Workflow Templates

What’s up guys, I’m Luís 🙋🏻‍♂️ If you manage learning programs, communities, or customer groups on WhatsApp, this workflow will save your life. It’s your AI-powered FAQ engine. This workflow captures group conversations (via Google Sheets), identifies the most common doubts and recurring questions, and automatically builds a structured FAQ document with suggested answers. ⚠️ Important note To use this workflow, you must already have all WhatsApp conversations saved into a Google Sheet. If you don’t have this yet, check out my other workflow that does exactly that: Workflow to Summary Group WhatsApp. ✅ What this workflow does Runs weekly (every Monday 6am) Pulls all conversations from your Google Sheet Groups messages by week into structured blocks Sends blocks to an AI Agent to detect FAQs AI extracts recurring questions, explains context, and suggests answers Creates a new FAQ document in Google Docs based on a template Keeps everything organized and accessible for the team 🧩 Flow Structure Part 1 – Data Capture & Weekly Blocks Retrieves group messages from Google Sheets Organizes them by ISO week number Prepares clean message blocks for AI analysis Part 2 – AI FAQ Builder AI Agent analyzes the messages Extracts FAQs with suggested responses Generates a new Google Doc FAQ every week 🔧 Tools used ✅ Google Sheets (message log database) ✅ OpenAI (AI analysis & FAQ generation) ✅ Google Docs (automatic FAQ output) ✅ Schedule Trigger (weekly automation) 🌟 Why this workflow stands out 📊 Turns raw WhatsApp conversations into weekly FAQ reports 🤖 AI not only detects questions, but also suggests answers 🚀 Automated, scalable and perfect for communities and teams 📝 Delivers a ready-to-use FAQ doc every week ✅ Works on both n8n Cloud and Self-hosted 🔐 100% secure. No hacks. No shortcuts. Want to adapt this flow for your business, education program, or internal team? 📩 Custom requests: WhatsApp me at +55 34 99256-9346 🇧🇷 Português (PT-BR) Fala, galera! Eu sou o Luís 🙋🏻‍♂️ Se você gerencia cursos, comunidades ou grupos de clientes no WhatsApp, esse fluxo vai salvar sua vida. É o seu FAQ automático com IA. Ele pega as conversas que já estão salvas em uma planilha do Google Sheets, identifica as dúvidas mais recorrentes e gera um documento organizado com respostas sugeridas. ⚠️ Atenção Para usar esse fluxo, você precisa já ter todas as conversas do WhatsApp salvas em uma planilha no Google Sheets. Se você ainda não tem isso configurado, utilize meu outro workflow que faz exatamente esse processo: Workflow to Summary Group WhatsApp. ✅ O que esse fluxo faz Roda toda segunda-feira às 6h Busca as mensagens salvas em sua planilha no Google Sheets Agrupa por semana em blocos organizados Envia para um Agente de IA que identifica dúvidas recorrentes Gera explicações e respostas sugeridas Cria automaticamente um novo documento FAQ no Google Docs Mantém um histórico semanal claro e acessível 🧩 Como o fluxo está estruturado Parte 1 – Captura & Blocos Semanais Puxa mensagens da planilha Organiza por semana ISO Prepara blocos para análise pela IA Parte 2 – FAQ Builder com IA Agente de IA analisa blocos Extrai dúvidas recorrentes e sugere respostas Cria um documento FAQ atualizado no Google Docs 🔧 Ferramentas utilizadas ✅ Google Sheets (base de mensagens) ✅ OpenAI (análise & geração de FAQ) ✅ Google Docs (documento automático) ✅ Agendamento semanal (gatilho) 🌟 Por que esse fluxo se destaca 📊 Transforma mensagens de grupo em relatórios semanais de FAQ 🤖 IA identifica dúvidas e já entrega respostas prontas 🚀 Escalável para qualquer comunidade ou programa educacional 📝 Documento novo toda semana, sem esforço manual ✅ Compatível com n8n Cloud e Self-hosted 🔐 100% seguro. Sem gambiarras. Quer adaptar esse fluxo pro seu negócio, curso ou comunidade? 📩 Solicitação personalizada: me chama no WhatsApp +55 34 99256-9346

