by Jimleuk
This n8n template demonstrates how to calculate the evaluation metric "Relevance" which in this scenario, measures the relevance of the agent's response to the user's question. The scoring approach is adapted from the open-source evaluations project RAGAS and you can see the source here https://github.com/explodinggradients/ragas/blob/main/ragas/src/ragas/metrics/_answer_relevance.py How it works This evaluation works best for Q&A agents. For our scoring, we analyse the agent's response and ask another AI to generate a question from it. This generated question is then compared to the original question using cosine similarity. A high score indicates relevance and the agent's successful ability to answer the question whereas a low score means agent may have added too much irrelevant info, went off script or hallucinated. Requirements n8n version 1.94+ Check out this Google Sheet for a sample data https://docs.google.com/spreadsheets/d/1YOnu2JJjlxd787AuYcg-wKbkjyjyZFgASYVV0jsij5Y/edit?usp=sharing
by David Roberts
Overview This workflow takes some French text, and translates it into spoken audio. It then transcribes that audio back into text, translates it into English and generates an audio file of the English text. To do so, it uses ElevenLabs (which has a free tier) and OpenAI. Setup These steps should only take a few minutes: In ElevenLabs, add a voice to your voice lab and copy its ID. Add it to the 'Set voice ID' node Get your ElevenLabs API key (click your name in the bottom-left of ElevenLabs and choose ‘profile’) In the 'Generate French audio' node, create a new header auth cred. Set the name to xi-api-key and the value to your API key In the 'credential' field of the 'Transcribe audio' node, create a new OpenAI cred with your OpenAI API key Run the workflow by clicking the orange button at the bottom of the canvas
by Pavel Zamorev
This n8n template automates the transformation of raw meeting notes into structured tasks and documents using GPT (or another model) , syncing them to Notion and TickTick via a Telegram bot. Use Cases Automate note-taking and formatting for daily standups, brainstorming sessions, or client calls. Reduce cognitive load by eliminating manual tracking of ideas and tedious formatting. Convert discussions into actionable tasks instantly with TickTick and structured notes in Notion. How It Works Capture Notes: Send raw meeting notes to a Telegram bot. AI Processing: The workflow sends the text to AI, which: Removes duplicates and extracts key points. Formats content into structured Markdown notes for Notion. Identifies tasks with deadlines (e.g., "- Prepare presentation (Responsible: John, Deadline: Friday)"). Task Parsing: Extracts task titles, removing metadata like "Responsible" and "Deadline." Review & Edit: The bot returns formatted notes and tasks for review in Telegram. Sync & Publish: Notes are published to a Notion database. Tasks are exported to TickTick via API. Confirmation: A Telegram reaction (e.g., 👌 emoji) confirms successful processing. Setup Instructions Set Up Telegram Bot: Create a Telegram bot via BotFather and obtain an API token. Add the token to the "Telegram Trigger" and "Send-Edited-Notes" nodes under credentials (telegramApi). Configure OpenAI: Obtain an OpenAI API key and add it to the "Edit-Notes" node (openAiApi credentials). Ensure the model is set to gpt-4.1-mini in the node parameters. Set Up Notion: Create a Notion database for notes (e.g., "Meetings"). Add the database ID to the "Create a Database Page" node (databaseId). Configure Notion API credentials (notionApi) in the node. Set Up TickTick: Obtain a TickTick API key and add it to the "Create a Task" node (tickTickOAuth2Api credentials). Specify your TickTick project ID in the node (projectId). Deploy Workflow: Ensure your n8n instance is self-hosted to support community nodes (TickTick, Notion). Activate the workflow in n8n. Test: Send a test message to the Telegram bot (e.g., "Discussed project timeline. Tasks: - Prepare slides (Responsible: Alice, Deadline: Friday)"). Verify that notes appear in Notion, tasks in TickTick, and a 👌 reaction in Telegram. Configuration Examples Telegram Trigger: { "parameters": { "updates": ["message"], "additionalFields": {} }, "credentials": { "telegramApi": { "id": "your-telegram-api-id", "name": "meeting notes" } } } OpenAI Prompt (in "Edit-Notes" node): Analyze