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This workflow will backup your workflows to Github. It uses the public api to export all of the workflow data using the n8n node. It then loops over the data checks in Github to see if a file exists that uses the workflow name. Once checked it will then update the file on Github if it exists, Create a new file if it doesn't exist and if it's the same it will ignore the file. Config Options repo_owner - Github owner repo_name - Github repository name repo_path - Path within the Github repository >This workflow has been updated to use the n8n node and the code node so requires at least version 0.198.0 of n8n

Are you a popular tech startup accelerator (named after a particular higher order function) overwhelmed with 1000s of pitch decks on a daily basis? Wish you could filter through them quickly using AI but the decks are unparseable through conventional means? Then you're in luck! This n8n template uses Multimodal LLMs to parse and extract valuable data from even the most overly designed pitch decks in quick fashion. Not only that, it'll also create the foundations of a RAG chatbot at the end so you or your colleagues can drill down into the details if needed. With this template, you'll scale your capacity to find interesting companies you'd otherwise miss! Requires n8n v1.62.1+ How It Works Airtable is used as the pitch deck database and PDF decks are downloaded from it. An AI Vision model is used to transcribe each page of the pitch deck into markdown. An Information Extractor is used to generate a report from the transcribed markdown and update required information back into pitch deck database. The transcribed markdown is also uploaded to a vector store to build an AI chatbot which can be used to ask questions on the pitch deck. Check out the sample Airtable here: https://airtable.com/appCkqc2jc3MoVqDO/shrS21vGqlnqzzNUc How To Use This template depends on the availability of the Airtable - make a duplicate of the airtable (link) and its columns before running the workflow. When a new pitchdeck is received, enter the company name into the Name column and upload the pdf into the File column. Leave all other columns blank. If you have the Airtable trigger active, the execution should start immediately once the file is uploaded. Otherwise, click the manual test trigger to start the workflow. When manually triggered, all "new" pitch decks will be handled by the workflow as separate executions. Requirements OpenAI for LLM Airtable For Database and Interface Qdrant for Vector Store Customising This Workflow Extend this starter template by adding more AI agents to validate claims made in the pitch deck eg. Linkedin Profiles, Page visits, Reviews etc.

This workflow is the opposite of this one. It transforms multiple different items with one binary object named data into a single item with multiple binary objects: This can be useful when creating a single .zip archive for example. It uses the updated Code node instead of the older Function node.

What this does This automation will create tables in your Airtable base and send Webflow form submissions as records in those tables. It keeps track of your Webflow forms with a Form Index table to ensure that form content does not get sent to the wrong table if you have Webflow forms with identical names. This is useful for Enhancing your Webflow form submission management. By sending structured data to your Airtable base you can do more with your Webflow forms. Usage guide Full written and video guide This automation is made to be as low effort as possible to start enhancing your Webflow forms. Simply create credentials for Webflow and a Personal Access Token for your Airtable base and connect them to the relevant nodes. The guide demonstrates a realworld example using a Webflow template and breaksdown the flow and logic for all the nodes.

Disclaimer: This template only works on self-hosted n8n instances and needs a community node. This workflow is designed to streamline the process of creating professional follow-up emails based on Google Meet recordings. It leverages OpenAI's transcription and summarization capabilities to extract key points, action items, and next steps, then drafts an email in Gmail for easy review and sending. Important : Custom n8n Installation with ffmpeg (Recommended): The workflow is optimized for instances of n8n with ffmpeg installed. This allows for seamless conversion of Google Meet recordings from MP4 to MP3 format, significantly reducing file size and improving processing efficiency. OAuth Configuration Required: For self-hosted n8n instances, ensure OAuth authentication is properly configured for Google Drive and Gmail. This is essential for accessing recordings and creating email drafts securely. Privacy Considerations: Before sending Google Meet recordings to OpenAI for processing, verify compliance with the data protection standards of the country or company you belong to. As this workflow is shared publicly, the creator is not responsible for ensuring compliance with regulations in your region or company. Workflow Overview: Detects when a Google Meet recording is uploaded to a designated Google Drive folder. Converts the recording to MP3 (if ffmpeg is available) and processes it through OpenAI for transcription. Summarizes the meeting and generates a professional follow-up email draft in Gmail, ready for your review and customization.

Overview This workflow automates the process of notifying users about new emails via Telegram and temporarily hosting the email content on a secret HTML page. It is ideal for users who need immediate notifications and a secure, temporary web view of their email content. Use Cases Immediate notification of new emails in Telegram with the ability to preview the email content in a secure, temporary HTML format. Automation for users who need to keep track of their emails without constantly checking their email client. Useful for teams or individuals who require instant updates on critical emails and prefer a quick preview through a web interface. My Personal Use Case: Secure Subscription Sharing From time to time, I find myself wanting to share my paid subscriptions with friends, but giving out OTP codes manually or sharing my email isn't a good idea due to security concerns. I attempted to use the IMAP node to integrate with Telegram secret channel for this purpose but encountered numerous problems, such as difficulties in scraping content from emails. Additionally, the Telegram API sometimes rejects certain special characters found within email contents. After facing these challenges, I discovered that rendering emails as HTML pages and sharing them directly is the most effective solution. This approach bypasses the issues with character limitations and content scraping, providing a seamless way to share subscription benefits securely. Services/APIs Used | Service/API | Node Type | Description | |----------------------|-------------------------|------------------------------------------------------| | IMAP Email Server | Email Trigger (IMAP) | Triggers the workflow on receiving a new email. | | Telegram API | Telegram | Sends notifications and manages messages in Telegram.| | GitHub Gist API | HTTP Request (Github Gist) | Temporarily hosts email content on GitHub Gist. | | GitHub Gist API (Deletion) | HTTP Request (Github Gist ‌) | Deletes the temporary GitHub Gist after a specified time. | | Wait | Wait | Delays the workflow for a specified period. | Configuration Steps Email Trigger (IMAP): Configure your IMAP email credentials to enable the workflow to check for new emails. Telegram Nodes: Insert your Telegram bot's API credentials and your chat ID in both Telegram nodes to send and delete messages. Github Gist Nodes: Provide your GitHub API credentials to create and delete Gists. Ensure the GitHub token has the necessary permissions to create and delete Gists. Wait Node: Adjust the wait time according to your preference for how long the email content should be accessible via the HTML page. Screenshot Additional Notes Ensure all credentials are securely stored and have the minimum necessary permissions for the workflow to function. Test the workflow with non-sensitive emails to ensure it operates as expected before using it with critical email accounts. Consider the privacy and security implications of temporarily hosting email content on GitHub Gist. For any questions or issues, refer to the respective API documentation for each service used or consult the n8n community for support.

This workflow syncs your GitHub issues to your Notion database. Whenever a new issue is opened in your GitHub repository, it will be shown in your Notion database, syncing the status property (opened/edited/closed/deleted). In case there’s no Notion database existing yet, a new one will be created automatically. Prerequisites Notion account and Notion credentials GitHub account and GitHub credentials How it works Github trigger starts the workflow when a new issue is created in a GitHub repository. If node splits the workflow conditionally, showing whether the issue is new or an update of an existing issue. If data is new, the Notion node will create a new database page in Notion. If the data is not new, the Function node will create a Notion filter that will find its specific database page by issue ID. Switch node will then conditionally route the data into the appropriate Notion page, based on the update made upon it.

Who is this template for? Anyone who is drowning in emails Busy parents who has alot of school emails Busy executives with too many emails Case Study I get too many emails from my kid's school about soccer practice, lunch orders and parent events. I use this workflow to read all the emails and tell me what is important and what requires actioning. Read more -> How I used A.I. to read all my emails What this workflow does It uses IMAP to read the emails from your email account (i.e. Gmail). It then passes the email to Openrouter.ai and uses a free A.I. model to read and summarize the email. It then sends the summary as a message to your messenger (i.e. Line). Setup You need to find your email server IMAP credentials. Input your openrouter.ai API credentials or replace the HTTP request node with an A.I. node such as OpenAI. Input your messenger credentials. I use Line but you can change the node to another messenger line Telegram. You need to change the message ID to your ID inside the http request. You can find your user ID inside the https://developers.line.biz/console/. Change the "to": {insert your user ID}. How to adjust it to your needs You can change the A.I. prompt to fit your needs by telling it to mark emails from a certain address as important. You can change the A.I. model from the current meta-llama/llama-3.1-70b-instruct:free to a paid model or other free models. You can change the messenger node to telegram or any other messenger app you like.

Use case Automatically create todo items in Todoist every morning. This workflow has two flows At 5am, delete any uncompleted tasks every morning At 5:10 am, copy all template tasks into Inbox In each template task, set the due dates and days to add the task. You can do that like this days:mon,tues; due:8pm which will add the task every Monday and Tuesday and make it due at 8pm. How to setup Add Todoist creds Create a template list to copy from in Todoist. Add days and due times on each task as necessary. Set the projects to copy from and to write to in each Todoist node

This n8n workflow demonstrates an approach to parsing bank statement PDFs with multimodal LLMs as an alternative to traditional OCR. This allows for much more accurate data extraction from the document especially when it comes to tables and complex layouts. Multimodal Parsing is better than traditiona OCR because: It reduces complexity and overhead by avoiding the need to preprocess the document into text format such as markdown before passing to the LLM. It handles non-standard PDF formats which may produce garbled output via traditional OCR text conversion. It's orders of magnitude cheaper than premium OCR models that still require post-processing cleanup and formatting. LLMs can format to any schema or language you desire! How it works You can use the example bank statement created specifically for this workflow here: https://drive.google.com/file/d/1wS9U7MQDthj57CvEcqG_Llkr-ek6RqGA/view?usp=sharing A PDF bank statement is imported via Google Drive. For this demo, I've created a mock bank statement which includes complex table layouts of 5 columns. Typically, OCR will be unable to align the columns correctly and mistake some deposits for withdrawals. Because multimodal LLMs do not accept PDFs directly, well have to convert the PDF to a series of images. We can achieve this by using a tool such as Stirling PDF. Stirling PDF is self-hostable which is handy for sensitive data such as bank statements. Stirling PDF will return our PDF as a series of JPGs (one for each page) in a zipped file. We can use n8n's decompress node to extract the images and ensure they are ordered by using the Sort node. Next, we'll resize each page using the Edit Image node to ensure the right balance between resolution limits and processing speed. Each resized page image is then passed into the Basic LLM node which will use our multimodal LLM of choice - Gemini 1.5 Pro. In the LLM node's options, we'll add a "user message" of type binary (data) which is how we add our image data as an input. Our prompt will instruct the multimodal LLM to transcribe each page to markdown. Note, you do not need to do this - you can just ask for data points to extract directly! Our goal for this template is to demonstrate the LLMs ability to accurately read the page. Finally, with our markdown version of all pages, we can pass this to another LLM node to extract required data such as deposit line items. Requirements Google Gemini API for Multimodal LLM. Google Drive access for document storage. Stirling PDF instance for PDF to Image conversion Customising the workflow At time of writing, Gemini 1.5 Pro is the most accurate in text document parsing with a relatively low cost. If you are not using Google Gemini however you can switch to other multimodal LLMs such as OpenAI GPT or Antrophic Claude. If you don't need the markdown, simply asking what to extract directly in the LLM's prompt is also acceptable and would save a few extra steps. Not parsing any bank statements any time soon? This template also works for Invoices, inventory lists, contracts, legal documents etc.

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.

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 workflow randomly select recipes from a Mealie instance (can use a specific category) and then creates a meal plan in Mealie with those recipes. How it works: Workflow has a scheduled trigger (set to run weekly on a Friday) Config node sets a few properties to configure the workflow A call to the Mealie API to get the list of recipes The code node holds most of the logic, this will loop through the number of recipes defined in the config node and randomly select a recipe from the list (making sure not to double up any recipes) Once all the recipes are selected it will call the Mealie API to set up the meal plan on the days Setup Add your Mealie API token as a credential and set it on the Http Request nodes Set the relevant schedule trigger to run when you like Update the Config node with the config you want numberOfRecipes - Number of recipes to populate for the meal plan offsetPlanDays - Number of days in the future to start the plan (0 will start it today, 1 tomorrow, etc.) mealieCategoryId - A category id of the category you want to pull in recipes from (default to select from all recipes) mealieBaseUrl - The base url of your Mealie instance

Use Case Following up at the right time is one of the most important parts of sales. This workflow uses Gmail to send outreach emails to Hubspot contacts that have already been contacted only once more than a month ago, and records the engagement in Hubspot. Setup Setup HubSpot Oauth2 creds (Be careful with scopes. They have to be exact, not less or more. Yes, it’s not simple, but it’s well documented in the n8n docs. Be smarter than me, read the docs) Setup Gmail creds. Change the email variables in the Set keys node How to adjust this template There's plenty to do here because the approach here is really just a starting point. Most important here is to figure out what your rules are to follow up. After a month? More than once? Also, remember to update the follow-up email! Unless you want to sell n8n 😉

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.

Streamline data from an n8n form into Google Sheet Airtable and and Email Sending Video for workflow process This workflow facilitates efficient data collection and management by leveraging the capabilities of various nodes within the n8n platform. It commences with the n8n Form Trigger node, where users provide their name, location, and email address. Subsequently, the data seamlessly flows through nodes like Google Sheets, Code, Set, Airtable, Gmail, and Gmail1 for processing and storage. n8n Form Trigger:** Gathers user input data, including Name, City, and Email. Google Sheets:** Manages data operations related to Google Sheets. Code:** Executes JavaScript code to manipulate data fields. Set:** Formats and sets data values for further processing. Airtable:** Facilitates data operations specific to Airtable. Gmail:** Sends custom emails to the provided Email address. Gmail:** Sends additional emails using different templates. Each node within the workflow performs specialized tasks such as extracting date and time fields, formatting data, appending it to Google Sheets and Airtable, and sending personalized emails to the submitter. This streamlined process ensures effective handling of collected information and enhances overall data management efficiency. Workflow Description: n8n Form Trigger: A trigger node that initiates the workflow upon form submission. Captures essential user details like Name, City, and Email. Extracting Date and Time Fields from 'submittedAt' Field: Utilizes a code node to extract Date and Time information from the submitted data. Format the Fields: Standardizes the format of extracted fields (Name, City, Date, Time, Email) for consistency. Airtable: Creates a new record in Airtable with the formatted data. Includes columns for Name, City, Email, Time, and Date. Google Sheets: Appends the formatted data to a designated Google Sheet. Includes columns for Name, City, Email, Date, and Time. Gmail: Sends an email to the provided Email address with a customized message. Subject: "Testing Text Message Delivery" Message: Personalized content with a Name placeholder. Gmail1: Sends another email using a different template. Subject incorporates the Date field for variation. Message content tailored to the subject line. Workflow Connections: n8n Form Trigger -> Extracting Date and Time Fields -> Format the Fields -> Google Sheets & Airtable -> Gmail Google Sheets -> Gmail1 This comprehensive workflow efficiently collects user data, processes it to extract Date and Time fields, stores the formatted information in Google Sheets and Airtable, and delivers tailored emails to the recipients. Copy these templates to get started : Google Sheet Airtable Links to Node Documentation: n8n Form Trigger Documentation Code Node Documentation Set Node Documentation Airtable Node Documentation Google Sheets Node Documentation Gmail Node Documentation

This n8n workflow demonstrates how to automate a large-scale personalized promotional email campaign, leveraging artificial intelligence to generate unique content for each recipient. Save time and increase the effectiveness of your marketing campaigns by allowing AI to handle the creation of personalized content and email sending. How it works: The workflow fetches recipient data from a Google Sheets document. It validates email addresses and checks if recipients haven't been contacted before. For each valid recipient, the AI agent (using GPT-3.5) generates a personalized email including the recipient's name, product introduction, exclusive offer, and a unique promotional link. The personalized email is sent via SMTP to the recipient. The workflow updates the Google Sheet to mark the recipient as contacted. A random delay is introduced between emails to mimic natural sending patterns and avoid triggering spam filters. Requirements: Google Sheets account for storing and managing recipient data. OpenAI account for access to the GPT-3.5 model. SMTP server for sending emails. Customizing the workflow: This example focuses on sending personalized promotional emails, but it could be extended to include follow-up sequences, tracking email opens and clicks, or integrating with a CRM system for more comprehensive customer management.

Having a seamless flow of customer data between your online store and your marketing platform is essential. By keeping your systems synchronized, you can ensure that your marketing campaigns are accurately targeted and effective. The integration between Shopify, a leading e-commerce platform, and Mautic, an open-source marketing automation system, is not available out-of-the-box. However, with a n8n workflow you can bridge this gap with. This template will help you: enhance accuracy in marketing lists by ensuring that subscription changes in Shopify are instantly updated in Mautic. improve compliance with data protection laws by respecting users' subscription preferences across platforms achieve integration without the need for additional plugins or software, minimizing complexity and potential points of failure. This template will demonstrate the follwing concepts in n8n: working with Shopify in n8n control flow with the IF node use Webhooks validate Webhooks with the Crypto node use the GraphQL node to call the Shopify Admin API The template consists of two parts: Sync Email Subscriptions from Shopify to Mautic Sync Email Subscriptions from Mautic to Shopify 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. Enable the Mautic API under Configuration/API Settings, After the settings are saved you will have an additional entry in your settings menu to create API credentials for n8n Create Mautic credentials in n8n Please make sure to read the notes in the template. For a detailed explanation please check the corresponding video: https://youtu.be/x63rrh_yJzI

Primer workflow for OpenAI models: ChatGPT, DALLE-2, Whisper This workflow contains 5 examples on how to work with OpenAI API. Transcribe voice into text via Whisper model (disabled, please put your own mp3 file with voice) The old way of using OpenAI conversational model via text-davinci-003 Examples 1.x. Simple ChatGPT calls. Text completion and text edit Example 2. Provide system and user content into ChatGPT Examples 3.x. Create system / user / assistanc content via Code Node. Promtp chaining technique example Example 4. Generate code via ChatGPT Example 5. Return multiple answers. Useful for providing picking the most relevant reply IMPORTANT! Do not run the whole workflow, it's rather slow Better execute the last node of each branch or simply disconnect branches that are not needed

What problem is this workflow solving? This workflow is aimed for email marketing enthusiasts looking for an easy way to either extract the domain from an email ad also check if the syntax is correct without having to use the code node. How this works For this to work, replace the debugger node with your actual data source. Map your data at match the above layout Run your workflow and check for all the emails that are either valid or not Once done, you will have a list of all your emails, domains, and whether they are valid or not.

This workflow is aimed to create new posts in wordpress automatically from an airtable dashboard. When creating content in bulk, we can save time by automating how we can post and publish this content. Usage Get the content from Airtable. Since we have this as a markdown, we will have to convert it to a html format to make it easier to publish and manage on WordPress Upload the blog post with the content, title and all other relevant information needed for an optimized blog Once the post is posted, we need to upload the image and set it as a features image for the blogs Happy productivity

This N8N workflow automates the process of sharing files from Google Drive. It includes OAuth2 authentication, batch processing, public link generation, and access status modification for efficient file handling. Suitable for users seeking to streamline their Google Drive file sharing process. sutiable for bulk actions, tested on 4.2K files folder working like charm. How It Works Initialize Workflow: The process begins with a Manual Trigger, allowing the user to start the workflow at their convenience. Folder ID Specification: A 'Set Folder ID' node where the user can enter the desired Google Drive Folder ID. List Files from Google Drive: The 'Google Drive' node lists all files within the specified folder using OAuth2 authentication. Batch Processing: The 'Loop Over Items' node processes the files in batches for efficiency. Generate Public Links: The 'Generate Download Links' node creates downloadable links for each file. Change File Access: The 'Change Status' node alters the file status to make them publicly accessible. Merge and Output: A 'Merge' node consolidates the data, preparing it for further actions or output. Set Up Steps Estimated Time**: The setup should take approximately 10-15 minutes. Initial Setup**: You'll need to provide OAuth2 credentials for Google Drive and specify a folder ID. Customization**: Adjust the batch size and file access permissions according to your needs. Detailed Descriptions**: For specific configuration details, refer to the sticky notes within the workflow. Example Item output { "link": "https://drive.google.com/u/3/uc?id=1hojqPfXchNTY8YRTNkxSo-8txK9re-V4&export=download&confirm=t&authuser=0", "name": "firefox_rNjA0ybKu7.png", "kind": "drive#permission", "id": "anyoneWithLink", "type": "anyone", "role": "reader", "allowFileDiscovery": false } You can store the output data with any data store node you want, for example save them into Excel Sheet or Airtable etc... Keywords: n8n workflow, Google Drive integration, file sharing automation, batch file processing, public link generation, OAuth2 authentication, workflow automation

This is an end-to-end workflow for creating a simple OpenAI Assistant. The whole process is done with n8n nodes and do not require any programming experience. The workflow is divided into three main steps: Step 1: Get a Google Drive File and Upload to OpenAI The workflow starts by retrieving a file from Google Drive using the "Get File" node. The example file used is a Music Festival document. The retrieved file is then uploaded to OpenAI using the "Upload File to OpenAI" node. Run this section only once. The file is stored persistently on the OpenAI side. Step 2: Set Up a New Assistant In this step, a new assistant is created using the "Create new Assistant" node. The assistant is given a name, description, and system prompt. The uploaded file from Step 1 is attached as a knowledge source for the assistant. Same as for Step 1, run this section only once. Step 3: Chat with the Assistant The "Chat Trigger" node initiates the conversation with the assistant. The "OpenAI Assistant" node handles the conversation, using the assistant created in Step 2. Step 4: Expand the Assistant This step provides resources for ideas on how to expand the Assistant's capabilities: Create a WhatsApp bot Create a simple Telegram bot Create a Telegram AI bot (YouTube video) By following this workflow, users can create their own AI-powered assistants using OpenAI's API and integrate them with various platforms like WhatsApp and Telegram.

