Workflow Templates

AI-Driven Handbook Generator with Multi-Agent Orchestration (Pyragogy AI Village) This n8n workflow is a modular, multi-agent AI orchestration system designed for the collaborative generation of Markdown-based handbooks. Inspired by peer learning and open publishing workflows, it simulates a content pipeline where specialized AI agents act in defined roles, enabling true AI–human co-creation and iterative refinement. This project is a core component of Pyragogy, an open framework dedicated to ethical cognitive co-creation, peer AI–human learning, and human-in-the-loop automation for open knowledge systems. It implements the master orchestration architecture for the Pyragogy AI Village, managing a complex sequence of AI agents to process input, perform review, synthesis, and archiving, with a crucial human oversight step for final approval. How It Works: A Deep Dive into the Workflow's Architecture The workflow orchestrates a sophisticated content generation and review process, ideal for creating AI-driven knowledge bases or handbooks with human oversight. Webhook Trigger & Input:* The process begins when the workflow receives a JSON input via a *Webhook** (specifically at /webhook/pyragogy/process). This input typically includes details like the handbook's title, initial text, and relevant tags. Database Verification:* It first verifies the connection to a *PostgreSQL database** to ensure data persistence. Meta-Orchestrator:* A powerful *Meta-Orchestrator** (powered by gpt-4o from OpenAI) analyzes the initial request. Its role is to dynamically determine and activate the optimal sequence of specialized AI agents required to fulfill the input, ensuring tasks are dynamically routed and assigned based on each agent’s responsibility. Agent Execution & Iteration:** Each activated agent executes its step using OpenAI or custom endpoints. This involves: Content Generation: Agents like the Summarizer and the Synthesizer generate new content or refine existing text. Peer Review Board: A crucial aspect is the Peer Review Board, comprised of AI agents like the Peer Reviewer, the Sensemaking Agent, and the Prompt Engineer. This board evaluates the output for quality, coherence, and accuracy. Reprocessing & Redrafting: If the review agents flag a major_issue, they trigger redrafting loops by generating specific feedback for the Synthesizer. This mechanism ensures iterative refinement until the content meets the required standards. Human-in-the-Loop (HITL) Review:* For final approval, particularly for the Archivist agent's output, a *human review process* is initiated. An email is sent to a human reviewer, prompting them to approve, reject, or comment via a "Wait for Webhook" node. This ensures *human oversight** and quality control. Content Persistence & Versioning:** If the content is approved by the human reviewer: It's saved to a PostgreSQL database (specifically to the handbook_entries and agent_contributions tables). Optionally, the content can be committed to a GitHub repository for version control, provided the necessary environment variables are configured. Notifications:* The final output and the sequence of executed agents can be sent as a notification to *Slack**, if configured. Observe the dynamic loop: orchestrate → assign → generate → review (AI/human) → store Included AI Agents This workflow leverages a suite of specialized AI agents, each with a distinct role in the content pipeline: Meta-Orchestrator:** Determines the optimal sequence of agents to execute based on the input. Summarizer Agent:** Summarizes text into key points (e.g., 3 key points). Synthesizer Agent:** Synthesizes new text and effectively incorporates reprocessing feedback from review agents. Peer Reviewer Agent:** Reviews generated text, highlighting strengths, weaknesses, and suggestions, and indicates major_issue flags. Sensemaking Agent:** Analyzes input within existing context, identifying patterns, gaps, and areas for improvement. Prompt Engineer Agent:** Refines or generates prompts for subsequent agents, optimizing their output. Onboarding/Explainer Agent:** Provides explanations of the process or offers guidance to users. Archivist Agent:** Prepares content for the handbook, manages the human review process, and handles archiving to the database and GitHub. Setup Steps & Prerequisites To get this powerful workflow up and running, follow these steps: Import the Workflow: Import the pyragogy_master_workflow.json (or