the quick meeting notes from {{ $json.message.text }} Generate meeting notes and a task list in the following format:\nMeeting Notes:\n- [Note 1]\n- [Note 2]\n\nTasks:\n- [Task 1] \n- [Task 2] Notion Database Page { "parameters": { "resource": "databasePage", "databaseId": "your-notion-database-id", "title": "MN {{ $now }}", "blockUi": { "blockValues": [ { "textContent": "{{ $json.message.text }}" } ] } } } Requirements Requires an OpenAI API key (or another model). APIs: Pre-configured Notion and TickTick API credentials are required. The template includes setup guides. Setup: Uses community nodes, requiring a self-hosted n8n instance. Customizing This Workflow Replace the Telegram bot with a webhook or form for alternative inputs (e.g., mobile apps). Modify the OpenAI prompt in the "Edit-Notes" node to customize note and task formats. Add filters in the "Split Notes and Tasks" node to prioritize tasks (e.g., ++#urgent++). Integrate Google Calendar via an additional HTTP Request node to auto-set deadlines based on text (e.g., "by Friday").
by Max Tkacz
Who is this for This workflow is perfect for teams and individuals who manage extensive data in Notion and need a quick, AI-powered way to interact with their databases. If you're looking to streamline your knowledge management, automate searches, and get faster insights from your Notion databases, this workflow is for you. It’s ideal for support teams, project managers, or anyone who needs to query specific data across multiple records or within individual pages of their Notion setup. Check out the Notion template this Assistant is set up to use: https://www.notion.so/templates/knowledge-base-ai-assistant-with-n8n How it works The Notion Database Assistant uses an AI Agent built with Retrieval-Augmented Generation (RAG) to query this Knowledge Base style Notion database. The assistant can search across multiple properties like tags or question and retrieves content from inside individual Notion pages for additional context. Key features include: Querying the database with flexible filters. Searching within individual Notion pages and extracting relevant blocks. Providing a reference link to the exact Notion pages used to inform its responses, ensuring transparency and easy verification. This assistant uses two HTTP request tools—one for querying the Notion database and another for pulling data from within specific pages. It streamlines knowledge retrieval, offering a conversational, AI-driven way to interact with large datasets. Set up Find basic set up instructions inside the workflow itself or watch a quickstart video 👇
by Jimleuk
This n8n template demonstrates how easy it is to build an Outlook Calendar Assistant powered by an AI agent equipped with Tools. For teams using Outlook Calendar and Slack who need easier calendar management, this workflow can be a great first step to introducing powerful AI tools into your daily activities. How it works A Slack Trigger node is configured to catch "bot mentions" events in a designated channel. The message is parsed using the Edit fields node to extract only the required attributes of the event. An AI Agent equipped with Outlook Calendar Tools enables question and answer capability for the organisation's shared calendars and events. The AI agent's response is sent back to Slack as a reply to the user's query. How to use The workflow is triggered via @mention-ing the bot followed by the query. eg. "@bot how many meetings does Paul have to attend to this week?" To start listening to real mentions, you must activate the workflow and set it to production mode. You must use the production webhook URL for the event subscription. Some sample queries to try "What's included in the product team's sprint demo this week?" "Who's booked room 7 for this Thursday?" "When is Jim & Nik's sales meeting with Microsoft?" Requirements Slack for Chat and Trigger. To get connected to Slack, see the official n8n docs for Slack Credentials. Outlook for Agent Tools To get connected to Outlook, see the official n8n docs for Outlook Credentials. Customising this workflow Not using Slack? This template can be modified to work with Teams but requires a little more configuration. Agents can have any number of tools but an overloaded agent is prone to confusion! If this happens, try splitting into multiple agents serving separate needs.