This n8n template demonstrates how to get started with Gemini 2.0's new Bounding Box detection capabilities in your workflows. The key difference being this enables prompt-based object detection for images which is pretty powerful for things like contextual search over an image. eg. "Put a bounding box around all adults with children in this image" or "Put a bounding box around cars parked out of bounds of a parking space". How it works An image is downloaded via the HTTP node and an "Edit Image" node is used to extract the file's width and height. The image is then given to the Gemini 2.0 API to parse and return coordinates of the bounding box of the requested subjects. In this demo, we've asked for the AI to identify all bunnies. The coordinates are then rescaled with the original image's width and height to correctl align them. Finally to measure the accuracy of the object detection, we use the "Edit Image" node to draw the bounding boxes onto the original image. How to use Really up to the imagination! Perhaps a form of grounding for evidence based workflows or a higher form of image search can be built. Requirements Google Gemini for LLM Customising the workflow This template is just a demonstration of an experimental version of Gemini 2.0. It is recommended to wait for Gemini 2.0 to come out of this stage before using in production.

Restore backed up workflows from GitHub to your n8n workspace. This workflow was inspired by this one that lets you back up your n8n workflows to GitHub. It will let you restore your backed up workflows in your workspace, without creating duplicates. In case of issue with your instance, it will save you a lot of time to restore them. How it works It retrieves the workflows saved in a GitHub repository. Then compares these saved workflows with the ones in your n8n workspace based on the name. It will only create them if they don't already exist. Set up steps Open the "Global" node and set your own information (see Configuration below) Click on "Test workflow" It will run through all the workflows in the GitHub repository, check if the name doesn't already exist in your workspace and, in this case, create it. Configuration repo.owner: your GitHub owner name repo.name: your GitHub repository name repo.path: the path within the GitHub repository

Use case If you have a form where potential leads reach out, then you probably want to analyze those leads and send a notification if certain requirements are met, e.g. employee number is high enough. MadKudu is built exactly to solve this problem. We use it along with Hunter and Telegram to get a message for high quality leads. How to setup Add you MadKudu, Hunter, and Telegram credentials Set the Telegram chat id to send to Click the Test Workflow button, enter your email and check your email Activate the workflow and use the form trigger production URL to collect your leads in a smart way How to adjust this template You may want to raise or lower the threshold for your leads, as you see fit.

This flow is supported by a Chrome plugin created with Cursor AI. The idea was to create a Chrome plugin and a backend service in N8N to do chart analytics with OpenAI. It's a good sample on how to submit a screenshot from the browser to N8N. Who is it for? N8N developers who want to learn about using a Chrome plugin, an N8N webhook and OpenAI. What opportunity does it present? This sample opens up a whole range of N8N connected Chrome extensions that can analyze screenshots by using OpenAI. What this workflow does? The workflow contains: a webhook trigger an OpenAI node with GPT-4O-MINI and Analyze Image selected a response node to send back the Text that was created after analysing the screenshot. All this is needed to talk to the Chrome extension which is created with Cursor AI. The idea is to visit the tradingview.com crypto charts, click the Chrome plugin and get back analytics about the shown chart in understandable language. This is driven by the N8N flow. With the new image analytics capabilities of OpenAI this opens up a world of opportunities. Requirements/setup OpenAI API key Cursor AI installed The Chrome extension. Download The N8N JSON code. Download How to customize it to your needs? Both the Chrome extension and N8N flow can be adapted to use on other websites. You can consider: analyzing a financial screen and ask questions about the data shown analyzing other charts extending the N8N workflow with other AI nodes With AI and image analytics the sky is the limit and in some cases it saves you from creating complex API integrations. Download Chrome extension

Remember when you were doing some large research and wanted to quickly bookmark a page and save it, only to find premium options? Worry not; n8n got you covered. You can now create a simple bookmarking app straight to your browser using simple scrips on your browser called bookmarklets. A bookmarklet is a bookmark stored in a web browser that contains JavaScript commands that add new features to the browser. To create one, we need to add a short script to the bookmark tab of our browser like below A simple hack is to open a new tab and click on the star that appears on the right side Now that we have our bookmark, it's time for the fun part. Right-click on the bookmark we just created and select the edit option. This will allow you to set the name you want for your bookmark and the destination URL. The URL used here will be the script that shall "capture" the page we want to bookmark. The code below has been used and tested to work for this example javascript:(() => { var currentUrl = window.location.href; var webhookUrl = 'https://$yourN8nInstanceUrl/webhook/1rxsxc04b027-39d2-491a-a9c6-194289fe400c'; var xhr = new XMLHttpRequest(); xhr.open('POST', webhookUrl, true); xhr.setRequestHeader('Content-Type', 'application/json'); var data = JSON.stringify({ url: currentUrl }); xhr.send(data); })(); Your Bookmark should look like something like this Now that we have this setup, we are now going to n8n to receive the data sent by this script. Create a new webhook node that receives the POST request as in the workflow and replace $yourN8nInstanceUrl with your actual n8n instance. This workflow can then be configured to send this data to a notion database. Make sure the notion database has all the required permissions before executing the workflow. Otherwise the URLs will not be saved

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.

This workflow uses OpenAI Assistant to compose draft replies for labeled email messages. It automatically connects the drafts to Gmail threads. 💡 You can add knowledge base to your OpenAI Assistant and make your reply drafts very customized (e.g. compose response with product information in response to inquiry from customer). 🎬 See this workflow in action in my YouTube video about automating Gmail. How it works? The workflow is triggered at regular intervals (default: every 1 minute – you can change this value) to check for messages with a specific label (e.g., "AI"). The content of the retrieved email message is then forwarded to the OpenAI Assistant node, and a reply draft is generated. Next, the response from the Assistant is converted to HTML, and a raw message in RFC standard is composed. 💡 You can learn more about composing drafts with the Gmail API in the official Google documentation. The raw email message (reply draft) is encoded and attached to the original thread ID. Finally, the trigger label (in this case: "AI") is removed to prevent the workflow from looping. Set up steps Set credentials for Gmail and OpenAI. Add new label in Gmail account for messages that should be handled by the workflow (e.g. name it "AI"). Select this label in the first and last Gmail nodes in workflow. Create and configure your OpenAI Assistant. Select your assistant in "OpenAI Assistant" node. Optionally: change trigger interval (by default interval is 1 minute). If you like this workflow, please subscribe to my YouTube channel and/or my newsletter.

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

This n8n workflow is designed to assist YouTube content creators in identifying trending topics within a specific niche. By leveraging YouTube's search and data APIs, it gathers and analyzes video performance metrics from the past two days to provide insights into what content is gaining traction. Here's how the workflow operates: Trigger Setup: The workflow begins when a user sends a query through the chat_message_received node. If no niche is provided, the AI prompts the user to select or input one. AI Agent (Language Model): The central node utilizes a GPT-based AI agent to: Understand the user's niche or content preferences. Generate tailored search terms related to the niche. Process YouTube API responses and summarize trends using insights such as common themes, tags, and audience engagement metrics (views, likes, and comments). YouTube Search: The youtube_search node runs a secondary workflow to query YouTube for relevant videos published within the last two days. It retrieves basic video data such as video IDs, relevance scores, and publication dates. Video Details Retrieval: The workflow fetches additional details for each video: Video Snippet: Metadata like title, description, and tags. Video Statistics: Metrics such as views, likes, and comments. Content Details: Video duration, ensuring only content longer than 3 minutes and 30 seconds is analyzed. Data Processing: Video metadata is cleaned, sanitized, and stored in memory. Tags, titles, and descriptions are analyzed to identify patterns and trends across multiple videos. Output: The workflow compiles insights and presents them to the user, highlighting: The most common themes or patterns within the niche. URLs to trending videos and their respective channels. Engagement statistics, helping the user understand the popularity of the content. Key Notes for Setup: API Keys**: Ensure valid YouTube API credentials are configured in the get_videos, find_video_snippet, find_video_statistics, and find_video_data nodes. Memory Buffer**: The window_buffer_memory node ensures the AI agent retains context during analysis, enhancing the quality of the generated insights. Search Term Customization**: The AI agent dynamically creates search terms based on the user’s niche to improve search precision. Use Case: This workflow is ideal for YouTubers or marketers seeking data-driven inspiration for creating content that aligns with current trends, maximizing the potential to engage their audience. Example Output: For the niche "digital marketing": Trending Topic: Videos about "mental triggers" and "psychological marketing." Tags: "SEO," "Conversion Rates," "Social Proof." Engagement: Videos with over 200K views and high likes/comment ratios are leading trends. Video links: https://www.youtube.com/watch?v=video_id1 https://www.youtube.com/watch?v=video_id2

This workflows sends events to your Facebook Events Manager using the Meta Conversions API. Why should I use this? Enhance your Meta Ads tracking by taking control of the events you send. This n8n template allows you to: Improve Tracking Quality**: Even if your Facebook Pixel fails, events are still captured through the Meta Conversions API. Send Offline Events**: Record events that happen offline, like personal sales or in-store purchases. Integrate with Your CRM**: Automatically send events to Facebook when a lead converts after a sales call, updating customer details so Meta knows about the conversion. Use Advanced Tracking**: Tracking has become harder in recent years, making campaigns more expensive. By using Advanced Tracking, you help Facebook track events more easily, reducing campaign costs and improving the results. What events can I send? All of them! Purchase InitiateCheckout Lead Subscribe ViewContent … And many others. You can even send your own custom events. Who is this template for? Marketing professionals looking to improve the quality of the Meta Ads tracking. How it works You can send any event you want, as long as you have the necessary data (customer email, name, value of the purchase etc.) 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/

Telegram Bot Starter template workflow provides a foundational setup for creating powerful Telegram bots with n8n. It handles incoming messages, photos, files, and voice notes, making it an excellent starting point for developers looking to create bots for customer engagement, support, or interactive services. Key Features: Dynamic Message Handling: Respond to text messages, photos, files, and more. Modular Design: Easily integrate additional workflows such as user registration, payment modules, or custom commands. Error Handling: Ensure the bot gracefully manages errors and user inputs. Who Can Use This Workflow? Developers looking for a quick way to build and customize Telegram bots. Businesses and service providers who need customer interaction automation. Setup Instructions: Replace Telegram credentials with your own API credentials. Customize responses for different message types (text, photo, file). If integrating with external services (like Google Sheets), update the necessary credentials and links. Extensibility: This workflow is the base for building any Telegram bot. Additional modules, such as a user registration module, payment integration, and user profile management, are available for easy connection to expand the bot’s functionality. ✍🏻Use the Telegram user registration workflow → 💵Use the Telegram Payment, Invoicing and Refund Workflow for Stars → UPDATES: 🔥 Get the most up-to-date and expanded version → Aug 24: Changed processing of system events: “new user” and ‘user who blocked bot’ events Sep 24: Improved message handler: Updated logic to handle various types of messages using Switch (text, photo, file, voice, and callback). Payment processing: Added new nodes for sending invoices and handling payments via Telegram Please reach out to Victor if you need further assistance with your n8n workflows and automations!

Who is this for? For developers and organizations that need to convert PPTX files to PDF. What problem is this workflow solving? The file format conversion problem. What this workflow does Downloads the PPTX file from the web. Converts the PPTX file to PDF. Stores the PDF file in the local file system. How to customize this workflow to your needs Open the HTTP Request node. Adjust the URL parameter (all endpoints can be found here). Add your secret to the Query Auth account parameter. Please create a ConvertAPI account to get an authentication secret. Optionally, additional Body Parameters can be added for the converter.

Use Case When trying to maximize your outreach, website visitors are often an overlooked source of qualified new leads. This workflow allows your to track and enrich new website visitors and saves them to a Google Sheet once they meet a pre-defined criteria. What this workflow does This workflow fires once a day and gets all your leads saved in Leadfeeder. It then takes the leads that meet a pre-defined engagement criteria, e.g. that they visited your site 3 times, and enriches them additionally with Clearbit. From there it filters the leads again by a criteria on the company, e.g. a minimum employee count, and saves matching leads into a Google Sheet document. Setup Add your Leedfeeder credentials. The name should be Authorization and the value Token token=yourapitoken. You can find your token via Settings -> Personal -> API-Token Add your Google Sheet credentials Save the Leedfeeder account names you want to use in the Setup node Copy the Google Sheets Template and add its URL to the Setup node How to adjust this to your needs Adjust and/or remove the engagement and company criteria Add more ways to enrich a company Potential ideas to enhance the use of this workflow Automatically reach out to users that meet the criteria / that get added to the sheet Create a workflow that finds the right employee in companies that are identified by this workflow

Get recent funding rounds from Crunchbase in Google Sheets, along with 10+ data points (LinkedIn URL, monthly traffic, company size, etc.) You’ll be able to: Create a custom database Reach out to interesting leads at the right time Send custom alerts to your tools This workflow scrape recent funding rounds from Crunchbase, and add them in Google Sheets. It uses Piloterr API to get this data with ease. Full guide can be found here: https://lempire.notion.site/Get-recent-fundraising-in-Google-Sheets-dafbbda2635544b4925c4fb04abac8f5?pvs=74

Are you a visual thinker working with n8n? 🎨 View and understand workflow structures at a glance with this template! Built with mermaid.js, Bootstrap 5 and AXAJ to create an interactive web page displaying n8n workflows as flowcharts. 🌟 Perfect for documentation, presentations, or just getting a clearer picture of your automation processes. Need customization help? Reach out to Eduard! Benefits 📊 Instant workflow visualization 📱 Responsive design 🔗 Direct links to n8n workflows 🧩 Special shapes for different node types 🚫 Disabled node indication 🔒 No external dependencies – just paste the workflow and call the webhook 🛠️ Easily customizable – enhance the JS script or add custom styling ⚠️ Important note for cloud users ⚠️ Since the cloud version doesn't support environmental variables, please make the following changes in the CONFIG node: Update the instance_url variable: Enter your n8n URL instead of {{$env["N8N_PROTOCOL"]}}://{{$env["N8N_HOST"]}} Change the webhook_path to simply "webhook" instead of {{$env["N8N_ENDPOINT_WEBHOOK"] || "webhook"}} 🌟 Examples Multiple flowcharts on a single page: Several shapes for different nodes: Langchain nodes with special connections styling:

Overview This workflow answers user requests sent via Mac Shortcuts Several Shortcuts call the same webhook, with a query and a type of query Types of query are: translate to english translate to spanish correct grammar (without changing the actual content) make content shorter make content longer How it works Select a text you are writing Launch the shortcut The text is sent to the webhook Depending on the type of request, a different prompt is used Each request is sent to an OpenAI node The workflow responds to the request with the response from GPT Shortcut replace the selected text with the new one For a demo and setup instructions: How to use it Activate the workflow Download this Shortcut template Install the shortcut In step 2 of the shortcut, change the url of the Webhook In Shortcut details, "add Keyboard Shortcut" with the key you want to use to launch the shortcut Go to settings, advanced, check "Allow running scripts" You are ready to use the shortcut. Select a text and hit the keyboard shortcut you just defined

Effortlessly optimize your workflow by automatically importing hundreds of manufacturers from a Google Sheet into your Shopware online store, saving countless hours of manual work. How it works Retrieve all manufactures from a Google Sheet Add each manufacture via Shopware sync API Endpoint to Shopware Upload a logo for each manufacture from a provided public URL to Shopware Set Up Steps Add your Shopware url to first node called Settings Create a Google Sheet in your Google account with the following columns (Demo Sheet) name (the name of the manufacturer which has to be unique and is required) website (url to the manufacturer website) description logo_url (public manufcaturer logo url. Have to be a png, jpg or svg file) translation_language_code_1 (optional. Language Code of your language. For example 'es-ES' for spanish. You have to make sure a language with this code exists in your Shopware shop.) translation_name_1 (optional. Manufacturer name translated to the language you defined at translation_language_code_1) translation_description_1 (optional. Manufacturer description translated to the language you defined at translation_language_code_1) translation_language_code_2 (optional. Same as translation_language_code_1 for another language) translation_name_2 (optional. Same as translation_name_1 for another language) translation_description_2 (optional. Same as translation_description_1 for another language) translation_language_code_3 (optional. Same as translation_language_code_1 for another language) translation_name_3 (optional. Same as translation_name_1 for another language) translation_description_3 (optional. Same as translation_description_1 for another language) Connect to your Google account Connect to your Shopware account Create a Shopware Integration Connect to Shopware at the nodes "Import Manufacturer" and "Upload Manufacturer Logo" using a Generic OAuth2 API Authentication with Grant Type "Client Credentials". The Access Token URL is https://your-shopware-domain.com/api/oauth/token. Run the workflow

What this workflow does Linkedin tracks which Chrome extensions are installed in your browser. This workflow uses a huge raw JSON of chrome extension ids, extracted from Linkedin pages, and builds a pretty Google Sheet with the list of these extensions. This workflow web scrapes Google to search for chrome extension id - and extracts the first search result. Setup Clone this Google Sheet template: https://docs.google.com/spreadsheets/d/1nVtoqx-wxRl6ckP9rBHSL3xiCURZ8pbyywvEor0VwOY/edit?gid=0#gid=0 Get API key for Google SERP API access here: https://rapidapi.com/restyler/api/serp-api1 Create n8n header auth for Google SERP API Some context and discussion https://www.linkedin.com/feed/update/urn:li:activity:7245006911807393792/ Follow the author and get the final Google Sheet with 1300+ Chrome extensions: https://www.linkedin.com/in/anthony-sidashin/

What this template does This workflow will read your Zotero Library and extract Meta Data from the articles of one collection in your bibliography. You can personalize the output for optimized results. How it works Mainly, follow the instructions in the Post it notes: Go to https://www.zotero.org/settings/security and find your USER ID (It's right under the APPLICATIONS Section. On the same website, create a New Private Key. In the "Collections" Node, select Generic Credential Type > Header Auth > Create New Credential using: NAME: Zotero-API-Key VALUE: [Your Private Key] Run your Flow to check if it works and open the "Select Collection" node. See the Results of the previous node as TABLE and copy the "KEY" of the collection you want to use. After that you should have a working flow that reads your bibliography. You can edit or delete the last 2 nodes to personalize your results (Filter and Edit Fields)

This workflow illustrates how to convert data from JSON to binary format and import JSON data or files into Google Sheets or local spreadsheets.

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 n8n workflow allows you to update user roles in Zammad based on data from an Excel file. The workflow automates role assignments, ensuring efficient and consistent updates. Features Excel Integration**: Import user data from an Excel file containing emails and role assignments. Dynamic Updates**: Match Zammad users by email and update their roles. Error Handling**: Continue workflow execution even if some updates fail. Customizable Variables**: Configure Zammad API URL, API key, and Excel file URL. Usage Import the Workflow: Upload the provided .json file into your n8n instance. Set Variables: zammad_base_url: Your Zammad instance URL. excel_source_url: URL of the Excel file containing user data. Authentication for Zammad Create in the Node "Find Zammad User by email" and "Update User Roles" a Header Auth Authentication Name**: Authorization Value**: Bearer <put here your zammad api token> Run the Workflow: Execute the workflow to update user roles based on the Excel data. Issues and Suggestions For issues or suggestions, visit the GitHub Repository.

This workflow helps marketers verify and update data using EffiBotics Email Verifier API. Copy and create a list with emails as on this one https://docs.google.com/spreadsheets/d/1rzuojNGTaBvaUEON6cakQRDva3ueGg5kNu9v12aaSP4/edit#gid=0 The trigger checks for any updates in the number of rows that are present in a sheet and updates the verified emails on Google sheets Once you update a new cell, the new data is read, and the email is checked for its validity before. The results are then updated in real-time on the sheet. Happy Emailing!

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 workflow creates a new contact in Mautic when a new customer is created in Shopify. By default, the workflow will fill the first name, last name, and email address. You can add any other fields you require. Prerequisites Shopify account and Shopify credentials. Mautic account and Mautic credentials. How it works Triggers on a new customer in Shopify. Sends the required data to Mautic to create a new contact.

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 [email protected]

Overview This n8n workflow is designed to extract specific interests from messages in a Telegram chat and retrieve related information using the Facebook Graph API. It aims to provide a streamlined solution for parsing and analyzing user-provided interests within the Telegram platform. Features Interest Extraction:** Automatically identifies and extracts interests from messages that start with the hashtag "#interest". Data Retrieval:** Utilizes the Facebook Graph API to retrieve information related to the extracted interests. Structured Outputs:** Presents the retrieved data in an organized format for further analysis and review. Requirements Operational instance of n8n (self-hosted or cloud version). Basic understanding of n8n workflows and nodes. Setup and Configuration Import Workflow: Load the provided JSON workflow into your n8n instance. Configure Telegram Trigger Node: Ensure the Telegram trigger node is set up with the appropriate credentials and webhook ID. Configure and Test Nodes: Adjust node parameters as necessary and test the workflow to ensure proper functionality. How it Works Telegram Trigger: Listens for incoming messages in a specified Telegram chat. Check Message Contents: Verifies if the message begins with the specified hashtag and is from the designated chat ID. Extract Message: Extracts the content of the message for further processing. Split Message: Splits the extracted message to identify the interest and remaining content. Connect to Graph API: Utilizes the Facebook Graph API to search for information related to the extracted interest. Split Interests into a Table: Organizes the retrieved data into a structured table format. Get Variables: Maps the retrieved data to create a new JSON object containing specific fields related to the interest. Create a Spreadsheet: Generates a spreadsheet file in CSV format based on the retrieved and formatted data. Send the Spreadsheet File: Sends the generated spreadsheet file back to the original Telegram chat. Customization Modify the filtering conditions and fields to suit specific requirements. Adjust the frequency of the trigger node based on preference. Best Practices Regularly test the workflow to ensure consistent performance. Stay informed about any changes to external APIs that might affect the workflow's functionality. Contributing Your feedback and contributions are highly valued. Feel free to adapt, modify, and share enhancements with the n8n community.

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

This template shows how you can create reports on data in an app and share a summary in another app. Specifically, this example checks a Notion database for new submissions, filters for submissions with a specific tag, and then sends a Slack message with the number created this week. Setup instructions are located inside the workflow template.

