AI Automation
923 Ergebnisse — ausschließlich quellenverknüpfte n8n-Referenzen
WSpeed Up Social Media Banners With BannerBear.com
This n8n workflow shows an easy way to automate the creation of social media assets using AI and a service like BannerBear. Designed for the busy marketer, leveraging AI image generation capabilities can help cut down production times and allow reinvesting into higher quality content. How it works This workflow generates social media banners for online events. Using a form trigger, a user can define the banner text and suggest an image to be generated. This request is passed to OpenAI's Dalle-3 image generation service to produce a relevant graphic for the event banner. This generated image is uploaded and sent to BannerBear where a template will use it and the rest of the form data to produce the banner. BannerBear returns the final banner which can now be used in an assortment of posts and publications. Requirements A BannerBear.com account and template is required An OpenAI account to use the Dalle-3 service. Customising the workflow We've only shown a small section of what BannerBear has to offer. With experimentation and other asset generating services such as AI audio and video, you should be able to generate more than just static banners!
Automate Your RFP Process with OpenAI Assistants
This n8n workflow demonstrates how to automate oftern time-consuming form filling tasks in the early stages of the tendering process; the Request for Proposal document or "RFP". It does this by utilising a company's knowledgebase to generating question-and-answer pairs using Large Language Models. How it works A buyer's RFP is submitted to the workflow as a digital document that can be parsed. Our first AI agent scans and extracts all questions from the document into list form. The supplier sets up an OpenAI assistant prior loaded with company brand, marketing and technical documents. The workflow loops through each of the buyer's questions and poses these to the OpenAI assistant. The assistant's answers are captured until all questions are satisified and are then exported into a new document for review. A sales team member is then able to use this document to respond quickly to the RFP before their competitors. Example Webhook Request curl --location 'https://<n8n_webhook_url>' \ --form 'id="RFP001"' \ --form 'title="BlueChip Travel and StarBus Web Services"' \ --form 'reply_to="[email protected]"' \ --form 'data=@"k9pnbALxX/RFP Questionnaire.pdf"' Requirements An OpenAI accou
WInvoice data extraction with LlamaParse and OpenAI
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 alth
Enrich Pipedrive's Organization Data with OpenAI GPT-4o & Notify it in Slack
This workflow enriches new Pipedrive organization's data by adding a note to the organization object in Pipedrive. It assumes there is a custom "website" field in your Pipedrive setup, as data will be scraped from this website to generate a note using OpenAI. Then, a notification is sent in Slack. ⚠️ Disclaimer This workflow uses a scraping API. Before using it, ensure you comply with the regulations regarding web scraping in your country or state. Important Notes The OpenAI model used is GPT-4o, chosen for its large input token capacity. However, it is not the cheapest model if cost is very important to you. The system prompt in the OpenAI Node generates output with relevant information, but feel free to improve or modify it according to your needs. How It Works Node 1: Pipedrive Trigger - An Organization is Created This is the trigger of the workflow. When an organization object is created in Pipedrive, this node is triggered and retrieves the data. Make sure you have a "website" custom field in Pipedrive (the name of the field in the n8n node will appear as a random ID and not with the Pipedrive custom field name). Node 2: ScrapingBee - Get Organization's Website's Homepage Cont
WAutonomous AI crawler
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 a
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Talk to your SQLite database with a LangChain AI Agent 🧠💬
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.n8
Store Notion's Pages as Vector Documents into Supabase with OpenAI
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 the
Automate LinkedIn Outreach with Notion and OpenAI
This template is based on the following template. Thank you for the groundwork, Matheus. How it works: Store your snippets of text in a Notion table. Each snippet should have an image associated with it (copy + pasted into the text) Connect to your table via a Notion "integration", from which N8N can then query your pre-meditated posts The text is fed through an OpenAI assistant to boost engagement via formatting The re-formatted text along with the image pulled from the Notion snippet are combined into a post for your LinkedIn The row in the original Notion table from step 1 containing this post is set to a status of "Done" Set up steps: You will need to create a Notion "integration", which will yield a "secret key" which you enter into your N8N as a "Credential". You will need to create a LinkedIn "app" in order to post on your behalf. When creating your LinkedIn "app", you will be required to link this "app" to a company page on LinkedIn. If you are doing this for yourself, seach for the "Default Company Payge (for API testing)", and select this page as it is provided by LinkedIn for individuals. You can find your LinkedIn apps here, and if you get stuck, further instructions on
Classify lemlist replies using OpenAI and automate reply handling
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 ...
