Workflow Templates

Who is this for? This workflow is for everyone who wants to have easier access to their Odoo sales data without complex queries. Use Case To have a clear overview of your sales data in Odoo you typically needs to extract data from it manually to analyse it. This workflow uses OpenAI's language models to create an intelligent chatbot that provides conversational access to your Odoo sales opportunity data. How it works Creates a summary of all Odoo sales opportunities using OpenAI Uses that summary as context for the OpenAI chat model Keeps the summary up to date using a schedule trigger Set up steps: Configure the Odoo credentials Configure OpenAI credentials Toggle "Make Chat Publicly Available" from the Chat Trigger node.

"Ade Technical Analyst" is a dual-workflow AI system combining conversational intelligence with visual chart analysis through Telegram. The system features 11 primary nodes for conversation management and 8 secondary nodes for chart generation and analysis. Core Components: Telegram Integration: Message handling with dynamic typing indicators AI Personality: "Ade" - a financial analyst with 50+ years NYSE/LSE experience using Claude 3.5 Sonnet Chart Generation: TradingView integration via Chart-IMG API with MACD and volume indicators Visual Analysis: GPT-4O vision for technical pattern recognition Memory System: Session-based conversation context retention Target Users Individual traders seeking professional-grade analysis without subscription costs Financial advisors wanting 24/7 AI-powered client support Investment educators needing interactive learning tools Fintech companies requiring white-label analysis solutions Setup Requirements Critical Security Fix Needed: Remove hardcoded API key from Chart-IMG node immediately Store all credentials securely in n8n credential manager Required APIs: OpenRouter (Claude 3.5 Sonnet) OpenAI (GPT-4O vision) Chart-IMG API Telegram Bot Token Technical Prerequisites: n8n version 1.7+ with Langchain nodes Webhook configuration for Telegram Dual-workflow setup with proper ID referencing Workflow Requirements Security Compliance: Never hardcode API keys in workflow JSON files Use n8n credential manager for all sensitive data Implement proper session isolation for user data Include mandatory financial disclaimers Performance Specifications: Model temperature: 0.8 for balanced responses Token limit: 500 for optimized performance Dark theme charts with professional indicators Session-based memory management Need help customizing? Contact me for consulting and support or add me on LinkedIn

Transform your meetings into actionable insights automatically! This workflow captures meeting audio, transcribes conversations, generates AI summaries, and emails the results to participants—all without manual intervention. What's the Goal? Auto-record meetings** when they start and stop when they end Transcribe audio** to text using Vexa Bot integration Generate intelligent summaries** with AI-powered analysis Email summaries** to meeting participants automatically Eliminate manual note-taking** and post-meeting admin work Never miss important discussions** or action items again Why Does It Matter? Save 90% of Post-Meeting Time**: No more manual transcription or summary writing Never Lose Key Information**: Automatic capture ensures nothing falls through cracks Improve Team Productivity**: Focus on discussions, not note-taking Perfect Meeting Records**: Searchable transcripts and summaries for future reference Instant Distribution**: Summaries reach all participants immediately after meetings How It Works Step 1: Meeting Detection & Recording Start Meeting Trigger**: Detects when meeting begins via Google Meet webhook Launch Vexa Bot**: Automatically joins meeting and starts recording End Meeting Trigger**: Detects meeting end and stops recording Step 2: Audio Processing & Transcription Stop Vexa Bot**: Ends recording and retrieves audio file Fetch Meeting Audio**: Downloads recorded audio from Vexa Bot Transcribe Audio**: Converts speech to text using AI transcription Step 3: AI Summary Generation Prepare Transcript**: Formats transcribed text for AI processing Generate Summary**: AI model creates concise meeting summary with: Key discussion points Decisions made Action items assigned Next steps identified Step 4: Distribution Send Email**: Automatically emails summary to all meeting participants Setup Requirements Google Meet Integration: Configure Google Meet webhook and API credentials Set up meeting detection triggers Test with sample meeting Vexa Bot Configuration: Add Vexa Bot API credentials for recording Configure audio file retrieval settings Set recording quality and format preferences AI Model Setup: Configure AI transcription service (e.g., OpenAI Whisper, Google Speech-to-Text) Set up AI summary generation with custom prompts Define summary format and length preferences Email Configuration: Set up SMTP credentials for email distribution Create email templates for meeting summaries Configure participant list extraction from meeting metadata Import Instructions Get Workflow JSON: Copy the workflow JSON code Open n8n Editor: Navigate to your n8n dashboard Import Workflow: Click menu (⋯) → "Import from Clipboard" → Paste JSON → Import Configure Credentials: Add API keys for Google Meet, Vexa Bot, AI services, and SMTP Test Workflow: Run a test meeting to verify end-to-end functionality Your meetings will now automatically transform into actionable summaries delivered to your inbox!