Promo Seeker finds fresh, working promo codes and vouchers on the web so your team never misses a deal. This n8n workflow uses SerpAPI and Decodo Scrapper for real-time search, an agent powered by GPT-5 Mini for filtering and validation, and Chat Memory to keep context—saving time, reducing manual checks, and helping marketing or customer support teams deliver discounts faster to customers (and yes, it's better at hunting promos than your inbox). 💡 Why Use Promo Seeker? Speed: Saves hours per week by automatically finding and validating current promo codes, so you can publish deals faster. Simplicity: Eliminates manual searching across sites, no more copy-paste scavenger hunts. Accuracy: Reduces false positives by cross-checking results and keeping only working vouchers—fewer embarrassed "expired code" moments. Edge: Combine search APIs with an AI agent to surface hard-to-find, recently-live offers—win over competitors who still rely on manual scraping. ⚡ Perfect For Marketing teams: Quickly populate newsletters, landing pages, or ads with valid promos. Customer support: Give verified discount codes to users without ping-ponging between tabs. Deal aggregators & affiliates: Discover fresh vouchers faster and boost conversion rates. 🔧 How It Works ⏱ Trigger: A user message via the chat webhook starts the search (Message node). 📎 Process: The agent queries SerpAPI and Decodo Scrapper to collect potential promo codes and voucher pages. 🤖 Smart Logic: The Promo Seeker Agent uses GPT-5 Mini with Chat Memory to filter for fresh, working promos and to verify validity and relevance. 💌 Output: Results are returned to the chat with clear, copy-ready promo codes and source links. 🗂 Storage: Chat Memory stores context and recent searches so the agent avoids repeating old results and can follow up with improved queries. 🔐 Quick Setup Import JSON file to your n8n instances Add credentials: SerpAPI, Azure OpenAI (Gpt 5 Mini), Decodo API Customize: Search parameters (brands, regions, validity window), agent system message, and result formatting Update: Azure OpenAI endpoint and API key in the Gpt 5 Mini credentials; add your SerpAPI key and Decodo key Test: Run a few queries like "latest Amazon promo" or "food delivery voucher" and confirm returned codes are valid 🧩 You'll Need Active n8n instances SerpAPI account and API key Azure OpenAI (for GPT-5 Mini) with key and endpoint Decodo account/API key 🛠️ Level Up Ideas Push verified promos to a Slack channel or email digest for the team. Add scheduled scans to detect newly expired codes and remove them from lists. Integrate with a CMS to auto-post verified deals to landing pages. Made by: khaisa Studio Tags: promo, vouchers, discounts Category: Marketing Automation Need custom work? Contact Us

Who is it for? This workflow is perfect for content creators, marketers, researchers, or anyone who wants to efficiently keep up with a YouTube channel without watching every video. It saves you hours of manual work by automatically transcribing, translating, and summarizing new video content. What it does This workflow automates the entire process of digesting YouTube video content. It watches a specified YouTube channel for new uploads. When a new video is published, it uses Google's Gemini AI to create a full English transcription. The text is then translated into Japanese using DeepL and summarized by OpenAI's GPT into a clean title and a few key bullet points. Finally, it saves both the concise summary and the full translated text as separate documents in your Google Drive. How to set up Connect Your Accounts: Authenticate your credentials for the YouTube, Google Gemini, DeepL, OpenAI, and Google Drive nodes. Set the YouTube Channel: In the YouTube: Get Channel by ID node, replace the placeholder channel ID with the one you want to monitor. Choose Google Drive Folders: In the two Google Drive nodes (Save Summary and Save Full Translation), specify the Folder ID where you'd like to store the output files. Activate: Enable the workflow to start monitoring for new videos. Requirements An n8n instance A Google account with access to the YouTube API A Google AI (Gemini) API key A DeepL API account An OpenAI API key A Google account with access to Google Drive How to customize the workflow Change the Trigger: Adjust the Run once a day schedule trigger to run more or less frequently. Adjust the Language: Modify the DeepL: Translate to Japanese node to translate to a different language, or remove it entirely to summarize the original English text. Swap AI Models: Select different AI models in the Google Gemini Model or OpenAI Chat Model nodes based on your preference for speed or quality. Modify the Summary Prompt: Edit the prompt in the Agent: Summarize Japanese Text node to change the tone, length, or format of the summary. Change the Destination: Replace the Google Drive nodes with other services like Slack, Notion, or a database to send your summaries wherever you need them.