Gmail AI Auto-Responder: Create Draft Replies to incoming emails
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 h
WShare YouTube Videos with AI Summaries on Discord
Boost engagement on your Discord server by automatically sharing new YouTube videos along with AI generated summaries of their content. This workflow is ideal for content creators and community managers looking to provide value and spark interest through summarized content, making it easier for community members to decide if a video is of interest to them. Watch this video tutorial to learn more about the template. How it works RSS Feed Trigger**: Monitors your YouTube channel for new uploads using the RSS feed. Video Captions Retrieval**: Fetches video captions using the YouTube API to get detailed content data. AI Summary Generation**: Uses an AI model to generate concise summaries from the video captions, highlighting key points. Discord Notification**: Posts video announcements along with their AI generated summaries to a specified Discord channel using a webhook. Set up steps Configure YouTube RSS Feed: Set up the RSS feed node to detect new video uploads. Add your YouTube channel ID to the URL in the first node: https://www.youtube.com/feeds/videos.xml?channel_id=YOUR_CHANNEL_ID. Connect OpenAI Account: To enable AI summary generation, connect your OpenAI account in n8n. Set
Post New YouTube Videos to X
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
Automated AI image analysis and response via Telegram
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. Configurati
AI-Powered Children's Arabic Storytelling on Telegram
Template for Kids' Story in Arabic The n8n template for creating kids' stories in Arabic offers a versatile platform for storytellers to captivate young audiences with educational and interactive tales. It allows for customization to suit various use cases and can be set up effortlessly. Check this example: https://t.me/st0ries95 Use Cases Educational Platforms: Educational platforms can automate the creation and distribution of educational stories in Arabic for children using this template. By incorporating visual and auditory elements into the storytelling process, educational platforms can enhance learning experiences and engage young learners effectively. Children's Libraries: Children's libraries can utilize this template to curate and share a diverse collection of Arabic stories with young readers. The automated generation of visual content and audio files enhances the storytelling experience, encouraging children to immerse themselves in new worlds and characters through captivating narratives. Language Learning Apps: Language learning apps focused on Arabic can integrate this template to offer culturally rich storytelling experiences for children learning the language. By t
AI-Powered Children's English Storytelling on Telegram with OpenAI
Unleashing Creativity: Transforming Children's English Storytelling with Automation and AI Check this example: https://t.me/st0ries95 Summary In the realm of children's storytelling, automation is revolutionizing the way captivating tales are created and shared. This article highlights the transformative power of setting up a workflow for AI-powered children's English storytelling on Telegram. By delving into the use cases and steps involved, we uncover how this innovative approach is inspiring young minds and fostering a love for storytelling in children. Usecase The workflow for children's stories is a game-changer for content creators, educators, and parents seeking to engage children through imaginative and educational storytelling. Here's how this workflow is making a difference: Streamlined Content Creation: By providing a structured framework and automation for story generation, audio creation, and image production, the workflow simplifies the process of crafting captivating children's stories. Enhanced Educational Resources: Teachers can leverage this workflow to develop interactive educational materials that incorporate storytelling, making learning more engaging for stude
WTransforming Emails into Podcasts
Transforming Emails into Podcasts 🎙️ Check out this channel for example. The n8n workflow described here aims to revolutionize the way users engage with promotional emails by converting them into entertaining audio podcasts. This innovative project leverages automation through n8n to streamline tasks and enhance user experience. Project Benefit 🎧🌟 The primary goal of this project is to transform "CATEGORY_PROMOTIONS" emails into engaging audio content. By converting text into speech, users can enjoy promotional material hands-free, making it easier to consume information while on the go or relaxing. The workflow consists of several key steps orchestrated seamlessly to deliver a delightful experience to users. How to Use the Workflow: Gmail trigger Node: Initiates the workflow by fetching "CATEGORY_PROMOTIONS" emails at regular intervals. The Gmail Trigger node in your N8N workflow is set to poll for new emails every minute and is configured to filter emails with the label "CATEGORY_PROMOTIONS" before triggering the workflow. Steps to Use Filters Inside the Gmail Trigger Node: Configure Gmail Trigger Node: Set "Poll Times" to "Every Minute" to check for new emails at regular inte
Configure your own Image Creation API Using OpenAI DALLE-3
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.
Image Creation with OpenAI and Telegram
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 anal
Automate Screenshots with URLbox & Analyze them with AI
In this automation we first make a screenshot with a screenshot API called URLbox and then send this screenshot into the OpenAI API and analyze it. You can extend this automation by the way you want to ingest the website url's & names into this workflow. Options as data source: Postgres Google Sheets Your CRM ... Setup: Replace Website & URL in Setup Node Put in your URLbox API Key Put in your OpenAI credentials Click here for a blog article with more information on the automation.
Translate Telegram audio messages with AI (55 supported languages)
Use case This workflow enables a Telegram bot that can: Accept speech input in one of 55 supported languages Automatically detect the language spoken and translate the speech to another language Responds back with the translated speech output. This allows users to communicate across language barriers by simply speaking to the bot, which will handle the translation seamlessly. How does it work? Translation In the translation step the workflow converts the user's speech input to text and detects the language of the input text. If it's English, it will translate to French. If it's French, it will translate to English. To change the default translation languages, you can update the prompt in the AI node. Output In the output step, we provide the translated text output back to the user and speech output is generated in the translated language. Setup steps Obtain Telegram API Token Start a chat with the BotFather. Enter /newbot and reply with your new bot's display name and username. Copy the bot token and use it in the Telegram node credentials in n8n. Update the Settings node to customize the desired languages Activate the flow Full list of supported languages All supported languages:
OpenAI Assistant workflow: upload file, create an Assistant, chat with it!
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
WCompose reply draft in Gmail with OpenAI Assistant
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
Auto-label incoming Gmail messages with AI nodes
This workflow uses AI to analyze the content of every new message in Gmail and then assigns specific labels, according to the context of the email. Default configuration of the workflow includes 3 labels: „Partnership” - email about sponsored content or cooperation, „Inquiry” - email about products, services, „Notification” - email that doesn't require response. You can add or edit labels and descriptions according to your use case. 🎬 See this workflow in action in my YouTube video about automating Gmail. How it works? Gmail trigger performs polling every minute for new messages (you can change the trigger interval according to your needs). The email content is then downloaded and forwarded to an AI chain. 💡 The prompt in the AI chain node includes instructions for applying labels according to the email content - change label names and instructions to fit your use case. Next, the workflow retrieves all labels from the Gmail account and compares them with the label names returned from the AI chain. Label IDs are aggregated and applied to processed email messages. ⚠️ Label names in the Gmail account and workflow (prompt, JSON schema) must be the same. Set up steps Set credentials f
CWAssistant for Hubspot Chat using OpenAi and Airtable
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.