RAG chatbot for company documents using Google Drive and Gemini
This workflow implements a Retrieval Augmented Generation (RAG) chatbot that answers employee questions based on company documents stored in Google Drive. It automatically indexes new or updated documents in a Pinecone vector database, allowing the chatbot to provide accurate and up-to-date information. The workflow uses Google's Gemini AI for both embeddings and response generation. How it works The workflow uses two Google Drive Trigger nodes: one for detecting new files added to a specified Google Drive folder, and another for detecting file updates in that same folder. Automated Indexing: When a new or updated document is detected The Google Drive node downloads the file. The Default Data Loader node loads the document content. The Recursive Character Text Splitter node breaks the document into smaller text chunks. The Embeddings Google Gemini node generates embeddings for each text chunk using the text-embedding-004 model. The Pinecone Vector Store node indexes the text chunks and their embeddings in a specified Pinecone index. 7.The Chat Trigger node receives user questions through a chat interface. The user's question is passed to an AI Agent node. The AI Agent node uses a Vector Store Tool node, linked to a Pinecone Vector Store node in query mode, to retrieve relevant text chunks from Pinecone based on the user's question. The AI Agent sends the retrieved information and the user's question to the Google Gemini Chat Model (gemini-pro). The Google Gemini Chat Model generates a comprehensive and informative answer based on the retrieved documents. A Window Buffer Memory node connected to the AI Agent provides short-term memory, allowing for more natural and context-aware conversations. Set up steps Google Cloud Project and Vertex AI API: Create a Google Cloud project. Enable the Vertex AI API for your project. Google AI API Key: Obtain a Google AI API key from Google AI Studio. Pinecone Account: Create a free account on the Pinecone website. Obtain your API key from your Pinecone dashboard. Create an index named company-files in your Pinecone project. Google Drive: Create a dedicated folder in your Google Drive where company documents will be stored. Credentials in n8n: Configure credentials in your n8n environment for: Google Drive OAuth2 Google Gemini(PaLM) Api (using your Google AI API key) Pinecone API (using your Pinecone API key) Import the Workflow: Import this workflow into your n8n instance. Configure the Workflow: Update both Google Drive Trigger nodes to watch the specific folder you created in your Google Drive. Configure the Pinecone Vector Store nodes to use your company-files index.
By Mihai FarcasPulling data from services that n8n doesn’t have a pre-built integration for
You still can use the app in a workflow even if we don’t have a node for that or the existing operation for that. With the HTTP Request node, it is possible to call any API point and use the incoming data in your workflow Main use cases: Connect with apps and services that n8n doesn’t have integration with Web scraping How it works This workflow can be divided into three branches, each serving a distinct purpose: 1.Splitting into Items (HTTP Request - Get Mock Albums): The workflow initiates with a manual trigger (On clicking 'execute'). It performs an HTTP request to retrieve mock albums data from "https://jsonplaceholder.typicode.com/albums." The obtained data is split into items using the Item Lists node, facilitating easier management. 2.Data Scraping (HTTP Request - Get Wikipedia Page and HTML Extract): Another branch of the workflow involves fetching a random Wikipedia page using an HTTP request to "https://en.wikipedia.org/wiki/Special:Random." The HTML Extract node extracts the article title from the fetched Wikipedia page. 3.Handling Pagination (The final branch deals with handling pagination for a GitHub API request): It sends an HTTP request to "https://api.github.com/users/that-one-tom/starred," with parameters like the page number and items per page dynamically set by the Set node. The workflow uses conditions (If - Are we finished?) to check if there are more pages to retrieve and increments the page number accordingly (Set - Increment Page). This process repeats until all pages are fetched, allowing for comprehensive data retrieval.