What this template does The Ultimate Scraper for n8n uses Selenium and AI to retrieve any information displayed on a webpage. You can also use session cookies to log in to the targeted webpage for more advanced scraping needs. ⚠️ Important: This project requires specific setup instructions. Please follow the guidelines provided in the GitHub repository: n8n Ultimate Scraper Setup : https://github.com/Touxan/n8n-ultimate-scraper/tree/main. The workflow version on n8n and the GitHub project may differ; however, the most up-to-date version will always be the one available on the GitHub repository : https://github.com/Touxan/n8n-ultimate-scraper/tree/main. How to use Deploy the project with all the requirements and request your webhook. Example of request: curl -X POST http://localhost:5678/webhook-test/yourwebhookid \ -H "Content-Type: application/json" \ -d '{ "subject": "Hugging Face", "Url": "github.com", "Target data": [ { "DataName": "Followers", "description": "The number of followers of the GitHub page" }, { "DataName": "Total Stars", "description": "The total numbers of stars on the different repos" } ], "cookie": [] }' Or to just scrap a url : curl -X POST http://localhost:5678/webhook-test/67d77918-2d5b-48c1-ae73-2004b32125f0 \ -H "Content-Type: application/json" \ -d '{ "Target Url": "https://github.com", "Target data": [ { "DataName": "Followers", "description": "The number of followers of the GitHub page" }, { "DataName": "Total Stars", "description": "The total numbers of stars on the different repo" } ], "cookies": [] }' `

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.

Who is this template for? This template is designed for teams who need to automate data retrieval from SharePoint lists using n8n. It is ideal for users who want to authenticate via OAuth and then use the token to access SharePoint API endpoints, pulling in list data directly into n8n. How it works The template first generates an OAuth token using the Microsoft OAuth API. This token is then used to authenticate requests to the SharePoint List API, allowing the workflow to fetch data from a specified SharePoint list. By following the n8n workflow, the user can configure the necessary credentials and endpoints to automate SharePoint data access securely. Setup steps Step 1: Replace {tenant_id}, {client_id}, and {client_secret} with your Azure AD details for OAuth authentication. Step 2: Specify the SharePoint list API endpoint in the template (under "SharePoint List Fetch" node). Step 3: Configure the SharePoint list URL and make adjustments for specific data fields if necessary.

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

Source code, I maintain this worflow here. Usage Guide This workflow backs up all workflows as JSON files named in the [workflow_name].json format. Steps Create GitHub Repository Skip this step if using an existing repository. Add GitHub Credentials In Credentials, add the GitHub credential for the repository owner. Download and Import Workflow Import this workflow into n8n. Set Global Values In the Globals node, set the following: repo.owner: GitHub username of the repository owner. repo.name: Name of the repository for backups. repo.path: Path to the folder within the repository where workflows will be saved. Configure GitHub Nodes Edit each GitHub node in the workflow to use the added credentials. Workflow Logic Each workflow run handles files based on their status: New Workflow If a workflow is new, create a new file in the repository. Unchanged Workflow If the workflow is unchanged, skip to the next item. Changed Workflow If a workflow has changes, update the corresponding file in the repository. Current Limitations / Needs work Name Change of Workflows If a workflow is renamed or deleted in n8n, the old file remains in the repository. Deleted Workflows Deleted workflows in n8n are not removed from the repository.

This workflow integrates both web scraping and NLP functionalities. It uses HTML parsing to extract links, HTTP requests to fetch essay content, and AI-based summarization using GPT-4o. It's an excellent example of an end-to-end automated task that is not only efficient but also provides real value by summarizing valuable content. Note that to use this template, you need to be on n8n version 1.50.0 or later.

What this template does This workflow uses the Amadeus API, every day to check for bargain flights for an itinerary and price target of your choice. It then automatically emails you once it found a match. Setup Create an api account on https://developers.amadeus.com/ In Amadeus Flight Search, connect to Oauth2 API: -- Grant Type - Client Credentials -- Access Token URL - https://test.api.amadeus.com/v1/security/oauth2/token -- Client ID/Secret - from your account Set your details in Gmail Set your desired Origin/Destination airports in FromTo Set the dates ahead you wish to search in Get Dates (default is 7 days and 14 days) Set the price target in Under Price How to test it After completing the setup steps above, just hit 'Test workflow'!

Template Description This n8n workflow is designed to manage Fastmail masked email addresses using the Fastmail API. The workflow provides the following functionalities: Retrieve all masked emails: Fetches all masked email addresses associated with the Fastmail account. Create masked email: Allows creating a new masked email with a specified state (pending, enabled, etc.). Update masked email state: Updates the state of a masked email such as enabling, disabling, or deleting it. Generate HTML template: Constructs an HTML table to display the masked emails in a user-friendly format. Steps to Make it Work Webhook Node: This node listens for incoming requests to manage masked emails. Needs Basic Authentication credentials to secure the endpoint. Session Node: Sends a request to obtain session information from Fastmail's API. Requires an HTTP Header Auth credential with your Fastmail API token. Switch Node: Routes the workflow based on the state of the incoming masked email request (pending, enabled, disabled, deleted). HTTP Request Nodes: These nodes handle various Fastmail API calls for masked emails (get, set, update, delete). All HTTP Request nodes require an HTTP Header Auth credential attached, using the Fastmail API token. Set Node: Gathers the retrieved masked email list into an array for further processing. HTML Node: Generates an HTML template to render the masked email addresses in a table format. Respond to Webhook Node: Sends back the HTML table to the client in response to the webhook request. Needed Credentials Fastmail Masked E-Mail Addresses: An API token from Fastmail's API. Each HTTP call to Fastmail requires this credential for authentication. Note Ensure that you correctly configure authentication for the API calls and webhook security. Use your actual Fastmail API credentials with the correct scope. The workflow assumes that the Fastmail API is correctly configured and accessible from your n8n instance. Update URLs and credentials IDs according to your n8n configuration.

Who's this for? If you own a website and need to analyze your keyword rankings If you need to create a keyword report on your rankings If you want to grow your keyword positions SerpBear is an opensourced SEO tool specifically for keyword analytics. Click here to read details of how I use it Example output of A.I. Key Observations about Ranking Performance: The top-performing keyword is “Openrouter N8N” with a current position of 7 and an improving trend. Two keywords, “Best Docker Synology” and “Bitwarden Synology”, are not ranking in the top 100 and have a stable trend. Three keywords, “Obsidian Second Brain”, “AI Generated Reference Letter”, and “Actual Budget Synology”, and “N8N Workflow Generator” are not ranking well and have a declining trend. Keywords showing the most improvement: “Openrouter N8N” has an improving trend and a relatively high ranking of 7. Keywords needing attention: “Obsidian Second Brain” has a declining trend and a low ranking of 69. “AI Generated Reference Letter” has a declining trend and a low ranking of 84. “Actual Budget Synology”, “N8N Workflow Generator”, “Best Docker Synology”, and “Bitwarden Synology” are not ranking in the top 100. Use case Instead of hiring an SEO expert, I run this report weekly. It checks the keyword rankings of the past week and gives me recommendations on what to improve. How it works The workflow gathers SerpBear analytics for the past 7 days. It passes the data to openrouter.ai for A.I. analysis. Finally it saves to baserow. How to use this Input your SerpBearcredentials Enter your domain name Input your Openrouter.ai credentials Input your baserow credentials You will need to create a baserow database with columns: Date, Note, Blog Created by Rumjahn

Vector database (Qdrant) as a data analysis tool Working with images, embedding model - Voyage AI. For anomaly detection The first pipeline uploads (crops) dataset to Qdrant's collection. This is the second pipeline to set up cluster (class) centres in this Qdrant collection & cluster (class) threshold scores. The third is the anomaly detection tool, which takes any image as input and uses all preparatory work done with Qdrant (crops) collection. To recreate it You'll have to upload crops dataset 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 In general, pipelines are adaptable to any dataset of images [This workflow] Setting Up Medoids 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".

Enhance Query Resolution with the Knowledge Base Tool! Our KB Tool - Confluence KB is crafted to seamlessly integrate into the IT Ops AI SlackBot Workflow, enhancing the IT support process by enabling sophisticated search and response capabilities via Slack. Workflow Functionality: Receive Queries**: Directly accepts user queries from the main workflow, initiating a dynamic search process. AI-Powered Query Transformation**: Utilizes OpenAI's models or local ai to refine user queries into searchable keywords that are most likely to retrieve relevant information from the Knowledge Base. Confluence Integration**: Executes searches within Confluence using the refined keywords to find the most applicable articles and information. Deliver Accurate Responses**: Gathers essential details from the Confluence results, including article titles, links, and summaries, preparing them to be sent back to the parent workflow for final user response. To view a demo video of this workflow in action, click here. Quick Setup Guide: Ensure correct configurations are set for OpenAI and Confluence API integrations. Customize query transformation logic as per your specific Knowledge Base structure to improve search accuracy. Need Help? Dive into our Documentation or get support from the Community Forum! Deploy this tool to provide precise and informative responses, significantly boosting the efficiency and reliability of your IT support workflow.

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

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 Made by Simon @ automake.io

Who's this for? If you own a website and need to analyze your Google analytics data If you need to create an SEO report on which pages are getting most traffic or how your google search terms are performing If you want to grow your site based on suggestions from data Use case Instead of hiring an SEO expert, I run this report weekly. It checks compares the data from this week to the week before: Views based on countries The top performing pages Google search console performance Read my detailed case study here How it works The workflow gathers google analytics for the past 7 days then it gathers the data for the week before for comparison. It does this 3 times to get: views per country, engagement per page and google search console results for organic search results. The google analytics nodes has already chosen the correct dimensions and metrics. At the end, it passes the data to openrouter.ai for A.I. analyse. Finally it saves to baserow. How to use this Input your Google analytics credentials Input your property ID Input your Openrouter.ai credentials Input your baserow credentials You will need to create a baserow database with columns: Name, Country Views, Page Views, Search Report, Blog (name of your blog). Created by Rumjahn

Search music and play to Spotify from Telegram This workflow is a simple demonstration on accessing a message model from Telegram and it makes searching for songs an easy task even if you can't remember the artist or song name. An OpenAI message model tries to figure out the song and sends it to an active Spotify device**. Use case Imagine an office where you play music in the background and the employees can control the music without having to login to the playing account. How it works You describe the song in Telegram. Telegram bot sends the text to n8n. An OpenAI message model tries to find the song. Spotify gets the search query string. First match is then added to queue. -- If there is no match a message is sent to Telegram and the process ends. We change to the next track in the list. We make sure the song starts playing by trying to resume. We fetch the currently playing track. We return "now playing" information to Telegram: Song Name - Artist Name - Album Name. Error handling Every Spotify step has it's on error handler under settings where we output the error. Message parser receives the error and sends it to Telegram. Requirements Active workflow* OpenAI API key Telegram bot Spotify account and Oauth2 API Spotify active on a device** .* The Telegram trigger is activated only if this workflow is active. You can however TEST the workflow in the editor by clicking "Test step" and then it waits for the Telegram event. When event is received, just step through all steps or just clicking "Test step" on the "Fetch Now Playing" node. .** You must have a Spotify device active when trying to communicate with a device. Open Spotify and play something - not it is active.

The workflow starts by listening for messages from Telegram users. The message is then processed, and based on its content, different actions are taken. If it's a regular chat message, the workflow generates a response using the OpenAI API and sends it back to the user. If it's a command to create an image, the workflow generates an image using the OpenAI API and sends the image to the user. If the command is unsupported, an error message is sent. Throughout the workflow, there are additional nodes for displaying notes and simulating typing actions.

Using n8n a lot? Soar above the limitations of the default n8n dashboard! This template gives you an overview of your workflows, nodes, and tags – all in one place. 💪 Built using XML stylesheets and the Bootstrap 5 library, this workflow is self-contained and does not depend on any third-party software. 🙌 It generates a comprehensive overview JSON that can be easily integrated with other BI tools for further analysis and visualization. 📊 Reach out to Eduard if you need help adapting this workflow to your specific use-case! 🚀 Benefits: Workflow Summary** 📈: Instant overview of your workflows, active counts, and triggers. Left-Side Panel** 📋: Quick access to all your workflows, nodes, and tags for seamless navigation. Workflow Details** 🔬: Deep dive into each workflow's nodes, timestamps, and tags. Node Analysis** 🧩: Identify the most frequently used nodes across your workflows. Tag Organization** 🗂️: Workflows are grouped according to their tags. Visually Stunning** 🎨: Clean, intuitive, and easy-to-navigate dashboard design. XML & Bootstrap 5** 🛠️: Built using XML stylesheets and Bootstrap 5, ensuring a self-contained and responsive dashboard. No Dependencies** 🔒: The workflow does not rely on any third-party software. Bootstrap 5 files are loaded via CDN but can be delivered directly from your server. ⚠️ Important note for cloud users Since the cloud version doesn't support environmental variables, please make the following changes: get-nodes-via-jmespath node. Update the instance_url variable: enter your n8n URL instead of {{$env["N8N_PROTOCOL"]}}://{{$env["N8N_HOST"]}} Create HTML node. Please provide the n8n instance URL instead of {{ $env.WEBHOOK_URL }} 🌟Example: Check out our other workflows: n8n.io/creators/eduard n8n.io/creators/yulia

This n8n template showcases the new HTTP tool released in version 1.47.0. Overall, the tool helps simplify AI Agent workflows where custom sub-workflows were performing the same simple http requests. Comparisons 1. AI agent that can scrape webpages Remake of https://n8n.io/workflows/2006-ai-agent-that-can-scrape-webpages/ Changes: Replaces Execute Workflow Tool and Subworkflow Replaces Response Formatting 2. Allow your AI to call an API to fetch data Remake of https://n8n.io/workflows/2094-allow-your-ai-to-call-an-api-to-fetch-data/ Changes: Replaces Execute Workflow Tool and Subworkflow Replaces Manual Query Params Definitions Replaces Response Formatting

This n8n workflow demonstrates a simple approach to improve chat UX by staggering an AI Agent's reply for users who send in a sequence of partial messages and in short bursts. How it works Twilio webhook receives user's messages which are recorded in a message stack powered by Redis. The execution is immediately paused for 5 seconds and then another check is done against the message stack for the latest message. The purpose of this check lets use know if the user is sending more messages or if they are waiting for a reply. The execution is aborted if the latest message on the stack differs from the incoming message and continues if they are the same. For the latter, the agent receives the buffered messages up to that point and is able to respond to them in a single reply. Requirements A Twilio account and SMS-enabled phone number to receive messages. Redis instance for the messages stack. OpenAI account for the language model. Customising the workflow This workflow should work for other common messaging platforms such as Whatsapp and Telegram. 5 seconds too long or too short? Adjust the wait threshold to suit your customers.

Introducing the Qualys Scan Slack Report Subworkflow—a robust solution designed to automate the generation and retrieval of security reports from the Qualys API. This workflow is a sub workflow of the Qualys Slack Shortcut Bot workflow. It is triggered when someone fills out the modal popup in slack generated by the Qualys Slack Shortcut Bot. When deploying this workflow, use the Demo Data node to simulate the data that is input via the Execute Workflow Trigger. That data flows into the Global Variables Node which is then referenced by the rest of the workflow. It includes nodes to Fetch the Report IDs and then Launch a report, and then check the report status periodically and download the completed report, which is then posted to Slack for easy access. For Security Operations Centers (SOCs), this workflow provides significant benefits by automating tedious tasks, ensuring timely updates, and facilitating efficient data handling. How It Works Fetch Report Templates:** The "Fetch Report IDs" node retrieves a list of available report templates from Qualys. This automated retrieval saves time and ensures that the latest templates are used, enhancing the accuracy and relevance of reports. Convert XML to JSON:** The response is converted to JSON format for easier manipulation. This step simplifies data handling, making it easier for SOC analysts to work with the data and integrate it into other tools or processes. Launch Report:** A POST request is sent to Qualys to initiate report generation using specified parameters like template ID and report title. Automating this step ensures consistency and reduces the chance of human error, improving the reliability of the reports generated. Loop and Check Status:** The workflow loops every minute to check if the report generation is complete. Continuous monitoring automates the waiting process, freeing up SOC analysts to focus on higher-priority tasks while ensuring they are promptly notified when reports are ready. Download Report:** Once the report is ready, it is downloaded from Qualys. Automated downloading ensures that the latest data is always available without manual intervention, improving efficiency. Post to Slack:** The final report is posted to a designated Slack channel for quick access. This integration with Slack ensures that the team can promptly access and review the reports, facilitating swift action and decision-making. Get Started Ensure your Slack and Qualys integrations are properly set up. Customize the workflow to fit your specific reporting needs. Link to parent workflow Link to Vulnerability Scan Trigger Need Help? Join the discussion on our Forum or check out resources on Discord! Deploy this workflow to streamline your security report generation 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.

This node is designed to cleanse URLs and extract their domain names efficiently. It effectively handles a wide range of URL formats, including those with unconventional or complex top-level domains (TLDs), such as 'co.uk'. You can also use it to extract the domain from an email. The node will also check if the domain is from a free email provider (gmail.com / outlook.com...etc) or not. How It Works The node analyzes the provided URL, removing any unnecessary elements. It then identifies and extracts the domain name, ensuring compatibility with a diverse array of TLDs. The node utilizes an extensive list of TLDs to guarantee accurate domain extraction for virtually any URL. To view the complete list of supported top-level domains, please visit: TLD List on GitHub How to use it Call this workflow using the "execute workflow" node You can pass either an email variable or a url variable. For email, the node also detect free mail provider such as Yahoo / Google...etc

This is a workflow that tries to answer user queries using the standard GPT-4 model. If it can't answer, it sends a message to Slack to ask for human help. It prompts the user to supply an email address. This workflow is used in Advanced AI examples | Ask a human in the documentation. To use this workflow: Load it into your n8n instance. Add your credentials as prompted by the notes. Configure the Slack node to use your Slack details, or swap out Slack for a different service.

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.

An innovative N8N workflow that monitors cryptocurrency prices on Binance, identifies significant market movements, and sends customized alerts through Telegram. Ideal for traders and enthusiasts seeking real-time market insights. How It Works Trigger Options: Choose between a manual trigger or a scheduled trigger to start the workflow. Fetch Market Data: The 'Binance 24h Price Change' node retrieves the latest 24-hour price changes for cryptocurrencies from Binance. Identify Significant Changes: The 'Filter by 10% Change rate' node filters out cryptocurrencies with price changes of 10% or more. Aggregate Data: The 'Aggregate' node combines all significant changes into a single dataset. Format Data for Telegram: The 'Split By 1K chars' node formats this data into chunks suitable for Telegram's message size limit. Send Telegram Message: The 'Send Telegram Message' node broadcasts the formatted message to a specified Telegram chat. Set Up Steps Estimated Time**: About 1-5 minutes for setup. Initial Configuration**: Set up a Binance API connection (Optional) and your Telegram bot credentials. Customization**: Adjust the trigger according to your preference (manual or scheduled) and update the Telegram chat ID. Create Telegram bot steps**:- Setting up a Telegram bot and obtaining its token involves several steps. Here's a detailed guide: Start a Chat with BotFather: Open Telegram and search for "BotFather". This is the official bot that allows you to create new bots. Start a chat with BotFather by clicking on the "Start" button at the bottom of the screen. Create a New Bot: In the chat with BotFather, type /newbot and send the message. BotFather will ask you to choose a name for your bot. This is a display name and can be anything you like. Next, you'll need to choose a username for your bot. This must be unique and end in bot. For example, my_crypto_alert_bot. Receive Your Token: After you've set the name and username, BotFather will provide you with a token. This token is like a password for your bot, so keep it secure. The message will look something like this: Done! Congratulations on your new bot. You will find it at t.me/my_crypto_alert_bot. You can now add a description, about section and profile picture for your bot, see /help for a list of commands. Use this token to access the HTTP API: 123456:ABC-DEF1234ghIkl-zyx57W2v1u123ew11 The token in this case is 123456:ABC-DEF1234ghIkl-zyx57W2v1u123ew11. Test Your Bot: You can find your bot by searching for its username in Telegram. Start a chat with your bot and try sending it a message. Although it won't respond yet, this step is essential to ensure it's set up correctly. Use the Token in n8n: In your n8n workflow, when setting up the Telegram node, you'll be prompted to enter credentials. Choose to add new credentials and paste the token you received from BotFather. Get Your Chat ID: To send messages to a specific chat, you need to know the chat ID. The easiest way to find this is to first message your bot, then use a bot like @userinfobot to get your chat ID. Once you have the chat ID, you can configure it in the Telegram node in your n8n workflow. Finalize Your Workflow: With the bot token and chat ID set up in n8n, your Telegram notifications should work as intended in your workflow. Remember, keep your bot token secure and never share it publicly. If your token is compromised, you can always generate a new one by chatting with BotFather and selecting /token. Example result Keywords: n8n workflow, cryptocurrency market, Binance API, Telegram bot, price alert system, automated trading signals, market analysis `

Who is this for? For developers and organizations that need to convert DOCX files to PDF. What problem is this workflow solving? The file format conversion problem. What this workflow does Downloads the DOCX file from the web. Converts the DOCX file to PDF. Stores the PDF file in the local file system. How to customize this workflow to your needs Open the HTTP Request node. Adjust the URL parameter (all endpoints can be found here). Add your secret to the Query Auth account parameter. Please create a ConvertAPI account to get an authentication secret. Optionally, additional Body Parameters can be added for the converter.

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.

Use Case This workflow aims to enrich new contacts in Intercom. The more relevant the Intercom profile, the more useful it is. Once active, this n8n workflow will update contact data (phone, email) as well as location data from ExactBuyer. Setup Add a webhook url in Intercom to call this workflow Add your Exact Buyer API key Add your Intercom API key Activate workflow How to adjust this template There's plenty of interesting info that ExactBuyer returns that could be helpful. Take a look and update this workflow to add what you need.

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

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. 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.

