Workflow Templates

About: This workflow automates the transcription of YouTube videos by processing a video URL provided via a chat message. Designed for users who need quick access to video content in text form, this workflow ensures a seamless experience for transcribing videos on demand, regardless of the topic. Who is this for? This workflow is designed for individuals who need quick and accurate transcriptions of YouTube videos without watching them in full. It is particularly useful for: Students who need text-based notes from educational videos. Researchers looking to extract information from lectures or discussions. Professionals who prefer reading over watching videos. Casual users who want an efficient way to summarize video content. What problem is this workflow solving? Manually transcribing YouTube videos is time-consuming and prone to errors. Watching long videos just to extract key information is inefficient. This workflow automates transcription, allowing users to quickly convert video content into text. Use cases include: Summarizing lectures or webinars. Extracting insights from interviews and discussions. Creating searchable text from video content. Generating reference material without watching entire videos. What This Workflow Does? This workflow automates the transcription of YouTube videos by: Accepting Input: User provide a YouTube video URL through a chat message. Processing the Video: It utilizes an external transcription service to retrieve the full transcript of the YouTube video from the provided URL. Enhancing Output: An AI model (OpenAI) refines the transcription for accuracy and readability. Delivering Results: The final text transcript is returned to the user via the chat interface. Setup: Install n8n: Ensure you have n8n installed and running. Import the Workflow: Copy the JSON workflow file into your n8n instance. Configure API Keys: Set up your Supadata (Supadata) API key for transcription. Configure the OpenAI (OpenAI) API key for additional processing. Run the Workflow: Provide a YouTube video URL and receive a transcription in response. How to customize this workflow to your needs: The workflow is flexible and can be tailored to suit specific requirements. Here are some customization ideas: Language Support:** Adjust the transcription language in both the HTTP Request and OpenAI nodes to support transcriptions in different languages (e.g., French, German). Integrate with Other Services:** Store transcriptions in a database, send them via email, or connect with a document management system. Notification:** Add a notification node (e.g., email or Slack) to alert you when the transcription is complete, especially for long videos. Quality Check:** Integrate an additional AI step to summarize or highlight key points in the transcript for quicker insights. This workflow is designed to be scalable, efficient, and adaptable to various transcription needs. Limitations Video Length Limitation:** Very long videos may not have a complete transcription due to constraints in processing capacity or service limitations. Transcription Dependency:** The accuracy of the transcription relies entirely on the presence of video captions or subtitles. If a video lacks these, no transcription will be generated. Access Restrictions:** Private or restricted YouTube videos may not be accessible for transcription due to permission limitations. Processing Time:** The time required to process a video can vary significantly, especially for longer videos, depending on the transcription service and server resources. Regional Restrictions:** Some YouTube videos may have geographic or regional access limitations, which could prevent the workflow from retrieving the content for transcription.

