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An example workflow for a multilanguage Telegram bot. It allows adding many new languages to the bot without editing the workflow. Important note! Due to some breaking API changes in NocoDB some of its node options are not working at the moment (MAY 2022). These two nodes were replaced by HTTP request nodes. Functionality is still the same.

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.

Task: Conditional filtering and branching items Why: Filtering and branching data based on conditions allows you to build complex workflows that work with more than one data flow scenario Main use cases: Filter out data that is not relevant for the rest of the workflow Split data to several branches of the workflow, where we want the data to be treated differently in the rest of the workflow

Who this template is for This template is for everyone who needs to work with XML data a lot and wants to convert it to JSON instead. Use case Many products still work with XML files as their main language. Unfortunately, not every software still supports XML, as many switched to more modern storing languages such as JSON. This workflow is designed to handle the conversion of XML data to JSON format via a webhook call, with error handling and Slack notifications integrated into the process. How this workflow works Triggering the workflow: This workflow initiates upon receiving an HTTP POST request at the webhook endpoint specified in the "POST" node. The endpoint, designated as , can be accessed externally by sending a POST request to that URL. Data routing and processing: Upon receiving the POST request, the Switch node routes the workflow's path based on conditions determined by the content type of the incoming data or any encountered errors. The Extract From File and Edit Fields (Set) nodes manage XML input processing, adapting their actions according to the data's content type. XML to JSON conversion: The XML data extracted from the input is passed through the "XML" node, which performs the conversion process, transforming it into JSON format. Response handling: If the XML-to-JSON conversion is successful, a success response is sent back with a status of "OK" and the converted JSON data. If there are any errors during the XML-to-JSON conversion process, an error response is sent back with a status of "error" and an error message. Error handling: in case of an error during processing, the workflow sends a notification to a Slack channel designated for error reporting. Set up steps Set up your own in the Webhook node. While building or testing a workflow, use a test webhook URL. When your workflow is ready, switch to using the production webhook URL. Set credentials for Slack.

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.

Based on Jonathan's workflow backup template This workflow will backup your credentials to GitHub. It uses a CLI command to export all credentials. It then loops over the data checks in GitHub to see if a file exists that uses the credential name. Once checked it will: update the file on GitHub if it exists; create a new file if it doesn't exist; ignore if it's the same. Config Options repo.owner - Github owner repo.name - Github repository name repo.path - Path within the Github repository ⚠ The credentials are all decrypted. Make sure you save them safely or tweak the CLI command to store them encrypted.== > This workflow has been updated to use the n8n node and the code node so requires at least version 0.198.0 of n8n

This workflow checks a Google Calendar at 8am on the first of each month to get anything that has been marked as a Holiday or Illness. It then merges the count for each person and sends an email with the list. To use this workflow you will need to set the credentials to use for the Google Calendar node and Send Email node. You will also need to select the calendar ID and fill out the information in the send email node. This workflow searches for Events that contain "Holiday" or "Illness" in the summary. If you want to change this you can modify it in the Switch node.

This workflow sends a OpenAI GPT reply when an email is received from specific email recipients. It then saves the initial email and the GPT response to an automatically generated Google spreadsheet. Subsequent GPT responses will be added to the same spreadsheet. Additionally, when feedback is given for any of the GPT responses, it will be recorded to the spreasheet, which can then be used later to fine-tune the GPT model. Prerequisites OpenAI credentials Google credentials How it works This workflow is essentially a two-in-one workflow. It triggers off from two different nodes and have very different functionality from each trigger. The flow triggered from On email received node is as follows: Triggers off on the On email received node. Extract the email body from the email. Generate a response from the email body using the OpenAI node. Reply to the email sender using the Send reply to recipient node. A feedback link is also included in the email body which will trigger the On feedback given node. This is used to fine-tune the GPT model. Save the email body and OpenAI response to a Google Sheet. If a sheet does not exist, it will be created. The flow triggered from On feedback given node is as follows: Triggers off when a feedback link is clicked in the emailed GPT response. The feedback, either positive or negative, for that specific GPT response is then recorded to the Google Sheet.