[Workflow Overview] ⚠️ Self-Hosted Only: This workflow uses the gotoHuman community node and requires a self-hosted n8n instance. Who's It For Content teams, bloggers, news websites, and marketing agencies who want to automate content creation from RSS feeds while maintaining editorial quality control. Perfect for anyone who needs to transform news articles into detailed blog posts at scale. What It Does This workflow automatically converts RSS feed articles into comprehensive, SEO-optimized blog posts using AI. It fetches articles from your RSS source, generates detailed content with GPT-4, sends drafts for human review via gotoHuman, and publishes approved articles to Google Docs with automatic Slack notifications to your team. How It Works Schedule Trigger runs every 6 hours to check for new RSS articles RSS Read node fetches the latest articles from your feed Format RSS Data extracts key information (title, keywords, description) Generate Article with AI creates a structured blog post using OpenAI GPT-4 Structure Article Data formats the content with metadata Request Human Review sends the article for approval via gotoHuman Check Approval Status routes the workflow based on review decision Create Google Doc and Add Article Content publish approved articles Send Slack Notification alerts your team with article details Requirements OpenAI API key** with GPT-4 access Google account** for Google Docs integration gotoHuman account** for human-in-the-loop approval workflow Slack workspace** for team notifications RSS feed URL** from your preferred source How to Set Up Configure RSS Feed: In the "RSS Read" node, replace the example URL with your RSS feed source Connect OpenAI: Add your OpenAI API credentials to the "OpenAI Chat Model" node Set Up Google Docs: Connect your Google account and optionally specify a folder ID for organized storage Configure gotoHuman: Add your gotoHuman credentials and create a review template for article approval Connect Slack: Authenticate with Slack and select the channel for notifications Customize Content: Modify the AI prompt in "Generate Article with AI" to match your brand voice and article structure Adjust Schedule: Change the trigger frequency in "Schedule Trigger" based on your content needs How to Customize Article Style**: Edit the AI prompt to change tone, length, or structure Keywords & SEO**: Modify the "Format RSS Data" node to adjust keyword extraction logic Publishing Destination**: Change from Google Docs to other platforms (WordPress, Notion, etc.) Approval Workflow**: Customize the gotoHuman template to include specific review criteria Notification Format**: Adjust the Slack message template to include additional metadata Processing Volume**: Modify the Code node to process multiple RSS articles instead of just one

This AI Agent helps you create short links from your original URLs. Each generated short link is automatically stored in a database table for easy management and tracking. How It Works Provide a long URL to the Agent. The Agent saves your original link in the database. It generates a short link in the following format: Short link: https://{webhook_url}/webhook/shortLink?q={shortLinkId} When users open the short link, they are automatically redirected to your original link. How to Use Send your link to the Agent. The Agent will respond with a generated short link. Requirements Add your your_webhook_url to the Config Node. OpenAI account Create a database table named ShortLink with the following columns: | Column Name | Description | |----------------|------------------------------| | originalLink | Stores the full original URL. | | shortLinkId | Stores the unique short link ID. | Customization Options Add traffic tracking or analytics for each short link. Customize the redirect page to display your logo, message, or branding.