In this guide, we’ll walk you through setting up an AI-driven workflow that automatically processes highly-rated food photos from a Google Sheet, generates AI-powered captions, shares them to Pinterest, and updates the sheet to reflect the posts. Ready to automate your food photo sharing? Let’s dive in! What’s the Goal? Automatically detect and process highly-rated food photos (4 stars or above) from a Google Sheet. Use AI to generate engaging and relevant captions. Share the photos with captions to Pinterest via the Pinterest API. Update the Google Sheet to mark photos as posted. Enable scheduled automation for consistent posting. By the end, you’ll have a self-running system that shares your best food photos effortlessly. Why Does It Matter? Manual photo sharing is time-consuming and inconsistent. Here’s why this workflow is a game changer: Zero Human Error**: AI ensures consistent captions and posting accuracy. Time-Saving Automation**: Automatically handle photo sharing, boosting efficiency. Scheduled Posting**: Maintain a regular presence on Pinterest without manual effort. Focus on Creativity**: Free your team from repetitive posting tasks. Think of it as your tireless social media assistant that keeps your Pinterest feed vibrant. How It Works Here’s the step-by-step magic behind the automation: Step 1: Trigger the Workflow Detect new photos to post using the Daily Post Scheduler node (e.g., once daily). Initiate the workflow at a scheduled time to check for new food photos. Step 2: Fetch Food Photos from Sheet Retrieve rows from the Google Sheet that contain food photo metadata like image URLs, ratings, and status. Step 3: Filter 4+ Star Dishes Filter only those food entries with high ratings (4 stars or above) and unposted status. Step 4: AI Caption Generator Use AI (e.g., GPT/OpenAI) to create engaging and relevant captions for selected food photos. Step 5: Upload to Pinterest Automatically post the food photo with the generated caption to Pinterest via the Pinterest API. Step 6: Mark as Posted in Sheet Update the Google Sheet to reflect that the photo has been successfully shared. How to Use the Workflow? Importing a workflow in n8n is a straightforward process that allows you to use pre-built workflows to save time. Below is a step-by-step guide to importing the Automated Food Photo Sharing workflow in n8n. Steps to Import a Workflow in n8n Obtain the Workflow JSON Source the Workflow: Workflows are shared as JSON files or code snippets, e.g., from the n8n community, a colleague, or exported from another n8n instance. Format: Ensure you have the workflow in JSON format, either as a file (e.g., workflow.json) or copied text. Access the n8n Workflow Editor Log in to n8n (via n8n Cloud or self-hosted instance). Navigate to the Workflows tab in the n8n dashboard. Click Add Workflow to create a blank workflow. Import the Workflow Option 1: Import via JSON Code (Clipboard): Click the three dots (⋯) in the top-right corner to open the menu. Select Import from Clipboard. Paste the JSON code into the text box. Click Import to load the workflow. Option 2: Import via JSON File: Click the three dots (⋯) in the top-right corner. Select Import from File. Choose the .json file from your computer. Click Open to import. Setup Notes Google Sheet Columns**: Ensure your Google Sheet includes the following columns: Image URL, Rating (numeric, e.g., 1-5), Feedback (text), Pin Title, Pin Description, Destination URL, Board ID, and Status (e.g., "Pending" or "Posted"). Google Sheets Credentials**: Configure OAuth2 settings in the Fetch Food Photos node with your Google Sheet ID and credentials. AI Model**: Set up the AI Caption Generator node with OpenAI credentials (e.g., API key). Pinterest API**: Authorize the Upload to Pinterest node with Pinterest API credentials (e.g., Bearer Token) and obtain the Board ID. Scheduling**: Adjust the Daily Post Scheduler node to your preferred posting time (e.g., daily at 9 AM).

Turn any LinkedIn post into a personalized cold email opener that sounds like a human wrote it in seconds. Whether you're in sales, partnerships, or outreach, this tool reads LinkedIn posts like a human, distills the core message, and gives you a smart, conversational opener to kick off the relationship the right way. How It Works: 1.) Paste the post + author info into a short form. 2.) AI reads the post like a B2B sales expert would. 3.) Output = personalized opener, company name, prospect’s name, and next steps. 4.) Copy-paste into your cold email and hit send. The opener isn’t generic fluff — it references real details, sounds natural, and shows you actually paid attention. Perfect For: SDRs and BDRs Agency outreach Partnership prospecting Any cold outreach that starts with a real conversation Setup Steps Setup time: ~2-3 mins 1.) Add your OpenAI credentials (or use n8n’s built-in credits). 2.) Open the form and test it with the sample post. 3.) Tweak the AI prompt if you want to target a different niche or tone. (Optional) Connect to Google Sheets, a CRM, or your email tool. You're live.

This n8n template demonstrates an approach to image embeddings for purpose of building a quick image contextual search. Use-cases could for a personal photo library, product recommendations or searching through video footage. How it works A photo is imported into the workflow via Google Drive. The photo is processed by the edit image node to extract colour information. This information forms part of our semantic metadata used to identify the image. The photo is also processed by a vision-capable model which analyses the image and returns a short description with semantic keywords. Both pieces of information about the image are combined with the metadata of the image to form a document describing the image. This document is then inserted into our vector store as a text embedding which is associated with our image. From here, the user can query the vector store as they would any document and the relevant image references and/or links should be returned. Requirements Google account to download image files from Google Drive. OpenAI account for the Vision-capable AI and Embedding models. Customise this workflow Text summarisation is just one of many techniques to generate image embeddings. If the results are unsatisfactory, there are dedicated image embedding models such as Google's vertex AI multimodal embeddings.