Introduction The Traveler Co-Pilot empowers you to confidently traverse the world, connecting with ease and breaking language barriers: Engage in conversations with locals Navigate menus at foreign eateries Comprehend road signs effortlessly. Features Seamless Speech-to-Speech Translation** Communicate in any of the 55 supported languages, and witness the bot translate your words into another language in real-time, all through speech. Visual Translation Magic** Capture images containing text, and the bot will work its magic by recognizing and translating the text into the desired language, right before your eyes. Setup Steps Open the Settings node and specify the languages you would like to work with

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

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.

This workflow is a template example for making Discord GPT-powered bots. Incoming user requests are analysed and categorised via OpenAI node with the help of a hand-crafted prompt. The response message is then routed to a different Discord channel.

Telegram N8N workflow (de)activator What does it do? This workflow helps you to quickly activate or deactivate a workflow through Telegram. Sometimes we are not able to access a PC to resolve an issue if something goes wrong with a workflow. If you, like me, use Telegram to send yourself error reports, you can quickly react in case of urgency. Just by sending '/stop' combined with the name you use for a workflow, you can deactivate a workflow, or reactivate it with '/start'. For example '/stop marketing'. Walkthrough: https://watch.screencastify.com/v/uWQ88gZKj57WTGOOqSW2 (6min) Instructions Create a Telegram API key through botfather (https://t.me/botfather). Add it to the telegram credentials. For the N8N nodes, go to settings in your n8n instance. Then 'n8n API' and 'create an API key'. To ensure that only we can send commands to the bot, we need the chat ID of our DM with our newly created bot. Open the the Telegram trigger and click on 'listen to events'. Go to Telegram and send a direct message to the bot, this will trigger the Telegram node. Go to the filter node and fill in the chat id you want to filter for with the data you got from the test event in the Telegram node. In the first Switch node you can find the commands, in this case it is '/start' and '/stop'. When you send a message to your bot starting with either of those, it will go to the next switch nodes. Next it will check what other word it contains. As an example I have used the words 'marketing' and 'sales', both corresponding to a marketing and sales workflow. The last nodes will either activate or deactivate a workflow.

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.

This n8n workflow verifies the deliverability of mailing addresses stored in Groundhogg CRM by integrating with Lob’s address verification service. Who is this for? This template is designed for Groundhogg CRM 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 Groundhogg CRM Webhook sent to n8n Verify if the address is deliverable via LOB Report back to Groundhogg CRM Set Up Steps Watch this setup video: https://www.youtube.com/watch?v=nrV0P0Yz8FI Takes 10-30 minutes to set up Accounts Needed: Groundhogg CRM 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 Groundhogg CRM 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 Groundhogg CRM’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 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

Use GPT-3 to classify email responses in lemlist. And automate: Slack alerts when a lead is interested the creation of tasks when a lead is OOO unsubscription of leads when they request it

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 workflow will take an alert from Syncro, determine if it's an agent_offline_trigger type, then determine if it's a new alert or a close to an existing alert, and then submit it to OpsGenie. New alerts will create a new alert in OpsGenie and resolved alerts will close the alert in OpsGenie. It doesn't require any kind of Google Sheets because OpsGenie allows you to submit a unique ID (known as an alias) along with the alert, which can be referenced later when closing the alert. The trigger type can be changed to suit your needs. You will need to create an API integration in OpsGenie. In Syncro, in addition to setting up the appropriate notification to webhook, you will also need a script that closes the agent_offline_trigger alert and an automated remediation to trigger that script when the asset goes offline (the script is queued and run when the asset comes back online). > This workflow is part of an MSP collection, The original can be found here: https://github.com/bionemesis/n8nsyncro

This is the fourth workflow for the Mattermost Standup Bot. This workflow sends the team a message every morning to ask them three standup questions. What have you accomplished since your last report? What do you want to accomplish until your next report? Is anything blocking your progress? Once answered, the answers are sent to a Mattermost channel. The "Read Config" nodes will need to be updated to point to the ID of the "Standup Bot - Read Config" workflow and the "Override Config" node will need to point to "Standup Bot - Override Config"

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

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.