By JonathanFully automated AI video generation & multi-platform publishing
Description This comprehensive n8n automation template orchestrates a complete end-to-end workflow for generating engaging short-form Point-of-View (POV) style videos using multiple AI services and automatically publishing them across major social media platforms. It takes ideas from a Google Sheet and transforms them into finished videos with captions, voiceovers, and platform-specific descriptions, ready for distribution. Who Is This For? Content Creators & Agencies: Mass-produce unique short-form video content for various clients or channels with minimal manual effort. Digital Marketers: Automate video content pipelines to boost online presence and engagement across multiple platforms simultaneously. Social Media Managers: Schedule and distribute consistent video content efficiently without juggling multiple tools and manual uploads. Businesses: Leverage AI to create branded video content for marketing, reducing production time and costs. What Problem Does This Workflow Solve? Creating and distributing high-quality short-form video content consistently across multiple social networks is incredibly time-consuming and resource-intensive. This workflow tackles these challenges by: Automating Idea-to-Video Pipeline: Generates video concepts, image prompts, scripts, images, video clips, and voiceovers using AI. Streamlining Video Assembly: Automatically combines generated assets into a final video using a template. Generating Platform-Optimized Descriptions: Creates relevant descriptions for posts by transcribing the final video audio. Automating Multi-Platform Publishing: Uploads the final video and description to TikTok, Instagram, YouTube, Facebook, and LinkedIn simultaneously. Reducing Manual Workload: Drastically cuts down the time and effort required for video production and distribution. Centralized Tracking: Updates a Google Sheet with results, costs, and status for easy monitoring. How It Works Trigger & Input: Runs on a daily schedule (configurable) and fetches new video ideas from a designated Google Sheet. AI Content Generation: Uses OpenAI to generate video captions and image prompts based on the idea. Uses PiAPI (Flux) to generate images from prompts. Uses PiAPI (Kling) to generate video clips from the images (Image-to-Video). Uses OpenAI to generate a voiceover script based on the captions. Uses ElevenLabs to generate voiceover audio from the script and uploads it to Google Drive. Video Assembly: Combines the generated video clips, captions, and voiceover audio using a Creatomate template to render the final video. Description Generation: Uploads the final video to Google Drive, extracts the audio using OpenAI (Whisper), and generates a social media description using OpenAI (GPT). Multi-Platform Distribution: Uses upload-post.com to upload the final video and generated description to TikTok, Instagram, YouTube, Facebook, and LinkedIn. Tracking & Notification: Updates the original Google Sheet row with output details (video link, costs, tokens used) and sends a completion notification via Discord. Setup Accounts & API Keys: Obtain accounts and generate API keys/credentials for: n8n Google Cloud Platform (for Google Sheets & Google Drive APIs + OAuth Credentials) OpenAI PiAPI ElevenLabs Creatomate upload-post.com Discord (Webhook URL) Google Sheet: Make a copy of the provided Google Sheet Template and connect it in the Load Google Sheet node. Creatomate Template: Set up a video template in Creatomate (use the provided JSON source code as a base) and note its Template ID. Configure Nodes: Enter all API Keys/Credentials in the Set API Keys node and other relevant credential sections (Google nodes, upload-post nodes, etc.). Configure Google Drive nodes (Folder IDs, Permissions). Configure the upload-post.com nodes with your user identifier and necessary platform details (e.g., Facebook Page ID). Customize AI prompts within the OpenAI nodes (Generate Video Captions, Generate Image Prompts, Generate Script, Generate Description...) if desired. Set the Discord Webhook URL in the Notify me on Discord node. Enable Google APIs: Ensure Google Drive API and Google Sheets API are enabled in your Google Cloud Project. Requirements Accounts: n8n, Google (Sheets, Drive, Cloud Platform), OpenAI, PiAPI, ElevenLabs, Creatomate, The social media api Upload-Post, Discord. API Keys & Credentials: API Keys for OpenAI, PiAPI, ElevenLabs, Creatomate, upload-post.com. Google Cloud OAuth 2.0 Credentials. Discord Webhook URL. Templates: A configured Google Sheet based on the template, a configured Creatomate video template. (Potentially) Paid Plans: Some services (OpenAI, PiAPI, Creatomate, upload-post.com) may require paid plans depending on usage volume after free trials/credits are exhausted. Use this template to build a powerful, automated video content factory, scaling your production and distribution efforts across the social media landscape.