This workflow template creates an AI agent chatbot with long-term memory and note storage using Google Docs and Telegram integration. Google Docs Integration 📄 n8n Google Docs Node Setup Google Credentials Telegram Integration 💬 Telegram Setup Core Features 🌟 AI Agent Integration 🤖 Implements a sophisticated AI agent with memory management capabilities Uses GPT-4o-mini and DeepSeek models for intelligent conversation handling Maintains context awareness through session management Memory System 🧠 Long-term memory storage using Google Docs Separate note storage system for specific information Window buffer memory for maintaining conversation context Intelligent memory retrieval and storage mechanisms Communication Interface 💬 Telegram integration for message handling Real-time message processing and response generation Technical Components 🔧 Memory Architecture 📚 Dual storage system separating memories from notes Automated memory retrieval before each interaction Structured memory saving with timestamps AI Models 🤖 Primary GPT-4o-mini mini model for general interactions DeepSeek-V3 Chat for specialized processing Custom agent system with tool integration Storage Integration 💾 Google Docs integration for persistent storage Separate document management for memories and notes Automated document updates and retrievals

This automated workflow scrapes and processes the monthly "Who is Hiring" thread from Hacker News, transforming raw job listings into structured data for analysis or integration with other systems. Perfect for job seekers, recruiters, or anyone looking to monitor tech job market trends. How it works Automatically fetches the latest "Who is Hiring" thread from Hacker News Extracts and cleans relevant job posting data using the HN API Splits and processes individual job listings into structured format Parses key information like location, role, requirements, and company details Outputs clean, structured data ready for analysis or export Set up steps Configure API access to [Hacker News](https://github.com/HackerNews/API ) (no authentication required) Follow the steps to get your cURL command from https://hn.algolia.com/ Set up desired output format (JSON structured data or custom format) Optional: Configure additional parsing rules for specific job listing information Optional: Set up integration with preferred storage or analysis tools The workflow transforms unstructured job listings into clean, structured data following this pattern: Input: Raw HN thread comments Process: Extract, clean, and parse text Output: Structured job listing data This template saves hours of manual work collecting and organizing job listings, making it easier to track and analyze tech job opportunities from Hacker News's popular monthly hiring threads.

Use case Manually monitoring Reddit for viable business ideas is time-consuming and inconsistent. This workflow automatically analyzes trending Reddit discussions using AI to surface high-potential opportunities, filter irrelevant content, and generate actionable insights - saving entrepreneurs 10+ hours weekly in market research. What this workflow does This AI-powered workflow automatically collects trending Reddit discussions, analyzes posts for viable business opportunities using GPT-4, applies smart filters to exclude low-value content, and generates scored opportunity reports with market insights. It identifies unmet customer needs through sentiment analysis, prioritizes high-potential ideas using custom criteria, and outputs structured data to Google Sheets for actionable decision-making. Setup Add Reddit,Google and OpenAI credentials Configure target subreddits in Subreddit node Test workflow by testing workflow Review generated opportunity report in Google Sheets How to adjust this template Change data sources**: Replace Reddit trigger with Twitter/X or Hacker News API Modify criteria**: Adjust scoring thresholds in Opportunity Calculator node Add integrations**: Create automatic Slack alerts for urgent opportunities Generate draft business plans using AI Document Writer

How it works This workflow adds a priority to each Todoist item in your inbox, based on a list of projects that you add in the workflow. Setup Add your Todoist credentials Add your OpenAI credentials Set your project names and add priority