Who is this template for? This workflow template is designed for teams involved in training management and feedback analysis. It is particularly useful for: HR Departments**: Automating the collection and response to training feedback. Training Managers**: Streamlining the process of handling feedback and ensuring timely follow-up. Corporate Trainers**: Receiving direct feedback and taking actions to improve training sessions. This workflow offers a comprehensive solution for automating feedback management, ensuring timely responses, and improving the quality of training programs. How it works This workflow operates with an Airtable trigger but can be easily adapted to work with other triggers like webhooks from external applications. Once feedback data is captured, the workflow evaluates the feedback and directs it to the appropriate channel for action. Tasks are created in Usertask based on the feedback rating, and notifications are sent to relevant parties. Here’s a brief overview of this n8n workflow template: Airtable Trigger**: Captures new or updated feedback entries from Airtable. Switch Node**: Evaluates the feedback rating and directs the workflow based on the rating. Webhook**: Retrieves the result of a Usertask task. Task Creation**: Creates tasks in Usertask for poor feedback. Creates follow-up tasks for fair to good feedback. Documents positive feedback and posts recognition on LinkedIn for very good to excellent ratings. Notifications**: Sends email notifications to responsible parties for urgent actions. Sends congratulatory emails and posts on LinkedIn for positive feedback. To summarize Flexible Integration**: This workflow can be triggered by various methods like Airtable updates or webhooks from other applications. Automated Task Management**: It creates tasks in Usertask based on feedback ratings to ensure timely follow-up. Multichannel Notifications**: Sends notifications via email and LinkedIn to keep stakeholders informed and recognize successes. Comprehensive Feedback Handling**: Automates the evaluation and response to training feedback, improving efficiency and response time. Instructions: Set Up Airtable: Create a table in Airtable to capture training feedback. Configure n8n: Set up the Airtable trigger in n8n to capture new or updated feedback entries. Set Up Usertask: Configure the Usertask nodes in n8n to create and manage tasks based on feedback ratings. Configure Email and LinkedIn Nodes: Set up the email and LinkedIn nodes to send notifications and post updates. Test the Workflow: Run tests to ensure the workflow captures feedback, creates tasks, and sends notifications correctly. Video : https://youtu.be/U14MhTcpqeY Remember, this template was created in n8n v1.38.2.

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.

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.

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 ...

Use case Slackbots are super powerful. At n8n, we have been using them to get a lot done.. But it can become hard to manage and maintain many different operations that a workflow can do. This is the base workflow we use for our most powerful internal Slackbots. They handle a lot from running e2e tests for Github branch to deleting a user. By splitting the workflow into many subworkflows, we are able to handle each command seperately, making it easier to debug as well as support new usecases. In this template, you can find eveything to setup your own Slackbot (and I made it simple, there's only one node to configure 😉). After that, you need to build your commands directly. This bot can create a new thread on an alerts channel and respond there. Or reply directly to the user. It responds for help request to return a help page. It automatically handles unknown commands. It also supports flags and environment variables. For example /cloudbot-test info mutasem --full-info -e env=prod would give you the following info, when calling subworkflow. How to setup Add Slack command and point it up to the webhook. For example. Add the following to the Set config node alerts_channel with alerts channel to start threads on instance_url with this instance url to make it easy to debug slack_token with slack bot token to validate request slack_secret_signature with slack secret signature to validate request help_docs_url with help url to help users understand the commands Build other workflows to call and add them to commands in Set Config. Each command must be mapped to a workflow id with an Execute Workflow Trigger node Activate workflow 🚀 How to adjust Add your own commands. Depending on your need, you might need to lock down who can call this.

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. 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.

