcripts from articles using Deepseek AI. Create visually appealing backgrounds with AI image generation tools. Add voiceovers with ElevenLabs TTS or similar services. Dynamic Video Compilation: Combine images, audio, and background music to craft short, dynamic videos. Fully customizable video length and music selection. YouTube Integration: Upload videos directly to YouTube, complete with autogenerated titles and descriptions. Organized Management: Titles and descriptions are saved to a Google Sheet for easy tracking and editing. How It Works Fetch trending topics from Google News using Deepseek. Convert the article's content into a readable transcript. Automatically create a voiceover, generate visuals, and combine them into a complete video. Upload the video to YouTube with a dynamic caption and description. Who Is It For? Content creators looking to expand their reach on YouTube Shorts. News agencies aiming to deliver content faster. Digital marketers needing quick, engaging videos. Setup Requirements API keys for Google News, ElevenLabs, OpenAI, and Deepseek. Basic knowledge of API integration and video content creation. Start creating trending, eye-catching YouTube Shorts in minutes. Automate your workflow and stay ahead in the content game!

Scrape Latest 20 TechCrunch Articles Who is this for? This workflow is designed for developers, researchers, and data analysts who need to track the latest trending repositories on GitHub. It is useful for anyone who wants to stay updated on popular open-source projects without manually browsing GitHub’s trending page. What problem is this workflow solving? Manually checking GitHub’s trending repositories daily can be time-consuming and inefficient. This workflow automates the extraction of trending repositories, providing structured data including repository name, author, description, programming language, and direct repository links. What this workflow does This workflow scrapes the trending repositories from GitHub’s trending page and extracts essential metadata such as repository names, languages, descriptions, and URLs. It processes the extracted data and structures it into an easy-to-use format. Setup Ensure you have n8n installed and configured. Import this workflow into your n8n instance. Run the workflow manually or schedule it to execute at regular intervals. (Optional) Customize the extracted data or integrate it with other systems. How to customize this workflow to your needs Modify the HTTP request node to target different GitHub trending categories (e.g., specific programming languages). Add further processing steps such as filtering repositories by stars, forks, or specific keywords. Integrate this workflow with Slack, email, or a database to store or notify about trending repositories. Workflow Steps Trigger execution manually using the "When clicking ‘Test workflow’" node. Send an HTTP request to fetch GitHub’s trending page using "Request to Github Trend". Extract the trending repositories box from the HTML response using "Extract Box". Extract all repository data including names, authors, descriptions, and languages using "Extract all repositories". Convert extracted data into a structured list for easier processing using "Turn to a list". Extract detailed repository information using "Extract repository data". Format and set variables to ensure clean and structured data output using "Set Result Variables". Note: Since GitHub’s trending page updates dynamically, ensure you run this workflow periodically to capture the latest trends.

Using PostBin to Test Webhooks Without Changing WEBHOOK_URL How it Works Many new n8n users struggle with testing webhooks when running n8n on localhost, as external services cannot reach localhost. This workflow introduces a technique using PostBin, which provides a temporary, publicly accessible URL to receive webhook requests. Generates a temporary webhook endpoint via PostBin. Uses this endpoint in place of localhost to test webhooks. Captures and displays the incoming webhook request data. Enables debugging and iterating without modifying the WEBHOOK_URL environment variable. Set Up Steps Estimated time:** ~5–10 minutes Create a PostBin instance to generate a publicly accessible webhook URL. Copy the PostBin URL and use it as the webhook destination in n8n. Trigger the webhook from an external service or manually. Inspect the request payload in PostBin to verify data reception. (EXAMPLE) Using PostBin for Webhook Testing in a BambooHR Integration How it Works In this example, we apply the PostBin technique to a BambooHR integration. Instead of manually configuring a webhook in BambooHR, this workflow automates webhook registration using the BambooHR API. The workflow: Uses the BambooHR API to programmatically register the PostBin URL as a webhook. Retrieves the most recent webhook calls made by BambooHR to the PostBin URL. (Optional) Sends a personalized Slack message for new employees using OpenAI. Set Up Steps Estimated time:** ~15–20 minutes Set up PostBin using the steps from the first section. Log into BambooHR to generate an API key for authentication. Run the workflow to register the PostBin URL as a webhook in BambooHR via the API. Retrieve recent webhook calls from PostBin to validate data reception. (Optional) Send a Slack notification using the processed data.

Workflow based on the following article. https://www.anthropic.com/news/contextual-retrieval This n8n automation is designed to extract, process, and store content from documents into a Pinecone vector store using context-based chunking. The workflow enhances retrieval accuracy in RAG (Retrieval-Augmented Generation) setups by ensuring each chunk retains meaningful context. Workflow Breakdown: 🔹 Google Drive - Retrieve Document: The automation starts by fetching a source document from Google Drive. This document contains structured content, with predefined boundary markers for easy segmentation. 🔹 Extract Text Content - Once retrieved, the document’s text is extracted for processing. Special section boundary markers are used to divide the text into logical sections. 🔹 Code Node - Create Context-Based Chunks: A custom code node processes the extracted text, identifying section boundaries and splitting the document into meaningful chunks. Each chunk is structured to retain its context within the entire document. 🔹 Loop Node - Process Each Chunk: The workflow loops through each chunk, ensuring they are processed individually while maintaining a connection to the overall document context. 🔹 Agent Node - Generate Context for Each Chunk: We use an Agent node powered by OpenAI’s GPT-4.0-mini via OpenRouter to generate contextual metadata for each chunk, ensuring better retrieval accuracy. 🔹 Prepend Context to Chunks & Create Embeddings - The generated context is prepended to the original chunk, creating context-rich embeddings that improve searchability. 🔹 Google Gemini - Text Embeddings: The processed text is passed through Google Gemini text-embedding-004, which converts the text into semantic vector representations. 🔹 Pinecone Vector Store - Store Embeddings: The final embeddings, along with the enriched chunk content and metadata, are stored in Pinecone, making them easily retrievable for RAG-based AI applications. Use Case: This automation enhances RAG retrieval by ensuring each chunk is contextually aware of the entire document, leading to more accurate AI responses. It’s perfect for applications that require semantic search, AI-powered knowledge management, or intelligent document retrieval. By implementing context-based chunking, this workflow ensures that LLMs retrieve the most relevant data, improving response quality and accuracy in AI-driven applications.

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

Template Description WDF Top Keywords: This workflow is designed to streamline keyword research by automating the process of generating, filtering, and analyzing Google and YouTube keyword data. Ensure compliance with local regulations and API terms of service when using this workflow. 📌 Purpose The WDF Top Keywords workflow automates collecting, processing, and managing keyword data for both Google and YouTube platforms. Leveraging multiple data sources and APIs ensures an efficient and scalable approach to identifying high-impact keywords for SEO, content creation, and marketing campaigns. Key Features Automates the generation of keyword suggestions using autocomplete APIs. Integrates with NocoDB to store and manage keyword data. Filters keywords based on monthly search volume and cost-per-click (CPC). Supports bulk import of keyword data into structured databases. Outputs both Google and YouTube keyword insights, enabling informed decision-making. 🎯 Target Audience This workflow is ideal for: Digital marketers aiming to optimize ad campaigns with data-driven insights. SEO specialists looking to identify high-potential keywords efficiently. Content creators seeking trending and relevant topics for their platforms. Agencies managing keyword research for multiple clients. ⚙️ How It Works Trigger: The workflow runs on-demand or at scheduled intervals. Keyword Generation: Retrieves base keywords from NocoDB. Generates autocomplete suggestions for Google and YouTube. Data Processing: Filters and formats keyword data based on specific criteria (e.g., search volume, CPC). Consolidates results for efficient storage and analysis. Storage and Output: Saves data into structured NocoDB tables for tracking and reuse. Bulk imports monthly search volume statistics for detailed analysis. 🛠️ Key APIs and Tools Used NocoDB**: Stores and organizes base and processed keyword data. DataForSEO API**: Provides search volume and keyword performance metrics. Google Autocomplete API**: Suggests relevant Google search terms. YouTube Autocomplete API**: Suggests trending YouTube keywords. Social Flood Docker Instance**: Serves as the local integration hub. Setup Instructions Required Tools: NocoDB n8n DataForSEO Account Social Flood Docker Instance Create the following NocoDB tables: Base Keyword Search Second Order Google Keywords Second Order YouTube Keywords Search Volume This template empowers users to handle complex keyword research tasks effortlessly, saving time and providing actionable insights. Share this template to enhance your workflow efficiency!

N8N for Beginners: Looping Over Items Description This workflow is designed for n8n beginners to understand how n8n handles looping (iteration) over multiple items. It highlights two key behaviors: Built-In Looping:** By default, most n8n nodes iterate over each item in an input array. Explicit Looping:* The *Loop Over Items* node allows controlled iteration, enabling *custom batch processing** and multi-step workflows. This workflow demonstrates the difference between processing an unsplit array of strings (single item) vs. a split array (multiple items). Setup 1. Input Data To begin, paste the following JSON into the Manual Trigger node: { "urls": [ "https://www.reddit.com", "https://www.n8n.io/", "https://n8n.io/", "https://supabase.com/", "https://duckduckgo.com/" ] } 📌 Steps to Paste Data: Double-click** the "Manual Trigger" node. Click "Edit Output" (top-right corner). Paste the JSON and Save. The node turns purple, indicating that test data is pinned. 1. Click "Test Workflow" button at the bottom of the canvas Explanation of the n8n Nodes in the Workflow | Node Name | Purpose | Documentation Link | |-----------|---------|--------------------| | Manual Trigger | Starts the workflow manually and sends test data | Docs | | Split Out | Converts an array of strings into separate JSON objects | Docs | | Loop Over Items (Loop Over Items 1) | Demonstrates how an unsplit array is treated as one item | Docs | | Loop Over Items (Loop Over Items 2) | Iterates over each item separately | Docs | | Wait | Introduces a delay per iteration (set to 1 second) | Docs | | Code | Adds a constant parameter (param1) to each item | Docs | | NoOp (Result Nodes) | Displays output for inspection | Docs | Execution Details 1. How the Workflow Runs Manual Trigger starts execution** with the pasted JSON data. The workflow follows two paths: Unsplit Array Path → Loop Over Items 1 Processes the entire array as a single item. Result1 & Result5: Show that the array was not split. Split Array Path → Split Out → Loop Over Items 2 Splits the array into separate objects. Result2, Result3, Result4: Show that each item is processed individually. A Wait node (1 sec delay) demonstrates controlled execution. Code nodes modify the JSON, adding a parameter (param1). 2. What You Will See | Node | Expected Output | |------|---------------| | Result1 & Result5 | The entire array is processed as one item. | | Result2, Result3, Result4 | The array is split and processed as individual items. | | Wait Node | Adds a 1-second delay per item in Loop Over Items 2. | Use Cases This workflow is useful for: ✅ API Data Processing: Loop through API responses containing arrays. ✅ Web Scraping: Process multiple URLs individually. ✅ Task Automation: Execute a sequence of actions per item. ✅ Workflow Optimization: Control execution order, delays, and dependencies. Notes Sticky notes are included in the workflow for easy reference. The Wait node is optional—remove it for faster execution. This template is structured for beginners but serves as a building block for more advanced automations.

Automate LinkedIn Prospecting with AI Agent and Get Results Straight to Google Sheets! A practical AI-powered workflow that helps you find relevant LinkedIn profiles using natural language queries and saves the results automatically to Google Sheets. 🎯 What It Actually Does Accepts natural language requests (e.g., "Find marketing managers in Paris") Uses AI to extract search parameters: Job titles Industry Location Searches for matching LinkedIn profiles Saves profile URLs and titles to Google Sheets 🛠️ Technical Components AI Query Processor Converts natural language to structured search parameters Handles various input formats and languages Maintains context for accurate parameter extraction Search Engine Integration Uses Google Custom Search API Handles pagination for multiple results Filters for actual LinkedIn profile URLs Data Storage Automatically saves to Google Sheets Stores profile titles and URLs Easy to access and export 📋 Prerequisites OpenAI API key Google Custom Search API credentials Google Sheets access 💡 Adaptation Possibilities This template can be modified to scrape other websites by: Changing the search domain in the HTTP Request node Adjusting the URL filter in the Code node Modifying the column structure in Google Sheets Updating the AI prompt for different parameter extraction Example adaptations: Twitter profile finder GitHub repository search Company website finder Professional blog discovery 🔧 Setup Instructions API Setup Configure Google Custom Search API Set up OpenAI API Prepare Google Sheets Workflow Configuration Import both workflows Connect your API credentials Set up your Google Sheet Test with a sample query 📝 Usage Example Input: "Find software developers in London working in fintech" Output: A Google Sheet containing: LinkedIn profile URLs of software developers Profile titles/headlines Ready for your review and outreach #AIAgent #WebScraping #Automation #n8n #Workflow #LinkedInProspecting

This workflow converts Notion pages to markdown, and then converts that markdown back to Notion blocks. It will triple the content of the last updated page it finds. This is useless by itself, but you can copy-paste from this workflow to create your own. Prerequisites A notion account with some pages or databases Setup instructions Create a notion credential and share some pages as described here: https://docs.n8n.io/integrations/builtin/credentials/notion/ How it works The HTTP Request gets notion child blocks from a page, because the default n8n block only gets plain text and no links. The first code block converts it to markdown. The second code block converts it back to Notion blocks The last HTTP block appends everything to the original Notion page, essentially duplicating it for the purpose of demoing the script. I hope in the future we get official n8n blocks that extract markdown, or use markdown to write to Notion. There is community block that also does this, but this template is easier: you can simply copy-paste the blocks from this workflow.

Webhook | Paper Summarization Who is this for? This workflow is designed for researchers, students, and professionals who frequently read academic papers and need concise summaries. It is useful for anyone who wants to quickly extract key information from research papers hosted on arXiv. What problem is this workflow solving? Academic papers are often lengthy and complex, making it time-consuming to extract essential insights. This workflow automates the process of retrieving, processing, and summarizing research papers, allowing users to focus on key findings without manually reading the entire paper. What this workflow does This workflow extracts the content of an arXiv research paper, processes its abstract and main sections, and generates a structured summary. It provides a well-organized output containing the Abstract Overview, Introduction, Results, and Conclusion, ensuring that users receive critical information in a concise format. Setup Ensure you have n8n installed and configured. Import this workflow into your n8n instance. Configure an external trigger using the Webhook node to accept paper IDs. Test the workflow by providing an arXiv paper ID. (Optional) Modify the summarization model or output format according to your preferences. How to customize this workflow to your needs Adjust the HTTPRequest node to fetch papers from other sources beyond arXiv. Modify the Summarization Chain node to refine the summary output. Enhance the Reorganize Paper Summary step by integrating additional language models. Add an email or Slack notification step to receive summaries directly. Workflow Steps Webhook receives a request with an arXiv paper ID. Send an HTTP request using "Request to Paper Page" to fetch the HTML content of the paper. Extract the abstract and sections using "Extract Contents". Split out all sections using "Split out All Sections" to process individual paragraphs. Clean up text using "Remove useless links" to remove unnecessary elements. Summarize extracted content using "Summarization Chain". Aggregate summarized content using "Aggregate summarized content". Reorganize the paper summary into structured sections using "Reorganize Paper Summary". Extract key information using "Content Extractor" to classify data into Abstract Overview, Introduction, Results, and Conclusion. Respond to the webhook with the structured summary. Note: This workflow is designed for use with arXiv research papers but can be adapted to process papers from other sources.