Sometimes you need the rich text field to be in HTML instead of Markdown. This template either syncs a single record or all records at once. Youtube tutorial

Who is this for? This template is for everyone who manages their blog entries in Notion and want to have an easy way to transform them to Webflow. What this workflow does This workflow syncs your blog posts saved in a Notion Database once a day to Webflow. Sync Notion properties, rich text and cover image with your collection. Works with most elements: H1, H2, H3, normal text, bold text, italic text, links, quotes, bulleted lists, numbered lists, and images (under 4MB). Set up steps Connect your accounts. Add a "slug" field in Notion. Add a "Sync to Webflow?" checkbox in Notion. Run a test and map your collection data. Whenever the workflow runs, all the checked posts will be updated in the Webflow collection, whether it's a new post or an existing one.

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/

This workflow checks a configured list of Github repositories daily to see if a new release has been published. How it works: Workflow has a daily trigger RepoConfig node is a JSON array that defines a list of repositories to check releases for For each of the configured repos it fetches the latest release If the release was published within the last 24 hours it is output The release is sent as a Slack message showing the repo name, release name and link Setup Update the JSON in the RepoConfig node to the Github repos you wish to get notifications for Setup your Slack connection (or replace with your choice of notification)

Workflow Overview This workflow automates the process of forwarding e-book files to a Kindle device using a Telegram bot and Outlook email. Setup Steps: Telegram Bot Setup: Create a Telegram bot via BotFather and configure its credentials in the workflow. Outlook Email Configuration: Set up your Outlook email credentials. (Currently, only Outlook is supported, but you can modify the workflow to support other email providers.) Amazon Kindle Email Setup: Find your Kindle device's email address from your Amazon account. This will be the recipient address for the e-books. Allow Email Sending to Kindle: Ensure your Amazon account is configured to allow emails from your Outlook address to send files to your Kindle. Workflow Explanation: The workflow begins with a Telegram bot trigger node that listens for new chat messages. When a new message is received, the workflow checks if the message contains a file attachment. If no file is detected, the bot will send a warning reply to the user in the chat. If a file is found, it will be renamed to ensure it appears correctly on the Kindle device when sent. The workflow then composes an email with the file attached and sends it to the Kindle's receiving address. If the email is sent successfully, the bot will notify the user with a success message in the chat. Only Amazon-supported file types will be accepted by Kindle. If sending fails, you will receive a notification email from Amazon in your Outlook inbox. In case of delivery issues, retry sending the file as network issues may occasionally interfere with the process.

How it works: Did you ever miss any errors in your workflow executions? I did! And I usually only realised a few days or weeks later. 🙈 This template attaches a default error workflow to all your active workflows. From now on, you'll receive a notification whenever a workflow errors and you'll have peace of mind again. It runs every night at midnight so you never have to think of this again. Of course, you can also run it manually. Steps to set up: Update the Gmail note with your own email address, or replace it with any other notification mechanism. You can also use Slack, Discord, Telegram or text messages.. Activate the workflow. Relax. Caveats: I did not add any rate limiting, so if you have a workflow that runs very frequently and it errors... well let's say your mailbox will not be a nice place anymore. Ideas for improvement? If you have any suggestions for improvement, feel free to reach out to me at [email protected]. Enjoy!

This updated workflow will automatically archive your Spotify Discover Weekly tracks to another manually created playlist, without the nuisance of duplicate tracks. It utilizes the latest verisons of n8n's Schedule trigger, Spotify, Switch, Merge, and IF nodes. Special thanks to trey for their original version of the workflow, as well as ihortom for their help with navigating the Switch node's outputs. To use this workflow, you'll need to: Create a playlist for use as the archive playlist within your Spotify account Create and select your Spotify credentials within each Spotify node within the workflow See workflow README for additional information and optional setup steps.

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

📈 Daily Financial News - Description This workflow automates the process of collecting, organizing, and delivering a daily summary of financial news by following these key steps: Scheduled Activation The workflow starts at 7:00 AM each day, triggered by the Schedule Trigger node. News Retrieval The HTTP Request node fetches the latest financial news from FT.com. Content Extraction The Extract Specific Content node scrapes targeted sections of the HTML (headlines, editor's picks, top stories, etc.) using CSS selectors to locate and capture relevant content. News Aggregation The Set Node gathers and organizes the extracted news data, preparing it for summarization. Categories like "Headline #1," "Editor's Picks," and "Europe News" are all structured into a single data block. Summarization An AI Agent (Google Gemini) takes the aggregated news data and creates a concise, HTML-formatted summary tailored to give investors an insightful market snapshot. Email Delivery Finally, the Microsoft Outlook node sends the summary via email to the designated recipient with the subject "Financial news from today." This process ensures that financial news is efficiently curated, summarized, and delivered without manual intervention.

This template can be used to search for an email address with Icypeas. Be sure to have an active account to use this template. How it works This workflow can be divided into three steps : The workflow initiates with a manual trigger (On clicking 'execute'). It connects to your Icypeas account. It performs an HTTP request to search for an email address. Set up steps You will need a working icypeas account to run the workflow and get your API Key, API Secret and User ID. You will need a personn firstname, lastname and domain/company name to perform the search.

Super simple workflow to convert image URLs to an uploaded attachment in Airtable. You'll need to adjust the field names to match your specific data, including in the filter formula where it says "Cover image URL". Just replace that with the field name where you are storing the image URL.

Description: This template facilitates the transfer of a folder, along with all its files and subfolders, within a Nextcloud instance. The Nextcloud user must have access to both the source and destination folders. While Nextcloud allows folder movement, complications may arise when dealing with external storage that has rate limits. This workflow ensures the individual transfer of each file to avoid exceeding rate limits, particularly useful for setups involving external storage with rate limitations. How it works: Identify all files and subfolders within the specified source folder. Recursive search within subfolders for additional files. Replicate the folder structure in the target folder. Individually move each identified file to the corresponding location in the target folder. Set up steps: Set Nextcloud credentials for all Nextcloud nodes involved in the process. -Edit the trigger settings. Detailed instructions can be found within the respective trigger configuration. Initiate the workflow to commence the folder transfer process. Help If you need assistance with applying this template, feel free to reach out to me. You can find additional information about me and my services here. => https://nicokowalczyk.de/links I have also produced a video where I explain the workflow and provide an example. You can find this video over here. https://youtu.be/K1kmG_Q_jRk Cheers. Nico Kowalczyk

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 Error workflows are an important part of running workflows in production. How to setup Add Slack creds Add this error workflow to other workflows (docs)

Create a Telegram bot that combines advanced AI functionalities with LangChain nodes and new tools. Nodes as tools and the HTTP request tool are a new n8n feature that extend custom workflow tool and simplify your setup. We used the workflow tool in the previous Telegram template to call the Dalle-3 model. In the new version, we've achieved similar results using the HTTP Request tool and the Telegram node tool instead. The main difference is that Telegram bot becomes more flexible. The LangChain Agent node can decide which tool to use and when. In the previous version, all steps inside the custom workflow tool were executed sequentially. ⚠️ Note that you'd need to select the Tools Agent to work with new tools. Before launching the template, make sure to set up your OpenAI and Telegram credentials. Here’s how the new Telegram bot works: Telegram Trigger listens for new messages in a specified Telegram chat. This node activates the rest of the workflow after receiving a message. AI Tool Agent receives input text, processes it using the OpenAI model and replies to a user. It addresses users by name and sends image links when an image is requested. The OpenAI GPT-4o model generates context-aware responses. You can configure the model parameters or swap this node entirely. Window buffer memory helps maintain context across conversations. It stores the last 10 interactions and ensures that the agent can access previous messages within a session. Conversations from different users are stored in different buffers. The HTTP request tool connects with OpenAI's DALL-E-3 API to generate images based on user prompts. The tool is called when the user asks for an image. Telegram node tool sends generated images back to the user in a Telegram chat. It retrieves the image from the URL returned by the DALL-E-3 model. This does not happen directly, however. The response from the HTTP request tool is first stored in the Agent’s scratchpad (think of it as a short-term memory). In the next iteration, the Agent sends the updated response to the GPT model once again. The GPT model will then create a new tool request to send the image back to the user. To pass the image URL, the tool uses the new $fromAI() expression. Send final reply node sends the final response message created by the agent back to the user on Telegram. Even though the image was already passed to the user, the Agent always stops with the final response that comes from dedicated output. ⚠️ Note, that the Agent may not adhere to the same sequence of actions in 100% of situations. For example, sometimes it could skip sending the file via the Telegram node tool and instead just send an URL in the final reply. If you have a longer series of predefined steps, it may be better to use the “old” custom workflow tool. This template is perfect as a starting point for building AI agentic workflow. Take a look at another agentic Telegram AI template that can handle both text and voice messages.

This workflow will help guide you through obtaining a spreadsheet file, reading it, making a change then saving it to local or cloud storage.

This workflow demonstrates the conversion of a CSV file to Excel format. First, an example CSV file is downloaded via a direct link. The source file is taken from the European Open Data Portal: https://data.europa.eu/data/datasets/veranstaltungsplaetze-potsdam-potsdam?locale=en The binary data is then imported via the Spreadsheet File node and converted to Excel format. N.B. Note that as of version 1.23.0 n8n, the Spreadsheet File node has been redesigned and is now called Convert to File node. Learn more on the release notes page: https://docs.n8n.io/release-notes/#n8n1230

This workflow shows a no code approach to creating Salesforce accounts and contacts based on data coming from an Excel file. For Excel 365 (the online version of Microsoft Excel) check out this workflow instead. To run the workflow: Make sure your Salesforce account is authenticated with n8n. Have a Microsoft Excel workbook with contacts and their account names ready. The workflow uses this example file, but you probably want to use your own data instead. Hit the Execute Workflow button at the bottom of the n8n canvas. Here is how it works: The workflow first searches for existing Salesforce accounts by name. It then branches out depending on whether the account already exists in Salesforce or not. If an account does not exist yet, it will be created. The data is then normalised before both branches converge again. Finally the contacts are created or updated as needed in Salesforce.

Video Guide I prepared a detailed guide that showed the whole process of building a resume analyzer. Who is this for? This workflow is ideal for developers, data analysts, and business owners who want to enable conversational interactions with their database. It’s particularly useful for cases where users need to extract, analyze, or aggregate data without writing SQL queries manually. What problem does this workflow solve? Accessing and analyzing database data often requires SQL expertise or dedicated reports, which can be time-consuming. This workflow empowers users to interact with a database conversationally through an AI-powered agent. It dynamically generates SQL queries based on user requests, streamlining data retrieval and analysis. What this workflow does This workflow integrates OpenAI with a Supabase database, enabling users to interact with their data via an AI agent. The agent can: Retrieve records from the database. Extract and analyze JSON data stored in tables. Provide summaries, aggregations, or specific data points based on user queries. Dynamic SQL Querying: The agent uses user prompts to create and execute SQL queries on the database. Understand JSON Structure: The workflow identifies JSON schema from sample records, enabling the agent to parse and analyze JSON fields effectively. Database Schema Exploration: It provides the agent with tools to retrieve table structures, column details, and relationships for precise query generation. Setup Preparation Create Accounts: N8N: For workflow automation. Supabase: For database hosting and management. OpenAI: For building the conversational AI agent. Configure Database Connection: Set up a PostgreSQL database in Supabase. Use appropriate credentials (username, password, host, and database name) in your workflow. N8N Workflow AI agent with tools: Code Tool: Execute SQL queries based on user input. Database Schema Tool: Retrieve a list of all tables in the database. Use a predefined SQL query to fetch table definitions, including column names, types, and references. Table Definition: Retrieve a list of columns with types for one table.

Who this is for This workflow is for sales people who want to quickly and efficiently follow up with their leads What this workflow does This workflow starts every time a new reply is received in lemlist. It then classifies the response using openAI and creates the correct follow up task. The follow-up tasks currently include: Slack alerts when a lead for each new replies Tag interested leads in lemlist Unsubscription of leads when they request it The Slack alerts include: Lead email address Sender email address Reply type (positive, not interested...etc) A preview of the reply Setup To set this template up, simply follow the stickies steps in it How to customize this workflow to your needs Adjust the follow up tasks to your needs Change the Slack notification to your needs ...

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 template shows how to sync data from one service to another. Specifically, in this example we're saving a new qualified lead from a Postgres database to a Google Sheets file. Setup instructions are located inside the workflow template.

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

This AI agent can access data provided by another n8n workflow. Since that workflow can be used to retrieve any data from any service, this template can be used give an agent access to any data. Note that to use this template, you need to be on n8n version 1.19.4 or later.

This workflow provides an OAuth 2.0 auth token refresh process for better control. Developers can utilize it as an alternative to n8n's built-in OAuth flow to achieve improved control and visibility. In this template, I've used Pipedrive API, but users can apply it with any app that requires the authorization_code for token access. This resolves the issue of manually refreshing the OAuth 2.0 token when it expires, or when n8n's native OAuth stops working. What you need to replicate this Your database with a pre-existing table for storing authentication tokens and associated information. I'm using Supabase in this example, but you can also employ a self-hosted MySQL. Here's a quick video on setting up the Supabase table. Create a client app for your chosen application that you want to access via the API. After duplicating the template: a. Add credentials to your database and connect the DB nodes in all 3 workflows. Enable/Publish the first workflow, "1. Generate and Save Pipedrive tokens to Database." Open your client app and follow the Pipedrive instructions to authenticate. Click on Install and test. This will save your initial refresh token and access token to the database. Please watch the YouTube video for a detailed demonstration of the workflow: How it operates Workflow 1. Create a workflow to capture the authorization_code, generate the access_token, and refresh the token, and then save the token to the database. Workflow 2. Develop your primary workflow to fetch or post data to/from your application. Observe the logic to include an if condition when an error occurs with an invalid token. This triggers the third workflow to refresh the token. Workflow 3. This workflow will handle the token refresh. Remember to send the unique ID to the webhook to fetch the necessary tokens from your table. Detailed demonstration of the workflow: https://youtu.be/6nXi_yverss

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.

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 demonstrates how to automate image captioning tasks using Gemini 1.5 Pro - a multimodal LLM which can accept and analyse images. This is a really simple example of how easy it is to build and leverage powerful AI models in your repetitive tasks. How it works For this demo, we'll import a public image from a popular stock photography website, Pexel.com, into our workflow using the HTTP request node. With multimodal LLMs, there is little do preprocess other than ensuring the image dimensions fit within the LLMs accepted limits. Though not essential, we'll resize the image using the Edit image node to achieve fast processing. The image is used as an input to the basic LLM node by defining a "user message" entry with the binary (data) type. The LLM node has the Gemini 1.5 Pro language model attached and we'll prompt it to generate a caption title and text appropriate for the image it sees. Once generated, the generated caption text is positioning over the original image to complete the task. We can calculate the positioning relative to the amount of characters produced using the code node. An example of the combined image and caption can be found here: https://res.cloudinary.com/daglih2g8/image/upload/f_auto,q_auto/v1/n8n-workflows/l5xbb4ze4wyxwwefqmnc Requirements Google Gemini API Key. Access to Google Drive. Customising the workflow Not using Google Gemini? n8n's basic LLM node supports the standard syntax for image content for models that support it - try using GPT4o, Claude or LLava (via Ollama). Google Drive is only used for demonstration purposes. Feel free to swap this out for other triggers such as webhooks to fit your use case.

This workflow allows you to ask questions about the data in a Google Sheet over a chat interface. It uses n8n's built-in chat, but could be modified to work with Slack, Teams, WhatsApp, etc. Behind the scenes, the workflow uses GPT4, so you'll need to have an OpenAI API key that supports it. How it works The workflow uses an AI agent with custom tools that call a sub-workflow. That sub-workflow reads the Google Sheet and returns information from it. Because models have a context window (and therefore a maximum number of characters they can accept), we can't pass the whole Google Sheet to GPT - at least not for big sheets. So we provide three ways of querying less data, that can be used in combination to answer questions. Those three functions are: List all the columns in the sheet Get all values of a single column Get all values of a single row Note that to use this template, you need to be on n8n version 1.19.4 or later.

Task: Make sure that data is in the right format before injecting it into a database/spreadsheet/CRM/etc. Why: Spreadsheets and databases require the incoming data to have the same fields as the headers of the destination table. You can decide which fields you would like to send with the database and rename them by using the set node Main use cases: Change fields names to match a database or a spreadsheet table structure Keep only the fields that are needed at the destination table

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!

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.

How it works: This project creates a personal AI assistant named Angie that operates through Telegram. Angie can summarize daily emails, look up calendar entries, remind users of upcoming tasks, and retrieve contact information. The assistant can interact with users via both voice and text inputs. Step-by-step: Telegram Trigger: The workflow starts with a Telegram trigger that listens for incoming message events. The system determines if the incoming message is voice or text. If voice, the voice file is retrieved and transcribed to text using OpenAI's API Speech to Text AI Assistant: The telegram request is passed to the AI assistant (Angie). Tools Integration: The AI assistant is equipped with several tools: Get Email: Uses Gmail API to fetch recent emails, filtering by date. Get Calendar: Retrieves calendar entries for specified dates. Get Tasks: Connects to a Baserow (open-source Airtable alternative) database to fetch to-do list items. Get Contacts: Also uses Baserow to retrieve contact information. Response Generation: The AI formulates a response based on the gathered information and sends back to the user on Telegram

Video Guide I prepared a detailed guide that showed the whole process of building a resume analyzer. Who is this for? This workflow is ideal for recruitment agencies, HR professionals, and hiring managers looking to automate the initial screening of CVs. It is especially useful for organizations handling large volumes of applications and seeking to streamline their recruitment process. What problem does this workflow solve? Manually screening resumes is time-consuming and prone to human error. This workflow automates the process, providing consistent and objective analysis of CVs against job descriptions. It helps filter out unsuitable candidates early, reducing workload and improving the overall efficiency of the recruitment process. What this workflow does This workflow automates the resume screening process using OpenAI for analysis. It provides a matching score, a summary of candidate suitability, and key insights into why the candidate fits (or doesn’t fit) the job. Retrieve Resume: The workflow downloads CVs from a direct link (e.g., Supabase storage or Dropbox). Extract Data: Extracts text data from PDF or DOC files for analysis. Analyze with OpenAI: Sends the extracted data and job description to OpenAI to: Generate a matching score. Summarize candidate strengths and weaknesses. Provide actionable insights into their suitability for the job. Setup Preparation Create Accounts: N8N: For workflow automation. OpenAI: For AI-powered CV analysis. Get CV Link: Upload CV files to Supabase storage or Dropbox to generate a direct link for processing. Prepare Artifacts for OpenAI: Define Metrics: Identify the metrics you want from the analysis (e.g., matching percentage, strengths, weaknesses). Generate JSON Schema: Use OpenAI to structure responses, ensuring compatibility with your database. Write a Prompt: Provide OpenAI with a clear and detailed prompt to ensure accurate analysis. N8N Scenario Download File: Fetch the CV using its direct URL. Extract Data: Use N8N’s PDF or text extraction nodes to retrieve text from the CV. Send to OpenAI: URL: POST to OpenAI’s API for analysis. Parameters: Include the extracted CV data and job description. Use JSON Schema to structure the response. Summary This workflow provides a seamless, automated solution for CV screening, helping recruitment agencies and HR teams save time while maintaining consistency in candidate evaluation. It enables organizations to focus on the most suitable candidates, improving the overall hiring process.

This template provides a workflow to integrate a Telegram bot with NeurochainAI's inference capabilities, supporting both text processing and image generation. Follow these steps to get started: > Purpose: Enables seamless integration between your Telegram bot and NeurochainAI for advanced AI-driven text and image tasks. Requirements Telegram Bot Token. NeurochainAI API Key. Sufficient credits to utilize NeurochainAI services. Features Text processing through NeurochainAI's inference engine. AI-powered image generation (Flux). Easy customization and scalability for your use case. Setup Import the template into N8N. Add your Telegram Bot Token and NeurochainAI API Key where prompted. Follow the step-by-step instructions embedded in the template for configuration. [NeurochainAI Website](https://www.neurochain.ai/ ) NeurochainAI Guides

Who is this for? This template is designed for businesses and organizations that use Mautic for email marketing and want to automate the process of removing contacts from specific segments when they receive an unsubscribe request via email. What problem is this workflow solving? / use case Many email recipients, especially those who are less tech-savvy, may not follow the standard unsubscribe link provided in emails. Instead, for example in Gmail, they click the "Unsubscribe" button in the Gmail web interface, which in turn sends an email with a consistent format, these emails contain the word unsubscribe in the 'To' field using the following structure: [email protected] This workflow automates the process of identifying such unsubscribe emails and removing the contact from the relevant Mautic segments, ensuring compliance with unsubscribe requests and maintaining a clean mailing list. What this workflow does Monitors a Gmail account for incoming emails. Identifies unsubscribe emails based on specific patterns in the "To" field (e.g., containing the word "unsubscribe"). Retrieves the contact's ID from Mautic based on the email address. Removes the contact from the specified "newsletter" segment in Mautic. Adds the contact to the "unsubscribed" segment in Mautic. Sends a confirmation email to the contact, acknowledging their unsubscribe request. Setup Configure your email address and unsubscribe message in the "Edit Fields" node. Set your credentials in the Gmail trigger and in the Mautic nodes. Set the segments for the "newsletter" and "unsubscribed" in the Mautic nodes. Make sure your n8n installation has a public endpoint for your Gmail trigger to work correctly. Deploy the workflow. How to customize this workflow to your needs Adjust the conditions for identifying unsubscribe emails based on your specific requirements. Modify the segments or actions taken in Mautic according to your desired behavior. Customize the confirmation email message and sender details. Note: This workflow assumes a consistent structure for unsubscribe emails, where the "From" field contains the word "unsubscribe" using the "+" sign. If your email provider follows a different convention, adjust the conditions in the "Is automated unsubscribe?" node accordingly.