How it works • Transcribes a WhatsApp voice or text message from a prospect using Whisper or GPT • Extracts key information (name, need, context, urgency) via AI • Matches the most relevant service pack by comparing the prospect’s need with Airtable data • Dynamically fills a branded template via APITEMPLATE (HTML or PDF) • Generates a clean, personalized business proposal — including dynamic links (payment, calendar, etc.) • Sends the final PDF back instantly via WhatsApp or email Set up steps • ⏱ Estimated setup time: 45–60 minutes • ✅ You’ll need:  ◦ WhatsApp Business Cloud API access (with webhook configured)  ◦ OpenAI API key (Whisper + GPT)  ◦ Airtable (to store service packs and client input)  ◦ APITEMPLATE account (template with placeholders like {{nom}}, {{prix}}, {{lien_reservation}}, etc.)  ◦ n8n instance (cloud or self-hosted) • 📦 Create your service packs in Airtable with associated links (Stripe, Calendly…) • 🔗 The proposal auto-includes these links dynamically inside the PDF • 🚀 Workflow orchestrates the end-to-end process: from WhatsApp input to PDF delivery

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.

How it works This template is a complete, hands-on tutorial that lets you build and interact with your very first AI Agent. Think of an AI Agent as a standard AI chatbot with superpowers. The agent doesn't just talk; it can use tools to perform actions and find information in real-time. This workflow is designed to show you exactly how that works. The Chat Interface (Chat Trigger): This is your window to the agent. It's a fully styled, public-facing chat window where you can have a conversation. The Brain (AI Agent Node): This is the core of the operation. It takes your message, understands your intent, and intelligently decides which "superpower" (or tool) it needs to use to answer your request. The agent's personality and instructions are defined in its extensive system prompt. The Tools (Tool Nodes): These are the agent's superpowers. We've included a variety of useful and fun tools to showcase its capabilities: Get a random joke. Search Wikipedia for a summary of any topic. Calculate a future date. Generate a secure password. Calculate a monthly loan payment. Fetch the latest articles from the n8n blog. The Memory (Memory Node): This gives the agent a short-term memory, allowing it to remember the last few messages in your conversation for better context. When you send a message, the agent's brain analyzes it, picks the right tool for the job, executes it, and then formulates a helpful response based on the tool's output. Set up steps Setup time: ~3 minutes This template is nearly ready to go out of the box. You just need to provide the AI's "brain." Configure Credentials: This workflow requires an API key for an AI model. Make sure you have credentials set up in your n8n instance for either Google AI (Gemini) or OpenAI. Choose Your AI Brain (LLM): By default, the workflow uses the Google Gemini node. If you have Google AI credentials, you're all set! If you prefer to use OpenAI, simply disable the Gemini node and enable the OpenAI node. You only need one active LLM node. Make sure it is connected to the Agent parent node. Explore the Tools: Take a moment to look at the different tool nodes connected to the Your First AI Agent node. This is where the agent gets its abilities! You can add, remove, or modify these to create your own custom agent. Activate and Test! Activate the workflow. Open the public URL for the Example Chat Window node (you can copy it from the node's panel). Start chatting! Try asking it things like: "Tell me a joke." "What is n8n?" "Generate a 16-character password for me." "What are the latest posts on the n8n blog?" "What is the monthly payment for a $300,000 loan at 5% interest over 30 years?"

Who’s it for 👥 This template is perfect for content creators, marketers, and researchers managing WeChat public account articles! 🚀 It’s ideal for n8n newcomers or anyone wanting to save time on manual content analysis, especially if you use Google Sheets for tracking. 📊 Whether you’re into AI, 欧阳良宜, or automation, this is for you! 😄 How it works / What it does 🔧 This workflow automates the retrieval, filtering, classification, and summarization of WeChat articles. 🌐 It reads RSS feed links from a Google Sheet, filters articles from the last 10 days ⏳, cleans HTML content 🧹, classifies them as relevant or not 🎯, generates insightful Chinese summaries with AI 🤖, and saves results to Google Sheets and Notion. 📝 Outputs are Slack-formatted for team collaboration! 💬 How to set up 🛠️ Prepare Google Sheets: Use your own documentId (replace the example) and set up sheets "Save Initial Links" (gid=198451233) and "Save Processed Data" (gid=1936091950). 📋 Configure Credentials: Add Google Sheets and OpenAI API credentials—avoid hardcoding keys! 🔐 Set RSS Feed: Update the rss_feed_url in the "RSS Read" node with your WeChat RSS feed. 🌐 Customize AI: Tweak "Relevance Classification" and "Basic LLM Chain" prompts for your topics (e.g., 欧阳良宜, AI). 🎨 Notion (Optional): Swap the databaseId (e.g., 22e79d55-2675-8055-a143-d55302c3c1b1) with your own. 📚 Run Workflow: Trigger manually via the "When clicking ‘Execute workflow’" node. 🚀 Requirements ✅ n8n account with Google Sheets and OpenAI integrations. Access to a WeChat public account RSS feed. Basic JSON and node config knowledge. How to customize the workflow 🎛️ Topic Adjustment: Update categories in "Relevance Classification" for new topics (e.g., "technology", "education"). 🌱 Summary Length: Modify the LLM prompt in "Basic LLM Chain" to adjust length or style. ✂️ Output Destination: Add Slack or Email nodes for more outputs. 📩 Date Filter: Change the "IF (Filter by Date)" condition (e.g., 7 days instead of 10). ⏰ Scalability: Use a "Schedule Trigger" node for automation. ⏳