Overview: Automate Your Google OAuth2 Credential Creation This workflow template streamlines the process of creating and naming individual Google OAuth2 credentials for multiple Google services within n8n. By automating tasks typically done manually, it saves significant time and reduces the risk of errors. Who Is This For? This template is perfect for: Marketers who frequently use Google Docs, Google Sheets, Google Slides, and Google Drive for document automation. Developers or technical users who manage numerous integrations and need to minimize credential creation overhead. Teams or solo users with multiple Google accounts who want to eliminate repetitive Google OAuth2 credential creation tasks. Prerequisite Knowledge • Basic familiarity with n8n, including how to configure nodes and connect services. • A Google OAuth JSON file (client ID, client secret, etc.) already set up in your Google Cloud Console. • An understanding of Google services (Docs, Sheets, Slides, Drive, Gmail, Calendar, Contacts and others) and which you may need for your use cases What Problem Does It Solve? Manually creating and naming separate OAuth2 credentials for each Google service can be time-consuming and prone to errors. For instance, if you manage 16 Google accounts, you might need to create 112 credentials manually. This workflow automates that process by using your Google OAuth JSON file and email address, generating uniquely named OAuth2 credentials for each Google service in just a single run per account. Key Features Manual Trigger – Start the workflow on demand to generate new credentials. Set Node for Google OAuth Details – Store your client ID, client secret, and other JSON info securely in one place. Automated Naming Convention – Use your Google email address to create distinct names for each credential, simplifying organization. Array of Google Services – Customize which services to create credentials for, such as Docs, Sheets, Slides, Drive, Gmail, Calendar, or Contacts. Batch Credential Creation – Split the array of Google services and automatically create separate OAuth2 credentials for each. Seamless OAuth2 Integration – Effortlessly authenticate all generated credentials within n8n. How to Set Up Insert Your JSON Details – Paste your Google OAuth 2.0 JSON data into the “Google JSON” node. Add Your Google Email Address – Specify your email address in the “Google Email” node to personalize the naming convention. Configure n8n Account Credentials – In the “n8n Create Credentials” node, select or add proper credentials (e.g., n8n API credentials). Execute the Workflow – Run the workflow to automatically generate individual OAuth2 credentials. Finalize in n8n – Visit your n8n Credentials dashboard to complete the OAuth sign-in for each newly created credential. Customization Options Modify the Services Array** – Easily add or remove Google products based on your workspace needs by editing the array in the “Services” node. Adjust Naming Logic** – Tailor the credential naming convention in the “n8n Create Credentials” node to match your organization’s style or best practices. Set Role-Based Access** – In n8n, control who can view and use these automatically generated credentials by adjusting user permissions. Time-Saving Example I initially had 16 Google accounts, requiring 112 credentials if done manually. With this workflow, I needed just one run per account—saving around two hours of repetitive data entry. Yes, I spent three hours building and documenting this, but it pays off quickly for anyone managing multiple accounts or large teams.

AI-Powered Workflow for Automated Video Creation Overview This workflow is designed for individuals and businesses looking to streamline the creation of engaging promotional videos. Whether you're marketing a product or developing a personal brand, this AI-driven system automates the entire video production process, from script generation to final video upload. Key Features 🎙️ AI-Generated Voiceovers with ElevenLabs Using ElevenLabs, this workflow converts text-based scripts into natural-sounding voiceovers, making your videos more engaging and professional. ✍️ Enhanced Prompt Engineering with Together AI To ensure high-quality content, Together AI refines and optimizes prompts, helping generate more compelling narratives and animations. 🎥 Image-to-Video Conversion with Hailuo AI With Hailuo AI, static images are transformed into dynamic animated videos, allowing for visually appealing content without the need for manual editing. 🧠 Intelligent Processing with OpenAI Various inference tasks, such as text generation and content refinement, are handled by OpenAI, ensuring smooth and efficient video production. Automated Video Upload & Sharing 📊 Google Sheets Integration Once the video is created, its downloadable URL is automatically uploaded to a Google Sheets document, making it easy to access and manage content. Add video title, video url, video status columns for tracking and archiving. 📢 Multi-Platform Distribution Users can download and upload the generated videos to major social media platforms, including Facebook, YouTube, Instagram, and TikTok, maximizing reach and engagement. Who Can Benefit? This workflow is ideal for: Marketers looking to create fast, automated promotional videos Content creators who want to streamline video production Businesses seeking an efficient way to generate engaging product showcases By leveraging the power of AI, this workflow simplifies video creation, saving time while delivering high-quality content. 🚀

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.

Fact-Checking Workflow Documentation Overview This workflow is designed for automated fact-checking of texts. It uses AI models to compare a given text with a list of facts and identify potential discrepancies or hallucinations. Components 1. Input The workflow can be initiated in two ways: a) Manually via the "When clicking 'Test workflow'" trigger b) By calling from another workflow via the "When Executed by Another Workflow" trigger Required inputs: facts: A list of verified facts text: The text to be checked 2. Text Preparation The "Code" node splits the input text into individual sentences Takes into account date specifications and list elements 3. Fact Checking Each sentence is individually compared with the given facts Uses the "bespoke-minicheck" Ollama model for verification The model responds with "Yes" or "No" for each sentence 4. Filtering and Aggregation Sentences marked as "No" (not fact-based) are filtered The filtered results are aggregated 5. Summary A larger language model (Qwen2.5) creates a summary of the results The summary contains: Number of incorrect factual statements List of incorrect statements Final assessment of the article's accuracy Usage Ensure the "bespoke-minicheck" model is installed in Ollama (ollama pull bespoke-minicheck) Prepare a list of verified facts Enter the text to be checked Start the workflow The results are output as a structured summary Notes The workflow ignores small talk and focuses on verifiable factual statements Accuracy depends on the quality of the provided facts and the performance of the AI models Customization Options The summarization function can be adjusted or removed to return only the raw data of the issues found The AI models used can be exchanged if needed This workflow provides an efficient method for automated fact-checking and can be easily integrated into larger systems or editorial workflows.

This automated workflow scrapes and processes the monthly "Who is Hiring" thread from Hacker News, transforming raw job listings into structured data for analysis or integration with other systems. Perfect for job seekers, recruiters, or anyone looking to monitor tech job market trends. How it works Automatically fetches the latest "Who is Hiring" thread from Hacker News Extracts and cleans relevant job posting data using the HN API Splits and processes individual job listings into structured format Parses key information like location, role, requirements, and company details Outputs clean, structured data ready for analysis or export Set up steps Configure API access to [Hacker News](https://github.com/HackerNews/API ) (no authentication required) Follow the steps to get your cURL command from https://hn.algolia.com/ Set up desired output format (JSON structured data or custom format) Optional: Configure additional parsing rules for specific job listing information Optional: Set up integration with preferred storage or analysis tools The workflow transforms unstructured job listings into clean, structured data following this pattern: Input: Raw HN thread comments Process: Extract, clean, and parse text Output: Structured job listing data This template saves hours of manual work collecting and organizing job listings, making it easier to track and analyze tech job opportunities from Hacker News's popular monthly hiring threads.

Automated YouTube Bedtime Story Video Generator (No Code) n8n Workflow Free Support: Setting up and getting the workflow tailord to your needs. One small free adjustment included. Transform your creative ideas into enchanting bedtime story videos with this fully automated n8n workflow. Designed for content creators, digital marketers, and storytellers, this tool streamlines the process of turning audio recordings into professional, engaging YouTube videos. Samautomation.work You will have the best and cheapest video rendering service online. Check the website for more information. You can customize every video and change all these settings: Change the aspact ratio to 16:9 for long form content. Check the API docs for more information. "settings": { "aspect_ratio": "9:16", "background_volume": 0.15, "voice_volume": 1.0, "font": "bangers", "font_size": 40, "text_color": "blue", "stroke_color": "white", "stroke_width": 10, "disable_captions": "true" More information on: Samautomation.work support Contact our whatsapp support if you have any questions, we are ready to assist with customizing the template if needed. Key Features Seamless Audio-to-Text Conversion:** Utilize OpenAI Whisper to convert audio recordings into accurate transcripts, ensuring every word of your story is captured. AI-Powered Image Generation:** Automatically generate beautiful, thematic visuals using advanced AI image tools that create captivating 16:9 backgrounds tailored for bedtime stories. Dynamic Video Compilation:** Merge images, voiceovers, and background music into a polished video with a few clicks. Customize video length, style, and audio levels to match your vision. Automated YouTube Integration:** Upload your videos directly to YouTube complete with autogenerated titles, descriptions, and metadata. Manage your content easily with real-time updates. Efficient Workflow Management:** Track your projects via Google Sheets and receive instant notifications through Telegram, keeping you always in the loop. Cost Efficiency:** Each video costs only 25 cents to produce, making this solution incredibly affordable for large-scale content creation. How It Works Capture & Transcribe: Record your bedtime story and let OpenAI Whisper transcribe the audio into text. Generate Stunning Visuals: Use integrated AI image generation to create dreamy visuals that complement your narrative. Compile Your Video: Combine the visuals, transcripts, and background music into a complete video ready for distribution. Publish & Manage: Automatically upload your video to YouTube, with all details saved and tracked in Google Sheets for seamless management. Who Is It For? This workflow is perfect for: Content Creators** looking to effortlessly produce engaging bedtime story videos. Digital Marketers** aiming to boost video content output without heavy manual intervention. Storytellers & Educators** who want to bring their narratives to life with a professional finish. Small Businesses & Startups** seeking scalable video production solutions. Setup Requirements API keys for OpenAI, Google Cloud Storage, and YouTube. Basic familiarity with n8n and API integration. A passion for storytelling and creative video production. Video Rendering with samautomation.work Start automating your video creation process today and captivate your audience with enchanting bedtime stories. With this workflow, you can save time, enhance productivity, and focus on what you do best—telling magical stories, all while keeping your production cost at just 25 cents per video! Ready to transform your content game? Get your Automated YouTube Bedtime Story Video Generator now and start creating charming videos in minutes! Demo video Check out the link to the demo video of the end result.

How it Works As n8n instances scale, teams often lose track of sub-workflows—who uses them, where they are referenced, and whether they can be safely updated. This leads to inefficiencies like unnecessary copies of workflows or reluctance to modify existing ones. This workflow solves that problem by: Fetching all workflows and identifying which ones execute others. Verifying that referenced subworkflows exist. Building a caller-subworkflow dependency graph for visibility. Automatically tagging sub-workflows based on their parent workflows. Providing a chart visualization to highlight the most-used sub-workflows. Set Up Steps Estimated time: ~10–15 minutes Set up n8n API credentials to allow access to workflows and tags. Replace instance_url with your n8n instance URL. Run the workflow to analyze dependencies and generate the graph. Review and validate assigned tags for sub-workflows. (Optional) Enable pie chart visualization to see the most-used sub-workflows. This workflow is essential for enterprise teams managing large n8n instances, preventing workflow duplication, reducing uncertainty around dependencies, and allowing safe, informed updates to sub-workflows.

n8n Creators Leaderboard Workflow Why Use This Workflow? The n8n Creators Leaderboard Workflow is a powerful tool for analyzing and presenting detailed statistics about workflow creators and their contributions within the n8n community. It provides users with actionable insights into popular workflows, community trends, and top contributors, all while automating the process of data retrieval and report generation. Benefits Discover Popular Workflows**: Identify workflows with the most unique visitors and inserters (weekly and monthly). Understand Community Trends**: Gain insights into what workflows are resonating with the community. Recognize Top Contributors**: Highlight impactful creators to foster collaboration and inspiration. Save Time with Automation**: Automates data fetching, processing, and reporting for efficiency. Use Cases For Workflow Creators**: Track performance metrics of your workflows to optimize them for better engagement. For Community Managers**: Identify trends and recognize top contributors to improve community resources. For New Users**: Explore popular workflows as inspiration for building your own automations. How It Works This workflow aggregates data from GitHub repositories containing statistics about workflow creators and their templates. It processes this data, filters it based on user input, and generates a detailed Markdown report using an AI agent. Key Features Data Aggregation: Fetches creator and workflow statistics from GitHub JSON files. Custom Filtering: Focuses on specific creators based on a username provided via chat. AI-Powered Reports: Generates comprehensive Markdown reports with summaries, tables, and insights. Output Flexibility: Saves reports locally with timestamps for easy access. Data Retrieval & Processing Creators Data**: Retrieved via an HTTP Request node from a JSON file containing aggregated statistics about creators. Workflows Data**: Pulled from another JSON file with workflow metrics like visitor counts and inserter statistics. Data Merging**: Combines creator and workflow data by matching usernames to provide enriched statistics. Report Generation The AI agent generates a Markdown report that includes: A summary of the creator’s contributions. A table of workflows with key metrics (e.g., unique visitors, inserters). Insights into trends or community feedback. The report is saved locally as a file with a timestamp for tracking purposes. Quick Start Guide Prerequisites Ensure your n8n instance is running. Verify that the GitHub base URL and file variables are correctly set in the Global Variables node. Confirm that your OpenAI credentials are configured for the AI Agent node. How to Start Activate the Workflow: Make sure the workflow is active in your n8n environment. Trigger via Chat: Use the Chat Trigger node to initiate the workflow by sending a message like: show me stats for username [desired_username] Replace [desired_username] with the username you want to analyze. Processing & Report Generation: The workflow fetches data, processes it, and generates a Markdown report. View Output: The final report is saved locally as a file (with a timestamp), which you can review to explore leaderboard insights.

🎬 YouTube Shorts Automation Tool 🚀 Automate the creation of high-performing YouTube Shorts in minutes! Who is this for? 🎯 Content Creators**: Generate engaging short videos effortlessly. Marketing Agencies**: Produce client-ready content quickly. Business Owners**: Promote products/services through viral short-form content. What problem does this solve? 🛠️ Creating short-form video content is time-consuming, complex, and skill-intensive. This workflow automates video creation, eliminating the need for video editing expertise while ensuring SEO optimization, high-quality visuals, and professional voiceovers. How it works 🌟 Enter your video idea into the chat interface. AI generates a script optimized for engagement and SEO. Voiceover is created with realistic AI narration. Relevant visuals are selected to match the script. The video is assembled and delivered via a shareable link. Setup ⚙️ (5-10 min) Connect required APIs (most have free tiers). Follow the guided setup (video tutorial included). Start generating professional YouTube Shorts instantly! Required APIs 🔗 Content Generation**: OpenAI, ElevenLabs (script & voiceover) Media Processing**: Cloudinary, Replicate (images & storage) Integration Tools**: 0codekit, Creatomate (video assembly) Customization 🎨 Adjust script styles & voiceover preferences. Modify visuals to match your brand. Optimize video length and format. 🚀 Start automating your YouTube Shorts today and grow your audience effortlessly!

This n8n workflow is designed to automate the aggregation, processing, and reporting of community statistics related to n8n creators and workflows. Its primary purpose is to generate insightful reports that highlight top contributors, popular workflows, and key trends within the n8n ecosystem. Here's how it works and why it's important: How It Works Data Retrieval: The workflow fetches JSON data files from a GitHub repository containing statistics about creators and workflows. It uses HTTP requests to access these files dynamically based on pre-defined global variables. Data Processing: The data is parsed into separate streams for creators and workflows. It processes the data to identify key metrics such as unique weekly and monthly inserters/visitors. Ranking and Filtering: The workflow sorts creators by their weekly inserts and workflows by their popularity. It selects the top 10 creators and top 50 workflows for detailed analysis. Report Generation: Using AI tools like GPT-4 or Google Gemini, the workflow generates a Markdown report summarizing trends, contributors, and workflow statistics. The report includes tables with detailed metrics (e.g., unique visitors, inserters) and insights into why certain workflows are popular. Distribution: The report is saved locally or uploaded to Google Drive. It can also be shared via email or Telegram for broader accessibility. Automation: A schedule trigger ensures the workflow runs daily or as needed, keeping the reports up-to-date. Why It's Important Community Insights**: This workflow provides actionable insights into the n8n community by identifying impactful contributors and popular workflows. This fosters collaboration and innovation within the ecosystem. Time Efficiency**: By automating data collection, processing, and reporting, it saves significant time and effort for community managers or administrators. Recognition of Contributors**: Highlighting top creators encourages engagement and recognizes individuals driving value in the community. Trend Analysis**: The workflow helps uncover patterns in usage, enabling better decision-making for platform improvements or feature prioritization. Scalability**: With its modular design, this workflow can be easily adapted to include additional metrics or integrate with other tools.