generate-collaborative-handbooks-with-gpt4o-multi-agent-orchestration-human-review.json) into your n8n instance. Connect Credentials: Postgres: Set up a Postgres Pyragogy DB credential (ID: pyragogy-postgres). OpenAI: Configure an OpenAI Pyragogy credential (ID: pyragogy-openai) for all OpenAI agents. GPT-4o is highly suggested for optimal performance. Email Send: Set up a configured email credential (e.g., for sending human review requests). Define Environment Variables: Define essential environment variables (an .env.template is included in the repository). These include: API base for OpenAI. Database connection details. (Optional) GitHub: For content persistence and versioning, configure GITHUB_ACCESS_TOKEN, GITHUB_REPOSITORY_OWNER, and GITHUB_REPOSITORY_NAME. (Optional) Slack: For notifications, configure SLACK_WEBHOOK_URL. Send a sample payload to your webhook URL (/webhook/pyragogy/process): { "title": "History of Peer Learning", "text": "Peer learning is an educational approach where students learn from and with each other...", "tags": ["education", "pedagogy"], "requireHitl": true } Ideal For This workflow is perfectly suited for: Educators and researchers exploring AI-assisted publishing and co-authoring with AI. Knowledge teams looking to automate content pipelines for internal or external documentation. Anyone building collaborative Markdown-driven tools or AI-powered knowledge bases. Documentation & Contributions: An Open Source and Collaborative Project This workflow is an open-source project and community-driven. Its development is transparent and open to everyone. We warmly invite you to: Review it:** Contribute your analysis, identify potential improvements, or report issues. Remix it:** Adapt it to your specific needs, integrate new features, or modify it for a different use case. Improve it:** Propose and implement changes that enhance its efficiency, robustness, or capabilities. Share it back:** Return your contributions to the community, either through pull requests or by sharing your implementations. Every contribution is welcome and valued! All relevant information for verification, improvement, and collaboration can be found in the official repository: 🔗 GitHub – pyragogy-handbook-n8n-workflow

This workflow allows you to send multi-step email campaigns using n8n, Gmail and Google Sheets. You define a sequence of emails, and a list of email addresses to send them to. The first email is sent to everyone, but the later emails in the sequence are only sent if no-one has replied to the thread yet. This means you only need to worry about replying to people who respond to your email, not chasing people who don’t. Requirements A list of emails in a Google sheet. You can define extra info that will be available to your email templates (e.g. name, company, etc.) A sequence of emails to send, plus how long to wait to send each one, e.g. On day 0:** “Hi, {name} — nice to meet you at the conference. Was wondering whether {company} would be interested in a quick call about X?” On day 3:** “Hi, {name}, just wanted to check in on this. Let me know if there’s any interest!” On day 7:** “{name}, just wanted to give this one last try” A Gmail account (although you could also swap out that part for any other email service) How it works When sending the emails, n8n inserts a hidden attribute in each one that tags it as being part of the email campaign. It then regularly looks through the email threads with that tag and checks whether: No-one has replied yet It’s time to send the next message The workflow doesn’t send emails on weekends. Notes This workflow is not intended for spam! Please use responsibly You can use this workflow for multiple different campaigns by making copies of the workflow and changing the sequence / Google Sheet that it uses

UGC Ads Factory — Automated AI Video Pipeline This n8n workflow turns a script and character/setting description from Google Sheets into a complete stitched UGC-style video ad, fully automated from intake to final delivery. --- Overview The workflow runs a full production pipeline in four stages: Image Generation An AI agent creates a photorealistic selfie prompt from the character/setting description. The image is generated with Kie (Nano Banana), then uploaded to Google Drive and shared. Scene Scripting The generated image is analyzed by Claude-4o-mini for visual consistency. Claude Opus then converts the user script into structured 8-second scenes with consistent visuals and environment-aware motion prompts. Video Clip Generation Each scene is sent to