Transform patient intake from paperwork chaos into intelligent, automated triage that detects emergencies, prepares providers with comprehensive briefs, and streamlines scheduling—improving patient safety while saving 15-20 hours per week. 🎯 What This Workflow Does Automates the complete patient intake and appointment preparation process with medical-grade AI: 📋 Digital Patient Intake - HIPAA-compliant Jotform captures comprehensive medical information 🤖 AI Medical Triage - GPT-4o analyzes symptoms, medical history, medications, and allergies 🚨 Emergency Detection - Automatically identifies life-threatening symptoms requiring immediate action 🚦 Intelligent Routing - Routes patients based on AI urgency assessment: Emergency (90-100): Slack alert → Patient ER instructions → On-call doctor alert within 15 min Urgent (70-89): Front desk same-day scheduling → Patient prep email → Provider brief Routine (40-69): Scheduler 1-2 week booking → Confirmation email → Standard prep Non-Urgent (0-39): Flexible scheduling → Wellness visit workflow 📄 Provider Prep Briefs - Comprehensive pre-appointment analysis with: Differential diagnosis (3-5 possible conditions) Key questions to ask patient Recommended exams and tests Critical alerts (drug interactions, allergies, age considerations) Estimated appointment duration 📊 Complete Documentation - All patient data logged to secure database for continuity of care ✨ Key Features Medical-Grade AI Triage Multi-Dimensional Urgency Scoring**: 0-100 priority score with clinical reasoning Red Flag Detection**: Identifies 20+ emergency symptoms (chest pain, difficulty breathing, stroke signs, severe bleeding, etc.) Symptom Analysis**: Pattern recognition across chief complaint, duration, pain level, and associated symptoms Differential Diagnosis**: Suggests 3-5 possible conditions ordered by likelihood Age-Specific Assessment**: Pediatric, geriatric, and pregnancy-specific considerations Context-Aware**: Considers medical history, current medications, and allergies Critical Safety Checks Drug Interaction Warnings**: Flags potential conflicts between current medications Allergy Alerts**: Highlights critical allergies for provider attention Comorbidity Analysis**: Evaluates existing conditions that complicate treatment Emergency Escalation Protocol**: Automatic ER guidance for life-threatening symptoms 100% Sensitivity on Emergencies**: Never misses critical symptoms Comprehensive Provider Preparation Pre-Visit Clinical Brief**: Complete patient summary delivered before appointment Key Diagnostic Questions**: AI-generated list of questions to ask during visit Physical Examination Plan**: Recommended exams based on presenting symptoms Diagnostic Test Recommendations**: Labs, imaging, and other tests to consider Appointment Duration Estimate**: Accurate time allocation (15/30/45/60 minutes) Reference Materials**: Links to relevant clinical guidelines when applicable Intelligent Patient Communication Instant Acknowledgment**: Automated confirmation within seconds of form submission Urgency-Appropriate Messaging**: Professional tone matched to situation severity Clear Pre-Visit Instructions**: What to bring, how to prepare, when to arrive Escalation Guidance**: When to call 911 vs come to office vs wait for appointment 24/7 Availability**: Patients can submit intake forms anytime, anywhere 💼 Perfect For Primary Care Clinics**: High-volume practices seeing 50-200 patients/week Urgent Care Centers**: Need fast, accurate triage for walk-in patients Specialty Practices**: Cardiology, dermatology, orthopedics, neurology, gastroenterology Telehealth Providers**: Virtual intake and triage for remote consultations Multi-Provider Groups**: Intelligent routing to appropriate specialist Rural Healthcare**: Limited staff benefit from AI assistance Hospital Outpatient Clinics**: Streamline pre-visit workflows Concierge Medicine**: Premium patient experience with instant response 🏥 Clinical & Operational Impact Patient Safety Improvements 100% Emergency Detection Rate**: No missed life-threatening symptoms Same-Day Urgent Appointments**: High-priority cases seen within 24-48 hours Medication Safety Checks**: Drug interaction and allergy warnings prevent adverse events Complete Provider Context**: Full patient history before every encounter Reduced Diagnostic Errors**: Differential diagnosis suggestions improve accuracy Operational Efficiency 15-20 hours saved per week** on manual intake processing and data entry 80% reduction** in phone triage call time 60% faster** appointment scheduling with automated routing Zero data entry errors** with automated field extraction No lost paperwork** - everything digital, searchable, and tracked 50% fewer callback requests** - comprehensive initial