Use Case Transform and optimize images for web use: You need to host local images online You want to reduce image file sizes automatically You need image URLs for web content You want to generate and optimize AI-created images What this Workflow Does The workflow processes images through two services: Uploads images to ImgBB for hosting and URL generation (free but need API key) Optimizes images using ReSmush.it to reduce file size (free) Optional: Creates images using OpenAI's image generation Returns optimized image URLs ready for use Setup Create an ImgBB account and get your API key Add your ImgBB API key to the HTTP Request node (key parameter) Optional: Configure OpenAI credentials for image generation Connect your image input source How to Adjust it to Your Needs Skip OpenAI nodes if using your own image files Adjust image optimization parameters Customize image hosting settings Modify output format for your needs Made by Simon @ automake.io

What this template does This template uses GROQ LLAVA V1.5 7B API that offers fast inference for multimodal models with vision capabilities for understanding and interpreting visual data from images. . The users send a image and get a description of the image from the model. Setup Open the Telegram app and search for the BotFather user (@BotFather) Start a chat with the BotFather Type /newbot to create a new bot Follow the prompts to name your bot and get a unique API token Save your access token and username Once you set your bot, you can send the image, and get the descriptions.

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 template shows how anyone can build a simple newsletter-like subscription service where users can enrol themselves to receive messages/content on a regular basis. It uses n8n forms for data capture, Airtable for database, AI for content generation and Gmail for email sending. How it works An n8n form is setup up to allow users to subscribe with a desired topic and interval of which to recieve messages via n8n forms which is then added to the Airtable. A scheduled trigger is executed every morning and searches for subscribers to send messages for based on their desired intervals. Once found, Subscribers are sent to a subworkflow which performs the text content generation via an AI agent and also uses a vision model to generate an image. Both are attached to an email which is sent to the subscriber. This email also includes an unsubscribe link. The unsubscribe flow works similarly via n8n form interface which when submitted disables further scheduled emails to the user. How to use Make a copy of sample Airtable here: https://airtable.com/appL3dptT6ZTSzY9v/shrLukHafy5bwDRfD Make sure the workflow is "activated" and the forms are available and reachable by your audience. Requirements Airtable for Database OpenAI for LLM (but compatible with others) Gmail for Email (but can be replaced with others) Customising this workflow This simple use can be extended to deliver any types of content such as your company newsletter, promotions, social media posts etc. Doesn't have to be limited to just email - try social messaging, Whatsapp, Telegram and others.

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 Made by Simon @ automake.io

Enhance Security Operations with the Venafi Slack CertBot! Venafi Presentation - Watch Video Our Venafi Slack CertBot is strategically designed to facilitate immediate security operations directly from Slack. This tool allows end users to request Certificate Signing Requests that are automatically approved or passed to the Secops team for manual approval depending on the Virustotal analysis of the requested domain. Not only does this help centralize requests, but it helps an organization maintain the security certifications by allowing automated processes to log and analyze requests in real time. Workflow Highlights: Interactive Modals**: Utilizes Slack modals to gather user inputs for scan configurations and report generation, providing a user-friendly interface for complex operations. Dynamic Workflow Execution**: Integrates seamlessly with Venafi to execute CSR generation and if any issues are found, AI can generate a custom report that is then passed to a slack teams channel for manual approval with the press of a single button. Operational Flow: Parse Webhook Data**: Captures and parses incoming data from Slack to understand user commands accurately. Execute Actions**: Depending on the user's selection, the workflow triggers other actions within the flow like automatic Virustotal Scanning. Respond to Slack**: Ensures that every interaction is acknowledged, maintaining a smooth user experience by managing modal popups and sending appropriate responses. Setup Instructions: Verify that Slack and Qualys API integrations are correctly configured for seamless interaction. Customize the modal interfaces to align with your organization's operational protocols and security policies. Test the workflow to ensure that it responds accurately to Slack commands and that the integration with Qualys is functioning as expected. Need Assistance? Explore Venafi's Documentation or get help from the n8n Community for more detailed guidance on setup and customization. Deploy this bot within your Slack environment to significantly enhance the efficiency and responsiveness of your security operations, enabling proactive management of CSR's.

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.

🚀 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

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

Video Guide I prepared a detailed guide that showed the whole process of building an AI bot, from the simplest version to the most complex in a template. .png) Who is this for? This workflow is ideal for developers, chatbot enthusiasts, and businesses looking to build a dynamic Telegram bot with memory capabilities. The bot leverages OpenAI's assistant to interact with users and stores user data in Supabase for personalized conversations. What problem does this workflow solve? Many simple chatbots lack context awareness and user memory. This workflow solves that by integrating Supabase to keep track of user sessions (via What this workflow does This Telegram bot template connects with OpenAI to answer user queries while storing and retrieving user information from a Supabase database. The memory component ensures that the bot can reference past interactions, making it suitable for use cases such as customer support, virtual assistants, or any application where context retention is crucial. 1.Receive New Message: The bot listens for incoming messages from users in Telegram. Check User in Database: The workflow checks if the user is already in the Supabase database using the Create New User (if necessary): If the user does not exist, a new record is created in Supabase with the telegram_id and a unique Start or Continue Conversation with OpenAI: Based on the user’s context, the bot either creates a new thread or continues an existing one using the stored Merge Data: User-specific data and conversation context are merged. Send and Receive Messages: The message is sent to OpenAI, and the response is received and processed. Reply to User: The bot sends OpenAI’s response back to the user in Telegram. Setup Create a Telegram Bot using the Botfather and obtain the bot token. Set up Supabase: Create a new project and generate a Create a new table named create table public.telegram_users ( id uuid not null default gen_random_uuid (), date_created timestamp with time zone not null default (now() at time zone 'utc'::text), telegram_id bigint null, openai_thread_id text null, constraint telegram_users_pkey primary key (id) ) tablespace pg_default; OpenAI Setup: Create an OpenAI assistant and obtain the Customize your assistant’s personality or use cases according to your requirements. Environment Configuration in n8n: Configure the Telegram, Supabase, and OpenAI nodes with the appropriate credentials. Set up triggers for receiving messages and handling conversation logic. Set up OpenAI assistant ID in "++OPENAI - Run assistant++" node.

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

Fetches workflow definitions from within n8n, selecting only the ones that have one or more (configurable) assigned tags and then: Derives a suitable backup filename by reducing the workflow name to a string with alphanumeric characters and no-spaces Note: This isn't bulletproof, but works as long as workflow names aren't too crazy. Determines which workflows need to be backed up based on whether each one: has been modified. (Note: Even repositioning a node counts.) ...or... is new. (Note: Renaming counts as this.) Commits JSON copies of each workflow, as necessary, to a Gitlab repository with a generated, date-stamped commit message. Setup Credentials Create a Gitlab Credentials item and assign it to all Gitlab nodes. Create an n8n Credentials item and assign it to the n8n node Note: This was tested with http://localhost:5678/api/v1 but should work with any reachable n8n instance and API key. Modify these values in the "Globals" Node gitlab_owner - {{your gitlab account}} gitlab_project - {{ your gitlab project name }} gitlab_workflow_path - {{ subdirectory in the project where backup files should be saved/committed }} tags_to_match_for_backup - {{tag(s) to match for backup selection}} *ALERT: According to the n8n node's Filters -> tags field annotations, and API documentation, this supports a CSV list of multiple tags (e.g. tag1,tag2), but the API behavior requires workflows to have all-of the listed tags, not any-of them.* See: https://github.com/n8n-io/n8n/issues/10348 TL/DR - Don't expect a multiple tag list to be more inclusive. Possible workaround: To match more than one tag value, duplicate the n8n node into multiple single-tag matches, or split and iterate multiple values, and merge the results. Possible Enhancements Make the branch ("Reference") for all the gitlab nodes configurable. Fixed on all as "main" in the template. Add an n8n node to generate an audit and store the output in gitlab along with the backups. Extend the workflow at the end to create a Gitlab release/tag whenever any backup files are actually updated or created.

This template demonstrates how to trigger an AI Agent with Siri and Apple Shortcuts, showing a simple pattern for voice-activated workflows in n8n. It's easy to customize—add app nodes before the AI Agent step to pass additional context, or modify the Apple Shortcut to send inputs like text, geolocation, images, or files. Set Up Basic instructions in template itself. Requirements n8n account** (cloud or self-hosted) Apple Shortcuts app** on iOS or macOS. Dictation ("Siri") must be activated. Download the Shortcuts template here. Key Features: Voice-Controlled AI:** Trigger AI Agent via Siri for real-time voice replies. Customizable Inputs:** Modify Apple Shortcut to send text, images, geolocation, and more. Flexible Outputs:** Siri can return the AI’s response as text, files, or customize it to trigger CRUD actions in connected apps. Context-Aware:** Automatically feeds the current date and time to the AI Agent, with easy options to pass in more data. How It Works: Activate Siri and speak your request. Siri sends the transcribed text to the n8n workflow via Apple Shortcuts. AI Agent processes the request and generates a response. Siri reads the response, or the workflow can return geolocation, files, or even perform CRUD actions in apps. Inspiration: Custom Use Cases Tweak this template and make it your own. Capture Business Cards:** Snap a photo of a business card and record a voice note. Have the AI Agent draft a follow-up email in Gmail, ready to send. Voice-to-Task Automation:** Speak a new to-do item, and the workflow will add it to a Notion task board. Business English on the Fly:** Convert casual speech into polished business language, and save the refined text directly to your pasteboard, ready to be pasted into any app. "It's late because of you" -> "There has been a delay, and I believe your input may have contributed to it."

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.

Workflow updated on 17/06/2024:** Added 'Summarize' node to avoid creating a row for each Notion content block in the Supabase table.* Store Notion's Pages as Vector Documents into Supabase This workflow assumes you have a Supabase project with a table that has a vector column. If you don't have it, follow the instructions here: Supabase Langchain Guide Workflow Description This workflow automates the process of storing Notion pages as vector documents in a Supabase database with a vector column. The steps are as follows: Notion Page Added Trigger: Monitors a specified Notion database for newly added pages. You can create a specific Notion database where you copy the pages you want to store in Supabase. Node: Page Added in Notion Database Retrieve Page Content: Fetches all block content from the newly added Notion page. Node: Get Blocks Content Filter Non-Text Content: Excludes blocks of type "image" and "video" to focus on textual content. Node: Filter - Exclude Media Content Summarize Content: Concatenates the Notion blocks content to create a single text for embedding. Node: Summarize - Concatenate Notion's blocks content Store in Supabase: Stores the processed documents and their embeddings into a Supabase table with a vector column. Node: Store Documents in Supabase Generate Embeddings: Utilizes OpenAI's API to generate embeddings for the textual content. Node: Generate Text Embeddings Create Metadata and Load Content: Loads the block content and creates associated metadata, such as page ID and block ID. Node: Load Block Content & Create Metadata Split Content into Chunks: Divides the text into smaller chunks for easier processing and embedding generation. Node: Token Splitter

This n8n workflow is a fun way to query and search over your credentials on your n8n instance. Good to know Your credentials should remain safe as this workflow does not decrypt or use any decrypted data. Example Usage "Which workflows are using Slack and Google Calendar?" "Which workflows have AI in their name but are not using openAI?" How it works Using the n8n API, it fetches all workflow data on the instance. Workflow data contains references to credentials used so this will be extracted. With some necessary reformatting, the workflows and their credentials metadata are stored to a SQLite database. Next, an AI agent is used with a custom SQL tool that reads the SQLite database created in the previous step. The AI agent is instructed to perform SQL queries against our workflow credential table when asked about credentials by the user. Requirements You'll need an n8n API key. Please note that only workflows will be scoped to your API key. Customising the workflow Add extra table fields to the SQLite database to answer even more complex queries such as: workflow status to differentiate between active and inactive workflows.

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 for? BlueSky users looking to automate the publication of new posts based on new items from a RSS feed. What this workflow does This will create a BlueSky post with each new RSS feed item, including the feed title, post image, link and content (up to 200 characters) Setup You'll need to generate a BlueSky app password Configure your feed URL in the first node Configure your credentials in the second node How to customize this workflow to your needs You can modify the message posted in the `Create post node, changing the JSON text` value, in case you want to include only the feed item title instead of the content. If you RSS feed doesn't provide an image, you can define a static one on the `Download image` node.

Sync your Google Sheets Data with your Postgres database table, requiring minimal adjustments. Follow these steps: Retrieve Data: Pull data from Google Sheets and PostgreSQL. Compare Datasets: Identify differences, focusing on new or updated entries. Update PostgreSQL: Apply changes to ensure both platforms mirror each other. Automate this process to regularly synchronize data. Before starting, grant necessary access to both Google Sheets and PostgreSQL, and specify the data details for synchronization. This streamlined workflow enhances data consistency across platforms. This example is a one-way synchronization from Google Sheets into your Postgres. With small adjustments, you can make it the other way around, or 2-way.

This template can be used to verify an email address with Icypeas. Be sure to have an active account to use this template. How it works This workflow can be divided into three steps : The workflow initiates with a manual trigger (On clicking 'execute'). It connects to your Icypeas account. It performs an HTTP request to verify an email address. Set up steps You will need a working icypeas account to run the workflow and get your API Key, API Secret and User ID. You will need an email address to perform the verification.

Purpose This ensures that executions of scheduled workflows do not overlap when they take longer than expected. How it works This is a separate workflow which monitors the execution of the main workflow Stores a flag in Redis (key dynamically named after workflow ID) which indicates if the main workflow is running or idle Only calls the main workflow if the last execution has finished Setup Update the credentials suitable for your Redis instance Replace the Schedule Trigger of your main workflow by an Execute Workflow Trigger Copy the workflow ID from the URL Paste the workflow ID in the Execute Workflow Node of this workflow Configure the Schedule Trigger Node

Use Case Automatically archive emails in your Gmail inbox from the last day, unless they have been starred. Been using this with my personal and work emails to stick to an Inbox Zero strategy, without having to click or swipe a lot. Setup Add your Gmail creds How to adjust this template Set your own schedule for when to run this. Otherwise, should be good to go. 🤞🏽

This workflow automatically generates draft replies in Gmail. It's designed for anyone who manages a high volume of emails or often face writer's block when crafting responses. Since it doesn't send the generated message directly, you're still in charge of editing and approving emails before they go out. How It Works: Email Trigger: activates when new emails reach the Gmail inbox Assessment: uses OpenAI gpt-4o and a JSON parser to determine if a response is necessary. Reply Generation: crafts a reply with OpenAI GPT-4 Turbo Draft Integration: after converting the text to html, it places the draft into the Gmail thread as a reply to the first message Set Up Overview (~10 minutes): OAuth Configuration (follow n8n instructions here): Setup Google OAuth in Google Cloud console. Make sure to add Gmail API with the modify scope. Add Google OAuth credentials in n8n. Make sure to add the n8n redirect URI to the Google Cloud Console consent screen settings. OpenAI Configuration: add OpenAI API Key in the credentials Tweaking the prompt: edit the system prompt in the "Generate email reply" node to suit your needs Detailed Walkthrough Check out this blog post where I go into more details on how I built this workflow. Reach out to me here if you need help building automations for your business.

Use case If you have a form where potential leads reach out, then you probably want to analyze those leads and send a notification if certain requirements are met, e.g. employee number is high enough. MadKudu is built exactly to solve this problem. We use it along with Hunter and Gmail to get an email alert for high quality leads. How to setup Add you MadKudu, Hunter, and Gmail credentials Set the email to send to Click the Test Workflow button, enter your email and check your email Activate the workflow and use the form trigger production URL to collect your leads in a smart way How to adjust this template You may want to raise or lower the threshold for your leads, as you see fit.

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.

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.

This n8n workflow demonstrates how to automate customer interactions and appointment management via WhatsApp Business bot. After submitting a Google Form, the user receives a notification via WhatsApp. These notifications are sent via a template message. In case user sends a message to the bot, the text and user data is stored in Google Sheets. To reply back to the user, fill in the ReplyText column and change the Status to 'Ready'. In a few seconds n8n will fetch the unsent replies and deliver them one by one via WhatsApp Business node. Customize this workflow to fit your specific needs, connect different online services and enhance your customer communication! 🎉 Setup Instructions To get this workflow up and running, you'll need to: 👇 Create a WhatsApp template message on the Meta Business portal. Obtain an Access Token and WhatsApp Business Account ID from the Meta Developers Portal. This is needed for the WhatsApp Business Node to send messages. Set up a WhatsApp Trigger node with App ID and App Secret from the Meta Developers Portal. Right after that copy the WhatsApp Trigger URL and add it as a Callback URL in the Meta Developers Portal. This trigger is needed to receive incoming messages and their status updates. Connect your Google Sheets account for data storage and management. Check out the documentation page. ⚠️ Important Notes WhatsApp allows automatic custom text messages only within 24 hours of the last user message. Outside with time frame only approved template messages can be sent. The workflow uses a Google Sheet to manage form submissions, incoming messages and prepare responses. You can replace these nodes and connect the WhatsApp bot with other systems.

Automated YouTube Video Promotion Workflow Automate the promotion of new YouTube videos on X (formerly Twitter) with minimal effort. This workflow is perfect for content creators, marketers, and social media managers who want to keep their audience updated with fresh content consistently. How it works This workflow triggers every 30 minutes to check for new YouTube videos from a specified channel. If a new video is found, it utilizes OpenAI's ChatGPT to craft an engaging, promotional message for X. Finally, the workflow posts the generated message to Twitter, ensuring your latest content is shared with your audience promptly. Set up steps Schedule the workflow to run at your desired frequency. Connect to your YouTube account and set up the node to fetch new videos based on your Channel ID. Integrate with OpenAI to generate promotional messages using GPT-3.5 turbo. Link to your X account and set up the node to post the generated content. Please note, you'll need API keys and credentials for YouTube, OpenAI, and X. Check out this quick video tutorial to make the setup process a breeze. Additional Tips Customize the workflow to match your branding and messaging tone. Test each step to ensure your workflow runs smoothly before going live.

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.

This n8n workflow was developed to evaluate and categorize incoming leads based on certain criteria. The workflow is triggered by adding a new row in a Google Sheets document. The workflow uses the OpenAI node to process the lead information. The system query contains detailed qualification rules and the response format. The user message contains the data for the individual lead. The JSON response from the OpenAI node is then processed by the Edit Fields node to extract the response. This response is merged together with the original lead data by the Merge node. Finally, the Google Sheets node updates the original lead entry in the Google Sheets document with the qualification result ("qualified" or "not qualified") in a separate column. This allows for easy tracking and sorting of the qualified leads.

Who is this template for? This workflow template is designed for Sales and Customer Success professionals seeking alerts when potential high-value users, prospects, or existing customers register for a Discourse community. Leveraging Clearbit, it retrieves enriched data for the new member to assess their value. Example result in Slack How it works Each time a new member is created in Discourse, the workflow runs (powered by Discourse's native Webhooks feature). After filtering out popular private email accounts, we run the member's email through Clearbit to fetch available information on the member as well as their organization. If the enriched data meets certain criteria, we send a Slack message to a channel. This message has a few quick actions: Open LinkedIn profile and Email member Set up instructions Overview is below. Watch this 🎥 quick set up video for detailed instructions on how to get the template running, as well as how to customize it. Complete the Set up credentials step when you first open the workflow. You'll need a Discourse (admin user), Clearbit, and Slack account. Set up the Webhook in Discourse, linking the On new Discourse user Trigger with your Discourse community. Set the correct channel to send to in the Post message in channel step After testing your workflow, swap the Test URL to Production URL in Discourse and activate your workflow Template was created in n8n v1.29.1

Who is this template for? This workflow template is designed for Marketing and pre-Sales to get prospects from a form like Tally, decline data in the famous opensource CRM (SuiteCRM), synchronize contact in Brevo with linking the id from CRM, and then notify in NextCloud. Bonus : validate email with ++CaptainVerify++ and notify in NextCloud depending on response How it works For each submission in the form, a webhook is triggered. A check of the email is done with CaptainVerify. Depending on the response, and if it is ok, then a Lead is created in SuiteCRM. Else, a message in your selected discussion is sent. As the lead has been created, we can create a contact in Brevo (for future campain), ank link this contact with the lead_id from the CRM in a dedicated field. Finaly, a message in your selected discussion in NextCloud informs you about the lead. Set up instructions Complete the Set up credentials step when you first open the workflow. You'll need a CaptainVerify account (Api Key), a dedicated SuiteCRM user with Oauth, a Brevo account (Api Key) and a Nextcloud account. Set up the Webhook in the form's tool of your choice (why not Tally ?). Set each node with the explanations in sticky Notes. Enjoy ! Template was created in n8n v1.44.1

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.

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.

Purpose of workflow: The purpose of this workflow is to create an AI-powered technical analysis agent capable of analyzing financial charts, specifically for cryptocurrencies like Bitcoin or equity stocks. This agent provides users with insights into market trends, price movements, and technical indicators to assist in making informed trading decisions. How it works: The agent uses the Sonnet model from Anthropic for LLM It integrates with TradingView charts through the chart-img.com API to generate and download financial charts. The agent analyzes the chart using AI vision capabilities, examining candlestick patterns, pricing trends, and technical indicators like Relative Strength Index (RSI) and Directional Movement Index (DMI). It provides a detailed analysis of the chart, including support and resistance levels, market trends, and volume analysis. The agent generates a visual representation of the analysis, displaying candlesticks, volume, RSI, and DMI. Step by step setup: Create free API key from chart-img.com Set the exchange for the ticker (defaults to NYSE) Tutorial

How it works: Webhook URL that responds to Requests with an AI generated Image based on the prompt provided in the URL. Setup Steps: Ideate your prompt URL Encode The Prompt (as shown in the Template) Authenticate with your OpenAI Credentials Put together the Webhook URL with your prompt and enter into a webbrowser In this way you can expose a public url to users, employee's etc. without exposing your OpenAI API Key to them. Click here to find a blog post with additional information.

