Gmail and Slack integration

Workflow Description This workflow automates the process of retrieving emails from a food delivery platform, extracting key order details, and sending notifications to a Slack channel. Additionally, the Slack message includes a Moze accounting app URL scheme link for quick expense tracking. Key Features Manual Trigger: Allows the workflow to be executed manually for immediate testing. Gmail Integration: Retrieves emails containing specific keywords in the subject line (e.g., "透過 Uber Eats 系統送出的訂單"). (You can adjust the keywords to fit your language.) Data Extraction: Parses the email content to extract key details such as: Order price Shop name Order date and time Slack Notification: Sends a notification to a specified Slack channel using a structured block format, including a link to record the expense in the Moze accounting app. Node Configurations Manual Trigger Purpose**: Starts the workflow manually for testing or immediate execution. Configuration**: No setup needed. Gmail Trigger Purpose**: Automatically polls Gmail for new emails matching specific subject keywords. Configuration**: Filters: q: subject:透過 Uber Eats 系統送出的訂單 (You can adjust the keywords to fit your language.) Polling Frequency: Every hour at 30 minutes past the hour. Credentials: Linked Gmail account. Extract Price, Shop, Date, Time Purpose**: Extracts key information from the email content using regular expressions. Extracted Data**: price: Order price (e.g., $200). shop: Shop name (e.g., "店名"). date: Order date (e.g., 2024.01.01). time: Order time converted to 24-hour format (e.g., 14:30). Slack Notification Purpose**: Sends a formatted message to a Slack channel with extracted order details. Message Content**: Text: Ubereat 訂餐資訊: 商家: {{ shop }} 金額: {{ price }} 日期: {{ date }} Moze App Link: Includes a clickable button in the Slack message with a pre-filled Moze app URL scheme: moze3://expense?amount={{ price }}&account=信用卡&subcategory=外送&store={{ shop }}&date={{ date }}&time={{ time }}&project=生活開銷 Channel: Slack channel ID associated with food delivery notifications. Additional Notes Customization**: Adjust the email subject filter (subject) to match other types of food delivery platforms or services. Error Handling**: Ensure regular expressions for data extraction match the email format. Test with sample emails before deployment. Moze URL Scheme Reference**: Learn more about Moze app URL schemes for customization by visiting the Moze Documentation. This workflow is ideal for automating expense tracking and centralizing notifications for food delivery orders, streamlining personal or team expense management. Image: UberEat Gmail with order information Slack text with button Click the button will call moze url scheme 工作流程描述 此工作流程自動化從外送平台獲取郵件，提取關鍵訂單詳細資訊，並將通知發送到指定的 Slack 頻道。此外，Slack 消息中包含一個 Moze 記帳 App URL Scheme 的連結，方便快速記帳。 主要功能 Manual Trigger：允許手動執行工作流程，方便測試。 Gmail Integration：從 Gmail 中提取包含特定關鍵字（例如：「透過 Uber Eats 系統送出的訂單」）的郵件。 資料提取：解析郵件內容，提取以下關鍵資訊： 訂單金額 商家名稱 訂單日期與時間 Slack 通知：將結構化的通知發送到指定的 Slack 頻道，並包含一個連結供用戶快速記帳。 節點設定 Manual Trigger 用途**：手動啟動工作流程以進行測試或即時執行。 設定**：無需額外設定。 Gmail Trigger 用途**：自動檢查 Gmail 中是否有符合特定主題關鍵字的新郵件。 設定**： 篩選條件： q: subject:透過 Uber Eats 系統送出的訂單 檢查頻率：每小時的 30 分。 憑證：已連結的 Gmail 帳號。 Extract Price, Shop, Date, Time 用途**：使用正則表達式從郵件內容中提取關鍵資訊。 提取的資料**： price：訂單金額（例如：$200）。 shop：商家名稱（例如：「店名」）。 date：訂單日期（例如：2024.01.01）。 time：訂單時間（24 小時制，例如：14:30）。 Slack 通知 用途**：將訂單詳細資訊以格式化消息發送到 Slack。 消息內容**： 文字： Ubereat 訂餐資訊: 商家: {{ shop }} 金額: {{ price }} 日期: {{ date }} Moze App 連結：Slack 消息中包含一個可點擊按鈕，預填 Moze App URL Scheme： moze3://expense?amount={{ price }}&account=信用卡&subcategory=外送&store={{ shop }}&date={{ date }}&time={{ time }}&project=生活開銷 頻道：與外送通知相關的 Slack 頻道。 補充說明 自訂化**：可調整郵件主題篩選條件（subject），以匹配其他外送平台或服務。 錯誤處理**：確保正則表達式匹配郵件格式。在部署前使用樣本郵件進行測試。 Moze URL Scheme 參考**：了解更多關於 Moze App URL Scheme 的客製化資訊，請參閱 Moze 官方文件。 此工作流程適合自動化費用記帳以及集中管理外送訂單通知，提升個人或團隊的費用管理效率。