By Juan Carlos Cavero GraciaGenerate leads with Google Maps
This workflow leverages n8n to perform automated Google Maps API queries and manage data efficiently in Google Sheets. It's designed to extract specific location data based on a given list of ZIP codes and categories. --- Features Queries the Google Maps API for location data using predefined ZIP codes and subcategories. Filters, de-duplicates, and organizes data into structured rows in Google Sheets. Implements exponential backoff retries to handle API rate limits. Logs and updates statuses directly in Google Sheets for easy tracking. --- Prerequisites Google OAuth Credentials: A configured Google Cloud project for Google Maps API and Sheets API access. Google Sheets: A sheet with ZIP codes and categories defined (e.g., "AZ Zips"). n8n Setup: A running instance of n8n with credentials configured for Google OAuth. --- Setup Instructions Prepare Google Sheets Add the ZIP codes to the "AZ Zips" sheet. Define subcategories in another sheet (e.g., "Google Maps Categories"). Provide the sheet's URL in the Settings node of the workflow. Configure API Access Set up Google OAuth credentials for Maps and Sheets APIs in n8n. Ensure your API key has access to the places.searchText endpoint. Workflow Customization Modify textQuery parameters in the GMaps API node to match your query needs. Adjust trigger intervals as required (e.g., manual or scheduled execution). Run the Workflow Execute the workflow manually or schedule periodic runs to keep your data updated. --- Notes This workflow includes robust error handling to retry failed API calls with exponential backoff. All data is organized and logged directly in Google Sheets for easy reference and updates. For more information or issues, feel free to reach out!
By Alex KimLearn n8n basics in 3 easy steps ✨
New to n8n? This simple tutorial is the perfect way to get started. In just a few minutes, you’ll build your first automation that runs on a schedule, fetches fresh data from the internet and delivers it straight to your inbox. What you’ll do Run the workflow to grab a random inspirational quote. See how data flows through each node as it moves from an API call to processing results. Connect Gmail and send the quote directly to your email. What you’ll learn How to trigger workflows manually and on a schedule ⏰ How to connect to external APIs and fetch data 🌐 How to use the Set node to structure and map data 🔧 How to connect Gmail to send the data 📩 Why it matters This workflow shows you the n8n basics step by step - no code required. By the end, you’ll know how to build, test, and share automations that run on their own, giving you the confidence to explore more advanced use cases. 🚀
By MihaAutomated web scraping: email a CSV, save to Google Sheets & Microsoft Excel
How it works: The workflow starts by sending a request to a website to retrieve its HTML content. It then parses the HTML extracting the relevant information The extracted data is storted and converted into a CSV file. The CSV file is attached to an email and sent to your specified address. The data is simultaneously saved to both Google Sheets and Microsoft Excel for further analysis or use. Set-up steps: Change the website to scrape in the "Fetch website content" node Configure Microsoft Azure credentials with Microsoft Graph permissions (required for the Save to Microsoft Excel 365 node) Configure Google Cloud credentials with access to Google Drive, Google Sheets and Gmail APIs (the latter is required for the Send CSV via e-mail node).
By Mihai Farcas⚡AI-powered YouTube video summarization & analysis
-- Disclaimer: This workflow uses a community node and therefore only works for self-hosted n8n users -- Transform YouTube videos into comprehensive summaries and structured analysis instantly. This n8n workflow automatically extracts, processes, and analyzes video transcripts to deliver clear, organized insights without watching the entire video. Time-Saving Features 🚀 Instant Processing Simply provide a YouTube URL and receive a structured summary within seconds, eliminating the need to watch lengthy videos. Perfect for research, learning, or content analysis. 🤖 AI-Powered Analysis Leverages GPT-4o-mini to analyze video transcripts, organizing key concepts and insights into a clear, hierarchical structure with main topics and essential points. Smart Processing Pipeline 📝 Automated Transcript Extraction Supports public YouTube video Handles multiple URL formats Extracts complete video transcripts automatically 🧠 Intelligent Content Organization Breaks down content into main topics Highlights key concepts and terminology Maintains technical accuracy while improving clarity Structures information logically with markdown formatting Perfect For 📚 Researchers & Students Quick comprehension of educational content and lectures without watching entire videos. 💼 Business Professionals Efficient analysis of industry talks, presentations, and training materials. 🎯 Content Creators Rapid research and competitive analysis of video content in your niche. Technical Implementation 🔄 Workflow Components Webhook endpoint for URL submission YouTube API integration for video details Transcript extraction system GPT-4 powered analysis engine Telegram notification system (optional) Transform your video content consumption with an intelligent system that delivers structured, comprehensive summaries while saving hours of viewing time.
By Joseph LePageSuggest meeting slots using AI
The purpose of this n8n workflow is to automate the process of identifying incoming Gmail emails that are requesting an appointment, evaluating their content, checking calendar availability, and then composing and sending a response email. Note that to use this template, you need to be on n8n version 1.19.4 or later.