Note: This template only works for self-hosted n8n. This n8n template demonstrates how to use the Langchain code node to track token usage and cost for every LLM call. This is useful if your templates handle multiple clients or customers and you need a cheap and easy way to capture how much of your AI credits they are using. How it works In our mock AI service, we're offering a data conversion API to convert Resume PDFs into JSON documents. A form trigger is used to allow for PDF upload and the file is parsed using the Extract from File node. An Edit Fields node is used to capture additional variables to send to our log. Next, we use the Information Extractor node to organise the Resume data into the given JSON schema. The LLM subnode attached to the Information Extractor is a custom one we've built using the Langchain Code node. With our custom LLM subnode, we're able to capture the usage metadata using lifecycle hooks. We've also attached a Google Sheet tool to our LLM subnode, allowing us to send our usage metadata to a google sheet. Finally, we demonstrate how you can aggregate from the google sheet to understand how much AI tokens/costs your clients are liable for. Check out the example Client Usage Log - https://docs.google.com/spreadsheets/d/1AR5mrxz2S6PjAKVM0edNG-YVEc6zKL7aUxHxVcffnlw/edit?usp=sharing How to use SELF-HOSTED N8N ONLY** - the Langchain Code node is only available in the self-hosted version of n8n. It is not available in n8n cloud. The LLM subnode can only be attached to non-"AI agent" nodes; Basic LLM node, Information Extractor, Question & Answer Chain, Sentiment Analysis, Summarization Chain and Text Classifier. Requirements Self-hosted version of n8n OpenAI for LLM Google Sheets to store usage metadata Customising this template Bring the custom LLM subnode into your own templates! In many cases, it can be a drop-in replacement for the regular OpenAI subnode. Not using Google Sheets? Try other databases or a HTTP call to pipe into your CRM.

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:

Automatically Categorize Gmail Emails with GPT-4o-mini Multi-Label Analysis Description The "Automatically Categorize Gmail Emails with GPT-4o-mini Multi-Label Analysis" template is designed specifically for professionals, business owners, entrepreneurs, and anyone struggling to manage a high volume of daily emails. It solves common inbox problems such as email overload, missed important messages, manual sorting inefficiencies, and unorganized inbox clutter. By using intelligent content analysis powered by GPT-4o-mini, this workflow automatically categorizes incoming Gmail messages with relevant labels, ensuring efficient email management and significantly boosting productivity. Workflow Overview How It Works Email Detection**: Continuously monitors your Gmail inbox every minute to detect new incoming emails. Content Extraction**: Retrieves key email components including sender details, subject line, and body content for analysis. Intelligent Labeling**: Utilizes GPT-4o-mini AI to contextually analyze each email and assign 1-3 relevant labels based on your existing Gmail label structure. Automatic Application**: Applies the selected labels directly to your emails, equipped with robust error-handling mechanisms to ensure accuracy and reliability. Key Benefits Organized Inbox**: Automatically maintains inbox order and clarity. Time-Saving**: Reduces manual email management effort significantly. Customization**: Fully adaptable to specific labeling and organizational requirements. Pre-conditions Before using this template, ensure the following prerequisites are met: Active Gmail account with OAuth2 enabled. Active OpenAI account with GPT-4o-mini API key. Clearly defined labels set up in your Gmail account (e.g., "Work", "Personal", "Urgent"). Setup Instructions Follow these straightforward setup steps to activate the workflow: Connect Gmail Account Authorize your Gmail account using OAuth2 (takes approximately 2-3 minutes). Configure OpenAI GPT-4o-mini API Enter and validate your GPT-4o-mini API key to enable advanced email analysis. Establish Gmail Labels Ensure necessary labels are created within Gmail. Examples include "Work", "Personal", and "Urgent". Activate and Verify Click the "Activate" button in n8n. Send a test email to your Gmail inbox to confirm that labels are applied correctly. Customization Tips You can easily customize this workflow to fit your specific needs: Modify Gmail Labels**: Create and adapt labels to match your business or personal categorization strategy. Adjust GPT-4o-mini Criteria**: Fine-tune the AI prompts to improve accuracy and relevance based on your unique email management needs. Expand the Workflow**: Integrate additional conditions, actions, or external applications to further automate and optimize your email management processes. Improve your daily workflow efficiency and achieve a clutter-free Gmail inbox by leveraging the power of GPT-4o-mini today.