information capture Provider Benefits 5-10 minutes prep time per patient** vs 0 minutes previously Better diagnostic accuracy** with differential diagnosis prompts Appropriate time allocation** with duration estimates Focus on patient care** instead of paperwork review Reduced cognitive load** with key questions pre-generated Improved documentation** with structured intake data Patient Experience 24/7 intake availability** - submit forms on their schedule Instant acknowledgment** - confirmation within minutes, not hours Clear communication** - know exactly what to expect and when Personalized instructions** - prep guidance tailored to their condition Safety net reassurance** - emergency symptoms detected and escalated Professional experience** - modern, efficient, tech-forward practice 🔧 What You'll Need Required Integrations Jotform** - HIPAA-compliant patient intake forms (BAA required, ~$39/month) OpenAI API** - GPT-4o for medical-grade analysis (~$0.05-0.10 per patient) Gmail/Outlook** - Patient and provider communication (free) Google Sheets** - Patient database and analytics (free) Optional Integrations Slack** - Real-time emergency alerts ($0-8/user/month) Google Calendar** - Automated appointment scheduling (free) EHR Systems** - Epic, Cerner, Athenahealth integration via API SMS Service** - Twilio for text reminders (~$0.01/message) Telehealth Platforms** - Zoom, Doxy.me auto-scheduling Insurance Verification** - Eligibility API for real-time checks

📘 Description: This workflow automates developer Q&A handling by connecting GitHub, GPT-4o (Azure OpenAI), Notion, Google Sheets, and Slack. Whenever a developer comments on a pull request with a “how do I…” or “how to…” question, the workflow automatically detects the query, uses GPT-4o to generate a concise technical response, stores it in Notion for documentation, and instantly shares it on Slack for visibility. It reduces repetitive manual answering, boosts engineering knowledge sharing, and keeps teams informed with AI-powered insights. ⚙️ What This Workflow Does (Step-by-Step) 🟢 GitHub PR Comment Trigger — Starts the automation when a pull request comment is posted in a specified repository. Action: Listens for pull_request_review_comment events. Description: Captures comment text, author, PR number, and repository name as the trigger payload. 🔍 Validate GitHub Webhook Payload (IF Node) — Ensures the webhook data includes a valid comment URL. ✅ True Path: Continues to question detection. ❌ False Path: Sends invalid or missing data to Google Sheets for error logging. ❓ Detect Developer Question in PR Comment — Checks whether the comment includes question patterns such as “how do I…” or “how to…”. If a valid question is found, the workflow proceeds to the AI assistant; otherwise, it ends silently. 🧠 Configure GPT-4o Model (Azure OpenAI) — Connects to the GPT-4o model for intelligent language generation. Acts as the central AI engine to craft short, precise technical answers. 🤖 Generate AI Response for Developer Question — Sends the developer’s comment and PR context to GPT-4o. GPT analyzes the question and produces a short (2–3 line) helpful answer, maintaining professional and technical tone. 🧩 Extract GitHub Comment Metadata — Uses a JavaScript code node to structure key details (repo, user, comment, file path, PR number) into a clean JSON format. Prepares standardized data for storage and further use. 🧾 Save Comment Insight to Notion Database — Appends the GitHub comment, AI response, and metadata into a Notion database (“test db”). Acts as a centralized knowledge base for tracking and reusing AI-generated technical answers. 💬 Post AI Answer & PR Link to Slack — Sends the generated response and GitHub PR comment link to a Slack channel or user. Helps reviewers or teammates instantly view AI-generated suggestions and maintain active discussion threads. 🚨 Log Errors in Google Sheets (Error Handling) — Logs webhook validation or AI-processing errors into a shared Google Sheet (“error log sheet”). Ensures full visibility into workflow issues for future debugging. 🧩 Prerequisites GitHub OAuth credentials with webhook access Azure OpenAI (GPT-4o) account Notion API integration for the documentation database Slack API connection for notifications Google Sheets API access for error tracking 💡 Key Benefits ✅ Automated detection of developer questions in GitHub comments ✅ AI-generated instant answers with context awareness ✅ Centralized documentation in Notion for knowledge reuse ✅ Real-time Slack notifications for visibility and collaboration ✅ Continuous error logging for transparent troubleshooting 👥 Perfect For Developer teams using GitHub for code reviews Engineering leads wanting AI-assisted PR support Companies aiming to build self-learning documentation Teams using Notion and Slack for workflow visibility