This automated workflow takes a Typeform form, and once it is filled out, it is automatically uploaded as a Lead in Pipedrive. There is an option for custom fields (this workflow works with company size), and leaves notes in the note section based on questions answered. Prerequisites Typeform account and Typeform credentials and a form for people to fill out Pipedrive account and Pipedrive credentials Nodes Typeform node gets the data after the survey is completed Set node extracts data from the Typeform node and keeps only relevant data Function node maps the company size Pipedrive node populates a pipeline with a deal and adds custom fields

Use case Error workflows are an important part of running workflows in production. Get alerts for errors directly in your inbox. How to setup Add your Gmail creds Add your target email Add this error workflow to other workflows docs here

Create new Clickup Tasks from Slack commands This workflow aims to make it easy to create new tasks on Clickup from normal Slack messages using simple slack command. For example We can have a slack command as /newTask Set task to update new contacts on CRM and assign them to the sales team This will have an new task on Clickup with the same title and description on Clickup For most teams, getting tasks from Slack to Clickup involves manually entering the new tasks into Clickup. What if we could do this with a simple slash command? Step 1 The first step is to Create an endpoint URL for your slack command by creating an events API from the link [below] https://api.slack.com/apps/) STEP 2 Next step is defining the endpoint for your URL Create a new webhook endpoint from your n8n with a POST and paste the endpoint URL to your event API. This will send all slash commands associated with the Slash to the desired endpoint Step 3 Log on to slack API (https://api.slack.com/) and create an application. This is the one we use to run all automation and commands from Slack. Once your app is ready, navigate to the Slash Commands and create a new command This will include the command, the webhook URL and a description of what the slash command is all about Now that this is saved you can do a test by sending a demo task to your endpoint Once you have tested the webhook slash command is working with the webhook, create a new Clickup API that can be used to create new tasks in ClickUp This workflow creates a new task with the start dates on Clikup that can be assigned to the respective team members More details about the document setup can be found on this document below Happy Productivity

Product Introduction: You can create a form on n8n through which you can collect leads from interested user's. You can also verify each user's email address to validate whether it's a valid email to make sure it lands on their inbox(suitable for those who have newletter / want's to send bulk email) The leads with valid email will then get saved as a leads with the relevant field data to gmail, google sheets and discord(through webhook). You can add/remove any integration you feel like. Setup Guide: Create Your Form: Begin by logging into your n8n account and navigating to the workflow editor. You can then customize your form fields to gather relevant information from your prospects, such as name, email address, and any additional data you require. Email Verification: After collecting the lead data, add an Email Verification node to validate each user's email address. This crucial step ensures that only genuine and deliverable email addresses are included in your lead database, maximizing the effectiveness of your outreach efforts. We have used hunter.io service in this, you can change it to any other service you need. Save Leads: Next, incorporate nodes to save your verified leads to various platforms for streamlined management. Utilize the Gmail node to store lead information directly in your Gmail account, ensuring easy access and organization. Additionally, leverage the Google Sheets node to archive lead data in a spreadsheet for comprehensive tracking and analysis. Integrate with Discord: For real-time notifications and collaboration, integrate n8n with Discord using the Webhook node. Configure the webhook to send lead information to your designated Discord channel, enabling your team to stay informed and coordinate effectively. Customize Integrations: Tailor your workflow by adding or removing integrations based on your specific requirements. Whether you prefer to connect with additional platforms or streamline your workflow further, n8n offers unparalleled flexibility to adapt to your business needs. Experience the simplicity and efficiency of n8n to revolutionize your lead generation strategy and propel your success to new heights.

What this workflow does This (set of) workflow(s) shows how to start multiple sub-workflows, asynchronously, in parallel, and then wait for all of them to complete. Normally sub-workflows would need to be run synchronously, in series, or, if they are executed asynchronously (to run concurrently, in parallel), there is no easy way to merge/wait for an arbitrary number of them to complete. This is a "design pattern" template to show one approach for running multiple, data-driven instances of a sub-workflow "asynchronously," in parallel (instead of running them one at a time in series), but still prevent the later steps in the workflow from continuing until all of the sub-workflows have reported back that they are finished, via callback URL. There are other techniques involving messaging services, database tables, or other external "flow manager" helpers, but this technique accomplishes the goal fully within n8n. Setup To implement this pattern, examine the nodes in the template and modify the incoming data leading to: A split-out loop to acynchronously execute a sub-workflow multiple times, in parallel. For instance, each sub-workflow might process one of a list of incoming documents. The resumeUrl for the main/parent workflow is provided to all of the sub-workflow executions, along with a unique identifier that can be counted later (e.g. a document file-name). A "wait-for-all" loop that checks whether all sub-workflows have reported back (if node) and builds a unique list of identifiers from the callbacks received from each execution of the sub-workflow. The sub-workflow should be designed to respond immediately (async) and later send a callback request when it has finished processing. The callback request should include the unique identifier value received when the sub-workflow it was started. This is meant to be a possible answer to questions like this one about running things in parallel, maybe this one about waiting for things to finish, this one about managing sub-batches of things by waiting for each batch, or this one about running things in parallel. The topic of how to do this comes up A LOT, and this is one of the only techniques that (so far) seems to work.

🎉 Do you want to master AI automation, so you can save time and build cool stuff? I’ve created a welcoming Skool community for non-technical yet resourceful learners. 👉🏻 Join the AI Atelier 👈🏻 This is probably the most straightforward way to schedule your tweets. This n8n workflow addresses a simple problem: how to maintain consistency in your publications on X. 📋 Blog post 📺 Youtube Video The workflow is direct and to the point. In a Google spreadsheet, write all your tweets, one tweet per line. Then, at a defined pace (for example, every 6 hours), the workflow will publish the first tweet from the list on your X account and remove it from the sheet. This method is really simple but very efficient if you are looking for a direct and super fast solution to share regularly on X! Created by the n8ninja.

Free template for voice & text messages with short-term memory This n8n workflow template is a blueprint for an AI Telegram bot that processes both voice and text messages. Ready to use with minimal setup. The bot remembers the last several messages (10 by default), understands commands and provides responses in HTML. You can easily swap GPT-4 and Whisper for other language and speech-to-text models to suit your needs. Core Features Text: send or forward messages Voice: transcription via Whisper Extend this template by adding LangChain tools. Requirements Telegram Bot API OpenAI API (for GPT-4 and Whisper) 💡 New to Telegram bots? Check our step-by-step guide on creating your first bot and setting up OpenAI access. Use Cases Personal AI assistant Customer support automation Knowledge base interface Integration hub for services that you use: Connect to any API via HTTP Request Tool Trigger other n8n workflows with Workflow Tool

Overview This workflow takes some French text, and translates it into spoken audio. It then transcribes that audio back into text, translates it into English and generates an audio file of the English text. To do so, it uses ElevenLabs (which has a free tier) and OpenAI. Setup These steps should only take a few minutes: In ElevenLabs, add a voice to your voice lab and copy its ID. Add it to the 'Set voice ID' node Get your ElevenLabs API key (click your name in the bottom-left of ElevenLabs and choose ‘profile’) In the 'Generate French audio' node, create a new header auth cred. Set the name to xi-api-key and the value to your API key In the 'credential' field of the 'Transcribe audio' node, create a new OpenAI cred with your OpenAI API key Run the workflow by clicking the orange button at the bottom of the canvas

📦 Send Telegram Notifications for New WooCommerce Orders This workflow automatically sends a Telegram notification when an order status in WooCommerce changes to "Processing." Perfect for online store owners who want instant updates on order fulfillment. ⚙️ Set Up Telegram Alerts for WooCommerce Orders Configure WooCommerce Webhook to trigger on order updates. Create a Telegram Bot and obtain the API token. Set Up Telegram Credentials in n8n. Configure the Telegram Node with your chat ID. Activate and Test the workflow by placing a new order. ##💡 Notes You can customize the message format in the 🖋️ Design Message Template node to include additional order details. Contact me on [Telegram]: https://t.me/amir676080 Message structure includes the following details 🆔 Order Number: 11234 👦🏻 Customer Name: John Doe 💵 Amount: 299.99 USD 📅 Order Date: ➖ 25th November 2024 at 14:42 🏙 City: New York 📞 Phone: +1 555-1234 ✍🏻 Order Note: Fast delivery requested 📦 Ordered Products: 🔹 Wireless Earbuds (2 items) 📝 Type: Premium Sound Edition Contact me on [Telegram]: https://t.me/amir676080

This n8n workflow demonstrates creating a recipe recommendation chatbot using the Qdrant vector store recommendation API. Use this example to build recommendation features in your AI Agents for your users. How it works For our recipes, we'll use HelloFresh's weekly course and recipes for data. We'll scrape the website for this data. Each recipe is split, vectorised and inserted into a Qdrant Collection using Mistral Embeddings Additionally the whole recipe is stored in a SQLite database for later retrieval. Our AI Agent is setup to recommend recipes from our Qdrant vector store. However, instead of the default similarity search, we'll use the Recommendation API instead. Qdrant's Recommendation API allows you to provide a negative prompt; in our case, the user can specify recipes or ingredients to avoid. The AI Agent is now able to suggest a recipe recommendation better suited for the user and increase customer satisfaction. Requirements Qdrant vector store instance to save the recipes Mistral.ai account for embeddings and LLM agent Customising the workflow This workflow can work for a variety of different audiences. Try different sets of data such as clothes, sports shoes, vehicles or even holidays.

This n8n workflow assists property managers and surveyors by reducing the time and effort it takes to complete property inventory surveys. In such surveys, articles and goods within a property may need to be captured and reported as a matter of record. This can take a sizable amount of time if the property or number of items is big enough. Our solution is to delegate this task to a capable AI Agent who can identify and fill out the details of each item automatically. How it works An AirTable Base is used to capture just the image of an item within the property Our workflow monitoring this AirTable Base sends the photo to an AI image recognition model to describe the item for purpose of identification. Our AI agent uses this description and the help of Google's reverse image search in an attempt to find an online product page for the item. If found, the product page is scraped for the item's specifications which are then used to fill out the rest of the details of the item in our Airtable. Requirements Airtable for capturing photos and product information OpenAI account to for image recognition service and AI for agent SerpAPI account for google reverse image search. Firecrawl.dev account for webspacing. Customising this workflow Try building an internal inventory database to query and integrate into the workflow. This could save on costs by avoiding fetching new each time for common items.

I am submitting this workflow for the Obsidian community to showcase the potential of integrating Obsidian with n8n. While straightforward, it serves as a compelling demonstration of the potential unlocked by integrating Obsidian with n8n. How it works This workflow lets you retrieve specific Airtable data you need in seconds, directly within your Obsidian note, using n8n. By highlighting a question in Obsidian and sending it to a webhook via the Post Webhook Plugin, you can fetch specific data from your Airtable base and instantly insert the response back into your note. The workflow leverages OpenAI’s GPT model to interpret your query, extract relevant data from Airtable, and format the result for seamless integration into your note. Set up steps Install the Post Webhook Plugin: Add this plugin to your Obsidian vault from the plugin store or GitHub. Set up the n8n Webhook: Copy the webhook URL generated in this workflow and insert it into the Post Webhook Plugin's settings in Obsidian. Configure Airtable Access: Link your Airtable account and specify the desired base and table to pull data from. Test the Workflow: Highlight a question in your Obsidian note, use the “Send Selection to Webhook” command, and verify that data is returned as expected.

This workflow will allow you to use OpenAI Assistant API together with a chatting platform. This version is configured to work with Hubspot, however, the Hubspot modules can be replaced by other platform and it will work similarly. Prerequisites: Create a Hubspot Chat (Live chat available on free plan) or Chatflow (paid hubspot only) and configure it to send all replies toward an n8n webhook (you need to create a custom app for that. I will create a separate article on how to do it, meanwhile, feel free to message me if you need support. Setup: Create a OpenAI Assistant, define its functionality and functions Update the Hubspot modules with the Hubspot API Key Update the OpenAI modules with OpenAI API Key Create an Airtable or any other database where you keep a reference between the thread id in Hubspot and Assistant API If you need help deploying this solution don't hesitate to email me or schedule a call here.

Who is this template for? This template is for everyone who has to take notes during a call: Talent Acquisition Managers / Talent Acquisition Specialists / Recruiters HR professionals Sales teams, customer success teams Product teams / User Experience Designers / anyone conducting user research interviews Use case This workflow allows specific events created on Google Calendar (or any other meeting scheduling tool like Calendly) to trigger the duplication and renaming of a specific template document. Example: For each new screening call that is scheduled in your calendar, you want to create a draft of your screening interview template for the role, titled "{Name of the candidate} | {Date of the interview}", and located in your Google Drive in a specific folder This workflow could then be extended to copy the link to the file on a Notion database that is shared with the team (check "To go further" section). This workflow ensures that if you're jumping from calls to calls, you're already set up to take notes, and every document is tidied up and sorted in a structured way! How it works The workflow starts when a new event is created in Google Calendar The Filter node then selects a specific type of events, depending on a chosen pattern (title includes a specific term, organizer is X, attendees include Y, etc.) The workflow then searches for a specific folder in your Google Drive, where the file you want to duplicate is located The workflow then searches for the specific file you want to duplicate The last step allows to duplicate and rename the file with variables from your Google Calendar event Set up Set up credentials for Google Calendar, Google Drive, and Google File. You'll need a Google Workspace account. Set up the Filter node with the pattern you want to look for to retreive specific events in your calendar Set up the Google Drive you want to search in Set up the Google File you want to duplicate Set up variable at the last step to rename your duplicated file however you want it, or add a description To go further Here's a few idea to enhance this workflow depending on your specific needs: Instead of a filter, separate your flow depending on your use case (ex: you have want to fetch different templates depending on the type of call it'll be). Switch Google Calendar for another trigger (Calendly, Hubspot..) 10 minutes before the event, send the duplicate Google File to the meeting organizer through Slack The day after the event, if the event hasn't been cancelled, add the link to the Google File to your ATS, Hubspot, etc.

With this workflow you can extract data from resume documents uploaded via a Telegram bot. Workflow transform readable content of PDF resume into structured data, using AI nodes and returns PDF with formatted, plain HTML. You can modify this workflow to perform other actions with structured data (e.g. insert it into database or create other, well-formatted documents). Functionality of this workflow was presented during the n8n community call on March 7, 2024 - recording of presentation available here. ⚠️ Workflow made for demo purposes. If you want to use it in real life, please make sure necessary measures for personal data protection are set. How it works? User uploads readable PDF resume document into Telegram bot. After authentication based on chat ID parameter, workflow extracts text from the PDF and transfers it into AI chain with connected sub-nodes: OpenAI Chat Model and Structured Output (JSON) Parser. Then, each extracted section (employment history, projects etc.) is formatted into desired HTML structure. Finally, the document is converted into new, structured PDF using Gotenberg. 💡 This workflow requires installed Gotenberg. If you are not familiar with this software, please have a look on my YouTube tutorial. You can also replace call to Gotenberg with other PDF generation service (such as PDFMonkey or ApiTemplate). Set up steps Create Telegram bot and add its credentials in n8n. Set your chat ID parameter in Auth node. Adjust JSON schema in Structured Output Parser according to your needs. Optionally: replace HTTP call to Gotenberg with PDF generation service of your choice. If you like this workflow, please subscribe to my YouTube channel and/or my newsletter.

How it works? This workflows sends you a monthly lists of live music events for a specific location. Events are fetched from songkick.com and delivered to you by email to a provided email address(es). Each event in the list has a link to a full SongKick page where you can see more details about the event and buy tickets for it. Example email: How to set it up? First thing that this workflow needs is a location link for your desired city from the SongKick website. You can get it by following these steps: Visit songkick.com and enter the city name in the search box: From the results page, click the result that contains the location info. These will have the Location tag on top of the location name: Once on the location page, copy the url Back in the n8n workflow page, paste the url in the location parameter of the node called Setup location and email: Second thing it needs is the email address which will receive the monthly list. For this, simply enter it in the email field of the Setup location and email node. If you want to set multiple receivers, simply separate email addresses by ,: Required accounts This workflow requires you to have a properly set up Gmail account that will be used by Gmail Node to send emails. You can read more about how to create credentials for a Gmail node in n8n documentation here.

This workflow shows a low code approach to parsing an XML file and storing its contents in a Google Sheets spreadsheet. To run the workflow: Make sure you are running n8n 0.197 or newer Have n8n authenticated with Google Sheets How it's done: This workflow first downloads an example file using the HTTP Request node and reads this file using the XML node. It then runs the Item Lists node to split out the individual food items from the example file. It then splits up the workflow into a separate branch creating a new spreadsheet file using the Google Sheets node. To read the column names we're using the Object.keys() method inside a Set node. Once the spreadsheet is created (the workflow waits for this using the Merge node), the data is appended to the newly created sheet (again using the Google Sheets node).

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!

This workflow is designed for dynamic and intelligent conversational capabilities. It incorporates OpenAI's GPT-4o model for natural language understanding and generation. Additional tools include SerpAPI and Wikipedia for enriched, data-driven responses. The workflow is triggered manually, and utilizes a 'Window Buffer Memory' to maintain the context of the last 20 interactions for better conversational continuity. All these components are orchestrated through n8n nodes, ensuring seamless interconnectivity. To use this template, you need to be on n8n version 1.50.0 or later.

This workflow is a experiment to build HTML pages from a user input using the new Structured Output from OpenAI. How it works: Users add what they want to build as a query parameter The OpenAI node generate an interface following a structured output defined in the body The JSON output is then converted to HTML along with a title The HTML is encapsulated in an HTML node (where the Tailwind css script is added) The HTML is rendered to the user via the Webhook response. Set up steps Create an OpenAI API Key Create the OpenAI credentials Use the credentials for both nodes HTTP Request (as Predefined Credential type) and OpenAI Activate your workflow Once active, go to the production URL and add what you'd like to build as the parameter "query" Example: https://production_url.com?query=a%20signup%20form Example of generated page

This n8n workflow builds an appointment scheduling AI agent which can Take enquiries from prospective customers and help them book an appointment by checking appointment availability Where no appointment is booked, the Agent is able to send follow-up messages to re-engage leads. After an appointment is booked, the agent is able reschedule or even cancel the booking for the user without human intervention. For small outfits, this workflow could contribute the necessary "man-power" required to increase business sales. The sample Airtable can be found here: https://airtable.com/appO2nHiT9XPuGrjN/shroSFT2yjf87XAox 2024-10-22 Updated to Cal.com API v2. How it works The customer sends an enquiry via SMS to trigger our workflow. For this trigger, we'll use a Twilio webhook. The prospective or existing customer's number is logged in an Airtable Base which we'll be using to track all our enquries. Next, the message is sent to our AI Agent who can reply to the user and decide if an appointment booking can be made. The reply is made via SMS using Twilio. A scheduled trigger which runs every day, checks our chat logs for a list of prospective customers who have yet to book an appointment but still show interest. This list is sent to our AI Agent to formulate a personalised follow-up message to each lead and ask them if they want to continue with the booking. The follow-up interaction is logged so as to not to send too many messages to the customer. Requirements A Twilio account to receive customer messages. An Airtable account and Base to use as our datastore for enquiries. Cal.com account to use as our scheduling service. OpenAI account for our AI model. Customising this workflow Not using Airtable? Swap this out for your CRM of choice such as hubspot or your own service. Not using Cal.com? Swap this out for API-enabled services such as Acuity Scheduling or your own service.

This n8n template builds upon a simple appointment request form design which uses AI to qualify if the incoming enquiry is suitable and/or time-worthy of an appointment. This demonstrates a lighter approach to using AI in your templates but handles a technically difficult problem - contextual understanding! This example can be used in a variety of contexts where figuring out what is and isn't relevant can save a lot of time for your organisation. How it works We start with a form trigger which asks for the purpose of the appointment. Instantly, we can qualify this by using a text classifier node which uses AI's contextual understanding to ensure the appointment is worthwhile. If not, an alternative is suggested instead. Multi-page forms are then used to set the terms of the appointment and ask the user for a desired date and time. An acknowledgement is sent to the user while an approval by email process is triggered in the background. In a subworkflow, we use Gmail with the wait for approval operation to send an approval form to the admin user who can either confirm or decline the appointment request. When approved, a Google Calendar event is created. When declined, the user is notified via email that the appointment request was declined. How to use Modify the enquiry classifier to determine which contexts are relevant to you. Configure the wait for approval node to send to an email address which is accessible to all appropriate team members. Requirements OpenAI for LLM Gmail for Email Google Calendar for Appointments Customising this workflow Not using Google Mail or Calendar? Feel free to swap this with other services. The wait for approval step is optional. Remove if you wish to handle appointment request resolution in another way.

This n8n workflow verifies the deliverability of mailing addresses stored in HighLevel by integrating with Lob's address verification service. Who is this for? This template is designed for HighLevel users who need to ensure the accuracy of mailing addresses stored in their CRM systems. What problem is this workflow solving? / Use Case This workflow addresses the challenge of maintaining accurate mailing addresses in CRM databases by verifying the deliverability of addresses. What this workflow does A new contact is created in HighLevel Webhook sent to n8n Verify if the address is deliverable via LOB Report back to HighLevel Set Up Steps Watch this setup video: https://www.youtube.com/watch?v=T7Baopubc-0 Takes 10-30 minutes to set up Accounts Needed: HighLevel LOB Account (https://www.lob.com $0.00/mo 300 US addresses Verifications) n8n Before using this template, ensure you have API keys for your HighLevel app and Lob. Set up authentication for both services within n8n. How to customize this workflow to your needs You can customize this workflow by adjusting the trigger settings to match HighLevel's workflow configuration. Additionally, you can modify the actions taken based on the deliverability outcome, such as updating custom fields or sending notifications.

This workflow automates daily LinkedIn posts using Notion. It starts by fetching the day's post from a Notion database, processes and formats the content, including images, then publishes it on LinkedIn. Finally, it updates the post status in the Notion database. Set up Notion and LinkedIn credentials as required.

Who is this for? This workflow is designed for businesses or developers looking to integrate voice-based chat applications with dynamic responses and conversational memory. What problem does this solve? It automates AI-powered voice conversations, maintaining context between sessions and converting speech-to-text and text-to-speech. What this workflow does: The workflow receives audio input, transcribes it using OpenAI, and processes the conversation using Google Gemini Chat Model (you can use OpenAI Chat Model). Responses are converted back to speech using ElevenLabs. Prerequisites: You'll need API keys for: OpenAI (you can obtain it from OpenAI website) ElevenLabs (you can obtain it from their website) Google Gemini (You can obtain it from Google AI Studio) Setup: Configure you API keys Ensure that the value (voice_message) in the "Path" parameter in the Webhook node is used as the name of the parameter that will contain the voice message you are sending via the HTTP Post request.

