Workflow Templates

This workflow allows users to convert a 2D image into a 3D model by integrating multiple AI and web services. The process begins with a user uploading or providing an image URL, which is then sent to a generative AI model capable of interpreting the content and generating a 3D representation in .glb format. The model is then stored and a download link is returned to the user. Main Steps Trigger Node: Initiates the workflow either via HTTP request, webhook, or manual execution. Image Upload or Input: The image is acquired via direct upload or URL input. API Integration: The image is sent to a 3D generation API (e.g., a service like Kaedim, Luma Labs, or a custom AI model). Model Generation: The external API processes the image and creates a 3D model. File Storage: The resulting 3D model is stored in cloud storage (e.g., S3, Google Drive, or a local server). Response to User: A download link for the 3D model is returned to the user via the same communication channel (HTTP response, email, or chat). Advantages Automation**: Eliminates the need for manual 3D modeling, saving time for artists, developers, and designers. AI-Powered**: Leverages AI to generate realistic and usable 3D models from simple 2D inputs. Scalability**: Can be triggered automatically and scaled up to handle many requests via n8n's automation. Integration-Friendly**: Easily extendable with other services like Discord, Telegram, or marketplaces for 3D assets. No-Code Configuration**: Built with n8n’s visual interface, making it editable without programming knowledge. How It Works Trigger: The workflow can be started manually ("When clicking ‘Test workflow’") or automatically at scheduled intervals ("Schedule Trigger"). Data Retrieval: The "Get new image" node fetches data from a Google Sheet, including the model image, product image, and product ID. 3D Image Creation: The "Create 3D Image" node sends the image data to the Fal.run API (Trellis) to generate a 3D model. Status Check: The workflow periodically checks the request status ("Get status" and "Wait 60 sec.") until the job is marked as "COMPLETED." Result Processing: Once completed, the 3D model URL is retrieved ("Get Url 3D image"), the file is downloaded ("Get File 3D image"), and uploaded to Google Drive ("Upload 3D Image"). Sheet Update: The final 3D model URL is written back to the Google Sheet ("Update result"). Set Up Steps Prepare Google Sheet: Create a Google Sheet with columns: IMAGE MODEL and 3D RESULT (empty). Example sheet: Google Sheet Template. Obtain Fal.run API Key: Sign up at Fal.ai and get an API key. Configure the Authorization header in the "Create 3D Image" node with Key YOURAPIKEY. Configure Workflow Execution: Run manually via the Test workflow button. For automation, set up the Schedule Trigger node (e.g., every 5 minutes). Verify Credentials: Ensure Google Sheets, Google Drive, and Fal.run API credentials are correctly set in n8n. Once configured, the workflow processes new entries in the Google Sheet, generates 3D models, and updates the results automatically. Need help customizing? Contact me for consulting and support or add me on Linkedin.

🧾 Personal Invoice Processor This N8N workflow automates the extraction and organization of personal invoices in Colombia received via Gmail. It includes the following key steps: 🔁 Flow Summary Email Trigger Polls Gmail every 30 minutes for emails with .zip attachments (assumed to contain invoices). Expects ZIP file following DIAN standards. ZIP File Handling Extracts all files. Filters only PDF and XML files for processing. Data Extraction & Processing Uses LangChain Agent + OpenAI (GPT-4o-mini) to extract: Tipo de documento (Factura / Nota Crédito) Número de factura Fecha de emisión (YYYY-MM-DD) NIT emisor y receptor (sin dígito de verificación) Razón social del emisor Subtotal, IVA, Total CUFE Resumen de compra (max 20 words, formatted sentence) Validation Ensures Total = Subtotal + IVA using a calculator node. Storage Uploads the original PDF to Google Drive. Renames the file to: YYYY-MM-DD-NUMERO_FACTURA.pdf. Inserts or updates invoice details in Google Sheets using a unique Key (NIT_Emisor + Numero_Factura) to prevent duplication. > ⚙️ Designed for personal use with minimal latency tolerance and high automation reliability.