A robust n8n workflow designed to enhance Telegram bot functionality for user management and broadcasting. It facilitates automatic support ticket creation, efficient user data storage in Redis, and a sophisticated system for message forwarding and broadcasting. How It Works Telegram Bot Setup: Initiate the workflow with a Telegram bot configured for handling different chat types (private, supergroup, channel). User Data Management: Formats and updates user data, storing it in a Redis database for efficient retrieval and management. Support Ticket Creation: Automatically generates chat tickets for user messages and saves the corresponding topic IDs in Redis. Message Forwarding: Forwards new messages to the appropriate chat thread, or creates a new thread if none exists. Support Forum Management: Handles messages within a support forum, differentiating between various chat types and user statuses. Broadcasting System: Implements a broadcasting mechanism that sends channel posts to all previous bot users, with a system to filter out blocked users. Blocked User Management: Identifies and manages blocked users, preventing them from receiving broadcasted messages. Versatile Channel Handling: Ensures that messages from verified channels are properly managed and broadcasted to relevant users. Set Up Steps Estimated Time**: Around 30 minutes. Requirements**: A Telegram bot, a Redis database, and Telegram group/channel IDs are necessary. Configuration**: Input the Telegram bot token and relevant group/channel IDs. Configure message handling and user data processing according to your needs. Detailed Instructions**: Sticky notes within the workflow provide extensive setup information and guidance. Live Demo Workflow Bot: Telegram Bot Link (Click here) Support Group: Telegram Group Link (Click here) Broadcasting Channel: Telegram Channel Link (Click here) Keywords: n8n workflow, Telegram bot, chat ticket system, Redis database, message broadcasting, user data management, support forum automation

This n8n workflow is designed to analyze email headers received via a webhook. The workflow splits into two main paths based on the presence of the received and authentication results headers. In the first path, if received headers are present, the workflow extracts IP addresses from these headers and then queries the IP Quality Score API to gather information about the IP addresses, including fraud score, abuse history, organization, and more. Geolocation data is also obtained from the IP-API API. The workflow collects and aggregates this information for each IP address. In the second path, if authentication-results headers are present, the workflow extracts SPF, DKIM, and DMARC authentication results. It then evaluates these results and sets fields accordingly (e.g., SPF pass/fail/neutral). The paths merge their results, and the workflow responds to the original webhook with the aggregated analysis, including IP information and authentication results. Potential issues during setup include ensuring proper configuration of the webhook calls with header authentication, handling authentication and API keys for the IP Quality Score API, and addressing any discrepancies or errors in the logic nodes, such as handling SPF, DKIM, and DMARC results correctly. Additionally, thorough testing with various email header formats is essential to ensure accurate analysis and response.

I'm currently trialing a 4 day work week for all staff at my company, and one of the major impacts on productivity is interruptions. As such, I opted to use N8N to create a workflow to monitor my Google Calendar and when an event starts, to update my Slack status with an emote and the title of the calendar task. Additionally I opted to include to change the colour of Philips Hue lamp located in my living room where my wife is currently working so she know's if she can interrupt me or not. My calendar is built on the theory behind the Diary Detox system and as such the Slack Status reflect the colours involved. This was achieved using the emote aliases for the relevant colour circles. The Philips Hue lamp status is changed via the local API with Home Assistant. This is a very similiar process to controlling it with something like the Streamdeck, but the workflow calls the Webhook instead of the Streamdeck. This process can be found in lots of Youtube videos such as this. This gives my wife a very quick and easy way to know if she can interrupt me in my office (when the lights are Green or Blue) or when I'm busy (Red). Please Note: The above images are not intended to be an incentive to create your own Squid Games. Additionally, when integrating Slack with N8N, there are 2 x APIs which can be used. Typically the Bot User OAuth Token is used, however in order for your Status to be updated, the User OAuth Token must be used with the users.profile:read and users.profile:write permissions enabled. For clarity, I have removed the Webhooks from the Workflow as this would allow any person to control my lights. These can be inserted in the HTTP Request nodes. Each node responds to a different automation within the Home Assistant infrastructure. Acknowledgement: I would also credit Jon (Discord) aka 8668 (Workflows) for writing the Function node which turns the ColorID into a named variable.