This n8n template demonstrates how you can leverage existing support site search to power your Support Chatbots and agents. Building a support chatbot need not be complicated! If building and indexing vector stores or duplicating data isn't necessarily your thing, an alternative implementation of the RAG approach is to leverage existing knowledge-bases such as support portals. In this way, document management and maintenance of your support agent is significantly reduced. Disclaimer: This template example uses AcuityScheduling's help center website but is not associated, supported nor endorsed by the company. How it works A simple AI agent is connected with chat trigger to receive user queries. The AI agent is instructed to fetch information from the knowledge-base via the attached custom workflow tool (aka "knowledgebase tool"). There is no step to replicate the entire support articles database into a vector store. You may choose not too because of time, cost and maintainence involved. Instead, the tool leverages the existing support portal's search API to retrieve knowledge-base articles. Finally, the search results are formatted before sending an aggregated response back to the agent. How to use? Customise the subworkflow to work with your own support portal API and format accordingly. Try the following queries How do I connect my icloud to acuityScheduling? How do I download past invoices for my Acuity account? Requirements OpenAI for LLM. If your organisation's APIs require authorisation, you may need to add custom credentials as necessary. Customising this workflow Add additional tools to reach other parts of your internal knowledgebase. Not using OpenAI? Feel free to swap but ensure the LLM has tools/function calling support.

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

Who is this for? This workflow is designed for HR professionals, employer branding teams, talent acquisition strategists, market researchers, and business intelligence analysts who want to monitor, understand, and act upon employee sentiment and company perception on Glassdoor. It's ideal for organizations that value real-time feedback, are tracking employer brand perception, or need summarized insights for leadership reporting without sifting through thousands of raw reviews. What problem is this workflow solving? Manually reviewing and analyzing Glassdoor reviews is tedious, subjective, and not scalable especially for larger companies or those with many subsidiaries. This workflow: Automates review collection by making a Glassdoor company request via the Bright Data Web Scrapper API. Uses Google Gemini to summarize the content. Sends an actionable summary to HR dashboards, leadership teams, or alert systems via the Webhook notification. What this workflow does Makes an HTTP Request to Glassdoor via the Bright Data Web Scrapper API. Polls the BrightData Glassdoor for the completion of the request. Downloads the Glassdoor response when a new snapshot is ready. Sends the prompt to Google Gemini for summarization. Delivers the summarized insights (strengths, weaknesses, sentiment, patterns) to a configured webhook or dashboard endpoint. Setup Sign up at Bright Data. Navigate to Proxies & Scraping and create a new Web Unlocker zone by selecting Web Unlocker API under Scraping Solutions. In n8n, configure the Header Auth account under Credentials (Generic Auth Type: Header Authentication). The Value field should be set with the Bearer XXXXXXXXXXXXXX. The XXXXXXXXXXXXXX should be replaced by the Web Unlocker Token. A Google Gemini API key (or access through Vertex AI or proxy). A webhook or endpoint to receive the summary (e.g., Slack, Notion, or custom HR dashboard). How to customize this workflow to your needs Change Summary Focus by updating the Summarization of Glassdoor Response node Summarization methods and prompts to extract specific insights: Cultural feedback Leadership issues Compensation comments Exit motivation Update the HTTP Request to Glassdoor node with a specific Glassdoor Company information that you are looking for. Format the output to produce a customized summary to Markdown or HTML for rich delivery. Integrate with HR Systems BambooHR, Workday, SAP SuccessFactors via API. Google Sheets or Airtable

Reddit Poster to Discord This workflow checks Reddit every 15 minutes for new posts and sends selected posts to a Discord channel via webhook. Flow Overview: Schedule Trigger Runs every 15 minutes. Fetch Latest Posts Retrieves up to 3 new posts from any subreddit. Filter Posts Skips moderator or announcement posts based on author ID. Fetch Full Post Data Gets full details for the remaining post. Extract Image URL Parses the post to extract a direct image link. Send to Discord Sends the post title, image, and link to a Discord webhook. Setup Notes: Create a Reddit app and connect credentials in n8n. Add your subreddit name to both Reddit nodes. Connect a Discord webhook for posting.