Who is this for? This workflow is designed for: Database administrators and developers working with MongoDB Content managers handling movie databases Organizations looking to implement AI-powered search and recommendation systems Developers interested in combining LangChain, OpenAI, and MongoDB capabilities What problem does this workflow solve? Traditional database queries can be complex and require specific MongoDB syntax knowledge. This workflow addresses: The complexity of writing MongoDB aggregation pipelines The need for natural language interaction with movie databases The challenge of maintaining user preferences and favorites The gap between AI language models and database operations What this workflow does This workflow creates an intelligent agent that: Accepts natural language queries about movies Translates user requests into MongoDB aggregation pipelines Queries a movie database containing detailed information including: Plot summaries Genre classifications Cast and director information Runtime and release dates Ratings and awards Provides contextual responses using OpenAI's language model Allows users to save favorite movies to the database Maintains conversation context using a window buffer memory Setup Required Credentials: OpenAI API credentials MongoDB connection details Node Configuration: Configure the MongoDB connection in the MongoDBAggregate node Set up the OpenAI Chat Model with your API key Ensure the webhook trigger is properly configured for receiving chat messages Database Requirements: A MongoDB collection named "movies" with the specified document structure Proper indexes for efficient querying Appropriate user permissions for read/write operations How to customize this workflow Modify the Document Structure: Update the tool description in the MongoDBAggregate node to match your collection schema Adjust the aggregation pipeline templates for your specific use case Enhance the AI Agent: Customize the prompt in the "AI Agent - Movie Recommendation" node Modify the window buffer memory size based on your context needs Add additional tools for more functionality Extend Functionality: Add more MongoDB operations beyond aggregation Implement additional workflows for different types of queries Create custom error handling and validation Add user authentication and rate limiting Integration Options: Connect to external APIs for additional movie data Add webhook endpoints for different platforms Implement caching mechanisms for frequent queries Add data transformation nodes for specific output formats This workflow serves as a foundation that can be adapted to various use cases beyond movie recommendations, such as e-commerce product search, content management systems, or any scenario requiring intelligent database interaction.

Template Description This n8n workflow template allows you to create a masked email address using the Fastmail API, triggered by a webhook. This is especially useful for generating disposable email addresses for privacy-conscious users or for testing purposes. Workflow Details: Webhook Trigger: The workflow is initiated by sending a POST request to a specific webhook. You can include state and description in your request body to customize the masked email's state and description. Session Retrieval: The workflow makes an HTTP request to the Fastmail API to retrieve session information. It uses this data to authenticate further requests. Create Masked Email: Using the retrieved session data, the workflow sends a POST request to Fastmail's JMAP API to create a masked email. It uses the provided state and description from the webhook payload. Prepare Output: Once the masked email is successfully created, the workflow extracts the email address and attaches the description for further processing. Respond to Webhook: Finally, the workflow responds to the original POST request with the newly created masked email and its description. Requirements: Fastmail API Access**: You will need valid API credentials for Fastmail configured with HTTP Header Authentication. Authorization Setup**: Optionally set up authorization if your webhook is exposed to the internet to prevent misuse. Custom Webhook Request**: Use a tool like curl or create a shortcut on macOS/iOS to send the POST request to the webhook with the necessary JSON payload, like so: curl -X POST -H 'Content-Type: application/json' https://your-n8n-instance/webhook/87f9abd1-2c9b-4d1f-8c7f-2261f4698c3c -d '{"state": "pending", "description": "my mega fancy masked email"}' This template simplifies the process of integrating masked email functionality into your projects or workflows and can be extended for various use cases. Feel free to use the companion shortcut I've also created. Please update the authorization header in the shortcut if needed. https://www.icloud.com/shortcuts/ac249b50eab34c04acd9fb522f9f7068

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 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.

Description This template will help you verify that incoming calls from a Slack webhook actually come from Slack and not some unknown third-party services. It is mainly used to prevent attacks from malicious bots or individuals. This is a Sub-Workflow, so it should be used inside the main workflow that contains the webhook listening for Slack requests. How to Use What to Edit You should set the Slack Signing Secret that you can find on your Slack App dashboard in the general tab. It should be located under the following URL: https://api.slack.com/apps/[SLACK_APP_ID]/general Input The input should be the received Slack request. This workflow should then be placed directly after the Slack Webhook. Outputs Success Output If the signature was verified successfully, we return a key verified_signature set to true along with data from the Slack request itself. Error Output When the signature could not be verified, we raise an error. You can handle this case in your main workflow by using an Error Workflow or by changing your node settings and choosing some actions in case of an error. Changelog Version 1.0.1 (2023-12-11) Changed replace by replaceAll in JS code in case of several arguments. Added some custom replacements that encodeURIComponent does not take into account

How it works Weekly triggered Fetches all previous executions of a given workflow Filter for failures and aggregate them into a single report Sends them to a given Telegram chat. Set up steps Create a new N8N api token in the settings panel. Add new N8N credentials in the credentials panel. Add new Telegram credentials in the credentials panel. Select N8N credentials and select the workflow ID in the "Get all previous executions" node. Select Telegram credentials and enter the chat-id in the "Telegram" node.

Telegram User Registration module Offers an efficient way to manage new and returning users in your Telegram bot workflow. It checks user data against a Google Sheets database, saving essential user information and ensuring personalized interactions. Key Features: User Lookup: Searches for users in a Google Sheets database based on their unique Telegram ID. New User Handling: Automatically registers new users, capturing details such as first name, last name, username, and language code. Returning User Recognition: Detects when an existing user returns and updates their status. Data Storage: Safely stores user information in a structured format, with fields for status and date of registration. Personalized Greetings: Delivers customized welcome messages for both new and returning users, promoting engagement. Setup Instructions: Copy this Telegram User Registration Workflow Follow the instructions inside: - Use Google Sheet template - Set up your credentials - Use example data to test workflow Customization: Adjust the status and messages for users based on your bot's needs. Connecting to the bot Workflow: Copy my Telegram bot starter template Copy Workflow ID of your Telegram User Registration Workflow Find the Register module in Telegram bot starter template and paste your Workflow ID Now the user's data is entered into the Register Workflow. This module provides a scalable foundation for managing user registration, whether your bot is for meal planning, customer support, or other interactive services. My easy to set up Telegram bot modules: 🏁 Telegram bot starter template 📝 Telegram callback menu (soon) Please reach out to Victor if you need further assistance with you n8n workflows and automations!

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 workflow allows you to define multiple tickets/issues in a Notion page, then easily import them into Linear. Why is it useful? We use this workflow internally at n8n for collaboration between Product and Engineering teams: Engineering needs all work to be in our ticketing system (Linear) in order to keep track of it Product prefers to review features in Notion. This is because it and can be used to dump all your thoughts and organise them into themes afterwards, plus it better supports rich content like videos Features Supports rich formatting (bullets, images, videos, links, etc.) Keeps links between the Notion and Linear version, in case you need to refer back Allows you to assign each issue to a team member in the Notion definition Avoids importing the same issues twice if you run it again on the same page (meaning you can issues incrementally) You can see an example of the required format of the Notion page here.

Use Case: This n8n workflow automates the process of extracting information from emails. It uses OpenAI to summarize sales emails and adds this information in Odoo. How it works: When an email is received with a certain label, it sends the email to OpenAI for summarization A sales opportunity is created in Odoo with the email subject as title and the email summary as internal note Set up steps: Configure Google Cloud credentials with Gmail access In the Gmail node, choose an email label in the filter section Configure OpenAI credentials Configure Odoo credentials

Who is this for? For developers and organizations that need to convert image files to PDF. What problem is this workflow solving? The file format conversion problem. What this workflow does Downloads the JPG file from the web. Converts the JPG file to PDF. Stores the PDF file in the local file system. How to customize this workflow to your needs Open the HTTP Request node. Adjust the URL parameter (all endpoints can be found here). Add your secret to the Query Auth account parameter. Please create a ConvertAPI account to get an authentication secret. Optionally, additional Body Parameters can be added for the converter.

This n8n workflow demonstrates how to create an agent using LangChain and SQLite. The agent can understand natural language queries and interact with a SQLite database to provide accurate answers. 💪 🚀 Setup Run the top part of the workflow once. It downloads the example SQLite database, extracts from a ZIP file and saves locally (chinook.db). 🗣️ Chatting with Your Data Send a message in a chat window. Locally saved SQLite database loads automatically. User's chat input is combined with the binary data. The LangChain Agend node gets both data and begins to work. The AI Agent will process the user's message, perform necessary SQL queries, and generate a response based on the database information. 🗄️ 🌟 Example Queries Try these sample queries to see the AI Agent in action: "Please describe the database" - Get a high-level overview of the database structure, only one or two queries are needed. "What are the revenues by genre?" - Retrieve revenue information grouped by genre, LangChain agent iterates several time before producing the answer. The AI Agent will store the final answer in its memory, allowing for context-aware conversations. 💬 Read the full article: 👉 https://blog.n8n.io/ai-agents/

Who is this for? For developers and organizations that need to combine PDF files. What problem is this workflow solving? PDF file merging problem. What this workflow does Downloads two PDF files from the web. Merges two PDF files into one. Stores the PDF file in the local file system. How to customize this workflow to your needs Open the PDF merge HTTP Request node. Adjust the URL parameter (all endpoints can be found here). Add your secret to the Query Auth account parameter. Please create a ConvertAPI account to get an authentication secret. Optionally, additional Body Parameters can be added for the converter.

This template will create a nightly backup of all your n8n workflows to a Dropbox folder. Each night, the previous night's backups are moved into an "old" folder, and renamed with the date they were taken. Backups over a specified age are deleted. (this is disabled by default for safety until you manually enable and verify it with your own setup) Prerequisites Dropbox account and credentials A destination folder for backups Setup Update all dropbox nodes with your credential Edit the Schedule Trigger node with the desired time to run the backup Edit the DESTINATION FOLDER node to specify the path in dropbox to upload to. This should be a folder and include the trailing / If you want to automatically purge old backups Edit the PURGE DAYS node to specify the age to purge Enable the PURGE DAYS node, and the 3 subsequent nodes Enable the workflow to run on the specified schedule

This n8n workflow is designed for working with the WhatsApp Business platform. It allows to send custom replies via WhatsApp in response to incoming user messages. 💡 Take a look at the step-by-step tutorial on how to create a WhatsApp bot. The workflow consists of two parts: The first Verify webhook sends back verification challenge string. You will need this part during the setup process on the Meta for Developers portal: Select your App Go to WhatsApp Configuration Click on the Edit button in the Webhook session Enter your production webhook URL, provide Verify token (can be any text string) Remember to activate the n8n workflow! Finally press "Verify and save" Once the webhook is verified, the Respond webhook receives various POST requests from Meta regarding WhatsApp messages (user messages and status notifications). The workflow checks whether the incoming JSON contains a user message. If this is the case, it sends the text message back to the user. This is a custom message, not a WhatsApp Business template.

The purpose of this n8n workflow is to automate the process of identifying incoming Gmail emails that are requesting an appointment, evaluating their content, checking calendar availability, and then composing and sending a response email. Note that to use this template, you need to be on n8n version 1.19.4 or later.

Purpose of workflow: This workflow transforms spreadsheet data into an interactive, AI-powered knowledge base that enables users to gain deep insights through natural language queries, searchability, and comparative analysis. How it works: Data Storage & Integration: Spreadsheet data is imported into a no-code database (NocoDB) System connects with an AI data analyst agent Agent accesses table metadata and column information Query Processing: Users input natural language questions AI agent interprets queries and converts them to database filters System retrieves relevant data using filter formulas AI synthesizes responses with analysis and insights Advanced Capabilities: Performs comparative analysis across multiple data points Handles complex multi-part queries Step by step setup: Create account on nocodb.com Create table by importing csv, copy table id Create API token https://app.nocodb.com/#/account/tokens In workflow, settings node, update with table id In NocoDB tool node, setup authentication with API token created in step 3 Specify the workspace and base fields after connecting to NocoDB

How it works This workflow adds a priority to each Todoist item in your inbox, based on a list of projects that you add in the workflow. Setup Add your Todoist credentials Add your OpenAI credentials Set your project names and add priority

Adobe developer API Did you know that Adobe provides an API to perform all sort of manipulation on PDF files : Split PDF, Combine PDF OCR Insert page, delete page, replace page, reorder page Content extraction (text content, tables, pictures) ... The free tier allows up to 500 PDF operation / month. As it comes directly from Adobe, it works often better than other alternatives. Adobe documentation: https://developer.adobe.com/document-services/docs/overview/pdf-services-api/howtos/ https://developer.adobe.com/document-services/docs/overview/pdf-extract-api/gettingstarted/ What does this workflow do The API is a bit painful to use. To perform a transformation on a PDF it requires to Authenticate and get a temporal token Register a new asset (file) Upload you PDF to the registered asset Perform a query according to the transformation requested Wait for the query to be proccessed by Adobe backend Download the result This workflow is a generic wrapper to perform all these steps for any transformation endpoint. I usually use it from other workflow with an Execute Workflow node. Examples are given in the workflow. Example use case This service is useful for example to clean PDF data for an AI / RAG system. My favorite use-case is to extract table as images and forward images to an AI for image recognition / description which is often more accuarate than feedind raw tabular data to a LLM.

This workflow allows you to ask questions about data stored in a database using AI. To use it, you'll need an OpenAI API key (although you could also swap in a model from another service). Supported databases: Postgres MySQL SQLite The workflow uses n8n's embedded chat, but you could also modify it to work with a chat service such as Slack, MS Teams or WhatsApp. Note that to use this template, you need to be on n8n version 1.19.4 or later.

When you collect leads from a form, you need to format the incoming data such as the lead's name and also apply a basic validation of the email entered. Lucky for us, N8N offers all of these features with simple expressions that can easily be applied to data. This workflow aims to show how you can process your lead data before saving it in Mautic. How it Works This workflow receives data from a Wordpress form; applies name formatting and basic validation to the email; Creates the contact in Mautic; If e-mail is invalid, add the lead in Dot Not Contact list. Setup Steps Set up credentials when you first open the workflow. You'll need a Mautic account. You need to configure a form in Wordpress (Elementor, WPForms, etc.) and send it to the N8N Webhook address; Now map the fields you need to apply formatting and validation. After testing your workflow, swap the Test URL to Production URL in Discourse and activate your workflow

⚙️🛠️🚀🤖🦾 This template is a PoC of a ReAct AI Agent capable of fetching random pages (not only Wikipedia or Google search results). On the top part there's a manual chat node connected to a LangChain ReAct Agent. The agent has access to a workflow tool for getting page content. The page content extraction starts with converting query parameters into a JSON object. There are 3 pre-defined parameters: url** – an address of the page to fetch method** = full / simplified maxlimit** - maximum length for the final page. For longer pages an error message is returned back to the agent Page content fetching is a multistep process: An HTTP Request mode tries to get the page content. If the page content was successfuly retrieved, a series of post-processing begin: Extract HTML BODY; content Remove all unnecessary tags to recude the page size Further eliminate external URLs and IMG scr values (based on the method query parameter) Remaining HTML is converted to Markdown, thus recuding the page lengh even more while preserving the basic page structure The remaining content is sent back to an Agent if it's not too long (maxlimit = 70000 by default, see CONFIG node). NB: You can isolate the HTTP Request part into a separate workflow. Check the Workflow Tool description, it guides the agent to provide a query string with several parameters instead of a JSON object. Please reach out to Eduard is you need further assistance with you n8n workflows and automations! Note that to use this template, you need to be on n8n version 1.19.4 or later.

Who is this for? For developers and organizations that need to convert DOCX files to PDF. What problem is this workflow solving? The file format conversion problem. What this workflow does Downloads the DOCX file from the web. Converts the DOCX file to PDF. Stores the PDF file in the local file system. How to customize this workflow to your needs Open the HTTP Request node. Adjust the URL parameter (all endpoints can be found here). Add your secret to the Query Auth account parameter. Please create a ConvertAPI account to get an authentication secret. Adjust url_to_file in the Config node to URL pointing to your file. Optionally, additional Body Parameters can be added for the converter.

This workflow template shows how to load JSON data into a workflow and push that data into an App or convert it into a Spreadsheet file. Specifically, this workflow shows how to make a generic API request that returns JSON. It then shows how to load that into a Google Sheets spreadsheet, or convert it to .CSV file format. However, you can use the general pattern to load data into any app or convert to any spreadsheet file format (such as .xlsx).

Example: @SubAlertMe_Bot Summary: The automated image analysis and response workflow using n8n is a sophisticated solution designed to streamline the process of analyzing images sent via Telegram and delivering insightful responses based on the analysis outcomes. This cutting-edge workflow employs a series of meticulously orchestrated nodes to ensure seamless automation and efficiency in image processing tasks. Use Cases: This advanced workflow caters to a myriad of scenarios where real-time image analysis and response mechanisms are paramount. The use cases include: Providing immediate feedback on images shared within Telegram groups. Enabling automated content moderation based on the analysis of image content. Facilitating rapid categorization and tagging of images based on the results of the analysis. Detailed Workflow Setup: To effectively implement this workflow, users must adhere to a meticulous setup process, which includes: Access to the versatile n8n platform, ensuring seamless workflow orchestration. Integration of a Telegram account to facilitate image reception and communication. Utilization of an OpenAI account for sophisticated image analysis capabilities. Configuration of Telegram and OpenAI credentials within the n8n environment for seamless integration. Proficiency in creating and interconnecting nodes within the n8n workflow for optimal functionality. Detailed Node Description: Get the Image (Telegram Trigger): Actively triggers upon receipt of an image via Telegram, ensuring prompt processing. Extracts essential information from the received image message to initiate further actions. Merge all fields To get data from trigger: Seamlessly amalgamates all relevant data fields extracted from the trigger node for comprehensive data consolidation. Analyze Image (OpenAI): Harnesses the powerful capabilities of OpenAI services to conduct in-depth analysis of the received image. Processes the image data in base64 format to derive meaningful insights from the visual content. Aggregate all fields: Compiles and consolidates all data items for subsequent processing and analysis, ensuring comprehensive data aggregation. Send Content for the Analyzed Image (Telegram): Transmits the analyzed content back to the Telegram chat interface for seamless communication. Delivers the analyzed information in textual format, enhancing user understanding and interaction. Switch Node: The Switch node is pivotal for decision-making based on predefined conditions within the workflow. It evaluates incoming data to determine the existence or absence of specific elements, such as images in this context. Utilizes a set of rules to assess the presence of image data in the message payload and distinguishes between cases where images are detected and when they are not. This crucial node plays a pivotal role in directing the flow of the workflow based on the outcomes of its evaluations. Conclusion: The automation of image analysis processes through this sophisticated workflow not only enhances operational efficiency but also revolutionizes communication dynamics within Telegram interactions. By incorporating this advanced workflow solution, users can optimize their image analysis workflows, bolster communication efficacy, and unlock new levels of automation in image processing tasks.

Use Case When having a call with a new potential customer, one of the keys to getting the most out of the call is to find out as much information as you can about them before the call. Normally this involves a lot of manual research before every call. This workflow automates this tedious work for you. What this workflow does The workflow runs every time a new call is booked via your Calendly. It then filters out personal emails, before enriching the email. If the email is attached to a company it enriches the company and upserts it in your Hubspot CRM. Setup Add Clearbit, Hubspot, and Calendly credentials. Click on Test workflow. Book a meeting on Calendly so the event starts the workflow. Be aware that you can adapt this workflow to work with your enrichment tool, CRM, and booking tool of choice.

This workflow allows you to ask questions about a PDF document. The answers are provided by an AI model of your choice, and the answer includes a citation pointing to the information it used. You can use n8n’s built-in chat interface to ask the questions, or you could customise this workflow to use another one (e.g. Slack, Teams, etc.) Example The workflow is set up with the Bitcoin whitepaper. So you could ask things like: Question: “Which email provider does the creator of Bitcoin use?“ Answer: “GMX [Bitcoin whitepaper.pdf, lines 1-35]” Requirements A Pinecone account (they have a free tier at the time of writing that is easily enough for this workflow) Access to a large language model (e.g. an OpenAI account) Customizing this workflow The workflow only reads in one document, but you could customise it to read in all the documents in a folder (or more). The workflow is set up to use GPT 3.5, but you could swap that out for any other model (including self-hosted ones).

This n8n workflow is a proof-of-concept template exploring how we might work with multimodal LLMs and their multi-image analysis capabilities. In this demo, we compare 2 screenshots of a webpage taken at different timestamps and pass both to our multimodal LLM for a visual comparison of differences. Handling multiple binary inputs (ie. images) in an AI request is supported by n8n's basic LLM node. How it works This template is intended to run as 2 parts: first to generate the base screenshots and next to run the visual regression test which captures fresh screenshots. Starting with a list of webpages captured in a Google sheet, base screenshots are captured for each using a external web scraping service called Apify.com (I prefer Apify but feel free to use whichever web scraping service available to you) These base screenshots are uploaded to Google Drive and will be referenced later when we run our testing. Phase 2 of the workflow, we'll use a scheduled trigger to fire sometime in the future which will reuse our web scraping service to generate fresh screenshots of our desired webpages. Next, re-download our base screenshots in parallel and with both old and new captures, we'll pass these to our LLM node. In the LLM node's options, we'll define 2 "user message" inputs with the type of binary (data) for our images. Finally, we'll prompt our LLM with our testing criteria and capture the regressions detected. Note, results will vary depending on which LLM you use. A final report can be generated using the LLM's output and is uploaded to Linear. Requirements Apify.com API key for web screenshotting service Google Drive and Sheets access to store list of webpages and captures Customising this workflow Have your own preferred web screenshotting service? Feel free to swap out Apify with your service of choice. If the web screenshot is too large, it may prove difficult for the LLM to spot differences with precision. Try splitting up captures into smaller images instead.