🎥 YouTube Video AI Agent Workflow This n8n workflow template allows you to interact with an AI agent that extracts details and the transcript of a YouTube video using a provided video ID. Once the details and transcript are retrieved, you can chat with the AI agent to explore or analyze the video's content in a conversational and insightful manner. 🌟 How the Workflow Works 🔗 Input Video ID: The user provides a YouTube video ID as input to the workflow. 📄 Data Retrieval: The workflow fetches essential details about the video (e.g., title, description, upload date) and retrieves its transcript using YouTube's Data API and additional tools for transcript extraction. 🤖 AI Agent Interaction: The extracted details and transcript are processed by an AI-powered agent. Users can then ask questions or engage in a conversation with the agent about the video's content, such as: Summarizing the transcript. Analyzing key points. Clarifying specific sections. 💬 Dynamic Responses: The AI agent uses natural language processing (NLP) to generate contextual and accurate responses based on the video data, ensuring a smooth and intuitive interaction. 🚀 Use Cases 📊 Content Analysis**: Quickly analyze long YouTube videos by querying specific sections or extracting summaries. 📚 Research and Learning**: Gain insights from educational videos or tutorials without watching them entirely. ✍️ Content Creation**: Repurpose transcripts into blogs, social media posts, or other formats efficiently. ♿ Accessibility**: Provide an alternative, text-based way to interact with video content for users who prefer reading over watching. 🛠️ Resources for Getting Started Google Cloud Console** (for API setup): Visit Google Cloud's Get Started Guide to configure your API access. YouTube Data API Key Setup**: Follow this guide to create and manage your YouTube Data API key. Install n8n Locally**: Refer to this installation guide for setting up n8n on your local machine. ✨ Sample Prompts "Tell me about this YouTube video with id: JWfNLF_g_V0" "Can you provide a list of key takeaways from this video with id: [youtube-video-id]?"

💡🌐 Essential Multipage Website Scraper with Jina.ai Use responsibly and follow local rules and regulations This N8N workflow enables automated multi-page website scraping using Jina.ai's powerful web scraping capabilities, with seamless integration to Google Drive for content storage. Here's how it works: Main Features The workflow automatically scrapes multiple pages from a website's sitemap and saves each page's content as a separate Google Drive document. Key Components Input Configuration Starts with a sitemap URL (default: https://ai.pydantic.dev/sitemap.xml)** Processes the sitemap to extract individual page URLs Includes filtering options to target specific topics or pages Scraping Process Uses Jina.ai's web scraper to extract content from each URL Converts webpage content into clean markdown format Extracts page titles automatically for document naming Storage Integration Creates individual Google Drive documents for each scraped page Names documents using the format "URL - Page Title" Saves content in markdown format for better readability Usage Instructions Set your target website's sitemap URL in the "Set Website URL" node Configure the "Filter By Topics or Pages" node to select specific content Adjust the "Limit" node (default: 20 pages) to control batch size Connect your Google Drive account Run the workflow to begin automated scraping Additional Features Built-in rate limiting through the Wait node to prevent overloading servers Batch processing capability for handling large sitemaps The workflow requires no API key for Jina.ai, making it accessible for immediate use while maintaining responsible scraping practices.

🎦🚀 YouTube Video Comment Analysis Agent This n8n workflow is designed to help YouTube creators analyze video details and comments to generate a comprehensive and actionable report. The workflow provides insights into video performance, audience engagement, and viewer feedback, helping creators identify trends, interests, and opportunities for future content creation. ✨ Key Features Video Performance Analysis: Extracts metrics like views, likes, and comments to evaluate the video's success. Comment Sentiment Analysis: Determines the tone of comments (positive, neutral, or negative) to understand audience sentiment. Recurring Themes Detection: Identifies common topics or questions in comments to highlight viewer interests. Engagement Drivers: Pinpoints what aspects of the video resonated most with viewers. Actionable Recommendations: Offers strategies for creating follow-up content or improving future videos. Keyword Suggestions: Extracts frequently mentioned terms for better discoverability on YouTube. Collaboration Opportunities: Suggests potential partnerships based on viewer feedback or related channels. 🛠️ How to Use Set Up Workflow Variables: Add your GOOGLE_API_KEY and the VIDEO_ID of the YouTube video you want to analyze in the "Workflow Variables" node. Ensure your Google API key has access to the YouTube Data API. Run the Workflow: Trigger the workflow manually or through another workflow using the "Execute Workflow Trigger" node. The workflow will fetch video details and comments using pagination to ensure all data is captured. Generate Insights: The workflow processes video details and comments to create a detailed report with actionable insights. Outputs include sentiment analysis, engagement drivers, content opportunities, and audience profiling. View or Share Results: The report is converted into Markdown and can be emailed via Gmail or saved to Google Drive as a document. 🌟 Value from This Workflow Gain a deeper understanding of your audience's preferences and feedback. Identify trends and engagement drivers to replicate success in future videos. Discover new content opportunities based on viewer questions and suggestions. Improve discoverability by leveraging keyword suggestions extracted from comments. Build stronger connections with your audience by addressing their needs effectively.

Summary This template uses the item handling nodes, and expression-support in n8n, without using a Code node, to extract multiple attachments from a GMail (trigger input) message/event, and (conditionally) upload each of them to Google Drive. Note: There is another template titled Get Multiple Attachments from Gmail and upload them to GDrive that does basically the same thing, but it uses a Code node. Details Using Split Out instead of Code The “secret” to how this works is that n8n supports a special input field name $binary that references the entire set of (multiple) binary data sub-elements in a single input item. It may look like an expression, but in this case it is a “fixed” (literal) value used as the Fields to Split Out parameter value. Dealing with names that are prefixed/suffixed with an Index The next challenge with multiple attachments from a GMail message is that each one is still assigned different name like "attachment_0", "attachment_1", etc. This makes it tricky to reference them in a generic way. However, once n8n splits the items out, the binary in each item is always the first (i.e. index-zero / [0]) and ONLY key/value. So, that makes it possible get the key-name and attributes of the corresponding value indirectly with some clever expression syntax. Input Data Field Name -> Expression: {{ $binary.keys()[0] }} - This returns the name, regardless of whether it is "attachment_0", "attachment_1", or whatever else. Attachment file name: -> Expression: {{ $binary.values()[0].fileName }} Attachment file name extension: -> Expression: {{ $binary.values()[0].fileExtension }} Attachment file type: -> Expression: {{ $binary.values()[0].fileType }} Attachment file size (e.g. string "100 kB"): -> Expression: {{ $binary.values()[0].fileSize }} Attachment file size (numeric): -> Expression: {{ $binary.values()[0].fileSize.split(' ')[0].toNumber() }} Attachment mime type: -> Expression: {{ $binary.values()[0].mimeType }} Attachment id (storage GUID): -> Expression: {{ $binary.values()[0].id }} Flow Control Since each of the attachments becomes a single item, it is relatively straightforward to introduce other n8n nodes like If, Switch, or Filter and route each single attachment item into different workflow paths. The template demonstrates how each attachment binary could be routed based on its file size, as an example.

Turn BBC News Articles into Podcasts using Hugging Face and Google Gemini Effortlessly transform BBC news articles into engaging podcasts with this automated n8n workflow. Who is this for? This template is perfect for: Content creators** who want to quickly produce podcasts from current events. Students** looking for an efficient way to create audio content for projects or assignments. Individuals** interested in generating their own podcasts without technical expertise. Setup Information Install n8n: If you haven't already, download and install n8n from n8n.io. Import the Workflow: Copy the JSON code for this workflow and import it into your n8n instance. Configure Credentials: Gemini API: Set up your Gemini API credentials in the workflow's LLM nodes. Hugging Face Token: Obtain an access token from Hugging Face and add it to the HTTP Request node for the text-to-speech model. Customize (Optional): Filtering Criteria: Adjust the News Classifier node to fine-tune the selection of news articles based on your preferences. Output Options: Modify the workflow to save the generated audio file to a cloud storage service or publish it to a podcast hosting platform. Prerequisites An active n8n instance. Basic understanding of n8n workflows (no coding required). API credentials for Gemini and a Hugging Face account with an access token. What problem does it solve? This workflow eliminates the manual effort involved in creating podcasts from news articles. It automates the entire process, from fetching and filtering news to generating the final audio file. What are the benefits? Time-saving:** Create podcasts in minutes, not hours. Easy to use:** No coding or technical skills required. Customizable:** Adapt the workflow to your specific needs and preferences. Cost-effective:** Leverage free or low-cost services like Gemini and Hugging Face. How does it work? The workflow fetches news articles from the BBC website. It filters articles based on their suitability for a podcast. It extracts the full content of the selected articles. It uses Gemini LLM to create a podcast script. It converts the script to speech using Hugging Face's text-to-speech model. The final podcast audio is ready for use. Nodes in the Workflow Fetch BBC News Page: Retrieves the main BBC News page. News Classifier: Categorizes news articles using Gemini LLM. Fetch BBC News Detail: Extracts detailed content from suitable articles. Basic Podcast LLM Chain: Generates a podcast script using Gemini LLM. HTTP Request: Converts the script to speech using Hugging Face. Add Story I'm excited to share this workflow with the n8n community and help content creators and students easily produce engaging podcasts! Additional Tips Explore the n8n documentation and community resources for more advanced customization options. Experiment with different filtering criteria and LLM prompts to achieve your desired podcast style.

Telegram Personal Assistant with Long-Term Memory & Note-Taking This n8n workflow transforms your Telegram bot into a powerful personal assistant that handles voice, photo, and text messages. The assistant uses AI to interpret messages, save important details as long-term memories or notes in a Baserow database, and recall information for future interactions. 🌟 How It Works Message Reception & Routing Telegram Integration: The workflow is triggered by incoming messages on your Telegram bot. Dynamic Routing: A switch node inspects the message to determine whether it's voice, text, or photo (with captions) and routes it for the appropriate processing. Content Processing Voice Messages: Audio files are retrieved and sent to an AI transcription node to convert spoken words into text. Text Messages: Text is directly captured and prepared for analysis. Photos: If an image is received, the bot fetches the file (and caption, if provided) and uses an AI-powered image analysis node to extract relevant details. AI-Powered Agent & Memory Management The core AI agent (powered by GPT-4o-mini) processes the incoming message along with any previous conversation history stored in PostgreSQL memory buffers. Long-Term Memory: When a message contains personal or noteworthy information, the assistant uses a dedicated tool to save this data as a long-term memory in Baserow. Note-Taking: For specific instructions or reminders, the assistant saves concise notes in a separate Baserow table. The AI agent follows defined rules to decide which details are saved as memories and which are saved as notes. Response Generation After processing the message and updating memory/notes as needed, the AI agent crafts a contextual and personalized response. The response is sent back to the user via Telegram, ensuring smooth and natural conversation flow. 🚀 Key Features Multimodal Input:** Seamlessly handles voice, photo (with captions), and text messages. Long-Term Memory & Note-Taking:** Uses a Baserow database to store personal details and notes, enhancing conversational context over time. AI-Driven Contextual Responses:** Leverages an AI agent to generate personalized, context-aware replies based on current input and past interactions. User Security & Validation:** Incorporates validation steps to verify the user's Telegram ID before processing, ensuring secure and personalized interactions. Easy Baserow Setup:** Comes with a clear setup guide and sample configurations to quickly integrate Baserow for managing memories and notes. 🔧 Setup Guide Telegram Bot Setup: Create your bot via BotFather and obtain the Bot Token. Configure the Telegram webhook in n8n with your bot's token and URL. Baserow Database Configuration: Memory Table: Create a workspace titled "Memories and Notes". Set up a table (e.g., "Memory Table") with at least two fields: Memory (long text) Date Added (US date format with time) Notes Table: Duplicate the Memory Table and rename it to "Notes Table". Change the first field's name from "Memory" to "Notes". n8n Workflow Import & Configuration: Import the workflow JSON into your n8n instance. Update credentials for Telegram, Baserow, OpenAI, and PostgreSQL (for memory buffering) as needed. Adjust node settings if you need to customize AI agent prompts or memory management rules. Testing & Deployment: Test your bot by sending various message types (text, voice, photo) to confirm that the workflow processes them correctly, updates Baserow, and returns the appropriate response. Monitor logs to ensure that memory and note entries are correctly stored and retrieved. ✨ Example Interactions Voice Message Processing:** User sends a voice note requesting a reminder. Bot Response: "Thanks for your message! I've noted your reminder and saved it for future reference." Photo with Caption:** User sends a photo with the caption "Save this recipe for dinner ideas." Bot Response: "Got it! I've saved this recipe along with the caption for you." Text Message for Memory Saving:** User: "I love hiking on weekends." Bot Response: "Noted! I’ll remember your interest in hiking." Retrieving Information:** User asks: "What notes do I have?" Bot Response: "Here are your latest notes: [list of saved notes]." 🛠️ Resources & Next Steps Telegram Bot Configuration:** Telegram BotFather Guide n8n Documentation:** n8n Docs Community Forums:** Join discussions and share your customizations! This workflow not only streamlines message processing but also empowers users with a personal AI assistant that remembers details over time. Customize the rules and responses further to fit your unique requirements and enjoy a more engaging, intelligent conversation experience on Telegram!

The YogiAI workflow automates sending daily yoga pose reminders and related information via Line Push Messages . This automation leverages data from a Google Sheets database containing yoga pose details such as names, image URLs, and links to ensure users receive personalized and engaging content every day. Purpose Provide users with daily yoga pose suggestions tailored to their practice. Deliver visually appealing and informative content through Line's Flex Messages, including images and clickable links. Log user interactions and preferences back into Google Sheets to refine future recommendations. Key Features Automated Daily Reminders : Sends a curated list of yoga poses at a scheduled time (21:30 Bangkok time). Dynamic Content Generation : Uses AI to rewrite and format messages in a user-friendly manner, complete with emojis and clear instructions. Integration with Google Sheets : Pulls data from a predefined Google Sheet and logs interactions for continuous improvement. Customizable Messaging : Ensures JSON outputs are properly formatted for Line’s Flex Message API, allowing for interactive and visually rich content. Data Source Google Sheets Structure The workflow relies on a Google Sheet structured as follows: PoseName : The name of the yoga pose. uri : The image URL representing the pose. url : A clickable link directing users to more information about the pose. Sample Data Layout Supine Angle https://example.com/SupineAngle-tn146.png https://example.com/pose/SupineAngle Warrior II https://example.com/WarriorII-tn146.png https://example.com/pose/WarriorII *Note : Ensure that you update the Google Sheet with your own data. Refer to this sample sheet for reference. * Scheduled Trigger The workflow is triggered daily at 21:30 (9:30 PM) Bangkok Time (Asia/Bangkok) . This ensures timely delivery of reminders to users, keeping them engaged with their yoga practice. Workflow Process Data Retrieval Node: Get PoseName Fetches yoga pose details from the specified range in the Google Sheet. Content Generation Node: WritePosesToday Utilizes Azure OpenAI to craft user-friendly text, complete with emojis and clear instructions. Node: RewritePosesToday Formats the AI-generated text specifically for Line messaging, ensuring compatibility and visual appeal. JSON Formatting Node: WriteJSONflex Generates JSON structures required for Line’s Flex Messages, enabling carousel displays of yoga pose images and links. Node: Fix JSON Ensures all JSON outputs are correctly formatted before being sent via Line. Message Delivery Node: Line Push with Flex Bubble Sends the final message, including both text and Flex Message carousels, directly to users via Line Push Messages. Logging Interactions Nodes: YogaLog & YogaLog2 Logs each interaction back into Google Sheets to track which poses were sent and how often they appear, refining future recommendations. Setup Prerequisites Google Sheets Account : Set up a Google Sheet with the required structure and populate it with your yoga pose data. Line Developer Account : Create a Line channel to obtain necessary credentials for sending push messages. Azure OpenAI Account : Configure access to Azure OpenAI services for generating and formatting content. Intended Audience This workflow is ideal for: Yoga Instructors : Seeking to engage students with daily pose suggestions. Fitness Enthusiasts : Looking to maintain consistency in their yoga practice. Content Creators : Interested in automating personalized and visually appealing content distribution.