This n8n template provides a powerful AI-powered chatbot that acts as your personal Spotify DJ. Simply tell the chatbot what kind of music you're in the mood for, and it will intelligently create a custom playlist, give it a fitting name, and populate it with relevant tracks directly in your Spotify account. The workflow is built to be flexible, allowing you to easily change the underlying AI model to your preferred provider, making it a versatile starting point for any AI-driven project. Who is this for? Music lovers:** Instantly create playlists for any activity, mood, or genre without interrupting your flow. Developers & AI enthusiasts:** A perfect starting point to understand how to build a functional AI Agent that uses tools to interact with external services. Automation experts:** See a practical example of how to chain AI actions and sub-workflows for more complex, stateful automations. What problem does this solve? Manually creating a good playlist is time-consuming. You have to think of a name, search for individual songs, and add them one by one. This workflow solves that by: Automating playlist creation:** Turns a simple natural language request (e.g., "I need a playlist for my morning run") into a fully-formed Spotify playlist. Reducing manual effort:** Eliminates the tedious task of searching for and adding multiple tracks. Providing player control:** Allows you to manage your Spotify player (play, pause, next) directly from the chat interface. Centralizing music management:** Acts as a single point of control for both creating playlists and managing playback. How it works Trigger & input: The workflow starts when you send a message in the Chat Trigger interface. AI agent & tool-use: An AI Agent, powered by a Large Language Model (LLM), interprets your message. It has access to a set of "tools" that allow it to interact with Spotify. Playlist creation sub-workflow: If you ask for a new playlist, the Agent calls a sub-workflow using the Create new playlist tool. This sub-workflow uses another AI call to brainstorm a creative playlist name and a list of suitable songs based on your request. Spotify actions: The sub-workflow then connects to Spotify to: Create a new, empty playlist with the generated name. Search for each song from the AI's list to get its official Spotify Track ID. Add each track to the new playlist. Player control: If your request is to control the music (e.g., "pause the music"), the Agent uses the appropriate tool (Pause player, Resume player, etc.) to directly control your active Spotify player. Setup Accounts & API keys: You will need active accounts and credentials for: Your AI provider (e.g., OpenAI, Groq, local LLMs via Ollama): To power the AI Agent and the playlist generation. Spotify: To create playlists and control the player. You'll need to register an application in the Spotify Developer Dashboard to get your credentials. Configure credentials: Add your AI provider's API key to the Chat Model nodes. The template uses OpenAI by default, but you can easily swap this out for any compatible Langchain model node. Add your Spotify OAuth2 credentials to all Spotify and Spotify Tool nodes. Activate workflow: Once all credentials are set and the workflow is saved, click the "Active" toggle. You can now start interacting with your Spotify AI Agent via the chat panel! Taking it further This template is a great foundation. Here are a few ideas to expand its capabilities: Become the party DJ:** Make the Chat Trigger's webhook public. You can then generate a QR code that links to the chat URL. Party guests can scan the code and request songs directly from their phones, which the agent can add to a collaborative playlist or the queue. Expand the agent's skills:** The Spotify Tool node has more actions available. Add a new tool for Add to Queue so you can ask the agent to queue up a specific song without creating a whole new playlist. Integrate with other platforms:** Swap the Chat Trigger for a Telegram or Discord trigger to build a Spotify bot for your community. You could also connect it to a Webhook to take requests from a custom web form.