Telegram Rich Output Helper Workflow Who is this for? Builders of Telegram chat‑bots, AI assistants, or notification services who already run n8n and need to convert long, mixed‑media answers from an LLM (or any upstream source) into Telegram‑friendly messages. Prerequisites A Telegram bot created with @BotFather. The bot’s HTTP API token saved as a Telegram API credential in n8n. n8n ≥ 1.0 with the built‑in Telegram node still installed. A parent workflow that calls this one via Execute Workflow and passes: chatId — the destination chat ID (integer). output — a string that can contain plain text and HTTP links to images, audio, or video. What the workflow does Extract Links – A JavaScript Code node scans output, deduplicates URLs, and classifies each by file extension. Link Path If no media links exist, the text path is used. Otherwise, each link is routed through a Switch node that triggers the correct Telegram call (sendPhoto, sendAudio, sendVideo) so users get inline previews or players. Text Path An IF node checks whether the remaining text exceeds Telegram’s 1 000‑character limit. When it does, a Code node slices the text at line boundaries; SplitInBatches then sends the chunks sequentially so nothing is lost. All branches converge, keeping the whole exchange inside one execution. Customisation tips Adjust the character limit** – edit the first expression in “If text too long”. Filter/enrich links** – extend the regex or add MIME checks before dispatch. Captions & keyboards** – populate additionalFields in the three “Send back” nodes. Throughput vs. order* – tweak the batch size in both *SplitInBatches** nodes. With this template in place, your users receive the complete message, playable media, and zero manual formatting – all within Telegram’s API limits.

What it is- I wanted to create a simple, easy-to-use, MCP server for your Discord bot(s). How to set up- Literally all you do is select your bot auth (or crease a new Discord Bot auth if you havn't entered your key in n8n before) and that's IT! How to use it- You can now ask your bot to do things via any MCP client, including from within N8N workflows! Note: If you need an example, you can check out my simple quickstart Discord MCP Server that uses 4o to send messages to channels on your server and users who are members of the server the bot is in. Need help? Want access to more workflows and even live Q&A sessions with a top verified n8n creator.. All 100% free? Join the community

Auto Starter On importing workflows these will not be auto started, even if the old version was running. To fix this we created this workflow that can be run after n8n starts. It fits in our auto deploy pipeline and modified n8n container that will import workflows, start n8n and start the tagged workflows. Start this workflow after n8n starts. It will get all workflows in the running n8n instance. If the files have a tag 'Auto start' the workflow will be started. Check our Export workflows with readable names workflow for autostarting workflows after deployment. Configuration You need a a n8n api key configured.

Overall Description & Potential << What Does This Flow Do? >> Overall, this workflow is an intelligent sales outreach automation engine that transforms raw leads from a form or a list into highly personalized, ready-to-send introductory email drafts. The process is: it starts by fetching data, enriches it with in-depth AI research to uncover "pain points," and then uses those research findings to craft an email that is relevant to the solutions you offer. This system solves a key problem in sales: the lack of time to conduct in-depth research on every single lead. By automating the research and drafting stages, the sales team can focus on higher-value activities, like engaging with "warm" prospects and handling negotiations. Using Google Sheets as the main dashboard allows the team to monitor the entire process—from lead entry, research status, and email drafts, all the way to the send link—all within a single, familiar interface. << Potential Future Enhancements >> This workflow has a very strong foundation and can be further developed into an even more sophisticated system: Full Automation (Zero-Touch): Instead of generating a manual-click link, the output from the AI Agent can be directly piped into a Gmail or Microsoft 365 Email node to send emails automatically. A Wait node could be added to create a delay of a few minutes or hours after the draft is created, preventing instant sending. Automated Follow-up Sequences: The workflow can be extended to manage follow-up emails. By using a webhook to track email opens or replies, you could build logic like: "If the intro email is not replied to within 3 days, trigger the AI Agent again to generate follow-up email #1 based on a different template, and then send it." AI-Powered Lead Scoring: After the research stage, the AI could be given the additional task of scoring leads (e.g., 1-10 or High/Medium/Low Priority) based on how well the target company's profile matches your ideal customer profile (ICP). This helps the sales team prioritize the most promising leads. Full CRM Integration: Instead of Google Sheets, the workflow could connect directly to HubSpot, Salesforce, or Pipedrive. It would pull new leads from the CRM, perform the research, draft the email, and log all activities (research results, sent emails) back to the contact's timeline in the CRM automatically. Multi-Channel Outreach: Beyond email, the AI could be instructed to draft personalized LinkedIn Connection Request messages or WhatsApp messages. The workflow could then use the appropriate APIs to send these messages, expanding your outreach beyond just email.