🐶🤖 AI Agent for Pet Shops – Automate Customer Service & Bookings! 🐾💡 Transform Your Pet Shop with AI-Powered Automation! 🚀 Enhance customer experience and optimize operations with this n8n AI Agent designed for pet shops. 📲🐾 Automate client interactions, appointment scheduling, and service recommendations—saving time and increasing revenue! 🔹 Key Features: ✅ Instant WhatsApp responses – AI-powered chatbot handles customer inquiries. 💬 ✅ Automated appointment scheduling – Clients can book services hassle-free. 📅✂️ ✅ Personalized reminders – Reduce no-shows with automated notifications. 📢🐾 ✅ Customer data & service history management – Track interactions effortlessly. 📊📁 ✅ Product & service recommendations – Improve sales with smart suggestions. 🎁🐶 📌 How It Works 1️⃣ The workflow captures customer inquiries via WhatsApp. 2️⃣ AI processes requests, provides information, and offers booking options. 3️⃣ Clients can schedule grooming, vet visits, or other services in seconds. 4️⃣ Automated reminders ensure appointments are remembered. 5️⃣ Customer data is stored for better service personalization. ⚙️ Setup & Customization 🔧 Connect your WhatsApp API (evolution) for instant messaging. 🔧 Integrate with Google Calendar for appointment booking. 🔧 Customize reminders, services, and pricing rules to fit your business. 💡 Reduce manual work, improve customer satisfaction, and scale your pet shop with AI automation! 🐶🤖 [PT-BR] Agente de IA para Pet Shops – Atendimento e Agendamentos Automatizados! 🐾💡 Transforme Seu Pet Shop com Automação Inteligente! 🚀 Otimize o atendimento ao cliente e agilize processos com este Agente de IA para n8n. 📲🐾 Automatize interações, agendamentos e recomendações de serviços—economizando tempo e aumentando as vendas! 🔹 Principais Funcionalidades: ✅ Atendimento automático no WhatsApp – IA responde clientes instantaneamente. 💬 ✅ Agendamento de serviços automatizado – Clientes marcam banho, tosa ou consultas facilmente. 📅✂️ ✅ Lembretes personalizados – Reduza faltas com notificações automáticas. 📢🐾 ✅ Gestão de clientes e histórico de serviços – Controle dados de forma eficiente. 📊📁 ✅ Sugestão de produtos e serviços – Venda mais com recomendações inteligentes. 🎁🐶 📌 Como Funciona 1️⃣ O fluxo recebe perguntas dos clientes via WhatsApp. 2️⃣ A IA processa os pedidos e fornece opções de agendamento. 3️⃣ O cliente escolhe o serviço desejado e agenda em segundos. 4️⃣ Lembretes automáticos garantem que os clientes não esqueçam os horários. 5️⃣ O histórico do cliente é salvo para oferecer um atendimento mais personalizado. ⚙️ Configuração e Personalização 🔧 Conecte sua API do WhatsApp (evolution) para interação automática. 🔧 Integre ao Google Calendar para gerenciar agendamentos. 🔧 Personalize valores, serviços e regras de envio de lembretes conforme sua necessidade. 💡 Automatize processos, melhore a experiência do cliente e escale seu pet shop com IA! 🚀

This workflow creates an automated system for monitoring and receiving notifications about new videos from your favorite YouTube channels through RSS feeds, with customizable email and Telegram notifications. 🌟 Key Features 📡 RSS Feed Management Accepts custom YouTube channel IDs or uses default channels Automatically creates RSS feeds for each YouTube channel Monitors channels for new video uploads Labels and filters recent videos within a 3-day window (change this as required) 📨 Multi-Channel Notification System Sends Telegram notifications with video thumbnails and links Delivers customized email notifications in two formats: Individual emails for each new video Single digest email containing all new videos ⚙️ Content Processing Fetches detailed video information using YouTube API Creates responsive HTML email templates with video previews Includes video thumbnails, titles, descriptions, and direct links Maintains professional formatting across different email clients 🛠️ Setup Requirements 🔑 API Configuration YouTube Data API credentials Gmail account for sending notifications Telegram bot token and chat ID OpenAI API key for content processing 📋 Channel Management Add YouTube channel IDs through form input Configure default channel list Set notification preferences Adjust monitoring schedule This workflow is perfect for content creators, marketers, or anyone wanting to stay updated with their favorite YouTube channels through automated, professionally formatted notifications delivered via email and Telegram.

🚀 TikTok Video Automation Tool ✨ (Frequent Updates) Create viral TikTok videos effortlessly — no editing skills required! Who is this for? 🎯 ✅ Content Creators: Pump out engaging short videos in minutes. ✅ Marketing Agencies: Deliver high-quality client content — fast. ✅ Business Owners: Promote your brand with attention-grabbing TikToks. What problem does this solve? 🛠️ Short-form video content is king, but creating it takes time, skill, and effort. This tool automates the entire process, from scriptwriting to video production, ensuring SEO-optimized, high-quality content without any manual editing. How it works 🌟 1️⃣ Enter your video idea and choose where to receive the final video (TikTok upload or link via WhatsApp, Gmail, etc.). 2️⃣ AI crafts a high-engagement script with SEO optimization. 3️⃣ Voiceover is generated with ultra-realistic AI narration. 4️⃣ Relevant visuals are selected to perfectly match the script. 5️⃣ Your TikTok video is assembled and either directly uploaded to TikTok or delivered via a shareable link. Quick & Easy Setup ⚙️ (5-10 min) 🔹 Connect required APIs (most have free plans). 🔹 Follow the step-by-step setup (video tutorial included). 🔹 Start generating professional TikTok videos instantly! Required APIs 🔗 Content & Voiceover:** OpenAI (Paid), ElevenLabs (Free) Media Processing:** Cloudinary (Free), Replicate (Paid) Video Assembly:** 0codekit (Free), Creatomate (Free) Optional Integrations 🔗 Messaging & Sharing:** WhatsApp, Telegram, Gmail, Outlook Direct Upload:** TikTok Customization 🎨 Adjust script styles & voiceover preferences. Modify visuals to align with your brand. Optimize video length and format. 🚀 Start automating your TikTok content today and grow your audience on autopilot!

Automatically Create and Post YouTube Shorts from Podcasts and Other Videos Using AI (Simplified). Transform podcasts and other videos into captivating, fully optimized YouTube Shorts with this all-in-one automation solution—designed for content creators who repurpose engaging clips. By leveraging advanced YouTube analytics, this template identifies the most compelling moments from your source material and automatically crafts them into scroll-stopping shorts. With intelligent editing, auto-generated titles and descriptions, and customizable scheduling, your clips become instantly post-ready, helping you expand your reach while saving hours on manual editing. Key Features Analytics-Driven Highlight Extraction:** Automatically analyzes engagement metrics to select the best moments from podcasts or other creators' videos, ensuring each clip resonates with your audience. AI-Powered Editing:** Applies professional-grade editing—adding captions, effects, transitions, and more—to create visually stunning, high-impact shorts. Auto-Generated Metadata:** Seamlessly creates dynamic titles and descriptions, fully optimizing your clips for immediate upload. Customizable Scheduling:** Enables you to set upload intervals that align with your strategy, ensuring a steady stream of content on your channel. Seamless YouTube Integration:** Directly connects with YouTube’s API, streamlining the process so your channel remains active and engaging with minimal effort. Designed specifically for content creators repurposing YouTube videos—and requiring only a Sipkes Studio account (it's Free) for full functionality—this simplified automation template streamlines the conversion of long-form content into bite-sized, shareable clips. Elevate your content strategy, maximize audience engagement, and reclaim valuable time with a solution built to drive your channel's growth.

🌐 Confluence Page AI Chatbot Workflow This n8n workflow template enables users to interact with an AI-powered chatbot designed to retrieve, process, and analyze content from Confluence pages. By leveraging Confluence's REST API and an AI agent, the workflow facilitates seamless communication and contextual insights based on Confluence page data. 🌟 How the Workflow Works 🔗 Input Chat Message The workflow begins when a user sends a chat message containing a query or request for information about a specific Confluence page. 📄 Data Retrieval The workflow uses the Confluence REST API to fetch page details by ID, including its body in the desired format (e.g., storage, view). The retrieved HTML content is converted into Markdown for easier processing. 🤖 AI Agent Interaction An AI-powered agent processes the Markdown content and provides dynamic responses to user queries. The agent is context-aware, ensuring accurate and relevant answers based on the Confluence page's content. 💬 Dynamic Responses Users can interact with the chatbot to: Summarize the page's content. Extract specific details or sections. Clarify complex information. Analyze key points or insights. 🚀 Use Cases 📚 Knowledge Management**: Quickly access and analyze information stored in Confluence without manually searching through pages. 📊 Team Collaboration**: Facilitate discussions by summarizing or explaining page content during team chats. 🔍 Research and Documentation**: Extract critical insights from large documentation repositories for efficient decision-making. ♿ Accessibility**: Provide an alternative way to interact with Confluence content for users who prefer conversational interfaces. 🛠️ Resources for Getting Started Confluence API Setup: Generate an API token for authentication via Atlassian's account management portal. Refer to Confluence's REST API documentation for endpoint details and usage instructions. n8n Installation: Install n8n locally or on a server using the official installation guide. AI Agent Configuration: Set up OpenAI or other supported language models for natural language processing.

Daily Real Estate Deal Finder Automation This automation is aimed to send you daily deals via email every morning at 9AM in real estate markets you are interested in with strict search criteria you provide. It uses ZillowAPI to get up to date listings and RentZestimates. From there it calculates a host of investing metrics such as your Down PMT, Cash on Cash ROI, Monthly Cash Flow, Monthly Maintenance and Vacancy Loss. Prerequisites N8N account Google account with OAuth setup here's a video for help: https://youtu.be/LTuy83t_Rt4?si=0XdpxM7G48gtFDe6 Google Sheets API enabled RapidAPI account with Zillow API credentials Blank Google Sheet created with specific columns Step 1: Create a New Workflow Create a new workflow in N8N Name it something meaningful like "Daily Real Estate Deal Finder" Credentials you will need: Google OAuth credentials (here's a video for help: https://www.youtube.com/watch?v=LTuy83t_Rt4&t=22s) Google sheets API enabled, RapidAPI Zillow credentials Step 2: Configure Search Parameters in Set Parameters Node Define your real estate search criteria as key-value pairs: Example location: "Austin, TX" min_bed: 2 min_bath: 2, min_price: 250000, max_price: 400000, propertyType: "Single Family= True" Step 3: Update Google Sheet Create a new Google Sheets Create the following columns Address, Price, Rent Zestimate, Cash onCash RoI, Monthly CashFlow and Down Pmt Make sure your google sheets node in N8N is mapping to the correct columns and the correct sheet Troubleshooting Tips If Zillow API fails, check your API credentials and request limits For calculation errors, verify your formulas in the Code node If Google Sheets node fails, ensure proper column mapping Always test with a small data set before running in production Happy Investing please let me know if you have any questions or trouble This workflow will now automatically search for real estate deals matching your criteria, calculate investment metrics, update your tracking spreadsheet, and email you a summary each morning. Here is the entire step by step tutorial to set this up: https://www.youtube.com/watch?v=OSeLeKc375Y&t=6s

CallForge - AI Gong Sales Call Processor Streamline your sales call analysis with CallForge, an automated workflow that extracts, enriches, and refines Gong.io call data for AI-driven insights. Who is This For? This workflow is designed for: ✅ Sales teams looking to automate sales call insights. ✅ Revenue operations (RevOps) professionals optimizing call data processing. ✅ Businesses using Gong.io to analyze and enhance sales call transcripts. What Problem Does This Workflow Solve? Manually analyzing sales calls is time-consuming and prone to inconsistencies. While Gong provides raw call data, interpreting these conversations and improving AI-generated summaries can be challenging. With CallForge, you can: ✔️ Automate transcript extraction from Gong.io. ✔️ Enhance AI insights by adding product and competitor data. ✔️ Reduce errors from AI-generated summaries by correcting mispronunciations. ✔️ Eliminate duplicate calls to prevent redundant processing. What This Workflow Does 1. Extracts Gong Call Data Retrieves call recordings, metadata, meeting links, and duration from Gong. 2. Removes Duplicate Entries Queries Notion** to ensure that already processed calls are not duplicated. 3. Enriches Call Data Fetches integration details** from Google Sheets. Retrieves competitor insights** from Notion. Merges data** to provide AI with a more comprehensive context. 4. Prepares AI-Friendly Transcripts Cleans up transcripts** for structured AI processing. Reduces prompt complexity** for more accurate OpenAI outputs. 5. Sends Processed Data to an AI Call Processor Delivers the cleaned and enriched transcript** to an AI-powered workflow for generating structured call summaries. How to Set Up This Workflow 1. Connect Your APIs 🔹 Gong API Access – Set up your Gong API credentials in n8n. 🔹 Google Sheets Credentials – Provide API access for retrieving integration data. 🔹 Notion API Setup – Connect Notion to fetch competitor insights and store processed data. 🔹 AI Processing Workflow – Ensure an OpenAI-powered workflow is in place for structured summaries. CallForge - 01 - Filter Gong Calls Synced to Salesforce by Opportunity Stage CallForge - 02 - Prep Gong Calls with Sheets & Notion for AI Summarization CallForge - 03 - Gong Transcript Processor and Salesforce Enricher CallForge - 04 - AI Workflow for Gong.io Sales Calls CallForge - 05 - Gong.io Call Analysis with Azure AI & CRM Sync CallForge - 06 - Automate Sales Insights with Gong.io, Notion & AI CallForge - 07 - AI Marketing Data Processing with Gong & Notion CallForge - 08 - AI Product Insights from Sales Calls with Notion 2. Customize to Fit Your Needs 💡 Modify Data Sources – Update connections if using a different CRM, database, or analytics tool. 💡 Adjust AI Processing Logic – Optimize transcript formatting based on your preferred AI model. 💡 Expand Data Enrichment – Integrate CRM data, industry benchmarks, or other insights. Why Use CallForge? By automating Gong call processing, CallForge empowers sales teams to: 📈 Gain valuable AI-driven insights from calls. ⚡ Speed up decision-making with cleaner, structured data. 🛠 Improve sales strategies based on enriched, accurate transcripts. 🚀 Start automating your Gong call analysis today!