by Paul
AI Database Assistant with Smart Query's & PostgreSQL Integration Description: 🚀 Transform Your Database into an Intelligent AI Assistant This workflow creates a smart database assistant that safely handles natural language queries without crashing your system. Features dual-agent architecture with built-in query limits and PostgreSQL optimization – perfect for commercial applications! ✅ Ideal for: SaaS developers building database search features 🔍 Database administrators providing safe AI access 🛡️ Business teams needing user-friendly data queries 📊 Anyone wanting ChatGPT-like database interaction 🤖 🔧 How It Works 1️⃣ User asks a question – "Show me top 10 popular products" 2️⃣ Main AI Agent – Interprets the request and ensures safety limits 3️⃣ SQL Sub-Agent – Generates precise PostgreSQL queries 4️⃣ Database executes – Returns formatted, limited results safely ⚡ Setup Instructions 1️⃣ Prepare Your Database Ensure PostgreSQL is accessible from n8n Note your table structure and column names Set up database connection credentials 2️⃣ Customize the Templates Replace [YOUR_TABLE_NAME] with your actual table name Update [YOUR_FIELDS] with your column names Modify examples to match your use case Important**: Keep all LIMIT clauses intact! 3️⃣ Configure the Agents Copy Main Agent system message to your primary AI node Copy Sub-Agent system message to your SQL generator node Connect the sub-workflow between both agents 4️⃣ Test & Deploy Test with sample queries like "Show me 5 recent items" Verify query limits work (max 50 results) Deploy and monitor performance 🎯 Why Use This Workflow? ✔️ System Protection – Built-in limits prevent crashes from large queries ✔️ Natural Language – Users ask questions in plain English ✔️ Commercial Ready – Generic templates work with any database ✔️ Dual-Agent Safety – Smart interpretation + precise SQL generation ✔️ PostgreSQL Optimized – Handles complex schemas and data types 🚨 Critical Features Query Limits**: Default 10, maximum 50 results (can be modified) Error Prevention**: No unlimited data retrieval Smart Routing**: Natural language → Safe SQL → Formatted results Customizable**: Works with any PostgreSQL database schema 🔗 Start building your AI database assistant today – safe, smart, and scalable!
by Alfred Nutile
This guide will show you how to use a workflow as a reusable tool in n8n, such as integrating an AI Agent or other specialized processes into your workflows. By the end of this example, you'll have a simple, reusable workflow that can be easily plugged into larger projects, making your automations more efficient and scalable. With this approach, you can create reusable workflows like "Scrape a Page," "Search Brave," or "Generate an Image," which you can then call whenever needed. While n8n makes it easy to build these workflows from scratch, setting them up as reusable components saves time as your automations grow in complexity. Setup Add the "Execute Workflow Trigger" node Add the node(s) to perform the desired tasks in the workflow Add a final "Set" or "Edit Fields" node at the end to ensure all external workflows return a consistent output format Details In this example, the "Execute Workflow Trigger" expects input in the following JSON format: [ { "query": { "url": "https://en.wikipedia.org/wiki/some_info" } } ] Once your external workflow is ready, you can instruct the AI Agent to use this tool by connecting it to the external workflow. Set up the schema type to "Generate from JSON Example" using this structure: { "url": "URL_TO_GET" } Finally, ensure your external workflow includes a "Set" or "Edit Fields" node at the end to define the response format. This helps keep the outputs of your reusable workflows consistent and predictable.