Kie VEO3 for video generation. The workflow polls until each clip is complete, then uploads clips to Google Drive and updates status per scene. Video Stitching After all scene clips are completed, clips are sorted and merged into one final video using fal.ai FFmpeg. The stitched output is uploaded to Drive, and the final links are written back to Sheets. --- Google Sheets Structure This workflow uses two tabs in one spreadsheet: Videos (campaign-level tracking) Main input/output tab with script, character description, aspect ratio, and global run status (Create → Processing → Completed / Failed), plus final video links. Video Data (scene-level tracking) One row per scene with scene script JSON, scene number, image URL, clip links, and per-scene status. This tab enables robust scene retries and progress visibility. --- Triggers Every 30 minutes: processes new rows in Videos where LAUNCH CREATION = Create Every 15 minutes: reprocesses rows in Video Data where LAUNCH = Redo Execute Workflow Trigger: allows orchestration from another workflow --- Error Handling API nodes retry on failure with a 5-second delay Failed image or clip generations are written to Sheets with error details Individual failed scenes can be retried by setting LAUNCH = Redo in Video Data Final stitching runs only after verifying all required scenes are completed --- External Services Kie API — image generation (Nano Banana) and video generation (VEO3) OpenRouter (Claude Opus) — prompt engineering and scene script generation OpenAI (Claude-4o-mini) — image analysis for visual continuity fal.ai — FFmpeg-based clip stitching Google Drive — asset storage and share links Google Sheets — input/output control plane and status tracking --- Usage Add a row in Videos with script, character/setting description, and aspect ratio. Set LAUNCH CREATION to Create. Wait for the scheduled run (or trigger from another workflow). Track scene progress in Video Data. Retrieve final video links in Videos once status is Completed. To retry failed scenes, set scene status to Redo in Video Data.

This n8n template lets you summarize team member activity on Slack for the past week and generates a report. For remote teams, chat is a crucial communication tool to ensure work gets done but with so many conversations happening at once and in multiple threads, ideas, information and decisions usually live in the moment and get lost just as quickly - and all together forgotten by the weekend! Using this template, this doesn't have to be the case. Have AI crawl through last week's activity, summarize all threads and generate a casual and snappy report to bring the team back into focus for the current week. A project manager's dream! How it works A scheduled trigger is set to run every Monday at 6am to gather all team channel messages within the last week. Each message thread are grouped by user and data mined for replies. Combined, an AI analyses the raw messages to pull out interesting observations and highlights. The summarized threads of the user are then combined together and passed to another AI agent to generate a higher level overview of their week. These are referred to as the individual reports. Next, all individual reports are summarized together into a team weekly report. This allows understanding of group and similar activities. Finally, the team weekly report is posted back to the channel. The timing is important as it should be the first message of the week and ready for the team to glance over coffee. How to use Ideally works best per project and where most of the comms happens on a single channel. Avoid combining channels and instead duplicate this workflow for more channels. You may need to filter for specific team members if you want specific team updates. Customise the report to suit your organisation, team or the channel. You may prefer to be more formal if clients or external stakeholders are also present. Requirements Slack for chat platform Gemini for LLM (or switch for other models) Customising this workflow If the slack channel is busy enough already, consider posting the final report to email. Pull in project metrics to include in your report. As extra context, it may be interesting to tie the messages to production performance. Use an AI Agent to query for knowledgebase or tickets relevant to the messages. This may be useful for attaching links or references to add context. Channel not so busy or way too busy for 1 week? Play with the scheduled trigger and set an interval which works for your team.