CallForge - AI Gong Transcript PreProcessor Transform your Gong.io call transcripts into structured, enriched, and AI-ready data for better sales insights and analytics. Who is This For? This workflow is designed for: ✅ Sales teams looking to automate call transcript formatting. ✅ Revenue operations (RevOps) professionals optimizing AI-driven insights. ✅ Businesses using Gong.io that need structured, enriched call transcripts for better decision-making. What Problem Does This Workflow Solve? Manually processing raw Gong call transcripts is inefficient and often lacks essential context for AI-driven insights. With CallForge, you can: ✔ Extract and format Gong call transcripts for structured AI processing. ✔ Enhance metadata using sales data from Salesforce. ✔ Classify speakers as internal (sales team) or external (customers). ✔ Identify external companies by filtering out free email domains (e.g., Gmail, Yahoo). ✔ Enrich customer profiles using PeopleDataLabs to identify company details and locations. ✔ Prepare transcripts for AI models by structuring conversations and removing unnecessary noise. What This Workflow Does 1. Retrieves Gong Call Data Calls the Gong API to extract call metadata, speaker interactions, and collaboration details. Fetches call transcripts for AI processing. 2. Processes and Cleans Transcripts Converts call transcripts into structured, speaker-based dialogues. Assigns each speaker as either Internal (Sales Team) or External (Customer). 3. Extracts Company Information Retrieves Salesforce data** to match customers with existing sales opportunities. Filters out free email domains* to determine the *customer’s actual company domain**. Calls the PeopleDataLabs API to retrieve additional company data and location details. 4. Merges and Enriches Data Combines Gong metadata, Salesforce customer details and insights**. Ensures all necessary data is available for AI-driven sales insights. 5. Final Formatting for AI Processing Merges all call transcript data into a single structured format for AI analysis. Extracts the final cleaned, enriched dataset for further AI-powered insights. How to Set Up This Workflow 1. Connect Your APIs 🔹 Gong API Access – Set up your Gong API credentials in n8n. 🔹 Salesforce Setup – Ensure API access if you want customer enrichment. 🔹 PeopleDataLabs API – Required to retrieve company and location details based on email domains. 🔹 Webhook Integration – Modify the webhook call to push enriched call data to an internal system. CallForge - 01 - Filter Gong Calls Synced to Salesforce by Opportunity Stage CallForge - 02 - Prep Gong Calls with Sheets & Notion for AI Summarization CallForge - 03 - Gong Transcript Processor and Salesforce Enricher CallForge - 04 - AI Workflow for Gong.io Sales Calls CallForge - 05 - Gong.io Call Analysis with Azure AI & CRM Sync CallForge - 06 - Automate Sales Insights with Gong.io, Notion & AI CallForge - 07 - AI Marketing Data Processing with Gong & Notion CallForge - 08 - AI Product Insights from Sales Calls with Notion How to Customize This Workflow 💡 Modify Data Sources – Connect different CRMs (e.g., HubSpot, Zoho) instead of Salesforce. 💡 Expand AI Analysis – Add another AI model (e.g., OpenAI GPT, Claude) for advanced conversation insights. 💡 Change Speaker Classification Rules – Adjust internal vs. external speaker logic to match your team’s structure. 💡 Filter Specific Customers – Modify the free email filtering logic to better fit your company’s needs. Why Use CallForge? 🚀 Automate Gong call transcript processing to save time. 📊 Improve AI accuracy with enriched, structured data. 🛠 Enhance sales strategy by extracting actionable insights from calls. Start optimizing your Gong transcript analysis today!

CallForge - AI-Powered Sales Call Data Processor Automate sales call analysis and store structured insights in Notion with AI-powered intelligence. Who is This For? This workflow is ideal for: ✅ Sales teams looking to automate call insight processing. ✅ Sales operations managers managing AI-driven call analysis. ✅ Revenue teams using Gong, Fireflies.ai, Otter.ai, or similar transcription tools. It streamlines sales call intelligence, ensuring that insights such as competitor mentions, objections, and customer pain points are efficiently categorized and stored in Notion for easy access. 🔍 What Problem Does This Workflow Solve? Manually reviewing and documenting sales call takeaways is time-consuming and error-prone. With CallForge, you can: ✔ Identify competitors mentioned in sales calls. ✔ Capture objections and customer pain points for follow-up. ✔ Track sales call outcomes and categorize insights automatically. ✔ Store structured sales intelligence in Notion for future reference. ✔ Improve sales strategy with AI-driven, automated call analysis. 📌 Key Features & Workflow Steps 🎙️ AI-Powered Call Data Processing This workflow processes AI-generated sales call insights and structures them in Notion databases: Triggers automatically when AI call analysis data is received. Extracts competitor mentions from the call transcript and logs them in Notion. Identifies and categorizes sales objections for better follow-ups. Processes integration mentions, capturing tools or platforms referenced in the call. Extracts customer use cases, categorizing pain points and feature requests. Aggregates all extracted insights and updates relevant Notion databases. 📊 Notion Database Integration Competitors → Logs mentioned competitors for sales intelligence. Objections → Tracks and categorizes common objections from prospects. Integrations → Captures third-party tools & platforms discussed in calls. Use Cases → Stores customer challenges & product feature requests. 🛠 How to Set Up This Workflow 1. Prepare Your AI Call Analysis Data Ensure AI-generated sales call data is passed into the workflow. Compatible with Gong, Fireflies.ai, Otter.ai, and other AI transcription tools. 2. Connect Your Notion Database Set up Notion databases for: 🔹 Competitors (tracks competing products) 🔹 Objections (logs customer objections & concerns) 🔹 Integrations (captures mentioned platforms & tools) 🔹 Use Cases (categorizes customer pain points & feature requests) 3. Configure n8n API Integrations Connect your Notion API key** in n8n under “Notion API Credentials.” Set up webhook triggers** to receive data from your AI transcription tool. Test the workflow** using a sample AI-generated call transcript. CallForge - 01 - Filter Gong Calls Synced to Salesforce by Opportunity Stage CallForge - 02 - Prep Gong Calls with Sheets & Notion for AI Summarization CallForge - 03 - Gong Transcript Processor and Salesforce Enricher CallForge - 04 - AI Workflow for Gong.io Sales Calls CallForge - 05 - Gong.io Call Analysis with Azure AI & CRM Sync CallForge - 06 - Automate Sales Insights with Gong.io, Notion & AI CallForge - 07 - AI Marketing Data Processing with Gong & Notion CallForge - 08 - AI Product Insights from Sales Calls with Notion 🔧 How to Customize This Workflow 💡 Modify Notion Data Structure – Adjust fields to match your company’s CRM setup. 💡 Enhance AI Data Processing – Align fields with different AI transcription providers. 💡 Expand with CRM Integration – Sync insights with HubSpot, Salesforce, or Pipedrive. 💡 Add Notifications – Send alerts via Slack, email, or webhook when key competitor mentions or objections are detected. ⚙️ Key Nodes Used in This Workflow 🔹 If Nodes – Checks if AI-generated data includes competitors, integrations, objections, or use cases. 🔹 Notion Nodes – Creates or updates entries in Notion databases. 🔹 Split Out & Aggregate Nodes – Processes multiple insights and consolidates AI outputs. 🔹 Wait Nodes – Ensures smooth sequencing of API calls and database updates. 🔹 HTTP Request Node – Sends AI-extracted insights to Notion for structured storage. 🚀 Why Use This Workflow? ✔ Eliminates manual data entry and speeds up sales intelligence processing. ✔ Ensures structured and categorized sales insights for decision-making. ✔ Improves team collaboration with AI-powered competitor tracking & objections logging. ✔ Seamlessly integrates with Notion to centralize and manage sales call insights. ✔ Scalable for teams using n8n Cloud or self-hosted deployments. This workflow empowers sales teams with automated AI insights, streamlining sales strategy and follow-ups with minimal effort. 🚀

CallForge - AI-Powered Marketing Insights Extraction from Sales Calls Automate marketing intelligence gathering from AI-analyzed sales calls and store insights in Notion. 🎯 Who is This For? This workflow is designed for: ✅ Marketing teams looking to extract trends and insights from sales conversations. ✅ Product managers who need direct customer feedback from sales calls. ✅ Revenue operations (RevOps) teams optimizing AI-driven call analysis. It streamlines AI-powered marketing intelligence, identifying customer pain points, competitor mentions, and recurring trends—all automatically stored in Notion. 🔍 What Problem Does This Workflow Solve? Manually reviewing sales call transcripts for marketing insights is time-consuming and inconsistent. With CallForge, you can: ✔ Extract key marketing insights from AI-analyzed sales calls. ✔ Track recurring discussion topics across multiple conversations. ✔ Generate actionable marketing recommendations for strategy and content. ✔ Store structured insights in Notion for seamless access. This automation eliminates manual work and ensures marketing teams get data-driven insights from real customer conversations. 📌 Key Features & Workflow Steps 🎙️ AI-Driven Marketing Insights Processing This workflow processes AI-generated sales call insights and organizes them in Notion databases: Triggers when AI sales call data is received. Identifies marketing-related data (trends, customer pain points, competitor mentions). Extracts key marketing insights, categorizing product discussions and recurring topics. Logs trends across multiple calls, ensuring marketing teams spot recurring themes. Processes actionable insights, capturing marketing strategy recommendations. Stores all findings in Notion, enabling structured, searchable insights. 📊 Notion Database Integration Marketing Insights** → Logs key trends and product mentions from sales calls. Recurring Topics** → Tracks frequently discussed themes across calls. Actionable Recommendations** → Stores AI-generated recommendations for marketing teams. 🛠 How to Set Up This Workflow 1. Prepare Your AI Call Analysis Data Ensure AI-generated sales call insights are available. Compatible with Gong, Fireflies.ai, Otter.ai, and other AI transcription tools. 2. Connect Your Notion Database Set up Notion databases for: 🔹 Marketing Insights (logs trends and product mentions) 🔹 Recurring Topics (tracks frequently discussed customer concerns) 🔹 Actionable Recommendations (stores marketing strategy insights) 3. Configure n8n API Integrations Connect your Notion API key** in n8n under “Notion API Credentials.” Set up webhook triggers** to receive AI-generated sales insights. Test the workflow** using a sample AI sales call analysis. 🔧 How to Customize This Workflow 💡 Modify Notion Data Structure – Adjust fields to match marketing strategy needs. 💡 Refine AI Data Processing Rules – Customize what insights are extracted and logged. 💡 Integrate with Slack or Email – Notify teams when key marketing trends emerge. 💡 Expand CRM Integration – Sync insights with HubSpot, Salesforce, or Pipedrive. CallForge - 01 - Filter Gong Calls Synced to Salesforce by Opportunity Stage CallForge - 02 - Prep Gong Calls with Sheets & Notion for AI Summarization CallForge - 03 - Gong Transcript Processor and Salesforce Enricher CallForge - 04 - AI Workflow for Gong.io Sales Calls CallForge - 05 - Gong.io Call Analysis with Azure AI & CRM Sync CallForge - 06 - Automate Sales Insights with Gong.io, Notion & AI CallForge - 07 - AI Marketing Data Processing with Gong & Notion CallForge - 08 - AI Product Insights from Sales Calls with Notion ⚙️ Key Nodes Used in This Workflow 🔹 If Nodes – Detect if marketing insights, recurring topics, or recommendations exist in AI data. 🔹 Notion Nodes – Create and update entries in Notion databases. 🔹 Split Out & Aggregate Nodes – Process multiple insights and consolidate AI-generated data. 🔹 Wait Nodes – Ensure smooth sequencing of API calls and database updates. 🚀 Why Use This Workflow? ✔ Eliminates manual sales call review for marketing teams. ✔ Provides structured, AI-driven insights for marketing and product strategy. ✔ Tracks competitor mentions and customer pain points automatically. ✔ Improves content marketing and campaign planning with real customer insights. ✔ Scalable for teams using n8n Cloud or self-hosted deployments. This workflow empowers marketing teams by transforming sales call data into actionable intelligence, streamlining strategy, content planning, and competitor analysis. 🚀

CallForge - AI-Powered Product Insights Processor from Sales Calls Automate product feedback extraction from AI-analyzed sales calls and store structured insights in Notion for data-driven product decisions. 🎯 Who is This For? This workflow is designed for: ✅ Product managers tracking customer feedback and feature requests. ✅ Engineering teams identifying usability issues and AI/ML-related mentions. ✅ Customer success teams monitoring product pain points from real sales conversations. It streamlines product intelligence gathering, ensuring customer insights are structured, categorized, and easily accessible in Notion for better decision-making. 🔍 What Problem Does This Workflow Solve? Product teams often struggle to capture, categorize, and act on valuable feedback from sales calls. With CallForge, you can: ✔ Automatically extract and categorize product feedback from AI-analyzed sales calls. ✔ Track AI/ML-related mentions to gauge customer demand for AI-driven features. ✔ Identify feature requests and pain points for product development prioritization. ✔ Store structured feedback in Notion, reducing manual tracking and increasing visibility across teams. This workflow eliminates manual feedback tracking, allowing product teams to focus on innovation and customer needs. 📌 Key Features & Workflow Steps 🎙️ AI-Powered Product Feedback Processing This workflow processes AI-generated sales call insights and organizes them in Notion databases: Triggers when AI sales call data is received. Detects product-related feedback (feature requests, bug reports, usability issues). Extracts key product insights, categorizing feedback based on customer needs. Identifies AI/ML-related mentions, tracking customer interest in AI-driven solutions. Aggregates feedback and categorizes it by sentiment (positive, neutral, negative). Logs insights in Notion, making them accessible for product planning discussions. 📊 Notion Database Integration Product Feedback** → Logs feature requests, usability issues, and bug reports. AI Use Cases** → Tracks AI-related discussions and customer interest in machine learning solutions. 🛠 How to Set Up This Workflow 1. Prepare Your AI Call Analysis Data Ensure AI-generated sales call insights are available. Compatible with Gong, Fireflies.ai, Otter.ai, and other AI transcription tools. 2. Connect Your Notion Database Set up Notion databases for: 🔹 Product Feedback (logs feature requests and bug reports). 🔹 AI Use Cases (tracks AI/ML mentions and customer demand). 3. Configure n8n API Integrations Connect your Notion API key** in n8n under “Notion API Credentials.” Set up webhook triggers** to receive AI-generated sales insights. Test the workflow** using a sample AI sales call analysis. 🔧 How to Customize This Workflow 💡 Modify Notion Data Structure – Adjust fields to align with your product team's workflow. 💡 Refine AI Data Processing Rules – Customize how feature requests and pain points are categorized. 💡 Integrate with Slack or Email – Notify teams when recurring product issues emerge. 💡 Expand with Project Management Tools – Sync insights with Jira, Trello, or Asana to create product tickets automatically. ⚙️ Key Nodes Used in This Workflow 🔹 If Nodes – Detect if product feedback, AI mentions, or feature requests exist in AI data. 🔹 Notion Nodes – Create and update structured feedback entries in Notion. 🔹 Split Out & Aggregate Nodes – Process multiple insights and consolidate AI-generated data. 🔹 Wait Nodes – Ensure smooth sequencing of API calls and database updates. 🚀 Why Use This Workflow? ✔ Eliminates manual sales call review for product teams. ✔ Provides structured, AI-driven insights for feature planning and prioritization. ✔ Tracks AI/ML mentions to assess demand for AI-powered solutions. ✔ Improves product development strategies by leveraging real customer insights. ✔ Scalable for teams using n8n Cloud or self-hosted deployments. This workflow empowers product teams by transforming sales call data into actionable intelligence, optimizing feature planning, bug tracking, and AI/ML strategy. 🚀