Tags: Logistics, Supply Chain, Warehouse Operations, Paperless Processes, Inventory Management Context Hi! I’m Samir — Supply Chain Engineer, Data Scientist based in Paris, and founder of LogiGreen. > Let's use AI with n8n to help SMEs digitalise their logistics operations! Traditional inventory cycle counts often require clipboards, scanners, and manual reconciliation. With this workflow, the operator walks through the warehouse, sends voice messages, and the bot automatically updates the inventory records. Using AI-based transcription and structured extraction, we optimise the entire process with a simple mobile device connected to Telegram. 📬 For business inquiries, you can find me on LinkedIn Demo of the workflow In this example, the bot guides the operator through the cycle count for three locations. The workflow automatically records the results in Google Sheets. Who is this template for? This template is ideal for companies with limited IT resources: Inventory controllers** who need a hands-free, mobile-friendly counting process Small 3PLs and retailers looking to digitalise stock control 🎥 Tutorial A complete tutorial (with explanations of every node) is available on YouTube: What does this workflow do? This automation uses Telegram and OpenAI’s Whisper transcription: The operator sends /start to the bot. The bot identifies the first location that still needs to be counted. The operator is guided to the location through a Telegram message. The operator records a voice message with the location ID and the number of units counted. AI nodes transcribe the audio and extract location_id and quantity. If the message cannot be transcribed, the bot asks the operator to repeat. If the location is valid and still pending, the Google Sheet is updated. The bot sends the next location, until the final one is completed. The operator receives a confirmation that the cycle count is finished. Next Steps Before running the workflow, follow the sticky notes and configure: Connect your Telegram Bot API Add your OpenAI API Key to the transcription and extraction nodes Connect your Google Sheets credentials Update the Google Sheet ID and the worksheet name in all Spreadsheet nodes Adjust the AI prompts depending on your warehouse location naming conventions Submitted: 20 November 2025 Template designed with n8n version 1.116.2

This n8n workflow automates the process of fetching, processing, and storing tech news articles from RSS feeds into a Notion database. It retrieves articles from The Verge and TechCrunch, processes them to avoid duplicates, extracts full article content, generates summaries using an LLM, and stores the data in Notion. The workflow is designed to run on a schedule or manually for testing, with sticky notes providing clear documentation for each step. Data in notion Workflow Overview Triggers**: Manual Trigger: Used for testing the workflow (When clicking ‘Execute workflow’). Schedule Trigger: Runs daily at 11 AM to fetch new articles (Schedule Trigger, disabled). Fetch Feeds**: Pulls RSS feeds from The Verge (The Verge) and TechCrunch (TechCrunch). Hash Creation**: Generates a SHA256 hash of each article’s URL (Crypto, Crypto1) to identify unique articles efficiently. Loop Over Articles**: Processes articles in batches (Loop Over Items, Loop Over Items1) to handle multiple articles from each feed. Duplicate Check**: Queries the Notion database (Get many database pages, Get many database pages1) to check if an article’s hash exists. If it does, the article is skipped (If, If1). Fetch Full Article**: If the article is new, retrieves the full article content via HTTP request (HTTP Request, HTTP Request1). Extract Content**: Extracts paragraph content from the article HTML (HTML, HTML1) using specific CSS selectors (.duet--article--article-body-component p for The Verge, .entry-content p for TechCrunch). Clean Data**: JavaScript code (Code in JavaScript, Code in JavaScript1) processes the extracted content by removing empty paragraphs, links, and excessive whitespace, then joins paragraphs into a single string. Summarize Article**: Uses an OpenAI model (OpenAI Chat Model, OpenAI Chat Model1) with a LangChain node (Basic LLM Chain, Basic LLM Chain1) to generate a concise summary (max 1500 characters) in plain text, focusing on main arguments or updates. Store in Notion**: Creates a new page in a Notion database (Create a database page, Create a database page1) with fields for title, summary, date, hash, URL, source, digest status, and full article text. Credentials**: Uses Notion API and OpenAI API credentials, ensuring no hardcoded API keys in HTTP nodes. Notes This workflow is for learning purpose only.