Automated YouTube Leads: Turn Comments into Enriched Prospects Workflow Overview This cutting-edge n8n workflow is a powerful automation tool designed to revolutionize how businesses and marketers identify and qualify leads directly from YouTube video comments. By leveraging specialized Apify Actors and an intelligent AI agent, this workflow seamlessly transforms raw comment data into comprehensive lead profiles, saving valuable time and resources. This workflow automatically: Discovers & Scrapes Comments: Monitors a Google Sheet for new YouTube video URLs. Automatically extracts all comments from specified YouTube videos using a dedicated Apify Actor. Marks videos as "scrapped" to avoid reprocessing. Intelligent Lead Enrichment: Retrieves unprocessed comments from Google Sheets. Activates an advanced AI agent (powered by OpenRouter's cutting-edge models) to research comment authors. Utilizes Google Search (via Serper API) and specialized Apify scrapers (for website content and Instagram profiles) to find publicly available information like social media links, bios, and potential contact details. Generates concise descriptions for each lead based on gathered data. Organized Data Storage: Creates new entries in a dedicated Google Sheet for each new lead. Updates lead profiles with all discovered enriched data (email, social media, short bio, etc.). Marks comments as "processed" once their authors have been researched and enriched. Key Benefits 🤖 Full Automation: Eliminates manual data collection and research, freeing up your team for strategic tasks. 💡 Smart Lead Enrichment: AI intelligently sifts through information to build rich, actionable lead profiles. ⏱️ Time-Saving: Instant, scalable lead generation without human intervention. 📈 Enhanced Lead Quality: Go beyond basic contact info with comprehensive social and professional context. 📊 Centralized Data: All leads are neatly organized in Google Sheets for easy access and integration. Setup Requirements n8n Installation: Install n8n (cloud or self-hosted). Import the workflow configuration. Configure API credentials. Set up scheduling preferences for continuous operation. Google Sheets Credentials: A Google Cloud API key with access to Google Sheets. Set up OAuth2 authentication in n8n for read/write access to your "youtube leads" spreadsheet (containing "videos", "comments", and "leads" sheets). OpenRouter API Access: Create an OpenRouter account. Generate an API key to access their chat models (e.g., google/gemini-2.5-flash-preview-05-20) for AI agent operations. Apify API Access: Create an Apify account. Generate a personal API token. This token is used to run the following Apify Actors: mohamedgb00714/youtube-video-comments (for comment extraction) mohamedgb00714/fireScraper-AI-Website-Content-Markdown-Scraper (for website content extraction) mohamedgb00714/instagram-full-profile-scraper (for Instagram profile details) Serper API Key: Sign up for an account on Serper.dev. Obtain an API key for performing Google searches to find social media profiles and other information. Potential Use Cases Content Creators: Identify highly engaged audience members for community building or direct outreach. Marketing Teams: Discover potential customers or influencers interacting with competitor content. Sales Professionals: Build targeted lead lists based on specific interests expressed in comments. Market Researchers: Analyze audience demographics and interests by enriching profiles of commenters on relevant videos. Recruiters: Find potential candidates based on their expertise or engagement in industry-specific discussions. Future Enhancement Roadmap CRM Integration: Directly push enriched leads into popular CRM systems (e.g., HubSpot, Salesforce). Automated Outreach: Implement automated email or social media messaging for qualified leads. Sentiment Analysis: Analyze comment sentiment before enrichment to prioritize positive interactions. Multi-Platform Support: Expand comment extraction and lead enrichment to other platforms (e.g., TikTok, Facebook). Advanced Lead Scoring: Develop a scoring model based on engagement, profile completeness, and relevance. Ethical Considerations Data Privacy: Ensure all collected data is publicly available and used in compliance with relevant privacy regulations (e.g., GDPR, CCPA). Platform Guidelines: Adhere strictly to YouTube's Terms of Service and Apify's usage policies. Transparency: If engaging with leads, be transparent about how their information was obtained (if applicable). No Spam: This tool is designed for lead identification, not for unsolicited mass messaging. Technical Requirements n8n v1.0.0 or higher (recommended for latest features and stability) Google Sheets API access OpenRouter API access Apify API access Serper API access Stable internet connection Workflow Architecture [YouTube Video URLs (Google Sheet)] ⬇️ [Schedule/Manual Trigger] ⬇️ [Extract Comments (Apify YouTube Scraper)] ⬇️ [Save Raw Comments (Google Sheet)] ⬇️ [AI Agent (OpenRouter) for Lead Research] ⬇️ [Google Search (Serper) & Web Scraping (Apify FireScraper/Instagram Scraper)] ⬇️ [Save Enriched Leads (Google Sheet)] ⬇️ [Mark Comments Processed (Google Sheet)] Connect With Me Exploring AI-Powered Lead Generation? 📧 Email: mohamedgb00714@gmail.com 💼 LinkedIn: Mohamed el Hadi Msaid Transform your YouTube engagement into a powerful lead generation engine with intelligent, automated insights\!