LinkedIn Profile Tracker Automation Who is this for? This template is ideal for sales teams, recruiters, business development professionals, and relationship managers who need to monitor changes in their network's LinkedIn profiles. Perfect for agencies tracking client personnel changes, HR teams monitoring talent movements, sales professionals staying updated on prospect job changes, and content teams tracking influencer activity. What problem does this workflow solve? Manually checking LinkedIn profiles for updates like job changes, status modifications, profile edits, or latest posts is extremely time-consuming and easy to miss. This automation eliminates the need for constant manual monitoring while ensuring you never miss important changes that could signal new business opportunities, relationship updates, or content engagement opportunities. What this workflow does This workflow automatically monitors a list of LinkedIn profiles on a weekly schedule, detects any changes in: Personal information** (name, headline, summary) Job status** (hiring/open to work flags) Latest work experience** (new positions, company changes) Recent posts** (latest content activity) When changes are detected, it immediately sends Slack notifications with before/after comparisons and updates your tracking database to maintain historical records of all profile evolution. Setup Create a Ghost Genius API account and get your API key for LinkedIn profile scraping Configure HTTP Request nodes with Header Auth credentials using your Ghost Genius API key Set up your Google Sheets database with columns: Firstname, Lastname, LinkedIn URL, ID Tagline, Summary, Latest experience Open to work?, Hiring?, Latest post Configure Slack webhook integration for real-time notifications Set up credentials for Google Sheets and Slack following n8n documentation Add LinkedIn profile URLs to your Google Sheet to start monitoring How to customize this workflow Modify the schedule trigger** to check profiles daily, bi-weekly, or monthly based on your monitoring needs Customize Slack notification messages** to include additional context, mentions, or custom formatting Add email notifications** alongside Slack alerts for critical changes like job transitions Set up filtered notifications** to only alert on specific types of changes (e.g., job changes only, posts from key influencers) Add post content analysis** to detect mentions of your company or competitors Integrate with CRM systems** to automatically update lead records when profile changes occur

📈 How it works This n8n workflow allows you to interact with Binance Spot Trading API directly to: Place Limit Buy and Limit Sell orders Place Market Buy and Market Sell orders Query account info* and *open orders** Cancel all open orders** for a specific symbol All requests are signed using Binance's HMAC SHA256 signature method for secure trading. ⚙️ Setup Steps Create Binance API Credentials in n8n: Go to Credentials > New Choose Binance API Add api_key and api_secret Save as Binance API Import this workflow into your n8n instance. Update default values: In Set Parameter nodes like LimitBuy Parameter, change: symbol (e.g. BTCUSDT) quantity, price as needed Run the workflow manually via the Execute workflow trigger. ✅ Notes Credential node is marked with instructions. HMAC signatures are automatically calculated before making each request. HTTP nodes are preconfigured for Binance API v3. 🔒 No API key or secret is included.

🎥 AI Tour Video Generator with GPT-4o, RunwayML & ElevenLabs for Social Media' This n8n workflow generates 20-second faceless videos for social media by combining AI-generated images, audio, and video clips for a given tour destination. The output is a ready-to-publish video file, which can be pushed to social platforms and logged in a tracking sheet. ⚙️ Workflow Overview This system is divided into 4 main sections: 🧠 Generate Image Prompts 🎨 Generate Media (Images, Videos, Audio) 🛠️ Render & Upload 📈 Future Enhancements 🔌 Integration Setup Table | Integration | Service Used | Setup Instruction | |--------------------|----------------------------|------------------------------------------------------------------------------------| | OpenAI | GPT-4o (Prompt Generation) | Get API Key and configure in n8n | | Google Sheet | Idea I/O tracking | Connect Google account with OAuth/Credentials in n8n | | Piapia API | AI Image Generation | Sign up at piapia.ai and get API key | | Runway API | AI Video Generation | Register at runwayml.com for access | | ElevenLabs | AI Voice Generation | Sign up at elevenlabs.io for API key | | CreateMate API | Render Final Video | Visit createmate.ai to access API | | Google Drive | Upload/Share Final Video | Use n8n Google Drive node to configure credentials | ✅ Required Services & Tools Ensure you have active accounts with the following tools and services: ✅ OpenAI (GPT-4o + Embeddings) ✅ Google Sheets (for destination ideas and tracking) ✅ Piapia API (Image generation) ✅ RunwayML API (Video generation) ✅ ElevenLabs API (Voiceover TTS) ✅ Google Drive (Storage & Sharing) ✅ CreateMate (Video Rendering) ✅ Social Media Scheduler (Optional - Zapier, Buffer, Make.com) 🧠 1. Generate Image Prompts > Purpose: Prepares the content idea and generates visual prompts. | Step | Node Name | Function | |--------------|------------------------|-----------------------------------------------| | 🔁 Trigger | Schedule or Manual | Starts the workflow | | 📥 Grab Idea | Read Sheet | Pulls destination idea from Google Sheet | | ✍️ Set Content | Manual Input | Adds structure/narrative to the idea | | 🔀 Split | Split Out | Breaks input into chunks | | 🤖 GPT Agent | Image Prompt Agent | Uses GPT-4o to generate creative image prompts| | 🧹 Clean | Remove \n | Cleans up formatting | | 📌 Save | Set Prompts | Finalizes prompts for next stage | 🖼️ 2. Generate Media 🎨 Generate Images | Step | Function | |----------------|-----------------------------------------------------------| | Generate Image | Calls Piapia API with AI-generated prompts | | Wait | Adds delay for rendering (90 sec) | | Get Images | Retrieves final images for video | 🎥 Generate Videos | Step | Function | |----------------|-----------------------------------------------------------| | Generate Video | Calls RunwayML to generate video clips from the prompts | | Wait | 2-minute delay to allow video generation | | Get Videos | Fetches completed video clips | 🔊 Generate Audio | Step | Function | |------------------|----------------------------------------------------------| | Update Status | Logs progress in Google Sheet | | Sound Agent | Gemini or GPT generates narration text | | Set Audio | Formats narration for voice synthesis | | Generate Audio | Uses ElevenLabs for realistic voiceover | | Upload to Drive | Saves final audio to Google Drive | | Share File | Creates sharable URL for audio file | 🛠️ 3. Render & Upload > Purpose: Combines all elements (image, video, audio) into a single output and prepares for social media. | Step | Function | |-----------------|----------------------------------------------------------------| | Merge | Combines images, videos, and audio | | Split Out Parts | Breaks content for rendering | | Render Video | Uses CreateMate to render the final 20-second video | | Wait | Short delay to complete rendering | | Download Video | Saves output video locally or on Drive | | Update Sheet | Logs final video URL/status in Google Sheet | | Social Upload | (Coming Soon) Post to Instagram, YouTube Shorts, TikTok, etc. | 🧩 Pre-Conditions Before running the workflow: ✅ Google Sheet should be created with destination ideas ✅ All API keys must be configured in n8n ✅ Google Drive folder must exist for output videos ✅ Sufficient credit/quota must be available on AI platforms ✅ Internet access must be stable for external API calls 🚀 Outcome A polished 20-second travel destination video Combines AI visuals, short clips, and AI narration Ready for instant social media upload Fully automated** from idea to video file 🧠 Tech Stack Summary | Component | Tools Used | |-----------------|-------------------------------| | Language Model | GPT-4o (OpenAI), Gemini (Google) | | Image Generator | Piapia API | | Video Generator | RunwayML | | Audio Generator | ElevenLabs | | Storage | Google Drive | | Video Composer | CreateMate API | | Orchestration | n8n | 📈 Future Enhancements ✅ Smart Enhancements Dynamic hashtags & captions via AI Auto-post to TikTok, Instagram, YouTube via Buffer/Zapier Scene detection + matching B-roll Multilingual narration (e.g., Arabic, French, Malay) A/B testing of video versions to analyze performance 🧪 Testing Add-ons Add preview screen before upload Error tracking & retry flow Manual override before publishing 🧰 Customization Guide | Element | How to Customize | |----------------------|-------------------------------------------------------------------| | ✏️ Prompt Format | Change structure inside Set Content or Prompt Agent | | 🌍 Destination Ideas | Modify Google Sheet for different destinations/categories | | 🎨 Image Style | Customize prompt to Piapia (e.g., “in Pixar style”, “3D render”) | | 🎙️ Voiceover Script | Adjust tone/structure in the Sound Agent | | 📆 Posting Schedule | Use Zapier/Buffer for timed posting | | 🎯 Target Duration | Adjust number of clips or frame duration | 🙌 Community Value This workflow is ideal for: 📸 Travel content creators 🌍 Destination marketers 🏛️ Tourism boards 🧳 Travel SMEs looking for automation Feel free to fork, remix, or request a JSON export in the comments below!