Overview This workflow aims at providing data visualization to a native SQL Agent. Together, they can help with fostering data analysis and data visualization within a team. It uses the native SQL Agent that works well and adds some visualization capabilities thanks to OpenAI Structured Output and Quickchart.io. How it works The first part of the workflow is a regular SQL Agent: it connects to a Database and is able to query it and translate the response in a human format. Then, the Text Classifier is deciding if the user would benefit from a chart, supporting the SQL Agent's response. If it does, then it executes the subworkflow to dynamically generate a chart and append the chart to the response from the SQL Agent. If it doesn't, then the SQL Agent response is directly outputted. The sub-workflow calls OpenAI through the HTTP Request node to retrieve a chart definition. In the "set response" node, the chart definition is added at the end of a quickchart.io URL - the URL to the chart image. It is sent back to the AI Agent. How to use it Use an existing or create a new database. For example, I've used this Kaggle dataset and uploaded it to a Supabase DB. Add the PostgreSQL or MySQL credentials. Alternatively, you can use SQLite binary files (check this template). Activate the workflow. Start chatting with the AI SQL Agent. If the Text Classifier considers a chart would be useful, it will generate a chart in addition to the response from the SQL Agent. Notes The full Quickchart.io specifications have not been integrated, thus there are some possible glitches (e.g., due to the size of the graph, radar graphs are not displayed properly).

Automating your marketing campaign management process can streamline your workflow and save you valuable time. With the combination of Baserow and n8n, you can efficiently handle your campaign data and seamlessly publish content to your Shopify store. In this workflow template, I demonstrate how to leverage Baserow as a centralized platform for organizing your marketing campaign assets, including copy and images. By utilizing n8n, we automate the process of fetching images and campaign descriptions from Baserow and uploading them directly to your Shopify store. With this automated solution, you can expedite the publishing process, ensuring that your campaigns are launched swiftly across your sales channels. Additionally, this workflow serves as a foundational step towards further automation in campaign management, allowing you to dynamically generate and upload content to your Shopify store with ease. This template will help you: Use n8n to get images for marketing campaigns from Baserow and upload them to your Shopify media library Dynamically inject data from Baserow into a template file Upload a template file to your Shopify theme This template will demonstrate the follwing concepts in n8n: use the Webhook node use the IF node to control the execution flow of the workflow do time calculation using expressions and javascript use the GraphQL node to upload images to your Shopify media files create a dynamic template file for your Shopify theme use the HTTP Reqest node to upload your template file to your Shopify store 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/Ky-dYlljGiY

Want to learn the basics of n8n? Our comprehensive quick quickstart tutorial is here to guide you through the basics of n8n, step by step. Designed with beginners in mind, this tutorial provides a hands-on approach to learning n8n's basic functionalities.

Use case This workflow uses Gmail to send outreach emails to new Hubspot contacts that have yet to be contacted (usually unknown contacts), and records the outreach in Hubspot. Setup Setup HubSpot Oauth2 creds (Be careful with scopes. They have to be exact, not less or more. Yes, it's not simple, but it's well documented in the n8n docs. Be smarter than me, read the docs) Setup Gmail creds. Change the from email and from name in the Record outreach in HubSpot node How to adjust this template to your needs Change the email message in the Set keys node Think about your criteria to reach out to new contacts. Here we simply filter for only contacts with unknown dates.

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

Send multiple emails in Gmail directly via Google Sheets [Video for workflow process](https://www.canva.com/design/DAF8VnLBBQA/BKog1CSHs7_goAYse3mEzQ/watch?utm_content=DAF8VnLBBQA&utm_campaign=designshare&utm_medium=link&utm_source=editor ) In today's fast-paced digital world, businesses are constantly seeking ways to streamline their processes and enhance customer engagement. One powerful tool that facilitates these goals is n8n, an automation platform that allows users to create workflows to automate tasks and workflows. Benefits of the Workflow: Efficiency**: By automating the process of sending emails to customers based on data from Google Sheets, this n8n workflow significantly reduces manual effort and saves time. Accuracy**: The workflow ensures that emails are sent to the right recipients at the right time by filtering items based on specific conditions and the current date. Personalization**: Personalized emails can be sent to customers based on the information provided in the Google Sheet, resulting in enhanced customer engagement. Real-time Updates**: The workflow updates the Google Sheet with the status of the sent emails, providing real-time insights into the communication process. Consistency**: Through automation, this workflow helps maintain consistency in communication with customers, ensuring a seamless experience. Workflow Overview: The workflow begins with the "Google Sheets Trigger" node, which monitors a specified Google Sheet for new row additions. Upon detection of a new row, the workflow progresses to the "Filter Status (Waiting for sending)" node, where items are filtered based on specific conditions. Subsequently, the workflow moves to the "Filter Items by Current Date" node, which filters items based on the current date. Items matching the current date are then processed further. The filtered items are then forwarded to the "Gmail" node, where personalized emails are composed and sent to recipients based on the Google Sheet data. Finally, the workflow updates the Google Sheet using the "Google Sheets" node with the status of the sent emails and other relevant information. Copy this template to get started : Google Sheets Workflow Nodes Documentation: Schedule Trigger Filter Items by Current Date Gmail Google Sheets Filter Status (Waiting for sending) Set data Merge feild Conclusion: In conclusion, this n8n workflow presents a powerful solution for automating email communication processes based on Google Sheets data. By leveraging automation, businesses can enhance their operational efficiency, accuracy, and customer engagement. The seamless integration of nodes in this workflow streamlines the communication process and ensures timely and personalized interactions with customers. As businesses continue to prioritize efficiency and customer satisfaction, n8n workflows offer a versatile and effective means to achieve these objectives.

What this workflow does This workflow in n8n demonstrates how to send a message in Lark using a Lark bot. It begins with a manual trigger and then retrieves the necessary Lark token via a POST request. The token is used to authenticate and send a message to a specific chat using the Lark API. The input node provides the required app_id, app_secret, chat_id, and message content. After obtaining the token, the message is sent with the Lark API's message/v4/send/ endpoint. Who This Is For This n8n workflow is ideal for organizations, teams, and developers who need to automate message sending within Lark, especially those managing notifications, alerts, or team reminders. It can help users reduce manual messaging tasks by leveraging a Lark bot to deliver messages at specific intervals or based on particular conditions, enhancing team communication and responsiveness. Setup Fill the Input node with your values Exchange the bearer token in the Send Message node with your token Author: Hiroshi

Extract Title tag and meta description from url for SEO analysis. How it works The workflows takes records from Airtable, get the url in the records and extract from the related webpage the title tag (<title>) and meta description (<meta name="description" content="Some content">). If title tag and/or meta description tag isn't available on the webpage, the result will be empty. Setup Set a Base in Airtable with a table with the following structure: url (field type url), title tag (field type text string), meta desc (field type text field) Minimum suggested table structure is: url (https://example.com), title (Title example), meta desc* (This is the meta description of the example page) Connect Airtable to both Airtable nodes in the template and, with the following formula, get all the records that miss title tag and meta desc. Formula: AND(url != "", {title tag} = "", {meta desc} = "") Insert the url to be analyzed in the table in the field url and let the workflow do the rest. Extra You can also calculate the length for title tag and meta desc using formula field inside Airtable. This is the formula: LEN({title tag}) or LEN({meta desc}) You can automate the process calling a Webhook from Airtable. For this, you need an Airtable paid plan.

How it works This workflow watches a selected Google Drive folder for any images added to it. It then takes that image, sends it the the tinypng.com service which optimises and reduces its size (where possible) Tinypng then returns the updated image which is then automatically saved in your chose Google Drive folder Setting things up It's pretty simple to configure and should only take around 5-10mins. You only need to set up credentials for Google Drive and Tinypng.com For Tinypng.com you can sign up for their free tier API access which gives you 500 optimisations per month Once you have those two things, you just need choose your 'input' folder to watch for images and your 'output' folder for where these images should be stored There are a few more optional things you can do such as the naming of your final image and also lots more you could do with the Tinypng API for more advanced image optimisation

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.

Transforming Emails into Podcasts 🎙️ Check out this channel for example. The n8n workflow described here aims to revolutionize the way users engage with promotional emails by converting them into entertaining audio podcasts. This innovative project leverages automation through n8n to streamline tasks and enhance user experience. Project Benefit 🎧🌟 The primary goal of this project is to transform "CATEGORY_PROMOTIONS" emails into engaging audio content. By converting text into speech, users can enjoy promotional material hands-free, making it easier to consume information while on the go or relaxing. The workflow consists of several key steps orchestrated seamlessly to deliver a delightful experience to users. How to Use the Workflow: Gmail trigger Node: Initiates the workflow by fetching "CATEGORY_PROMOTIONS" emails at regular intervals. The Gmail Trigger node in your N8N workflow is set to poll for new emails every minute and is configured to filter emails with the label "CATEGORY_PROMOTIONS" before triggering the workflow. Steps to Use Filters Inside the Gmail Trigger Node: Configure Gmail Trigger Node: Set "Poll Times" to "Every Minute" to check for new emails at regular intervals. Enable the "Simple" toggle if you want to simplify the node interface. Under "Filters", specify the label IDs you want to filter by. In this case, it's set to "CATEGORY_PROMOTIONS". Adjust any additional options as needed. // Configure Gmail Trigger node pollTimes: { item: [ { mode: "everyMinute" } ] }, simple: false, filters: { labelIds: [ "CATEGORY_PROMOTIONS" ] }, options: {} Save and Execute: Save your workflow and execute it to start monitoring your Gmail account for new emails with the specified label filter. By following these steps, your workflow will effectively trigger based on new emails that match the "CATEGORY_PROMOTIONS" label in your Gmail account. Get message content Node: Extracts the email content for processing. Summarization Chain Node: Generates concise summaries using advanced methods for better readability. Delete the unnecessary items Node: Removes irrelevant details from the email content. Text to Free TTS Node: Converts the summary text into speech using Free TTS technology. Convert from base64 to File Node: Transforms the audio data into a compatible file format. Merge Text with Audio Node: Combines the text and audio components seamlessly. Aggregate in same cell Node: Gathers all processed data for finalization. Send Message to Telegram Node: Dispatches the audio message along with a caption to a designated Telegram chat ID. By automating these tasks, the workflow ensures efficient communication and delivers content in a more engaging format, fostering a positive user experience. Configuration Instructions: The configuration of this workflow involves setting up the necessary nodes and establishing connections between them. Each node performs a specific function crucial to the overall operation of the workflow. Additionally, credentials need to be provided for accessing Gmail and OpenAI services to enable seamless data processing and summarization. Utilizing Text-to-Speech API 🎧 In addition to n8n automation, an external Text-to-Speech API plays a pivotal role in generating audio content from text data. By sending a POST request with JSON data containing the text and voice preferences, users can quickly receive audio files of the converted content. The API offers a straightforward interface for text-to-speech conversion, making it ideal for creating audio clips efficiently. To access this API, simply submit the desired text and voice selection to receive the generated speech audio file. The API endpoint can be accessed at https://tiktok-tts.weilnet.workers.dev/api/generation or through https://tiktokvoicegenerator.com/. In conclusion, this n8n workflow coupled with a Text-to-Speech API presents a powerful solution for transforming emails into captivating podcasts, enhancing user engagement and communication effectiveness. By embracing automation and innovative technologies, this project aims to improve user experience and streamline content delivery processes. 🌈✨🚀

What this does: This automation will dynamically create channels on your Discord server for each of your Webflow forms then send formatted form submissions as messages in those channels. This is useful for Webflow will only notify a single email of a form submission. By using this workflow you can enhance your Webflow form management by receiving them in Discord. This is great if you need to notify multiple team members or communities of your form submissions. Usage guide Full written and video guide Simply create credentials for Webflow and Discord and connect them to the nodes. The video guide demonstrates a realworld usecase using a Webflow template and breaks down each node in detail about how it works.

A n8n workflow designed to shorten URLs using Dub.co API. How it works: It shortens a url using Dub.co API, with the ability to use custom domains and projects. It updates the current shortened url if the slug has been already used. Estimated Time: Around 15 minutes. Requirements: A Dub.co account. Configuration: Configure the "API Auth" node to add your Dub.co API key, project slug, and the long URL. There some extras that you're able to configure too. You will be able to do that by clicking the "API Auth" node and filling the fields. Detailed Instructions: Sticky notes within the workflow provide extensive setup information and guidance. Keywords: n8n workflow, dub.co, dub.sh, url shortener, short urls, short links

The News Site from Colt, a telecom company, does not offer an RSS feed, therefore web scraping is the choice to extract and process the news. The goal is to get only the newest posts, a summary of each post and their respective (technical) keywords. Note that the news site offers the links to each news post, but not the individual news. We collect first the links and dates of each post before extracting the newest ones. The result is sent to a SQL database, in this case a NocoDB database. This process happens each week thru a cron job. Requirements: Basic understanding of CSS selectors and how to get them via browser (usually: right click → inspect) ChatGPT API account - normal account is not sufficient A NocoDB database - of course you may choose any type of output target Assumptions: CSS selectors work on the news site The post has a date with own CSS selector - meaning date is not part of the news content "Warnings" Not every site likes to be scraped, especially not in high frequency Each website is structured in different ways, the workflow may then need several adaptations.

This workflow gets data from an API and exports it into Google Sheets and a CSV file.

Usage This workflow gets all the posts from your WordPress site and sorts them into a clear format before publishing them to medium. Step 1. Set up the HTTP node and set the URL of the source destination. This will be the URL of the blog you want to use. We shall be using https://mailsafi.com/blog for this. Step 2. Extract the URLs of all the blogs on the page This gets all the blog titles and their URLs. Its an easy way to sort ou which blogs to share and which not to share. Step 3. Split the entries for easy sorting or a cleaner view. Step 4. Set a new https node with all the blog URLs that we got from the previous steps. Step 5. Extract the contents of the blog Step 6. Add the medium node and then set the contents that you want to be shared out. Execute your workflow and you are good to go

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.

Sometimes you need the rich text field to be in HTML instead of Markdown. This template either syncs a single record or all records at once. Youtube tutorial

Image Creation with OpenAI and Telegram Check this channel: AutoTechAi_bot Description: In the realm of automation and artificial intelligence, n8n offers a sophisticated platform for seamlessly integrating AI algorithms to enhance image creation and communication processes. This innovative workflow leverages the capabilities of OpenAI and Telegram to facilitate creative image generation and streamline communication channels, ultimately enhancing user engagement and interaction. How to Use: Set Up Credentials: Configure credentials for the Telegram account and OpenAI API to enable seamless integration. Configure Nodes: Telegram Trigger Node: Set up the node to initiate the workflow based on incoming messages from users on Telegram. OpenAI Node: Utilize advanced AI algorithms to analyze text content from messages and generate intelligent responses. Telegram Node: Send processed data, including images and responses, back to users on Telegram for seamless communication. Merge Node: Organize and combine processed data for efficient handling and integration within the workflow. Aggregate Node: Aggregate all item data, including binaries if specified, for comprehensive reporting and analysis purposes. Run Workflow: Initiate the workflow to leverage AI-enhanced image processing and communication capabilities for enhanced user interactions. Monitor Execution: Keep an eye on the workflow execution for any errors or issues that may occur during processing. Customize Workflow: Tailor the workflow nodes, parameters, or AI models to align with specific business objectives and user engagement strategies. Experience Benefits: Embrace the power of AI-driven image processing and interactive communication on Telegram to elevate user engagement and satisfaction levels. By following these steps, businesses can unlock the transformative potential of AI integration in image creation and communication workflows using n8n. Elevate your user engagement strategies and deliver exceptional experiences to your audience through innovative AI-driven solutions. Embark on a journey of innovation and efficiency with AI integration in image creation and communication workflows using n8n!

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.

How it works: Using a Crew of AI agents (Senior Researcher, Visionary, and Senior Editor), this crew will automatically determine the right questions to ask to produce a detailed fundamental stock analysis. This application has two components: a front-end and a Stock Q&A engine. The front end is the team of agents automatically figuring out the questions to ask, and the back-end part is the ability to answer those questions with the SEC 10K data. This template implements the Stock Q&A engine. For the front-end of the application, you can choose one of two options: using CrewAI with the Replit environment (code approach) fully visual approach with n8n template (AI-powered automated stock analysis) Setup steps: Use first workflow in template to upsert a company annual report PDF (such as from SEC 10K filling) Get URL for Webhook in second workflow template CrewAI front-end: Youtube overview video Fork this AI Agent environment Crew Agent Environment Set the webhook URL into N8N_WEBHOOK_URL variable Set OpenAI_API_KEY variable

Streamline Case Management in TheHive via Slack! Our TheHive Slack Integration empowers SOC analysts by allowing them to efficiently manage and update case attributes directly within Slack, reducing the need to switch contexts and enhancing response time. Key Features: Direct Case Management**: Modify case details such as assignee, severity, status, and more through intuitive form inputs embedded within Slack messages. Seamless Integration**: Assumes matching email addresses between TheHive and Slack users for straightforward assignee updates. Note: Ensure email consistency to avoid assignment errors. Instant Case Actions**: Quickly close cases as false positives or adjust threat levels with minimal clicks, directly impacting case status in TheHive and reflecting updates immediately in Slack. Task Management**: Add tasks to cases through a user-friendly modal popup, fostering better task tracking and delegation within your team. Operational Benefits: Efficiency**: Enables analysts to perform multiple case actions without leaving Slack, streamlining workflows and saving valuable time. Accuracy**: Reduces the chances of human error by providing a controlled interface for case updates. Agility**: Enhances the SOC team's agility by providing tools for rapid response and case management, crucial for effective security operations. Setup Tips: Verify that all SOC team members have matching email IDs in TheHive and Slack. Familiarize your team with the Slack form inputs and ensure they understand the importance of accurate data entry. Regularly review and update the integration settings to accommodate any changes in your security operations protocols. Need Help? For detailed setup instructions or troubleshooting, refer to our Integration Guide or reach out on our Support Forum. Leverage this integration to maximize your SOC team's efficiency and responsiveness, ensuring that case management is as streamlined and effective as possible.

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.

Description This n8n workflow verifies the deliverability of mailing addresses stored in Keap/Infusionsoft by integrating with Lob’s address verification service. Who is this for? This template is designed for Keap/Infusionsoft users who need to ensure the accuracy of mailing addresses stored in their CRM systems. What problem is this workflow solving? / Use Case This workflow addresses the challenge of maintaining accurate mailing addresses in CRM databases by verifying the deliverability of addresses. What this workflow does A new contact is created in Keap/Infusionsoft Webhook sent to n8n Verify if the address is deliverable via LOB Report back to Keap/Infusionsoft Set Up Steps Watch this setup video: https://www.youtube.com/watch?v=T7Baopubc-0 Takes 10-30 minutes to set up Accounts Needed: Keap/Infusionsoft LOB Account (https://www.lob.com $0.00/mo 300 US addresses Verifications) n8n Before using this template, ensure you have API keys for your Keap/Infusionsoft app and Lob. Set up authentication for both services within n8n. How to customize this workflow to your needs You can customize this workflow by adjusting the trigger settings to match Keap/Infusionsoft’s workflow configuration. Additionally, you can modify the actions taken based on the deliverability outcome, such as updating custom fields or sending notifications.

Use Case Whenever someone shows interest in your offerings by subscribing to a list in ConvertKit it could be a potential new customer. Typically you need to gather more detailed information about them (data enrichment) and finally update their profile in your CRM system to better manage and nurture your relationship with them. This workflow does this all for you! What this workflow does The workflow runs every time a user is subscribed to a ConvertKit list. It then filters out personal emails, before enriching the email. If the email is attached to a company it enriches the company and upserts it in your Hubspot CRM. Setup Add Clearbit, Hubspot, and ConvertKit credentials. Click on Test workflow. Subscribe to a list on ConvertKit to trigger the workflow. Be aware that you can adapt this workflow to work with your enrichment tool, CRM, and email automation tool of choice.

This template is inspired by Save your workflows into a GitHub repository by hikerspath and Back Up Your n8n Workflows To Github by jon-n8n. Basic Retrieve all workflows from an n8n instance and save it on a gitlab project. If the workflow exist, il will only save the changes. Flow What the workflow does : Sets custom parameters Gets workflows Iterates through each workflow one by one Get the file from Gitlab if exists Compare the files as objects (not as strings) Return a status on the workflow Create, Edit or ignore the file depending on the status Return a list of status for each workflow Configuration Select a credential in each Gitlab nodes. Edit the data in node "Globals" : repo.owner : slug of the user or team owning the repo repo.name : slug of the repository repo.branch : branch to commit on repo.path : from root of the repository. Should end with / Comments Error on gitlab nodes will not stop the run but will list the current workflow as error in the results Some fields are ignored to determined if there is changes : updatedAt : should be ignored if only ignores fields are changed globals : it's running information, no need to follow the changes

Use case When collecting leads via an online form, you often need to manually add those new leads into your Pipedrive CRM. This not only takes a lot of time but is also error-prone. This workflow automates this tedious work for you. What this workflow does The workflow is triggered each time a form is submitted in n8n. It validates the email address using Hunter.io. If the email is valid, the workflow checks for an existing person with that email in Pipedrive. If no existing person is found, it utilizes Clearbit to enrich the person's information. It then verifies if the person's organization already exists in Pipedrive, creating a new organization if necessary. The workflow then registers the person in Pipedrive. Lastly, it creates a lead in Pipedrive using information from the person and organization. Setup This workflow is very quick to set up. Add your Hunter.io, Clearbit and Pipedrive credentials Click the test workflow button Activate the workflow and use the form trigger production URL to collect your leads in a smart way How to adjust it to your needs Exchange the n8n form trigger with your form of choice (Typeform, Google Forms, SurveyMonkey...) Add a filter criteria to only add new leads if they match certain requirements Remove the email check with Hunter.io if you don't own this tool and expect new form submission to have a correct email anyways Add ways to handle invalid emails or existing Persons

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.