The best content automation template in the market is now even better—with “deep research” on time-sensitive topics\! Unlike most n8n content automation templates that are mainly for “demo purposes,” this advanced n8n workflow is for the real PROs. It conducts in-depth research on the latest information about a topic, then automatically creates and publishes SEO-optimized blog posts to your WordPress website. In addition, it generates a unique image for each chapter and a featured image for the overall article, and it collects internal website links—seamlessly inserting links throughout each chapter and the entire article. Furthermore, it backs up all content and images to a designated folder in your Google Drive. This integrated approach not only creates high-quality, comprehensive content for readers but also enhances on-page SEO, improves navigation, and streamlines your content creation process—saving you time while ensuring your work is securely stored. This is a complimentary variation of the n8n WordPress Auto-Blogging Pro for SEO topics. That one specializes in auto-blogging content about established topics that do not need up-to-date information while this one takes it further by incorporating online research into the workflow. Both make up the perfect combo to run your blog on autopilot\! How It Works Trigger: It activates upon adding a new row to a Google Sheet. Users can control many customizable parameters, such as key topic, number of subtopics, target audience, length, and style. Initial Research: The workflow initiates preliminary research on the topic to gather insights for the content planning phase. Structure Planning: Based on the initial research, it plans a detailed structure for the entire article and breaks the article into subtopics strongly tied to the main topic. In-Depth Research & Writing: For each subtopic, it conducts further research to gather the most up-to-date, relevant information, then uses that research to write each chapter in depth. Image Generation: It generates and adds images for each chapter, as well as a featured image for the article. Internal Linking: The system gathers internal website links and strategically embeds them within each chapter and throughout the article, boosting SEO and enhancing user navigation. Final Assembly & Publishing: All texts, images, and links are combined into one comprehensive article, which is then published directly to your WordPress website. You can also choose to post it as a draft for final review. Auto Backup to Drive: Get peace of mind knowing all content (blog post and images) is automatically saved to Google Drive, organized in a folder named after the blog post title. Unique Features Deep Research: The workflow leverages advanced, real-time research to gather the latest information about a topic. It breaks down the key topic into subtopics and conducts in-depth research on each one, ensuring the most comprehensive and current knowledge. Full Automation: Designed to be 100% automated, the workflow runs without manual intervention once imported and configured. Simple Activation: It is easily triggered through the Google Sheets interface—simply add a new row to a Google Sheet. Customization Options: Offers a wide array of 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. Advanced Loop in Loop: Clever looping is used to write each chapter and generate images, ensuring optimal results. “Wait” nodes are added where appropriate to avoid API call rate limits. Automatic Content Saving: After the blog post is created, all content and images are automatically saved to Google Drive, preventing data loss. The folder is named after the blog post title. SEO-Optimized Content: It is designed to create SEO-optimized content using seed keywords. Internal Link Limit: The workflow limits the number of internal links to 20 by default. Error Catch: “If” nodes are strategically used to ensure that the output from AI nodes strictly meets the JSON schema, ensuring a smooth flow of data without interruption. And many more big and small improvements. Requirements Please make sure you have these requirements ready to ensure smooth deployment of this n8n workflow template: OpenAI API or equivalent for text and image generation PerplexityAI API or equivalent for online research A WordPress website (other website platforms will not work\!) Google Sheets for triggering the workflow, or a trigger of your choice Google Drive and Google Docs for auto backup Set Up Steps Install the Workflow Template: Import the JSON files into your n8n instance. There are 2 files: one for the main workflow and one for the research tool (PerplexityAI). Connect the Workflow with Your Accounts: Link your accounts for OpenAI API, PerplexityAI API, Google Drive, Google Sheets, Google Docs, and WordPress website. 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 Inputs: Adjust parameters like topic, target audience, and writing style to match your specific content needs. Optimize prompts for the 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 perfectly align with your needs and content strategy. Tips for PROs Image Generation: The default AI model for image generation is OpenAI’s Dall-E. However, the outputs of this model are not impressive. Consider using FLUX.1 for better image quality. Research: PerplexityAI is the tool of choice for research. The default model used in this workflow is “sonar” due to its fast speed and low cost. Feel free to experiment with its other models, including the “sonar-deep-research” model, which is dedicated to deep research. Triggering: Triggering with a new row on Google Sheets is limited and unreliable. Consider setting an auto trigger with a daily schedule at a specific time. You can even put the whole workflow in a loop to process multiple rows one-by-one from Google Sheets. Human in the Loop: It is possible to incorporate a human review process. For example, after the article is posted to WordPress as a draft, a human can review the draft. Only after approval will the post be published, and a final copy of the post will be saved to the shared Drive folder.

AI-Powered WhatsApp Assistant for Restaurant & Delivery – Automate Orders, Calculate Delivery Fees & Enhance Customer Service with n8n 📌 Optimize your restaurant's delivery process with AI-powered automation! This n8n workflow enables an intelligent WhatsApp assistant for restaurants, burger joints, and delivery businesses. The AI chatbot efficiently handles orders, calculates delivery fees based on distance, manages customer interactions, and seamlessly integrates with your CRM and database for streamlined operations. ⚠️ Important Notice: This template is only compatible with self-hosted n8n instances as it uses community nodes. Ensure secure credential management when configuring APIs. 🔹 Key Features ✅ AI-Powered Order Processing – Automatically receive and confirm orders via WhatsApp. ✅ Real-Time Distance Calculation – Determines the delivery distance and calculates the fee dynamically. ✅ Automated Customer Interaction – Engages customers with intelligent conversation and order updates. ✅ WhatsApp Integration – Processes messages, saves customer details, and retrieves past interactions. ✅ Secure Customer Data Storage – Saves order history, customer preferences, and location details in a database. ✅ Seamless CRM & POS System Integration – Sync orders and customer data with your existing platforms. 📌 How It Works 1️⃣ A customer sends a message via WhatsApp to start an order. 2️⃣ The AI assistant guides them through the menu, recommends items, and confirms their choices. 3️⃣ The system retrieves and saves customer details (name, phone number, and address). 4️⃣ The AI calculates the delivery distance and applies the appropriate delivery fee. 5️⃣ The order details are saved and forwarded to the restaurant’s system for preparation. 6️⃣ The assistant keeps the customer updated about the order status. ⚙️ Setup & Customization 🔧 Webhook for WhatsApp – Capture and process customer messages automatically. 🔧 OpenAI-Powered AI Assistant – Configure conversation flows for natural and engaging interactions. 🔧 Delivery Fee Calculation – Set your delivery price per kilometer and adjust base rates. 🔧 Database & CRM Integration – Store customer details, order history, and location data. 🔧 Customizable Order Flow – Adapt the workflow for different restaurant models. 🔧 Secure Credential Management – Store API keys safely to prevent unauthorized access. 💡 Requirements: This template is recommended for users with basic knowledge of n8n. If you need custom development or setup assistance, contact us via WhatsApp: +55 17 99155-7874. 🚀 Automate order processing, reduce manual tasks, and improve customer satisfaction with AI-powered WhatsApp automation! Assistente de WhatsApp com IA para Restaurantes & Delivery – Automatize Pedidos, Calcule Taxas de Entrega e Melhore o Atendimento ao Cliente com n8n 📌 Otimize o processo de entrega do seu restaurante com automação baseada em IA! Este fluxo para n8n permite criar um atendente virtual inteligente no WhatsApp, ideal para hamburguerias, restaurantes e serviços de delivery. O chatbot baseado em IA recebe pedidos, calcula a taxa de entrega com base na distância, interage com os clientes e integra-se ao seu CRM para operações mais eficientes. ⚠️ Aviso Importante: Este template é compatível apenas com instâncias auto-hospedadas do n8n, pois utiliza nós da comunidade. Certifique-se de gerenciar credenciais de forma segura ao configurar APIs. 🔹 Principais Funcionalidades ✅ Processamento Inteligente de Pedidos – Recebe e confirma pedidos automaticamente via WhatsApp. ✅ Cálculo Dinâmico da Taxa de Entrega – Mede a distância e aplica a taxa correta automaticamente. ✅ Atendimento Automatizado ao Cliente – Interage com clientes de forma natural e profissional. ✅ Integração com WhatsApp – Captura mensagens, armazena dados e recupera histórico de pedidos. ✅ Armazenamento Seguro de Dados do Cliente – Salva pedidos, preferências e endereços de entrega. ✅ Sincronização com CRM e Sistema de PDV – Conecta-se ao seu sistema de gestão para um fluxo contínuo. 📌 Como Funciona 1️⃣ O cliente envia uma mensagem via WhatsApp para iniciar um pedido. 2️⃣ O assistente de IA apresenta o menu, sugere itens e confirma a escolha do cliente. 3️⃣ O sistema captura e salva os dados do cliente (nome, telefone e endereço). 4️⃣ A IA calcula a distância de entrega e aplica a taxa de acordo com a localização. 5️⃣ Os detalhes do pedido são registrados e enviados para a cozinha. 6️⃣ O assistente atualiza o cliente sobre o status do pedido. ⚙️ Configuração e Personalização 🔧 Webhook para WhatsApp – Configuração para capturar e processar pedidos automaticamente. 🔧 Assistente de IA com OpenAI – Configuração de fluxos conversacionais naturais e envolventes. 🔧 Cálculo de Taxa de Entrega – Definição de valores por quilômetro e ajustes de tarifas base. 🔧 Banco de Dados & CRM – Armazena dados de clientes, histórico de pedidos e localização. 🔧 Fluxo de Pedidos Personalizável – Adapte para diferentes tipos de restaurantes e serviços de delivery. 🔧 Gerenciamento Seguro de Credenciais – Proteja suas chaves de API contra acessos não autorizados. 💡 Requisitos: Este template é recomendado para usuários que já possuem conhecimentos básicos em n8n. Se precisar de personalização ou suporte para instalação, entre em contato pelo WhatsApp: +55 17 99155-7874. 🚀 Automatize o processamento de pedidos, reduza tarefas manuais e melhore a satisfação dos clientes com um WhatsApp automatizado e inteligente!

Overview The n8n Workflow Cloner is a powerful automation tool designed to copy, sync, and migrate workflows across different n8n instances or projects. Whether you're managing multiple environments (development, staging, production) or organizing workflows within a team, this workflow automates the transfer process, ensuring seamless workflow deployment with minimal manual effort. By automatically detecting and copying only the missing workflows, this tool helps maintain consistency, improve collaboration, and streamline workflow migration between projects or instances. How to Use 1️⃣ Set Up API Credentials Configure API credentials for both source and destination n8n instances. Ensure the credentials have read and write access to manage workflows. 2️⃣ Select Source & Destination Update the "GET - Workflows" node to define the source instance. Set the "CREATE - Workflow" node to specify the destination instance. 3️⃣ Run the Workflow Click "Test Workflow" to start the transfer. The system will fetch all workflows from the source, compare them with the destination, and copy any missing workflows. 4️⃣ Change the Destination Project (Optional) By default, workflows are moved to the "KBB Workflows" project. Modify the "Filter" node to transfer workflows to a different project. 5️⃣ Monitor & Verify The Loop Over Items node ensures batch processing for multiple workflows. Log outputs provide details on transferred workflows and statuses. Key Benefits ✅ Automate Workflow Transfers – No more manual exports/imports. ✅ Sync Workflows Across Environments – Keep workflows up to date in dev, staging, and production. ✅ Effortless Team Collaboration – Share workflows across projects seamlessly. ✅ Backup & Migration Ready – Easily move workflows between n8n instances. Use Cases 🔹 CI/CD for Workflows – Deploy workflows between development and production environments. 🔹 Team Workflow Sharing – Share workflows across multiple n8n projects. 🔹 Workflow Backup Solution – Store copies of workflows in a dedicated backup project. Tags 🚀 Workflow Migration 🚀 n8n Automation 🚀 Sync Workflows 🚀 Backup & Deployment

Find Job Postings from LinkedIn, Indeed, and Glassdoor and Save Them to Google Sheets Using AI Overview Effortlessly discover and apply to jobs tailored to your profile—AI handles the search, you handle the interviews. Say goodbye to endless job board scrolling. This automation leverages AI to analyze your resume, identify your skills, experience, and more, to match you with the most relevant job opportunities. It sources job postings from LinkedIn, Indeed, Glassdoor, ZipRecruiter, Monster, and other public job sites on the web. With seamless integration and automatic organization of results, you can focus on applying rather than searching. Key Features Intelligent Resume Parsing Extracts key information from your PDF resume using AI. Identifies skills, experience, education, and job preferences. Targeted Job Matching Uses the parsed resume data to search for jobs that align with your profile. Ensures relevance by analyzing job descriptions for matching criteria. Automated Data Organization Compiles job listings into a structured Google Spreadsheet. Eliminates the need for manual data entry, saving valuable time. Easy Access and Review Stores results in a familiar Google Sheets format for easy tracking. Allows for filtering and sorting to prioritize applications. Setup Instructions Prerequisites A free API key for the job search service. Google Drive and Google Sheets accounts. An updated resume in PDF format. Step 1: Connect Your Resume Parsing AI Upload your PDF resume to Google Drive. Configure the AI parser node in n8n to extract relevant information. Map the extracted fields (e.g., skills, job title, experience) for job searching. Step 2: Automate the Job Search Use the extracted data to perform a job search on LinkedIn, Indeed, Glassdoor, and other supported job sites. Retrieve job postings based on relevant keywords and location preferences. Step 3: Save Job Listings to Google Sheets Create a new Google Sheet to store job listings. Set up the automation to write job details (e.g., title, company, location, link) into the sheet. Format the sheet for better readability and tracking. Step 4: Review and Apply to Jobs Open your Google Sheet to view job matches. Click on the links to apply directly on the respective job sites. Update the status of each job application as you progress. Why Use This Automation? Saves Time**: Automates job searching and listing compilation. Enhances Efficiency**: Eliminates manual scrolling and data entry. Improves Organization**: Keeps all job opportunities in a structured format. Optimizes Your Job Hunt**: Increases chances of landing the perfect role. Designed specifically for job seekers aiming to optimize their search process, this automation integrates with Google Drive and Sheets, streamlining your job hunt and enhancing your chances of finding the right opportunity. Get started today and accelerate your career growth!

Avoid Asking Redundant Questions with Dynamically Generated Forms using OpenAI Target Audience This workflow has been built for those who require a form to capture as much data as possible as well as the answers to predefined questions, whilst optimising the user experience by avoiding asking redundant questions. Use Case When creating a form to capture information, it can be useful to give the user an opportunity to input a long answer to a large, open-ended question. We then want to drill down to answer specific questions that we require the answer to. When doing this, we don't want to ask duplicate questions. This particular scenario imagines an AI consultancy capturing leads. What it Does This workflow requires users to input basic information and then answer an open ended question. The specific questions on the next page will only be those that weren't answered in the open-ended question. How it Works The open-ended question (and relevant basic information) is analysed by an LLM to determine which specific questions have not been answered. Chain-of-thought reasoning is utilised and the output structure is specified with the Structured Output Parser. Those questions that have already been answered are filtered out nodes. The remaining items are then used to generate the last page of the form. Once the user has filled in the final page of the form, they are shown a form completion page. Setup Add your OpenAI credentials Go to the Get Basic Information node and click Test Step Complete the form to test the generic use case Modify the prompt in Analyse Response to fit your use case Next Steps Add additional nodes to send an email to the form owner Add a subsequent LLM call to analyse the form response - those that are qualified should be given the opportunity to book an appointment

Are you a cord-cutter? Do you find yourself looking through the many titles of videos uploaded to Youtube, just to find the ones you want to watch? Even when you subscribe to the channels you like, do you find that you want to watch the news now and my tech/n8n videos later? Well, now you can have n8n grab the last 8 videos, posted in the last 24 hours, and put them in a playlist for the day; and, each day the old playlist is deleted. Are you tired of a channel filling your subscriptions with tons of videos a day; this workflow can be used for any channel, whether you are subscribed to the channel or not. It's a YouTube playlist automation. How it works: Create your list of prefered Youtube Channels in a Google Sheet and it will create you a daily playlist; and, it will delete the playlist created yesterday. Instructions To set this up, you need to create a Google Sheet with the following headings in line 1: Channel User Name Channel Name Channel Link Channel ID Copy the 'Create your Channel List' into it's own workflow and link the Sheets links to your new sheet. To get the 'Create your Channel List' to work, you need to visit each channel's page that you want included in your playlist; you need to get the "@" name of the channel and add it to the 'Channel User Name' column of your Google Sheet. For example: if you wanted to include this channel: Recruit Training Videos - Corporal Stock, you would search for the name, to add to the next available row of the 'Channel User Name' column: @CorporalStock Once you add all Channel User Names, run the 'Create your Channel list workflow, and it will fill in the remaining details. Now the 'YT Playlist Creator' can be run. Note: The first time the workflow us run, disconnect the 'Delete Yesterday's Playlist' leg, or the workflow will error and stop (because there is no 'Yesterday's Playlist'. Note: this was made to create a playlist every day, delete yesterday's playlist, and only get the last 8 videos posted within the last 24 hours. I choose to put the date (YYMMDD format) in front of the playlist, to ensure that it doesn't conflict with another playlist. Also, I have it notifying me in Telegram, so I know that the new playlist is posted.