Overview This workflow template automates lead management and customer inquiry processing by integrating ERPNext, AI agents, and email notifications. It streamlines the process of capturing leads, analyzing inquiries, and generating actionable responses. The workflow uses ERPNext to capture inquiries, analyzes them with AI, and notifies the appropriate team or individual, all while maintaining a professional approach. What This Template Does ERPNext Webhook Integration: Captures leads and inquiries through ERPNext webhooks. Triggers the workflow when a new lead is created. AI-Powered Inquiry Analysis: Uses AI to extract key details from lead notes (e.g., customer name, organization, inquiry summary). Classifies inquiries as valid or invalid based on relevance to products, services, or solutions. Contact Assignment: Matches inquiries to the appropriate contact(s) using a Google Sheets database or ERPNext contact information. Handles multiple contacts if required. Email Notifications: Generates professional email notifications for valid inquiries. Sends emails to the appropriate contact(s) with inquiry details and action steps. Invalid Lead Handling: Identifies invalid inquiries (e.g., unrelated to products or services) and flags them for follow-up or dismissal. Custom Email Formatting: Converts plain text into professionally formatted HTML emails. Ensures that communication is clear, concise, and visually appealing. How It Works Step 1: Capture Lead Data Webhook in ERPNext:** Create a webhook in ERPNext for the "Lead" DocType. Set the trigger to on_insert to capture new leads in real-time. Lead Details:** The workflow fetches lead details, including notes, contact information, and the source of the lead. Step 2: Validate and Analyze Inquiry AI Agent for Analysis:** An AI agent analyzes the lead notes to extract key details and classify the inquiry as valid or invalid. The analysis includes checking the relevance of the inquiry to products, services, or solutions offered by the company. Invalid Leads:** If the inquiry is invalid, the workflow flags it and stops further processing. Step 3: Assign Contact(s) Google Sheets Integration:** Uses a Google Sheets database to map products, services, or solutions to responsible contacts. Ensures that inquiries are directed to the right person or team. Multiple Contacts:** Handles cases where multiple contacts are responsible for a particular product or service. Step 4: Generate and Send Email Notifications AI-Generated Emails:** The workflow generates a professional email summarizing the inquiry. Emails include details like customer name, organization, inquiry summary, and action steps. Custom HTML Formatting:** Emails are converted to HTML for a polished and professional appearance. Send Notifications:** Sends email notifications through Microsoft Outlook or another configured email client. Optionally, notifies via WhatsApp or SMS for urgent inquiries. Step 5: Post-Inquiry Actions ERPNext Record Updates:** Updates the lead record in ERPNext with relevant details, including inquiry status and contact information. Setup Instructions Prerequisites ERPNext: A configured ERPNext instance with lead data and a webhook for the "Lead" DocType. Google Sheets: A sheet mapping products, services, or solutions to responsible contacts. AI Integration: Credentials for OpenAI or other supported AI platforms. Email Client: Credentials for Microsoft Outlook or another email client. Step-by-Step Setup ERPNext Configuration: Create a webhook for the "Lead" DocType in ERPNext. Test the webhook with sample data to ensure proper integration. Workflow Import: Import the workflow template into n8n. Configure nodes with your API credentials for ERPNext, Google Sheets, and AI tools. Google Sheets Integration: Prepare a Google Sheet with columns for product, service, or solution and the responsible contact(s). Link the sheet to the workflow. AI Agent Configuration: Customize the AI agent’s prompts to align with your business’s products and services. Adjust criteria for valid and invalid inquiries as needed. Email Setup: Configure the email client node with your email service credentials. Customize the email template for your organization. Testing: Run the workflow with sample leads to validate the entire process. Check email notifications, contact assignments, and record updates in ERPNext. Dos and Don’ts Dos: Test Thoroughly:** Test the workflow with various scenarios before deploying in production. Secure Credentials:** Keep API and email credentials secure to avoid unauthorized access. Customize Prompts:** Tailor AI prompts to match your business needs and language style. Use Professional Email Templates:** Ensure emails are clear and well-formatted. Don’ts: Skip Validation:** Always validate inquiry data to avoid sending irrelevant notifications. Overload the Workflow:** Avoid adding unnecessary nodes that can slow down processing. Ignore Errors:** Monitor logs and address errors promptly for a smooth workflow. Resources GET n8n Now N8N COURSE n8n Book YouTube Tutorial:** Watch the full step-by-step tutorial on setting up this workflow: SyncBricks YouTube Channel Courses and Training:** Learn more about ERPNext and AI automation through my comprehensive courses: SyncBricks LMS Support and Contact:** Email: amjid@amjidali.com Website: SyncBricks LinkedIn: Amjid Ali