This n8n workflow demonstrates how to build a simple uptime monitoring service using scheduled triggers. Useful for webmasters with a handful of sites who want a cost-effective solution without the need for all the bells and whistles. How it works Scheduled trigger reads a list of website urls in a Google Sheet every 5 minutes Each website url is checked using the HTTP node which determines if the website is either in the UP or DOWN state. An email and Slack message are sent for websites which are in the DOWN state. The Google Sheet is updated with the website's state and a log created. Logs can be used to determine total % of UP and DOWN time over a period. Requirements Google Sheet for storing websites to monitor and their states Gmail for email alerts Slack for channel alerts Customising the workflow Don't use Google Sheets? This can easily be exchanged with Excel or Airtable.

Overview The [n8n] YouTube Channel Advanced RSS Feeds Generator workflow facilitates the generation of various RSS feed formats for YouTube channels without requiring API access or administrative permissions. It utilizes third-party services to extract data, making it extremely user-friendly and accessible. Key Use Cases and Benefits Content Aggregation**: Easily gather and syndicate content from any public YouTube channel. No API Key Required**: Avoid the complexities and limitations of Google's API. Multiple Formats**: Supports ATOM, JSON, MRSS, Plaintext, Sfeed, and direct YouTube XML feeds. Flexibility**: Input can be a YouTube channel or video URL, ID, or username. Services/APIs Utilized This workflow integrates with: commentpicker.com**: For retrieving YouTube channel IDs. rss-bridge.org**: To generate various RSS formats. Configuration Instructions Start the Workflow: Activate the workflow in your n8n instance. Input Details: Enter the YouTube channel or video URL, ID, or username via the provided form trigger. Run the Workflow: Execute the workflow to receive links to 13 different RSS feeds, including community and video content feeds. Screenshots Additional Notes Customization**: You can modify the RSS feed formats or integrate additional services as needed. Support and Contributions For support, questions, or contributions, please visit the n8n community forum or the GitHub repository. We welcome contributions from the community!

This workflow assigns a user to an issue if they include "assign me" when opening or commenting. To use this workflow you will need to update the credentials used for the Github nodes.

This workflow automatically deletes user data from different apps/services when a specific slash command is issued in Slack. Watch this talk and demo to learn more about this use case. The demo uses Slack, but Mattermost is Slack-compatible, so you can also connect Mattermost in this workflow. Prerequisites Accounts and credentials for the apps/services you want to use. Some basic knowledge of JavaScript. Nodes Webhook node triggers the workflow when a Slack slash command is issued. IF nodes confirm Slack's verification token and verify that the data has the expected format. Set node simplifies the payload. Switch node chooses the correct path for the operation to perform. Respond to Webhook nodes send responses back to Slack. Execute Workflow nodes call sub-workflows tailored to deleting data from each individual service. Function node, Crypto node, and Airtable node generate and store a log entry containing a hash value. HTTP Request node sends the final response back to Slack.

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

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

This 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.

This workflow creates/updates/deletes a Notion database page when an issue is created/updated/deleted in Jira. Subsequent updates to the issue's title or status in Jira are updated in the Notion database. If you require more fields to send to Notion, this template is easily extendible which will be described in setup. The Notion database will require setup before the workflow can be used. Prerequisites Notion account and Notion credentials. Jira account and Jira credentials. How it works When a new issue is created in Jira, the workflow creates a new page in the Notion database will all the required fields. When the issue's title or status is updated in Jira, the workflow updates the specific Notion database page identified by the "Issue Key" field in Notion. If the status in Jira is set to "Done", the workflow will mark the Notion database page "Done" field as true. When the issue is deleted in Jira, the workflow archives the Notion database page. Setup This workflow requires that you set up a Notion database. To do so, follow the steps below: In Notion, create a new database. Add the following columns to the database: Done (with type "Checkbox") Title (renamed from "Name") Status (with the following options: "To Do", "In Progress", "Done") Link (with type "URL") Issue ID (with type "Number") Issue Key (with type "Text") Add any other fields you require to the database. Your database should look something like this Share the database to n8n. By default, the workflow will fill all the fields provided above, except for any other additional fields you add.