How it works Many users have asked in the support forum about different methods to analyze images and PDF documents with Google Gemini AI in n8n. This workflow answers that question by demonstrating five different approaches: Single image with auto binary passthrough - The simplest approach using AI Agent's automatic binary handling Multiple images with predefined prompts - For customized analysis with different instructions per image Native n8n item-by-item processing - For handling multiple items using n8n's standard workflow paradigm PDF analysis via direct API - For document analysis and text extraction Image analysis via direct API - For direct control over API parameters Each method has advantages depending on your specific use case, data volume, and customization needs. Set up steps Setup time: ~5-10 minutes You'll need: A Google Gemini API key n8n with HTTP Request and AI Agent nodes Important: For the HTTP Request nodes making direct API calls to Gemini (Methods 3, 4, and 5), you'll need to set up Query Authentication with your Gemini API key. Add a parameter named "key" with your API key value in the Query Auth section of these nodes. I'll updated this if I find better ways. Also let me know if you know other ways. Eager to learn :)

Sync Dartagnan Email Templates to Braze Why Use This Workflow Email marketing demands consistency across platforms. This workflow automatically synchronizes your email templates from Dartagnan to Braze, eliminating manual transfers and ensuring brand consistency. Perfect for marketing teams who need to maintain a unified email experience while leveraging the strengths of both platforms. Business Benefits Save Time**: Eliminate hours of manual template copying and formatting between platforms Maintain Consistency**: Ensure your email templates look identical across Dartagnan and Braze Reduce Errors**: Automated synchronization prevents human error in template transfers Streamline Workflows**: Create once in Dartagnan, use everywhere through Braze's distribution power Preserve Image Assets**: Keep images hosted on Dartagnan while properly formatting them for Braze How It Works This workflow performs a bi-directional sync between your Dartagnan email templates and Braze platform. It intelligently handles: Template Updates: Automatically updates existing templates in Braze when modified in Dartagnan New Template Creation: Creates new templates in Braze when added to Dartagnan Image URL Transformation: Properly embeds and formats image URLs to meet Braze requirements while keeping assets on Dartagnan infrastructure Technical Implementation The workflow uses a scheduled trigger to check for template changes and then processes them in batches: Authentication: Securely connects to both Dartagnan and Braze APIs Template Retrieval: Fetches current templates from Dartagnan Comparison Logic: Determines which templates need updating or creation in Braze Content Transformation: Processes HTML content and image URLs to ensure compatibility API Integration: Pushes changes to Braze through their Content Blocks API Customization Options This workflow can be customized to meet your specific needs: Sync Frequency**: Adjust the schedule to run hourly, daily, or on any custom schedule Template Filtering**: Add conditions to sync only specific templates based on tags or categories Error Handling**: Configure notification emails when synchronization issues occur Logging**: Enable detailed logs for troubleshooting and auditing Setup Requirements Setting up this workflow takes approximately 20-30 minutes and requires: Dartagnan Requirements API Client ID API Client Secret Template access permissions Braze Requirements Braze Instance URL API Key with content block permissions Appropriate rate limits configured Common Use Cases Email Campaign Coordination**: Maintain consistent templates across platforms for multi-channel campaigns Agency Work**: Design in Dartagnan, deploy through client's Braze instance Rebranding Projects**: Update templates once and propagate changes automatically International Marketing**: Maintain language variants across platforms with automatic synchronization Get Started Once installed, configure your API credentials, set your desired synchronization schedule, and let the workflow handle the rest. The initial sync will create all your templates in Braze, with subsequent runs only updating what's changed.

🎯 Automatically Create and Post Engaging TikTok Clips (with Audience Retention Videos) from Podcasts Using AI! 🚀 Effortlessly transform long-form podcast content into highly engaging, viral-ready TikTok clips with this end-to-end automation template. Designed for content creators already monetizing on TikTok and those looking to start earning from the platform, this workflow streamlines the process of extracting highlights, editing clips, and posting to TikTok, allowing you to maximize reach while minimizing manual effort. Key Features 🔹 AI-Powered Podcast Highlight Extraction Automatically identifies the best moments from any podcast video, ensuring each clip is engaging and shareable. 🔹 Smart Video Editing & Captioning Combines podcast highlights with a copyright-free attention retainer video (e.g., Minecraft parkour, GTA 5 gameplay) for increased audience retention. Auto-generated captions make clips more dynamic and accessible. 🔹 Automated Title Generation A Large Language Model (LLM) analyzes the clips to generate compelling titles, optimized for TikTok’s algorithm. 🔹 Hands-Free TikTok Posting Seamlessly schedules and automatically posts clips to your TikTok account at defined intervals, keeping your audience engaged without manual uploads. 🔹 Fully Automated Workflow From video download to content publishing 100% FREE, this template eliminates the need for time-consuming video editing, helping you scale your content strategy effortlessly, without having to pay for multiple subscriptions tediously. Simply find a podcast you like and a cool Minecraft parkour (or any engaging) video, send their YouTube URLs, and let the automation handle everything—from video downloading and audio processing to highlight extraction, editing, captions, and publishing. How It Works (Step-by-Step Guide) 1️⃣ Provide the YouTube URLs One for the main podcast video (where highlights will be extracted). One for the background attention retainer video (e.g., Minecraft parkour, GTA 5 gameplay). 2️⃣ Automation Downloads and Processes the Videos Downloads both videos. Extracts audio from the podcast for analysis. 3️⃣ AI Analyzes and Extracts Key Highlights Detects the most engaging moments from the podcast. 4️⃣ Creates Fully Edited Clips Merges podcast highlights with the attention retainer video. Generates captions automatically. 5️⃣ Optimizes for TikTok Uses AI to generate a compelling title for each clip. 6️⃣ Posts to TikTok Automatically Uploads clips at your preferred intervals with zero manual effort. Who Is This For? ✅ Content creators already making money on TikTok ✅ People looking to start earning with TikTok ✅ Podcasters wanting to repurpose content into bite-sized, viral clips Get Started Today! 🚀 This AI-driven automation is perfect for scaling your TikTok content effortlessly. To use this workflow, you’ll just need free accounts on Assembly, Andynocode, and Upload-Posts.

Overview Transform your Bitrix24 Open Line channels with an intelligent chatbot that leverages Retrieval-Augmented Generation (RAG) technology to provide accurate, document-based responses to customer inquiries in real-time. Use Case This workflow is designed for organizations that want to enhance their customer support capabilities in Bitrix24 by providing automated, knowledge-based responses to customer inquiries. It's particularly useful for: Customer service teams handling repetitive questions Support departments with extensive documentation Sales teams needing quick access to product information Organizations looking to provide 24/7 customer support What This Workflow Does Smart Document Processing Automatically processes uploaded PDF documents Splits documents into manageable chunks Generates vector embeddings for semantic understanding Indexes content for efficient retrieval AI-Powered Responses Utilizes Google Gemini AI to generate natural language responses Constructs answers based on relevant document content Maintains conversation context for coherent interactions Provides fallback responses when information is not available Vector Database Integration Stores document embeddings in Qdrant vector database Enables semantic search beyond simple keyword matching Retrieves the most relevant information for each query Maintains a persistent knowledge base that grows over time Webhook Handler Processes incoming messages from Bitrix24 Open Line channels Handles authentication and security validation Routes different types of events to appropriate handlers Manages session and conversation state Event Routing Intelligently routes different event types: ONIMBOTMESSAGEADD: Processes new user messages ONIMBOTJOINCHAT: Handles bot joining a conversation ONAPPINSTALL: Manages application installation ONIMBOTDELETE: Handles bot deletion Document Management Organizes processed documents in designated folders Tracks document processing status Moves indexed documents to appropriate locations Maintains document metadata for reference Interactive Menu Provides menu-based options for common user requests Customizable menu items and responses Easy navigation for users seeking specific information Fallback to operator option when needed Technical Architecture Components Webhook Handler: Receives and validates incoming requests from Bitrix24 Credential Manager: Securely manages authentication tokens and API keys Event Router: Directs events to appropriate processing functions Document Processor: Handles document loading, chunking, and embedding Vector Store: Qdrant database for storing and retrieving document embeddings Retrieval System: Searches for relevant document chunks based on user queries LLM Integration: Google Gemini model for generating natural language responses Response Manager: Formats and sends responses back to Bitrix24 Integration Points Bitrix24 API**: For bot registration, message handling, and user interaction Ollama API**: For generating document embeddings Qdrant API**: For vector storage and retrieval Google Gemini API**: For AI-powered response generation Setup Instructions Prerequisites Active Bitrix24 account with Open Line channels enabled Access to n8n workflow system Ollama API credentials Qdrant vector database access Google Gemini API key Configuration Steps Initial Setup Import the workflow into your n8n instance Configure credentials for all services Set up webhook endpoints Bitrix24 Configuration Create a new Bitrix24 application Configure webhook URLs Set appropriate permissions Install the application to your Bitrix24 account Document Storage Create a designated folder in Bitrix24 for knowledge base documents Configure folder paths in the workflow settings Upload initial documents to be processed Bot Configuration Customize bot name, avatar, and description Configure welcome messages and menu options Set up fallback responses Testing Verify successful installation Test document processing pipeline Send test queries to evaluate response qu

This workflow restores all n8n instance workflows from GitHub backups using the n8n API node. It complements the Backup Your Workflows to GitHub template by allowing users to seamlessly restore previously saved workflows. How It Works The workflow fetches workflows stored in a GitHub repository and imports them into your n8n instance. Setup Instructions To configure the workflow, update the Globals node with the following values: repo.owner** – Your GitHub username repo.name** – The name of your GitHub repository storing the workflows repo.path** – The folder path within the repository where workflows are stored For example, if your GitHub username is john-doe, your repository is named n8n-backups, and workflows are stored in a workflows/ folder, you would set: repo.owner → john-doe repo.name → n8n-backups repo.path → workflows/ Required Credentials GitHub API** – Access to your repository n8n API** – To import workflows into your n8n instance Who Is This For? This template is ideal for users who want to restore their workflows from GitHub backups, ensuring easy migration and recovery in case of data loss. Check out my other templates: 👉 My n8n Templates

This workflow restores all n8n instance credentials from GitHub backups using the n8n API node. It complements the Backup Your Credentials to GitHub template by allowing users to seamlessly restore previously saved credentials. How It Works The workflow fetches credentials stored in a GitHub repository and imports them into your n8n instance. Setup Instructions To configure the workflow, update the Globals node with the following values: repo.owner** – Your GitHub username repo.name** – The name of your GitHub repository storing the credentials repo.path** – The folder path within the repository where credentials are stored For example, if your GitHub username is john-doe, your repository is named n8n-backups, and credentials are stored in a credentials/ folder, you would set: repo.owner → john-doe repo.name → n8n-backups repo.path → credentials/ Required Credentials GitHub API** – Access to your repository n8n API** – To import credentials into your n8n instance Who Is This For? This template is ideal for users who want to restore their credentials from GitHub backups, ensuring easy migration and recovery in case of data loss. Check out my other templates: 👉 My n8n Templates

Overview This workflow retrieves all blog and event collection items from a Squarespace site and saves them into a Google Sheets spreadsheet. It uses pagination to fetch 20 items per request, ensuring all content is collected efficiently. How It Works The workflow queries your Squarespace blog and event collections. It fetches data in paginated batches (20 items per page). The retrieved data is formatted and inserted into Google Sheets. The workflow runs on demand or on a schedule, ensuring your data stays up to date. Requirements Credentials To use this template, you need: Your Squarespace collection URL Google Sheets API credentials Google Sheets Setup Use this sample Google Sheets template to get started quickly. Who Is This For? This template is designed for: Bloggers looking to manage and analyze content externally. Businesses and marketers tracking content performance. Anyone who needs an automated way to extract Squarespace blog and event data. Explore More Templates Check out my other n8n templates: 👉 n8n.io/creators/bangank36

This workflow retrieves all Squarespace Orders and saves them into a Google Sheets spreadsheet using the Squarespace Commerce API. It uses pagination to ensure all orders are collected efficiently. How It Works The workflow queries your Squarespace Orders API. It fetches data in paginated batches and inserts them into Google Sheets. The Global node is used to configure API parameters dynamically, allowing users to set date filters, pagination, and fulfillment status. The workflow runs on demand or on a schedule, ensuring your data stays up to date. Parameters This workflow allows you to customize the API request using the Global node settings: api-version** (string, required) – The current API version (see Squarespace Orders API documentation). modifiedAfter**={a-datetime} (string, conditional) – Fetch orders modified after a specific date (ISO 8601 format). modifiedBefore**={b-datetime} (string, conditional) – Fetch orders modified before a specific date (ISO 8601 format). cursor**={c} (string, conditional) – Used for pagination, cannot be combined with other filters. fulfillmentStatus**={status} (optional, enum) – Filter by fulfillment status: PENDING, FULFILLED, or CANCELED. maxPage** – Set -1 to enables infinite pagination to fetch all available orders. Requirements Credentials To use this workflow, you need: Squarespace API Key – Retrieve from your Squarespace settings. Google Sheets API credentials – Required to insert data into a spreadsheet. Google Sheets Setup Use the Squarespace order export feature to create a reference sheet. Google Sheets template is available Who Is This For? This workflow is designed for: Squarespace store owners exporting orders for tax reports, analytics, or sales tracking. Businesses automating order data retrieval for external reporting. Anyone needing an efficient way to extract Squarespace order data. Explore More Templates 👉 Check out my other n8n templates

Description This workflow reads a sitemap.xml file, extracts all URLs, and allows you to filter out specific types of links—such as PDF files, images, or any other content—based on your needs. Who Is This For? SEO Specialists** looking to analyze specific URLs in their sitemap. Developers** who need to extract links for automated processing. Content Managers** filtering out downloadable assets like PDFs or images. How It Works Fetch sitemap.xml – The workflow reads the sitemap file from a given URL. Extract URLs – Parses all the URLs listed in the sitemap. Filter URLs – Use a simple filter to extract only the links you need (e.g., *.pdf). Export or Process – The filtered list can be sent via email, stored in a database, or used in another workflow. Customization Edit the Set sitemap URL block and edit the sitemapUrl value to the sitemap you want to fetech. Edit the Filter URLs block and edit the filter contitions to meet your needs.