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. Also, this workflow is designed for non-English Google Meet recordings. If you record Google Meet conferences in English, you can use the native transcription feature and work directly with the transcript file, bypassing most of this workflow. 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. Processes the recording via one of the following paths (choose the path based on whether you record meetings with subtitles or not): Convert MP4 to MP3: If ffmpeg is available, the recording is converted to MP3 format and processed through OpenAI for transcription. Extract Subtitles: If subtitles are included in the Google Meet recording, they are extracted directly as a text file, bypassing the need for transcription and saving costs. Summarizes the meeting and generates a professional follow-up email draft in Gmail, ready for your review and customization.

This workflow was presented at the AI Developers meet up in San Fransico on 24 July, 2024. AI workflows Categorize incoming Gmail emails and assign custom Gmail labels. This example uses the Text Classifier node, simplifying this usecase. Ingest a PDF into a Pinecone vector store and chat with it (RAG example) AI Agent example showcasing the HTTP Request tool. We teach the agent how to check availability on a Google Calendar and book an appointment.

YouTube to X Post Overview This n8n workflow automates the process of promoting your latest YouTube videos on X (formerly Twitter). It ensures that posts are engaging, concise, and follow platform-specific requirements. Additionally, the workflow logs social posts into a Google Sheet for record-keeping. Features Fetch Latest YouTube Videos:** Pulls recently uploaded videos from a specified channel. Generate Engaging X Posts:** Uses OpenAI's GPT-4 to create tailored, witty posts about your videos. Character Limit Validation:** Ensures posts comply with X's character limit by rewriting if necessary. Post Scheduling:** Automates post publishing to X. Google Sheets Integration:** Logs posts and their status for tracking and management. Optional Notifications:** Sends updates via Discord, Slack, or Gmail (disabled by default). How It Works Trigger: Manually trigger the workflow or set a scheduled check for new videos (disabled by default). Fetch YouTube Videos: Retrieves the latest videos from your YouTube channel, filtering duplicates. Content Creation: OpenAI generates a witty and humanized post under 220 characters, using video title and description. If the post exceeds the character limit, it is rewritten automatically. Google Sheets Logging: Logs the generated post to a Google Sheet with details like time, date, and post status. Post to X: Publishes the generated post on X. Updates the Google Sheet with the post URL. Optional Notifications: Sends notifications about the published post via Discord, Slack, or Gmail. Setup Instructions Credentials: Add credentials for: YouTube API OpenAI API Google Sheets API X (formerly Twitter) API Use the accounts associated with "AlexK1919." YouTube Node: Specify your YouTube Channel ID in the Fetch Latest Videos node. Find your Channel ID here. Google Sheets Node: Configure the node with your Google Sheet for logging posts. Use the linked sheet: AlexK1919 Social Posts. OpenAI Node: Set up your OpenAI API key for generating posts. X Post Node: Connect your X account to the Post to X node. Optional Notifications: Configure Discord, Slack, or Gmail nodes for custom notifications. Customization Schedule:** Enable and modify the Check Every 2 Hours node to automatically check for new videos. Post Format:** Edit the OpenAI prompt in the Generate X Post node to tweak the tone or style of the generated posts. Additional Platforms:** Expand this workflow to post on other social platforms by adding respective nodes (e.g., Facebook, LinkedIn). Notes Posts are validated for character limits but are restricted to 220 characters to ensure compliance with X's guidelines and leave space for links. Posts are logged in the Google Sheet with details, including post status and timestamps. Current integrations are focused on promoting YouTube content; additional types can be supported with minor adjustments. Contact For support or inquiries: Alex Kim** About Me

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.

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 account to use AI services. Customising the workflow OpenAI assistants is only one approach to hosting a company knowledgebase for AI to use. Exploring different solutions such as building your own RAG-powered database can sometimes yield better results in terms of control of how the data is managed and cost.