Use Case This workflow is a slight variation of a workflow we're using at n8n. In most companies, employees have a lot of great ideas. That was the same for us at n8n. We wanted to make it as easy as possible to allow everyone to add their ideas to some formatted database - it should be somewhere where everyone is all the time and could add a new idea without much extra effort. Since we're using Slack, this seemed to be the perfect place to easily add ideas. In this example, we're adding the ideas to Google Sheets instead of Notion, like we do. What this workflow does This workflow waits for a webhook call within Slack, that gets fired when users use the /idea command on a bot that you will create as part of this template. It then checks the command, adds the idea to Google Sheets and notifies the user about the newly added idea as you can see below: Creating your Slack bot Visit https://api.slack.com/apps, click on New App and choose a name and workspace. Click on OAuth & Permissions and scroll down to Scopes -> Bot token Scopes Add the chat:write scope Head over to Slash Commands and click on Create New Command Use /idea as the command Copy the test URL from the Webhook node into Request URL Add whatever feels best to the description and usage hint Go to Install app and click install Setup Create a Google Sheets document with the columns Name and Creator Add your Google credentials Fill the Set me up node. Create your Slack app (see other sticky) Click Test workflow and use the /idea comment in Slack Activate the workflow and exchange the Request URL with the production URL from the webhook How to adjust it to your needs You can adjust the table in Google Sheets and for example, add different types of ideas or areas that they impact Rename the Slack command as it works best for you How to enhance this workflow At n8n we use this workflow in combination with some others. E.g. we have the following things on top: We additionally have a /bug Slack command that adds a new bug to Linear. Here we're using AI to classify the bugs and move it to the right team. (Bug command workflow and Ai Classifier workflow) We also added other types, like /pain to be less solution-driven To make it easier for everyone to give input, we added a Votes column that allows everyone to vote on ideas/pain points in the list We're also running a workflow once a week that highlights the most popular new ideas and the most active voters

This workflow extends n8n and uses R language graphic capabilities. This is a Telegram bot which fetches weather data via the openweathermap.org API, plots an image using ggoplot2 package from R and sends the image to the Telegram user.

Use Case In most companies, employees have a lot of great ideas. That was the same for us at n8n. We wanted to make it as easy as possible to allow everyone to add their ideas to some formatted database - it should be somewhere where everyone is all the time and could add a new idea without much extra effort. Since we're using Slack, this seemed to be the perfect place to easily add ideas and collect them in Notion. What this workflow does This workflow waits for a webhook call within Slack, that gets fired when users use the /idea command on a bot that you will create as part of this template. It then checks the command, adds the idea to Notion, and notifies the user about the newly added idea as you can see below: Creating your Slack bot Visit https://api.slack.com/apps, click on New App and choose a name and workspace. Click on OAuth & Permissions and scroll down to Scopes -> Bot token Scopes Add the chat:write scope Head over to Slash Commands and click on Create New Command Use /idea as the command Copy the test URL from the Webhook node into Request URL Add whatever feels best to the description and usage hint Go to Install app and click install Setup Add a Database in Notion with the columns Name and Creator Add your Notion credentials and add the integration to your Notion page. Fill the setup node below Create your Slack app (see other sticky) Click Test workflow and use the /idea comment in Slack Activate the workflow and exchange the Request URL with the production URL from the webhook How to adjust it to your needs You can adjust the table in Notion and for example, add different types of ideas or areas that they impact You might wanna add different templates in Notion to make it easier for users to fill their ideas with details Rename the Slack command as it works best for you How to enhance this workflow At n8n we use this workflow in combination with some others. E.g. we have the following things on top: We additionally have a /bug Slack command that adds a new bug to Linear. Here we're using AI to classify the bugs and move it to the right team. (see this template and this template) We also added other types, like /pain to be less solution-driven To make it easier for everyone to give input, we added a Votes column that allows everyone to vote on ideas/pain points in the list We're also running a workflow once a week that highlights the most popular new ideas and the most active voters (see here)