This n8n template builds a meeting assistant that compiles timely reminders of upcoming meetings filled with email history and recent LinkedIn activity of other people on the invite. This is then discreetly sent via WhatsApp ensuring the user is always prepared, informed and ready to impress! How it works A scheduled trigger fires hourly to check for upcoming personal meetings. When found, the invite is analysed by an AI agent to pull email and LinkedIn details of the other invitees. 2 subworkflows are then triggered for each invitee to (1) search for last email correspondence with them and (2) scrape their LinkedIn profile + recent activity for social updates. Using both available sources, another AI agent is used to summarise this information and generate a short meeting prep message for the user. The notification is finally sent to the user's WhatsApp, allowing them ample time to review. How to use There are a lot of moving parts in this template so in it's current form, it's best to use this for personal rather than team calendars. The LinkedIn scraping method used in this workflow requires you to paste in your LinkedIn cookies from your browser which essentially let's n8n impersonate you. You can retrieve this from dev console or ask someone technical for help! Note: It may be wise to switch to other LinkedIn scraping approaches which do not impersonate your own account for production. Requirements OpenAI for LLM Gmail for Email Google Calendar for upcoming events WhatsApp Business account for notifications Customising this workflow Try adding information sources which are relevant to you and your invitees. Such as company search, other social media sites etc. Create an on-demand version which doesn't rely on the scheduled trigger. Sometimes you want to know prepare for meetings hours or days in advance where this could help immensely.

Description: The closest definition to this workflow is a cheaper Modular Version of Perplexity online API empowered by LLM models that outperform the Perplexity Lama Model. This flow provides a seamless way to conduct detailed web searches, extract data, and generate insightful reports based on real-time information. It provides a webhook-based flow that gets any search question and reports back the results via a multi-level web search analysis and domain-specific emulation of an agent to deliver an unbiased expert report. This Flow is Ideal for market research, competitive analysis, or any scenario where actionable, structured insights are needed. A more complete, step-by-step guide is provided within the workflow, ensuring you have all the details to set up and customize each component. This tool is designed to function similarly to Perplexity by performing semantic search, reranking, and follow-up queries. However, it offers a unique advantage—complete customization at every stage. Modify any part of the process, from query refinement to data extraction, allowing you to tailor the workflow to your specific needs. Key Features: AI-Powered Query Generation and Expert Emulation**: Uses Google Gemini to transform user queries into expert-level searches, providing accurate and context-aware results. Dual-Stage Semantic Search with Intelligent Reranking**: Performs an initial search, reranks results, and refines the query based on findings to conduct a second, more targeted search. Top-Result Data Extraction**: Extracts content from the top three results of each search, capturing relevant insights from six total sources. Customizable API Options**: Pre-configured with free APIs (Google Gemini, DuckDuckGo, and Article Extraction APIs) but easily adaptable to other APIs if preferred. Automated, Insightful Reporting**: Synthesizes data into a cohesive report, providing expert-level insights tailored to the user’s query. Instructions for API Setup: This workflow is designed to work with free-tier APIs, offering a cost-effective way to retrieve high-quality data. Here’s how to set up each API, with detailed instructions included in the workflow: Google Gemini API (for Query Generation and Analysis): Visit Google AI Studio and log in. Create a free API key under "Get API Key" → "Create API Key in New Project." The free tier includes up to 15 requests per minute, 1 million tokens per minute, and up to 1,500 requests per