Real Estate Price-Reduced Property Opportunity Guide Overview This comprehensive automation solution targets FSBO properties listed on Zillow that have recently had their price reduced, providing both investment analysis and tailored outreach scripts. The workflow gathers comprehensive market data to analyze local trends for each specific city and incorporates this intelligence into personalized communication strategies (more aggressive in buyers' markets, more value-focused in sellers' markets). Key benefits: Identify motivated homeowners who have recently reduced their property prices Prepare data-driven offer strategies based on detailed market conditions Develop effective, personalized communication approaches Create a consistent, automated workflow to find and capitalize on opportunities Requirements Airtable account (free tier works) n8n automation platform OpenAI API key Zillow Rapid API access Basic understanding of automation workflows Step 1: Set Up Airtable Database Create a new Airtable base Set up a table with the following fields: Property ID (primary field) Address Price Status (single select field with options: "Contacted" and "Uncontacted") Phone Number Communication Template Market Analysis Offer Price Investment Metrics (Long text field for detailed financial analysis) Expected Cash Flow (Currency field) Expected ROI (Percentage field) Follow-up Date Set the default Status to "Uncontacted" Generate a Personal Access Token from Airtable settings for API connections Step 2: Configure Zillow API Connection Set up an HTTP request node in n8n to connect to Zillow's Rapid API Configure the search parameters: Listing type: "For Sale By Owner" Location: Your target market Price reduction: true Auction properties: false Add filters to: Exclude properties without contact information Only include listings with recent price reductions Filter by minimum square footage or bedrooms if desired Set maximum days since price reduction (e.g., last 14 days) Step 3: Market Analysis Workflow Our market analysis engine processes Zillow market data to provide strategic insights for each location: Comprehensive Market Indicators**: Current inventory levels and new listing rates Median list price and sale price comparison Days-to-pending metrics (current and historical) Sale-to-list price ratios Percentage of properties selling above/below list price Market Trend Analysis**: 6-month and year-over-year comparative trends Market trend scoring system (-10 to +10 scale) Market cycle position identification (Early, Mid, Late) Seasonal market pattern recognition Strategic Investment Guidance**: Market type classification (Buyer's, Balanced, Seller's) Negotiation power assessment Market timing recommendations Risk evaluation (Low to High scale) Actionable investment strategies based on current conditions This analysis is transformed into actionable advice that directs your negotiation approach and helps you calibrate offers appropriately for market conditions. Step 4: Calculate Investment Metrics Our investment calculator analyzes each Zillow property and its RentZestimate to provide comprehensive financial projections: Purchase & Financing Analysis**: Purchase price and standard acquisition costs (20% down payment, 3% closing costs) Loan amount and monthly mortgage payment (30-year term) Total initial investment calculation Monthly Expense Projections**: Property tax (2% of property value annually) Insurance (0.5% of property value annually) Maintenance reserves (1% of property value annually) Vacancy allowance (8% of rental income) Total monthly expense calculation Rental Income & Returns**: RentZestimate integration (with 1% rule fallback when unavailable) Monthly and annual cash flow projections Cash-on-cash ROI calculation Break-even timeline analysis Investment Quality Filtering**: Automatic filtering to show only positive cash flow properties Property identification with complete details (address, beds, baths, sqft) Full investment metrics breakdown for investor decision-making This calculator ensures you focus only on properties with profit potential, saving you countless hours of manual analysis. Step 5: Generate Communication Templates Create templates that combine: Property details (address, price, features) Market intelligence from your analysis Investment metrics showing the property's potential Configures your templates to include: A professional introduction Reference to the specific property address Mention of the price reduction A strategic cash offer (typically 5-15% below asking) Local market statistics to build credibility A clear call to action (request to visit the property) Step 6: Automated Workflow Set up the complete n8n workflow to: Check for new listings with price reductions daily Run market analysis on each new property Calculate potential investment returns Generate personalized communication templates Upload data to Airtable Flag properties ready for contact Update status to "Contacted" after outreach Troubleshooting If outreach isn't being tracked: Check API connections to Airtable If market data seems incorrect: Verify Zillow API parameters and location settings If offers are too low/high: Adjust your calculation parameters Step by Step tutorial: https://youtu.be/IqVw9CIL254?si=MKE5UY4rD0TOMLPg By following this guide, you'll have a functional system that can identify opportunities, analyze market conditions, and help you create personalized offers to potential sellers—all while minimizing the manual effort required so you can focus on closing deals.

Purpose This workflow creates a versioned backup of an entire Clockify workspace split up into monthly reports. How it works This backup routine runs daily by default The Clockify reports API endpoint is used to get all data from the workspace based on time entries A report file is being retrieved for every month starting with the current one, going back 3 month in total by default If changes happened during a day to any report, it is being updated in Github Prerequisites Create a private Github repository Create credentials for both Clockify and Github (make sure to give permissions for read and write operations) Setup Clone the workflow and select the belonging credentials Follow the instructions given in the yellow sticky notes Activate the workflow

This template is designed for community managers, developers, and enthusiasts who want to monitor and capture discussions on the n8n community forum by specific keywords. By tracking new topics that match your provided keyword, the workflow automatically logs them into a Google Sheet, helping you keep a pulse on trending discussions and manage community insights effortlessly. How it Works Keyword Monitoring: The workflow continuously monitors the n8n community forum for new topics containing your specified keyword. Data Extraction: When a matching topic is found, relevant details such as id, title, URL, and posting time are extracted. Google Sheets Integration: The extracted information is automatically appended as a new row in your Google Sheet, providing an organized log of community discussions. Alert Option: Optionally, you can add notifications (e.g., Slack messages or emails) to alert you when a new topic is captured, ensuring you never miss an important update. Set Up Steps Import the Workflow: Download and import the workflow into your n8n instance. Configure Keyword Monitoring: In the HTTP Request node, set your desired keyword to filter the n8n community topics. Set Up Google Sheets: Connect your Google Sheets account and specify the target sheet where the new topics should be logged. Customize Data Fields: Adjust the data extraction node parameters if you wish to capture additional details from each topic. Deploy and Test: Deploy the workflow and perform a test run to confirm that new topics matching the keyword are correctly added to your Google Sheet. Set Up Messaging Channels (Optional): Connect to Slack, Email or other providers to get instant messages when new topics are added into your Google Sheet. This template streamlines the process of tracking community discussions, ensuring you have timely and organized insights to enhance your community engagement and strategic decision-making. Enjoy seamless monitoring and easy data management with this ready-to-use n8n workflow template!

AI Story Generator with GPT-4o and Google Drive Integration Automatically generate complete stories with GPT-4o and seamlessly save them to Google Drive. Who is this for? Creative writers and authors Marketing and sales professionals Educators and content creators Fan fiction enthusiasts Anyone interested in automating storytelling with AI What problem is this workflow solving? Manually creating engaging, structured narratives can be time-consuming. Writers and content creators often struggle to maintain consistency, depth, and engaging storytelling structure. This workflow solves these challenges by automating story creation using advanced AI (GPT-4o) and proven storytelling techniques. What this workflow does This n8n automation generates comprehensive stories through an iterative AI-driven process: Step 1: Provide Your Story Idea Users input a clear description and specify their desired story format (short story, fan fiction, sales email, etc.). Step 2: AI-Driven Analysis GPT-4o analyzes the provided idea, categorizes the story, selects relevant storytelling frameworks inspired by PipDeck Storyteller Tactics, and determines narrative tone and direction. Step 3: Story and Character FoundationEstablishes core themes, emotional hooks, and detailed character backgrounds. Step 4: Initial Story Development Creates a structured plot outline including engaging elements such as hooks, twists, and resolutions. Step 5: Iterative Enhancement Refines the story through multiple automated prompts, improving narrative depth, character development, dialogue, and realism. Step 6: Editorial Feedback Generates automated critiques highlighting clichés, weak dialogues, and areas for improvement. Step 7: Final Polished Version Incorporates editorial feedback to produce a complete, polished, ready-to-use narrative. Step 8: Instant Google Drive OrganizationAutomatically saves the final story directly to your specified Google Drive folder for easy access and management. Setup Instructions Prerequisites: n8n account (cloud or self-hosted) GPT-4o API access via OpenAI Google Drive account Configure OpenAI Node: Add your GPT-4o API key in the OpenAI node settings. Configure Google Drive Node: Connect your Google Drive account by authenticating with n8n. Specify the folder where generated stories should be saved. Test Workflow: Run the workflow with a simple story prompt to ensure proper setup. How to Customize this Workflow Adjust Prompt Details: Modify AI prompt instructions to suit your specific story style and audience. Expand or Narrow Iterations: Change the number of iterations to balance between speed and story complexity. Customize Feedback Level: Adjust the level of editorial feedback provided. Dependencies and Requirements GPT-4o API from OpenAI Google Drive integration enabled in n8n Get Started Download and deploy this template today to streamline your storytelling process and produce consistently engaging, high-quality content effortlessly.

Summarize YouTube Videos & Chat About Content with GPT-4o-mini via Telegram Description This n8n workflow automates the process of summarizing YouTube video transcripts and enables users to interact with the content through AI-powered question answering via Telegram. It leverages the GPT-4o-mini model to generate summaries and provide insights based on the video’s transcript. How It Works Input: The workflow starts by receiving a YouTube video URL. This can be submitted through: A Telegram chat message. A webhook (e.g., triggered by a shortcut on Apple devices). Transcript Extraction: The URL is processed to extract the video transcript using the custom youtubeTranscripter community node (available here). The transcript is concatenated into a single text and stored in a Google Docs document. Summarization: The GPT-4o-mini AI model analyzes the transcript and generates a structured summary, including: A general overview. Key moments. Instructions (if applicable). The summary is then sent back to the user via Telegram. Interactive Q&A: Users can ask questions about the video content via Telegram. The AI retrieves the stored transcript from Google Docs and provides accurate, context-based answers, which are sent back through Telegram. Setup Instructions To configure this workflow, follow these steps: Import the Workflow: Download the provided JSON template and import it into your n8n instance. Install the Community Node: Install the youtubeTranscripter community node via npm: npm install n8n-nodes-youtube-transcription-kasha Important: This node requires a self-hosted n8n instance due to its external dependencies. Configure Nodes: Webhook: Set up the webhook to receive YouTube URLs. Alternatively, configure the Telegram node if using Telegram as the input method. Google Docs: Provide valid credentials to enable writing the transcript to a Google Docs document. AI Model: Set up the GPT-4o-mini model for summarization and Q&A functionality. Test the Workflow: Send a YouTube URL via your chosen input method (Telegram or webhook) and confirm that the summary is generated and delivered correctly. Customization Language**: Adjust the AI prompts to generate summaries and answers in any desired language. Output Format**: Modify the summary structure by editing the prompt in the summarization node. Input Methods**: Replace the Telegram node with another messaging or input node to adapt the workflow to different platforms. Who Can Benefit? This template is perfect for: Content Creators**: Quickly summarize video content for repurposing or review. Students and Researchers**: Extract key insights from educational or informational videos efficiently. General Users**: Interact with video content via AI without needing to watch the full video. Problem Solved This workflow simplifies video content consumption by: Automating the extraction and summarization of key points. Enabling interactive Q&A to address specific questions without rewatching the video. Additional Notes Disclaimer**: The youtubeTranscripter community node is required and only works on self-hosted n8n instances due to its reliance on external services. Apple Users**: Enhance your experience with a custom shortcut to share YouTube videos directly to the workflow. Download the shortcut here.

Who Is This For? Web developers SEO specialists Digital marketers What Problem Is This Workflow Solving? Automates the extraction of internal links from a webpage Eliminates the manual and error-prone process of collecting links Facilitates analysis of website structure and optimization What This Workflow Does Uses HTTP request node to fetch HTML content from a specified webpage Parses the HTML to identify and extract internal links Compiles a list of URLs directing to pages within the same domain Setup Configure the Set Base URL node: Set the url field to the URL you want to analyze. How to Customize This Workflow to Your Needs Change the target URL in the Set Base URL node to analyze different webpages. Add nodes to: Filter or categorize the extracted links Export the list to a database or CSV Send links via email or integrate with other tools This workflow can be used as a base for workflows to manage the process of extracting internal links, aiding in website optimization and SEO efforts.

This workflow scrapes Trustpilot reviews for a given profile and saves them into Google Sheets. How It Works Clone this Google Sheets template, which includes two sheets: trustpilot A raw collection of Trustpilot reviews. You can customize it as needed. helpfulcrowd This sheet follows the format from this HelpfulCrowd guide, with a slight modification: an added review_id column to support the upsert process. Once the workflow is complete, export the sheet as a CSV and upload it to HelpfulCrowd. For detailed steps, see this post. Running the Workflow You can trigger the workflow on-demand or schedule it to run at a set interval. Requirements Trustpilot business name** (e.g., n8n.io in https://www.trustpilot.com/review/n8n.io). Update this name and pagination settings in the Global node. Google Sheets API credentials** Check out my other templates: 👉 My n8n Templates

This workflow automates the process of analyzing emails and their attachments (PDFs and images) using AI models (DeepSeek, Gemini, and OpenRouter). It extracts and summarizes the content of emails and attachments, saves the summaries to Google Sheets, and sends a final consolidated summary via Telegram. This is a powerful tool for automating email analysis and summarization, saving time and ensuring that important information is easily accessible and actionable. Below is a breakdown of the workflow: 1. How It Works The workflow is designed to process incoming emails, analyze their content and attachments, and generate summaries. Here's how it works: Email Trigger: The workflow starts with the Email Trigger (IMAP) node, which monitors an email inbox for new emails. If an email contains attachments, the workflow processes them. Check for Attachments: The Contain Attachments? node checks if the email has attachments. If attachments are present, the workflow proceeds to process them. Process Attachments: The Get PDF and Images Attachments node extracts PDF and image attachments from the email. The Switch node separates PDFs and images for further processing: PDFs: The Extract from PDF node extracts text from PDFs, and the PDF Analyzer node summarizes the content. Images: The Analyze Image node uses AI to describe the content of images. Summarize Email Content: The Convert Text node converts the email's HTML content to plain text. The Email Summarization Chain node uses AI to generate a summary of the email's text content. Save Summaries: The Save Summary PDF, Save Summary Image, and Save Summary Text nodes save the summaries of PDFs, images, and email text, respectively, to Google Sheets. Consolidate Summaries: The All Summaries node aggregates the summaries of the email text, PDFs, and images. The Create Final Summary node uses AI to generate a unified summary of all the content. Send Final Summary: The Send Final Summary node sends the consolidated summary via Telegram to a specified chat ID. 2. Set Up Steps To set up and use this workflow in n8n, follow these steps: IMAP Configuration: Set up IMAP credentials in n8n for the Email Trigger (IMAP) node. Ensure the email account is accessible via IMAP. AI Model Configuration: Configure the DeepSeek, Gemini, and OpenRouter credentials in n8n for the Email Summarization Chain, PDF Analyzer, and Create Final Summary nodes. Ensure the AI models are set up to generate summaries. Google Sheets Integration: Set up Google Sheets credentials in n8n for the Save Summary PDF, Save Summary Image, and Save Summary Text nodes. Specify the Google Sheet and worksheet where the summaries will be saved. Telegram Integration: Set up Telegram credentials in n8n for the Send Final Summary node. Insert your Chat ID in the Telegram node to receive the final summary. Test the Workflow: Send an email with attachments (PDFs and images) to the monitored email account. The workflow will: Extract and summarize the email content and attachments. Save the summaries to Google Sheets. Send a consolidated summary via Telegram. Optional Customization: replace IMAP trigger with Gmail or Outlook trigger Modify the workflow to include additional features, such as: Adding more AI models for different types of analysis. Sending notifications via other channels (e.g., Slack, email). Integrating with other storage services (e.g., Dropbox, AWS S3).

Compare Local Ollama Vision Models for Image Analysis using Google Docs Process images using locally hosted Ollama Vision Models to extract detailed descriptions, contextual insights, and structured data. Save results directly to Google Docs for efficient collaboration. Who is this for? This workflow is ideal for developers, data analysts, marketers and AI enthusiasts who need to process and analyze images using locally hosted Ollama Vision Language Models. It’s particularly useful for tasks requiring detailed image descriptions, contextual analysis, and structured data extraction. What problem is this workflow solving? / Use Case The workflow solves the challenge of extracting meaningful insights from images in exhaustive detail, such as identifying objects, analyzing spatial relationships, extracting textual elements, and providing contextual information. This is especially helpful for applications in real estate, marketing, engineering, and research. What this workflow does This workflow: Downloads an image file from Google Drive. Processes the image using multiple Ollama Vision Models (e.g., Granite3.2-Vision, Gemma3, Llama3.2-Vision). Generates detailed markdown-based descriptions of the image. Saves the output to a Google Docs file for easy sharing and further analysis. Setup Ensure you have access to a local instance of Ollama. https://ollama.com/ Pull the Ollama vision models. Configure your Google Drive and Google Docs credentials in n8n. Provide the image file ID from Google Drive in the designated node. Update the list of Ollama vision models Test the workflow by clicking ‘Test Workflow’ to trigger the process. How to customize this workflow to your needs Replace the image source with another provider if needed (e.g., AWS S3 or Dropbox). Modify the prompts in the "General Image Prompt" node to suit specific analysis requirements. Add additional nodes for post-processing or integrating results into other platforms like Slack or HubSpot. Key Features: Detailed Image Analysis**: Extracts comprehensive details about objects, spatial relationships, text elements, and contextual settings. Multi-Model Support**: Utilizes multiple vision models dynamically for optimal performance. Markdown Output**: Formats results in markdown for easy readability and documentation. Google Drive Integration**: Seamlessly downloads images and saves results to Google Docs.