Who is this for? For developers and organizations that need to convert web page to PDF. What problem is this workflow solving? The web page conversion to PDF problem. What this workflow does Converts web page to PDF. Stores the PDF file in the local file system. How to customize this workflow to your needs Open the HTTP Request node. Adjust the URL parameter (all endpoints can be found here). Add your secret to the Query Auth account parameter. Please create a ConvertAPI account to get an authentication secret. Change the parameter url to the webpage you want to convert to pdf Optionally, additional Body Parameters can be added for the converter.

Do you want to avoid communication problems when launching phone calls? This workflow verifies landline and mobile phone numbers using the uProc Get Parsed and validated phone tool with worldwide coverage. You need to add your credentials (Email and API Key - real -) located at Integration section to n8n. Node "Create Phone Item" can be replaced by any other supported service with phone values, like databases (MySQL, Postgres), or Typeform. The "uProc" node returns the next fields per every parsed and validated phone number: country_prefix: contains the international country phone prefix number. country_code: contains the 2-digit ISO country code of the phone number. local_number: contains the phone number without international prefix. formatted: contains a formatted version of the phone number, according to country detected. valid: detects if the phone number has a valid format and prefix. type: the phone number type (mobile, landline, or something else). "If" node checks if the phone number is valid. You can use the result to mark invalid phone numbers in your database or discard them from future telemarketing campaigns.

Intelligently Segment PDFs by Table of Contents This workflow empowers you to automatically process PDF documents, intelligently identify or generate a hierarchical Table of Contents (ToC), and then segment the entire document's content based on these ToC headings. It effectively breaks down a large PDF into its constituent sections, each paired with its corresponding heading and hierarchical level. Why It's Useful Unlock the true structure of your PDFs for granular access and advanced processing: AI Agent Tool:** A key use case is to provide this workflow as a tool to an AI agent. The agent can then use the segmented output to "read" and navigate to specific sections of a document to answer questions, extract information, or perform tasks with much greater accuracy and efficiency. Targeted Content Extraction:** Programmatically pull out specific chapters or subsections for focused analysis, summarization, reporting, or repurposing content. Enhanced RAG Systems:** Improve your Retrieval Augmented Generation (RAG) pipelines by feeding them well-defined, contextually relevant document sections instead of entire, monolithic PDFs. This leads to more precise AI-generated responses. Modular Document Processing:** Process different parts of a document using distinct logic in subsequent n8n workflows by acting on individual sections. Data Preparation:** Seamlessly convert lengthy PDFs into a structured format where each section (including its heading, level, and content in multiple formats) becomes a distinct, manageable item. How It Works Ingestion & Advanced Parsing: The workflow ingests a PDF (via a provided URL or a pre-set one for manual runs). It then utilizes Chunkr.ai to perform Optical Character Recognition (OCR) and parse the document into detailed structural elements, extracting text, HTML, and Markdown for each segment. AI-Powered Table of Contents Generation: A Google Gemini AI model analyzes the initial pages of the document (where a ToC often resides) along with section headers extracted by Chunkr as a fallback. This allows it to construct an accurate, hierarchical Table of Contents in a structured JSON format, even if the PDF lacks an explicit ToC or if it's poorly formatted. Precise Content Segmentation: Sophisticated custom code then meticulously maps the AI-generated ToC headings to their corresponding content within the parsed document from Chunkr. It intelligently determines the precise start and end of each section. Structured & Flexible Output: The primary output provides each identified section as an individual n8n item. Each item includes the heading text, its hierarchical level (e.g., 1, 1.1, 2), and the full content of that section in Text, HTML, and Markdown formats. Optionally, the workflow can also reconstruct the entire document into a single, navigable HTML file or a clean Markdown file. What You Need To run this workflow, you'll need: Input PDF:** When triggered by another workflow: A URL pointing to the PDF document. When triggered manually: The workflow uses a pre-configured sample PDF from Google Drive for demonstration (this can be customized). Chunkr.ai API Key:** Required for the initial parsing and OCR of the PDF document. You'll need to insert this into the relevant HTTP Request nodes. Google Gemini API Credentials:** Necessary for the AI model to intelligently generate the Table of Contents. This should be configured in the Google Gemini Chat Model nodes. Outputs The workflow primarily generates: Individual Document Sections:** A series of n8n items. Each item represents a distinct section of the PDF and contains: heading: The text of the section heading. headingLevel: The hierarchical level of the heading (e.g., 1 for H1, 2 for H2). sectionText: The plain text content of the section. sectionHTML: The HTML content of the section. sectionMarkdown: The Markdown content of the section. Alternatively, you can configure the workflow to output: Full Reconstructed Document:** A single HTML file representing the entire processed document. A single Markdown file representing the entire processed document. This workflow is ideal for anyone looking to deconstruct PDFs into meaningful, manageable parts for advanced automation, AI integration, or detailed content analysis.