By n8n TeamLocal chatbot with retrieval augmented generation (RAG)
Build a 100% local RAG with n8n, Ollama and Qdrant. This agent uses a semantic database (Qdrant) to answer questions about PDF files. Tutorial Click here to view the YouTube Tutorial How it works Build a chatbot that answers based on documents you provide it (Retrieval Augmented Generation). You can upload as many PDF files as you want to the Qdrant database. The chatbot will use its retrieval tool to fetch the chunks and use them to answer questions. Installation Install n8n + Ollama + Qdrant using the Self-hosted AI starter kit Make sure to install Llama 3.2 and mxbai-embed-large as embeddings model. How to use it First run the "Data Ingestion" part and upload as many PDF files as you want Run the Chatbot and start asking questions about the documents you uploaded
By Thomas JanssenPersonal life manager with Telegram, Google services & voice-enabled AI
How it works: This project teaches you to create a personal AI assistant named Jackie that operates through Telegram. Jackie can summarize unread emails, check calendar events, manage Google Tasks, and handle both voice and text interactions. The assistant provides a comprehensive digital life management solution accessible via Telegram messaging. Key Features: Supports hands-free voice interaction Maintains conversation memory Integrates with major Google services Provides personalized assistance for email management, scheduling, and task organization Step-by-step: Telegram Trigger: The workflow starts with a Telegram trigger that listens for incoming message events. The system determines if the incoming message is voice or text input. Voice Processing: If a voice message is received, the workflow retrieves the voice file from Telegram and uses OpenAI's transcription API to convert speech to text. AI Assistant: The processed text (whether original text or transcribed voice) is passed to Jackie, the AI assistant powered by OpenRouter's language model. Tools Integration: Jackie is equipped with several productivity tools: Get Email: Uses Gmail API to fetch unread emails from the inbox with sender, date, subject, and summary information Google Calendar: Retrieves calendar events for specified dates, filtering out irrelevant future events Google Tasks: Both creates new tasks and retrieves existing tasks from Google Tasks lists API Keys Required: Telegram Bot API: Create a bot via @BotFather on Telegram to get your bot token OpenAI API: Required for voice-to-text transcription OpenRouter API: Powers the AI language model responses Google OAuth2: Needed for Gmail, Google Calendar, and Google Tasks integration Response Generation: The AI formulates intelligent responses based on the gathered information, current date context, and conversation history, then sends the response back to the user via Telegram in Markdown format.
By Derek CheungConversational Telegram bot with GPT-5/GPT-4o for text and voice messages
This n8n workflow leverages a Telegram Message Trigger to activate an intelligent AI Agent capable of processing both text and voice messages. When a user sends a message in text or in voice format, the workflow captures and transcribes it (if necessary), then passes it to the AI Agent for understanding and response generation. To enhance user experience, the bot also displays a typing indicator while processing requests, simulating a natural, human-like interaction. Key Features Multi-Modal Input: Supports both text messages and voice notes from users. Real-Time Interaction: Shows a “typing…” action in Telegram while the AI processes the input. AI Agent Integration: Provides intelligent, context-aware, and conversational responses. Seamless Feedback Loop: Replies are sent directly back to the user within Telegram for smooth interaction. How It Works The workflow triggers whenever a message or voice note is received on Telegram. If the input is a voice note, the workflow transcribes it into text. The text input is sent to the AI Agent for processing. While processing, the bot sends a typing indicator to the user. Once the AI generates a response, the workflow sends it back to the user in Telegram. Setup Instructions Create a Telegram Bot: Use @BotFather to create a bot and obtain your bot token. Configure n8n Credentials: Add Telegram API credentials in n8n with your bot token. Add credentials for any speech-to-text service used for voice transcription (e.g., Open AI Transcribe A Recording). Import the Workflow: Import this workflow into your n8n instance. Update all credential nodes to use your Telegram and transcription service credentials. Set Webhook URLs: Ensure Telegram webhook is set properly for your bot to receive messages. Make sure your n8n instance is publicly accessible for Telegram callbacks. Test the Workflow: Send text messages and voice notes to your Telegram bot and observe the AI responses. Customization Guidance Add new message handlers: Extend the workflow to handle additional message types (images, documents, etc.). Improve transcription: Swap or add speech-to-text services for better accuracy or language support. Enhance AI Agent: Customize prompts and