This n8n workflow is designed for security monitoring and incident response when suspicious login events are detected. It can be initiated either manually from within the n8n UI for testing or automatically triggered by a webhook when a new login event occurs. The workflow first extracts relevant data from the incoming webhook payload, including the IP address, user agent, timestamp, URL, and user ID. It then splits into three parallel processing paths. In the first path, it queries GreyNoise's Community API to retrieve information about the investigated IP address. Depending on the classification and trust level received from GreyNoise, the alert is given a High, Medium, or Low priority. This priority is assigned based on the best practices documentation from GreyNoise on how to apply their data to analysis. Once a priority is assigned, a message is sent to a Slack channel to notify users about the alert. The second path involves fetching geolocation data about the IP address using IP-API's Geolocation API and merging it with data from the UserParser node. This data is then combined with the data obtained from GreyNoise. In the third path, the UserParser node queries the Userparser IP address and user agent lookup API to obtain information about the user's IP and user agent. This data is merged with the IP-API data and GreyNoise data. The workflow then checks if the IP address is considered an unknown threat by examining both the noise and riot fields from GreyNoise. If it is considered an unknown threat, the workflow proceeds to retrieve the last 10 login records for the same user from a Postgres database. If there are any discrepancies in the login information, indicating a new location or device/browser, the user is informed via email. Potential issues when setting up this workflow include ensuring that credentials are correctly entered for GreyNoise and UserParser nodes, and addressing any discrepancies in the data sources that could lead to false positives or negatives in threat detection. Additionally, the usage of hardcoded API keys should be replaced with credentials for security and flexibility. Thorough testing and validation with sample data are crucial to ensure the workflow performs as expected and aligns with security incident response procedures.

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.

Use case To guarantee an effective sales process deals must be distributed between sales reps in the best way. Normally, this involves manually assigning new deals that have come in. This workflow automates it for you! What this workflow does This workflow runs once a day and checks for unassigned deals in your Hubspot CRM. Once it finds one, it enriches the deal with information about the assigned contact and their company. It then checks the region of the assigned company before looking at the company's employee size. Based on this, it assigns the deal to the right sales rep within your company. Requirements New deals in Hubspot need to be unassigned in the beginning New deals have to have an attached contact that has an attached company in Hubspot The company needs to have values for region and employee count in Hubspot Setup The setup is quite straight forward and will probably take a few minutes only. Add your Hubspot credentials Customize your criterias for assigning deals in the Assign by Region and the following Assign nodes Make sure deals are assigned to the right salesrep in the Hubspot nodes at the end Activate the workflow Customizing this to your needs Adjust the trigger interval to your needs. Currently, it defaults to once a day Adjust your region settings by adding/updating/removing options in the respective node Adjust your employee size settings by adding/updating/removing options in the respective node Ideas to enhance this flow Wrap each region's assigned criteria into different sub-workflows for easier maintainability. This will not consume additional execution counts. Add more logic on what happens once a deal does not match any criteria you've set

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.

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.

Have you ever wanted to throttle Plex when connecting remotely to your server? Well here is the script for you! The instructions to deploy are below: You will need: A plex server with Plex Pass (for webhooks) n8n running locally (either in docker on via the desktop app) Qbittorent with WebUI enabled Begin by installing n8n by visiting n8n.io. You can install the desktop version or the docker version, whichever works best for your but I'm doing this on my desktop version of n8n. Copy the code from this page into your n8n install canvas. You should see the script appear before your eyes. From there, you Double click on the Webhook node at the beginning of the script. Copy both the Test and Production URLs that appear there. Now make your way to Plex and visit your settings. On the left, you should see the webhooks option if you have Plex Pass. This will setup your triggers. Next visit your qBitTorrent instance and enable WebUI. Notate your Username, Password, and Port. You will also need to know the IP of the machine that qbittorent is running on. If you have an iPhone you can connect to the same wireless network as your computer and use the Fing app to scan the network for the IP. Open up the script and edit the Global Variables to reflect the values you copied. Hit save at the top right, and then activate the script. Enjoy!!