A powerful sub-agent that collects real-time market structure data from Binance for any trading pair — including price, volume, order book depth, and candlestick snapshots across multiple timeframes (15m, 1h, 4h, 1d). 🎥 Watch Tutorial: 🎯 Purpose This workflow powers the Quant AI system with: ✅ Real-time price feed (/ticker/price) ✅ 24-hour stats (OHLC, % change, volume via /ticker/24hr) ✅ Live order book depth (/depth) ✅ Latest candlestick data (/klines) for all major intervals All outputs are parsed and formatted using GPT and returned to the parent agent (e.g., Financial Analyst Tool) as a Telegram-optimized summary. ⚙️ Workflow Architecture | Node | Role | | ------------------------------------ | ------------------------------------------------------------ | | 🔗 Execute Workflow Trigger | Accepts input from parent workflow | | 🧠 Simple Memory | Stores session + symbol info | | 🤖 Binance SM Market Agent | Parses prompt, routes tool calls | | 💡 OpenAI Chat Model (gpt-4o-mini) | Converts raw data into a clean, readable format for Telegram | | 🌐 getCurrentPrice | Gets latest price | | 🌐 get24hrStats | Gets OHLC/volume over past 24 hours | | 🌐 getOrderBook | Gets top 100 bids and asks | | 🌐 getKlines | Gets latest 15m, 1h, 4h, and 1d candles | 📥 Input Requirements This workflow is not called directly by the user. Instead, it is triggered by another workflow, such as: { "message": "BTCUSDT", "sessionId": "539847013" } 📤 Telegram Output Example 📊 BTCUSDT Market Overview 💰 Price: $63,220 📈 24h Change: +2.3% | Volume: 45,210 BTC 📉 Order Book • Top Bid: $63,190 • Top Ask: $63,230 🕰️ Latest Candles • 15m: O: $63,000 | C: $63,220 | Vol: 320 BTC • 1h : O: $62,700 | C: $63,300 | Vol: 980 BTC • 4h : O: $61,800 | C: $63,500 | Vol: 2,410 BTC • 1d : O: $59,200 | C: $63,220 | Vol: 7,850 BTC ✅ Use Cases | Scenario | Output Provided | | ---------------------------------- | ------------------------------------------------------------ | | “Show current BTC price and trend” | Price, 24h stats, candles, and order book in one message | | “Candles for SOL” | 15m, 1h, 4h, 1d candlesticks for SOLUSDT | | Triggered by Quant AI system | Clean Telegram-ready summary with all structure tools merged | 🧩 Toolchain Breakdown | Tool Name | Endpoint | Purpose | | ----------------- | ---------------------- | ------------------------------ | | getCurrentPrice | /api/v3/ticker/price | Latest trade price | | get24hrStats | /api/v3/ticker/24hr | 24h OHLC, % change, volume | | getOrderBook | /api/v3/depth | Top 100 bids and asks | | getKlines | /api/v3/klines | 1-candle snapshot across 4 TFs | 🚀 Installation Steps Import the JSON into your n8n instance Connect your OpenAI credentials for the Chat Model node No Binance API key needed — public endpoints Trigger this tool only via: Binance SM Financial Analyst Tool Binance Spot Market Quant AI Agent 🔐 Licensing & Attribution © 2025 Treasurium Capital Limited Company Architecture, prompts, and trade structure are IP-protected. No unauthorized rebranding permitted. 🔗 For support: Don Jayamaha – LinkedIn