context management to tailor the AI’s personality and responses. AI Model Flexibility: Swap between different AI models (e.g., GPT-5, GPT-4, Claude, or custom LLMs) based on task type, cost, or performance preferences. By default, I use GPT-4o in this template. However, you can use the latest GPT-5 model by changing them in OpenAI Chat Model Node. It will show you a list of all the available models to choose. Tool-Based Control: Add custom tools to the AI Agent such as calendar access, Notion, Google Sheets, web search, database queries, or custom APIs—allowing for dynamic, multi-functional agents Security and Implementation Notes The Telegram node manages message reception and sending but does not directly handle AI processing. Voice transcription requires integration with external APIs; secure those credentials in n8n and monitor usage. To simulate typing, the workflow uses Telegram’s “sendChatAction” API method, providing users with feedback that the bot is processing. Ensure your AI API keys and Telegram tokens are securely stored in n8n credentials and not exposed in workflows or logs. Benefits Handles natural conversational inputs with text or voice. Provides a smooth, engaging user experience via typing indicators. Easy integration of advanced AI conversational agents with Telegram. Flexible for personal assistants, helpdesks, or interactive chatbots.
By RoninimousBuild your own N8N workflows MCP server
This n8n template shows you how to create an MCP server out of your existing n8n workflows. With this, any MCP client connected can get more done with powerful end-to-end workflows rather than just simple tools. Designing agent tools for outcome rather than utility has been a long recommended practice of mine and it applies well when it comes to building MCP servers; In gist, agents to be making the least amount of calls possible to complete a task. This is why n8n can be a great fit for MCP servers! This template connects your agent/MCP client (like Claude Desktop) to your existing workflows by allowing the AI to discover, manage and run these workflows indirectly. How it works An MCP trigger is used and attaches 4 custom workflow tools to discover and manage existing workflows to use and 1 custom workflow tool to execute them. We'll introduce an idea of "available" workflows which the agent is allowed to use. This will help limit and avoid some issues when trying to use every workflow such as clashes or non-production. The n8n node is a core node which taps into your n8n instance API and is able to retrieve all workflows or filter by tag. For our example, we've tagged the workflows we want to use with "mcp" and these are exposed through the tool "search workflows". Redis is used as our main memory for keeping track of which workflows are "available". The tools we have are "add Workflow", "remove workflow" and "list workflows". The agent should be able to manage this autonomously. Our approach to allow the agent to execute workflows is to use the Subworkflow trigger. The tricky part is figuring out the input schema for each but was eventually solved by pulling this information out of the workflow's template JSON and adding it as part of the "available" workflow's description. To pass parameters through the Subworkflow trigger, we can do so via the passthrough method - which is that incoming data is used when parameters are not explicitly set within the node. When running, the agent will not see the "available" workflows immediately but will need to discover them via "list" and "search". The human will need to make the agent aware that these workflows will be preferred when answering queries or completing tasks. How to use First, decide which workflows will be made visible to the MCP server. This example uses the tag of "mcp" but you can all workflows or filter in other ways. Next, ensure these workflows have Subworkflow triggers with input schema set. This is how the MCP server will run them. Set the MCP server to "active" which turns on production mode and makes available to production URL. Use this production URL in your MCP client. For Claude Desktop, see the instructions here - https://docs.n8n.io/integrations/builtin/core-nodes/n8n-nodes-langchain.mcptrigger/integrating-with-claude-desktop. There is a small learning curve which will shape how you communicate with this MCP server so be patient and test. The MCP server will work better if there is a focused goal in mind ie. Research and report, rather than just a collection of unrelated tools. Requirements N8N API key to filter for selected workflows. N8N workflows with Subworkflow triggers! Redis for memory and tracking the "available" workflows. MCP Client or Agent for usage such as Claude Desktop - https://claude.ai/download Customising this workflow If your targeted workflows do not use the subworkflow trigger, it is possible to amend the executeTool to use HTTP requests for webhooks. Managing available workflows helps if you have many workflows where some may be too similar for the agent. If this isn't a problem for you however, feel free to remove the concept of "available" and let the agent discover and use all workflows!
By Jimleuk