by Alex
This workflow contains community nodes that are only compatible with the self-hosted version of n8n. How It Works This template orchestrates a multi-step workflow that constructs a comprehensive four-zone automation matrix—Green, Yellow, Red, and White—grounded in the Human Agency Scale (HAS). When a user sends a job title via Telegram, the workflow routes both text and voice messages appropriately. Voice messages are transcribed via OpenAI's Whisper, while text inputs bypass transcription. Both streams merge into a single data flow. The AI Agent node, powered by GPT-4, analyzes the user's profession and core tasks. It also leverages live context by calling the Tavily search tool, ensuring the analysis incorporates up-to-date information. After the evaluation, the workflow formats and returns the completed matrix, with detailed task examples and rationales for each zone, back to the user via Telegram. Setup Instructions Create an OpenAI credential in n8n (model: GPT-4.1 mini). Add a Tavily credential with your API key (FREE plan available). Configure a Telegram Bot credential: API bot token. Import this JSON as a new workflow in n8n and map credentials in each node. Activate the workflow; test by sending sample job titles; adjust node timeouts and webhook settings as needed. Requirements n8n v1.0.0 or higher Active OpenAI API key (GPT-4.1 mini access) Tavily API key for web context search Telegram Bot token with correctly configured webhook Stable internet connectivity Audience & Problem This template is designed for consultants, HR professionals, and analysts who need a scalable, standardized approach to evaluate which routine tasks in a given profession can be automated, which require human oversight, and which should remain manual to preserve strategic judgment, creativity, and expertise.
by Ria
This is a demo workflow to showcase how to use Supabase to embed a document, retrieve information from the vector store via chat and update the database. Setup steps: set your credentials for Supabase set your credentials for an AI model of your choice set credentials for any service you want to use to upload documents please follow the guidelines in the workflow itself (Sticky Notes) Feedback & Questions If you have any questions or feedback about this workflow - Feel free to get in touch at ria@n8n.io
by Viktor
Nightly Discord Channel Cleanup This workflow runs every day at 9:00 p.m. and: Retrieves all Discord channels using your provided credentials. Pauses briefly to respect Discord API rate limits. Loops through each channel and fetches messages. Filters out messages older than seven days. Deletes those older messages, again pausing to stay within deletion rate limits. By setting up this workflow on a schedule, you can automatically keep Discord channels tidy and compliant with retention policies. 👨🎤 Setup Add your Discord credentials Change the server in each Discord node to the correct one Click the Test Workflow button Activate the workflow to run on a schedule
by DanielV
This workflow is designed to translate SRT subtitle files from one language to another using Google Translate. The workflow follows these main steps: Accept an SRT file upload and target language selection Extract and parse the SRT file content Split the content into translatable segments Translate each segment using Google Translate Reassemble the translated content into a proper SRT format Return the translated file to the user You'll need a Google Console Cloud account to access the Translate API. Who is this for? This workflow is designed for content creators, video editors, translators, and anyone who needs to translate subtitle files (.srt) from one language to another. It's particularly useful for those working with international content, educational materials, or preparing videos for global audiences. What problem does this workflow solve? Translating subtitle files manually is time-consuming and error-prone. Professional translation services can be expensive, especially for multiple videos or long content. This workflow automates the translation process while maintaining the proper SRT format including timestamps and subtitle numbering. Setup Set up Google Translate credentials: -- Create a Google Cloud project and enable the Google Translate API -- Create OAuth credentials and configure them in the Google Translate node Customize language options: -- The default workflow includes English (EN) and Japanese (JP) options -- Add more language options by editing the dropdown field in the "Receive SRT File to Translate" node -- Use standard language codes that Google Translate supports Add more languages: -- Edit the form trigger node to include additional language options in the dropdown
by Avkash Kakdiya
🔁 What This Workflow Does This automation fetches daily AI-related articles from trusted RSS feeds, summarizes them using OpenAI (GPT), and generates a ready-to-post LinkedIn update in your writing style. It then emails the post to you every morning for review and publishing. High-Level Steps: Triggers every morning via Cron. Fetches latest AI news from multiple RSS sources. Filters recent articles (last 24 hrs). Summarizes each article using OpenAI (ChatGPT). Generates a LinkedIn-style post using your tone. Sends the post to your Gmail for review. ⚙️ Setup Steps Estimated setup time: 15–30 minutes You’ll need: OpenAI API key Gmail account connected in n8n RSS feed URLs (defaults are provided) Add your email in the Gmail node to receive daily posts. Add your tone/style prompt in the ChatGPT nodes (instructions inside workflow).