This is an example that gets the logo, icon, and information of a company and stores it in Airtbale. You can set the values that you want to store in the Set node. If you want to store the data in a different database (Google Sheet, Postgres, MongoDB, etc.) replace the Airtable node with that node. You can refer to the documentation to learn how to build this workflow from scratch.

Create, iterate, and share! Transform a single image through multiple scenes while maintaining consistency. ✨ What this workflow does This template showcases FLUX.1 Kontext - Black Forest Labs' in-context image generation model that excels at maintaining character features across multiple transformations. Combined with the Upload Post community node for effortless multi-platform social media posting, you can create and share compelling visual stories instantly. The workflow demonstrates FLUX Kontext's core strength: character consistency across multiple image generations. Starting with a single input image, it: 🖼️ Loads an initial character image (example: a cute animal mascot) 📝 Defines multiple scene transformation prompts 🔄 Iteratively generates new scenes while preserving exact character features 🎯 Maintains visual consistency by reusing binary data from previous generations 📱 Auto-posts the complete transformation series to multiple social platforms simultaneously 🚀 Key Features: The Consistency Advantage Character Preservation**: FLUX Kontext's signature feature - maintains character features and style across transformations (requires specific prompting techniques) Iterative Context Building**: Each generation uses the previous image as context, creating visual continuity Binary Data Reuse**: Smart workflow design that feeds output from one generation as input to the next Multi-Scene Storytelling**: Transform your character across different environments while keeping them recognizable One-Click Multi-Platform Posting*: Upload Post eliminates the tedious process of posting to each platform individually 📱 Why use Upload Post? Posting the same content to TikTok, Instagram, LinkedIn, YouTube, Facebook, X (Twitter), and Threads individually is time-consuming and error-prone. The Upload Post service* simplifies this process: ✅ Connect once, post everywhere: Link all your social media accounts to Upload Post ✅ Single API call: Post to multiple platforms with one simple node ✅ No more platform juggling: Skip the endless switching between apps and dashboards ✅ Consistent timing: All platforms get your content simultaneously ✅ Trusted by 3,751+ users: Proven solution for content creators and marketers Instead of spending 30+ minutes manually posting to each platform, Upload Post does it all in seconds with a single n8n node! 🛠️ Prerequisites Required Accounts: Black Forest Labs API: Create account at dashboard.bfl.ai Get your API key for FLUX Kontext Pro access Upload Post Account: Sign up at upload-post.com* Connect your social media profiles (TikTok, Instagram, LinkedIn, YouTube, Facebook, X/Twitter, Threads) Get API credentials for automated posting Free tier available: 10 uploads/month 💡 Perfect For: Character Designers** maintaining brand character integrity across scenes Social Media Managers** creating engaging visual story series without manual posting Brand Marketers** ensuring character consistency across campaigns Storytellers** building visual narratives with consistent protagonists Agencies** managing multiple client accounts efficiently 🔧 Customization Options: Modify transformation prompts** to create your own character journey Adjust iteration steps** Change initial character image** Configure social platform targeting** (choose which platforms to post to) Customize post content** and formatting Experiment with different consistency scenarios** \ Affiliate link*