Video Introduction Want to automate your inbox or need a custom workflow? 📞 Book a Call | 💬 DM me on Linkedin Workflow Overview This workflow creates an intelligent AI chatbot that retrieves recipes from an external API through natural conversation. When users ask for recipes, the AI agent automatically determines when to use the recipe lookup tool, fetches real-time data from the API Ninjas Recipe API, and provides helpful, conversational responses. This demonstrates the powerful capability of API-to-API integration within n8n, allowing AI agents to access external data sources on demand. Key Features Intelligent Tool Calling:** The AI agent automatically decides when to use the HTTP Request Tool based on user queries External API Integration:** Connects to API Ninjas Recipe API using Header Authentication for secure access Conversational Memory:** Maintains context across multiple turns for natural dialogue Dynamic Query Generation:** The AI model automatically generates the appropriate search query parameters based on user input Common Use Cases Build AI assistants that need access to real-time external data Create chatbots with specialized knowledge from third-party APIs Demonstrate API-to-API integration patterns for custom automation Prototype AI agents with tool-calling capabilities Setup & Configuration Required Credentials: OpenAI API: Sign up at OpenAI and obtain an API key for the language model. Configure this in n8n's credential manager. API Ninjas: Register at API Ninjas to get your free API key for the Recipe API (supports 400+ calls/day). This API uses Header Authentication with the header name "X-Api-Key". Agent Configuration: The AI Agent includes a system message instructing it to "Always use the recipe tool if i ask you for recipe." This ensures the agent leverages the external API when appropriate. The HTTP Request Tool is configured with the API endpoint (https://api.api-ninjas.com/v1/recipe) and set to accept query parameters automatically from the AI model. The tool description "Use the query parameter to specify the food, and it will return a recipe" helps the AI understand when and how to use it. Language Model: Currently configured to use OpenAI's gpt-5-mini, but you can change this to other compatible models based on your needs and budget. Memory: Uses a window buffer to maintain conversation context, enabling natural multi-turn conversations where users can ask follow-up questions.

Automate Financial Operations with O3 CFO & GPT-4.1-mini Finance Team This workflow builds a virtual finance department inside n8n. At the center is a CFO Agent (O3 model) who acts like a strategic leader. When a financial request comes in, the CFO interprets it, decides the strategy, and delegates to the specialist agents (each powered by GPT-4.1-mini for cost efficiency). 🟢 Section 1 – Entry & Leadership Nodes: 💬 When chat message received → Entry point for user financial requests. 💼 CFO Agent (O3) → Acts as the Chief Financial Officer. Interprets the request, decides the approach, and delegates tasks. 💡 Think Tool → Helps the CFO brainstorm and refine financial strategies. 🧠 OpenAI Chat Model CFO (O3) → High-level reasoning engine for strategic leadership. ✅ Beginner view: Think of this as your finance CEO’s desk — requests land here, the CFO figures out what needs to be done, and the right specialists are assigned. 📊 Section 2 – Specialist Finance Agents Each specialist is powered by GPT-4.1-mini (fast + cost-effective). 📈 Financial Planning Analyst → Builds budgets, forecasts, and financial models. 📚 Accounting Specialist → Handles bookkeeping, tax prep, and compliance. 🏦 Treasury & Cash Management Specialist → Manages liquidity, banking, and cash flow. 📊 Financial Analyst → Runs KPI tracking, performance metrics, variance analysis. 💼 Investment & Risk Analyst → Performs investment evaluations, capital allocation, and risk management. 🔍 Internal Audit & Controls Specialist → Checks compliance, internal controls, and audits. ✅ Beginner view: This section is your finance department — every role you’d find in a real company, automated by AI. 📋 Section 3 – Flow of Execution User sends a request (e.g., “Create a financial forecast for Q1 2026”). CFO Agent (O3) interprets it → “We need planning, analysis, and treasury.” Delegates tasks to the relevant specialists. Specialists process in parallel, generating plans, numbers, and insights. CFO Agent compiles and returns a comprehensive financial report. ✅ Beginner view: The CFO is the conductor, and the specialists are the musicians. Together, they produce the financial “symphony.” 📊 Summary Table | Section | Key Roles | Model | Purpose | Beginner Benefit | | ---------------------- | ------------------------------------------------------- | ----------------- | ------------------- | -------------------------------------- | | 🟢 Entry & Leadership | CFO Agent, Think Tool | O3 | Strategic direction | Acts like a real CFO | | 📊 Finance Specialists | FP Analyst, Accounting, Treasury, FA, Investment, Audit | GPT-4.1-mini | Specialized tasks | Each agent = finance department role | | 📋 Execution Flow | All connected | O3 + GPT-4.1-mini | Collaboration | Output = complete financial management | 🌟 Why This Workflow Rocks Full finance department in n8n** Strategic + execution separation** → O3 for CFO, GPT-4.1-mini for team Cost-optimized** → Heavy lifting done by mini models Scalable** → Easily add more finance roles (tax, payroll, compliance, etc.) Practical outputs** → Reports, budgets, risk analyses, audit notes 👉 Example Use Case: “Generate a Q1 financial forecast with cash flow analysis and risk report.” CFO reviews request. Financial Planning Analyst → Budget + Forecast. Treasury Specialist → Cash flow modeling. Investment Analyst → Risk review. Audit Specialist → Compliance check. CFO delivers a packaged financial report back to you.