day. Brave Search API (for Web Search): To attain the free web search API tier from Brave, follow these steps: Visit api.search.brave.com Create an account Subscribe to the free plan (no charge) Navigate to the API Keys section Generate an API key. For the subscription type, choose "Free". Article Extraction API (for Content Extraction): Register on RapidAPI.com and subscribe to the Article Extraction API. The free plan allows up to 300 extractions per month. Enter your API key in each of the 6 extraction nodes for content retrieval. Alternative: In the workflow, we have provided the full instructions on how to replace the current flow with alternative API Keys and provided suggestions such as Scraper Tech API. Additional Tip: To use other APIs, you can generate a cURL request in RapidAPI’s playground, and then paste it into the HTTP Request node in n8n. This approach streamlines integration by automatically filling in headers and request details. Why Choose This Workflow? The Intelligent Online Web Researcher offers an all-in-one solution for complex, customizable online research. Unlike other tools that provide automated semantic search, this workflow is fully modifiable, allowing you to tailor each step, from the initial query and reranking to data extraction and reporting. With built-in instructions and a structure that’s easy to adapt, it’s ideal for commercial applications that require real-time, high-quality insights. Tags: Online Research, Web Search, Market Analysis, Web Search Automation, Data Extraction, Semantic Search, API Integration, Competitive Intelligence, Business Intelligence, Real-Time Reporting, Web Scrape, Data Crawler, Perplexity

This workflow let's a bot in Slack notify a specific channel when a new product in WooCommerce is published and live on the site. Prerequisites WooCommerce account Slack and a Slack bot How it works Listen for WooCommerce product creation If permalink starts with https://[your-url-here].com/product/ Slack bot notifies channel that a new product has been added. Please note, you must update the URL in the IF node to match your url. If your WooCommerce doesn't use the slug /product/, that will need to be updated too.

The provided workflow in n8n is designed to create a Business WhatsApp AI RAG (Retrieval-Augmented Generation) Chatbot. How it works: Webhook Setup: The workflow begins by setting up webhooks for verification and response. The Verify webhook receives GET requests and sends back a verification code, while the Respond webhook handles incoming POST requests from Meta regarding WhatsApp messages. Message Handling: Once a message is received, the workflow checks if the incoming JSON contains a user message. If it does, the message is processed further; otherwise, a generic response is sent. AI Agent Interaction: The user's message is passed to the AI Agent node, which uses a conversational agent with a predefined system message tailored for an electronics store. This ensures that the AI provides accurate and professional responses based on the knowledge base. Knowledge Base Utilization: The AI Agent references a knowledge base stored in Qdrant, a vector database. Documents from Google Drive are downloaded, vectorized using OpenAI embeddings, and stored in Qdrant for retrieval during conversations. Response Generation: The AI Agent generates a response using the OpenAI chat model (gpt-4o-mini) and sends it back to the user via WhatsApp. Set up steps: Create Qdrant Collection: Update the QDRANTURL and COLLECTION variables in the workflow. Use the Create collection HTTP request node to initialize the collection in Qdrant. Vectorize Documents: Configure the Get folder and Download Files nodes to fetch documents from a specified Google Drive folder. Use the Embeddings OpenAI node to generate embeddings for the downloaded files. Store the vectorized documents in Qdrant using the Qdrant Vector Store node. Configure Webhooks: Ensure both Verify and Respond webhooks have the same URL. Set the Verify webhook to use the GET HTTP method and the Respond webhook to use the POST HTTP method. Set Up AI Agent: Define the system prompt for the AI Agent, specifying guidelines for product information, technical support, customer service, and knowledge base usage. Link the AI Agent to the OpenAI chat model and configure any additional tools as needed. Test Workflow: Trigger the workflow manually using the When clicking ‘Test workflow’ node to ensure all components are functioning correctly. Monitor the flow of data through the nodes and verify that responses are being generated and sent accurately. By following these steps, the workflow will be fully operational, enabling a robust AI-powered chatbot capable of handling customer inquiries via WhatsApp. Need help customizing? Contact me for consulting and support or add me on Linkedin.