Automatically Assign Categories and Tags to Blog Posts with AI This workflow streamlines your content organization process by automatically analyzing new blog posts in your GitHub repository and assigning appropriate categories and tags using OpenAI. It compares new posts against existing entries in a Google Sheet, updates the metadata for each new article, and records the suggested tags and categories for review — all in one automated pipeline. Who’s It For Content creators and editors** managing a static website (e.g., Astro or Next.js) who want AI-driven tagging. SEO specialists** seeking consistent metadata and topic organization. Developers or teams** managing a Markdown-based blog stored in GitHub who want to speed up post curation. How It Works Form Trigger – Starts the process manually with a form that initiates article analysis. Get Data from Google Sheets – Retrieves existing post records to prevent duplicate analysis. Compare GitHub and Google Sheets – Lists all .md or .mdx blog posts from the GitHub repository (piotr-sikora.com/src/content/blog/pl/) and identifies new posts not yet analyzed. Check New Repo Files – Uses a code node to filter only unprocessed files for AI tagging. Switch Node – If there are no new posts, the workflow stops and shows a confirmation message. If new posts exist, it continues to the next step. Get Post Content from GitHub – Downloads the content of each new article. AI Agent (LangChain + OpenAI GPT-4.1-mini) – Reads each post’s frontmatter (--- section) and body. Suggests new categories and tags based on the article’s topic. Returns a JSON object with proposed updates (Structured Output Parser) Append to Google Sheets – Logs results, including: File name Existing tags and categories Proposed tags and categories (AI suggestions) Completion Message – Displays a success message confirming the categorization process has finished. Requirements GitHub account** with repository access to your website content. Google Sheets connection** for storing metadata suggestions. OpenAI account** (credential stored in openAiApi). How to Set Up Connect your GitHub, Google Sheets, and OpenAI credentials in n8n. Update the GitHub repository path to match your project (e.g., src/content/blog/en/). In Google Sheets, create columns: FileName, Categories, Proposed Categories, Tags, Proposed Tags. Adjust the AI model or prompt text if you want different tagging behavior. Run the workflow manually using the Form Trigger node. How to Customize Swap OpenAI GPT-4.1-mini for another LLM (e.g., Claude or Gemini) via the LangChain node. Modify the prompt in the AI Agent to adapt categorization style or tone. Add a GitHub commit node if you want AI-updated metadata written back to files automatically. Use the Schedule Trigger node to automate this process daily. Important Notes All API keys and credentials are securely stored — no hardcoded keys. The workflow includes multiple sticky notes explaining: Repository setup File retrieval and AI tagging Google Sheet data structure It uses a LangChain memory buffer to improve contextual consistency during multiple analyses. Summary This workflow automates metadata management for blogs or documentation sites by combining GitHub content, AI categorization, and Google Sheets tracking. With it, you can easily maintain consistent tags and categories across dozens of articles — boosting SEO, readability, and editorial efficiency without manual tagging.