by ARRE
Good to know: This workflow automatically processes product images from Google Drive, generates AI-powered background prompts using multiple AI models (ChatGPT, Claude, or Groq), creates professional background scenes using Pixelcut.ai, and saves enhanced images back to your Google Drive. Perfect for e-commerce businesses and product photography workflows. Who is this for? ➖E-commerce store owners who need professional product backgrounds ➖Product photographers looking to automate background generation ➖Marketing teams creating consistent product imagery ➖Small businesses wanting to enhance their product photos without expensive studio setups ➖Anyone who needs to quickly transform transparent product images into commercial-ready photos What problem is this workflow solving? This workflow solves the challenge of creating professional product photography backgrounds at scale. Instead of manually editing each product image or setting up expensive photo shoots, it automatically generates contextually appropriate backgrounds for your products using AI technology. It eliminates the time-consuming process of background creation while maintaining professional quality and consistency across your product catalog. What this workflow does: ✅Automatically fetches product images from your Google Drive folder ✅Downloads transparent/background-free product images ✅Uses advanced AI models (ChatGPT, Claude, or Groq) to generate intelligent background prompts based on product analysis ✅Creates professional backgrounds using Pixelcut.ai API with AI-generated or custom prompts ✅Saves enhanced product images back to Google Drive with organized naming ✅Processes multiple images in batch automatically How it works: 1️⃣Google Drive node searches for PNG product images in your specified folder 2️⃣Binary download node retrieves the actual image files for processing 3️⃣Optional AI agent analyzes products using your chosen AI model (OpenAI GPT-4, Claude, or Groq) and generates appropriate background prompts 4️⃣Pixelcut.ai API processes images and adds professional backgrounds using AI-generated or manual prompts 5️⃣Enhanced images are automatically saved back to Google Drive with "enhanced-" prefix How to use: Set up Google Drive OAuth2 credentials in n8n Create a Pixelcut.ai account and get your API key Configure your source folder ID in the Google Drive nodes Set up your output folder ID for enhanced images Choose and configure your preferred AI model credentials (OpenAI for ChatGPT, Anthropic for Claude, or Groq) Replace placeholder API keys with your actual credentials Execute the workflow to process your product images Requirements: ✅n8n instance (cloud or self-hosted) ✅Google Drive account with OAuth2 access ✅Pixelcut.ai API account and key ✅Product images in PNG format (transparent backgrounds recommended) ✅AI API credentials for automatic prompt generation (choose from): OpenAI API (for ChatGPT/GPT-4) Anthropic API (for Claude) Groq API (for fast inference) ✅Basic understanding of n8n workflows Customizing this workflow: 🟢Modify the image format filter to support JPG, WEBP, or other formats 🟢Switch between different AI models (ChatGPT, Claude, Groq) for prompt generation 🟢Customize background prompts for different product categories 🟢Add background removal step for products with existing backgrounds 🟢Switch to different AI background services (Deep-Image.ai, Remove.bg, etc.) 🟢Configure different AI model parameters for varied prompt creativity 🟢Add image resizing or quality optimization steps 🟢Create multiple output folders for different product categories 🟢Add error handling and retry mechanisms for failed processes 🟢Implement A/B testing with different AI models for prompt quality comparison
by Zakaria Ben
This workflow template is designed for dental assistants and anyone looking to automate appointment scheduling. It integrates Google Calendar for booking appointments and Google Sheets as a database to store patient information. How It Works The user interacts with the chatbot to schedule an appointment. The chatbot collects necessary details and checks availability via Google Calendar. If the requested time is available, the AI books the appointment. If unavailable, the AI suggests alternative time slots. Once booked, the AI logs the appointment details into Google Sheets for record-keeping. Setup Instructions 📌 Watch this 🎥 Setup Video for detailed instructions on running and customizing this workflow. Step 1: Set Up Credentials OpenAI API Key (for chatbot functionality). Google Account (for Google Sheets & Google Calendar integration). Step 2: Choose the Right Tools Select the correct Google Calendar in the Google Calendar tool. Choose the appropriate Google Sheets file in the Google Sheets tool. Step 3: Test Run a test to ensure everything works correctly. Once tested. Example Templates Below are sample Google Sheets template to help you get started.
by Yang
🧾 What this workflow does This workflow automatically generates avatar-style videos from the latest AI-related news using Dumpling AI and HeyGen. It runs every hour, scrapes trending articles, turns them into 30–60 second spoken scripts with GPT-4o, and produces short avatar videos with HeyGen. Finally, it logs the final video URL in a Google Sheet. 👤 Who is this for Newsletters and creators who want to automate AI trend updates Content marketers generating short-form video content Product teams experimenting with AI-generated summaries Automation enthusiasts combining LLMs + video + trending data ⚙️ How to set up 🔐 Requirements Dumpling AI API Key** stored securely as HTTP Header credential HeyGen API Key** added as an HTTP Header credential OpenAI API Key** for GPT-4o (can use GPT-4o-mini if preferred) Google Sheets account** with one column: Video link 🛠 Step-by-step setup Google Sheet Setup Create a Google Sheet with a single column named: Video link Update Credentials Use n8n’s credential manager to add tokens for: Dumpling AI HeyGen OpenAI Google Sheets Optional Customizations In the "Dumpling AI: Search AI News" node, you can change "query": "AI Agent" to other trending keywords (e.g., "Generative AI", "Autonomous Agents", etc.) Update the avatar_id and voice_id in the HeyGen request to match your preferred look/sound 🧠 How it works The Schedule Trigger runs hourly. Dumpling AI searches for fresh news related to "AI Agent." The top 4 news links are scraped for full content. Articles are merged and fed into GPT-4o via a LangChain Agent to produce a casual, conversational video script. HeyGen creates a video using the script, avatar, and voice. The workflow waits until the video rendering is complete. Once done, the final video link is logged into Google Sheets. 🧪 Customization Ideas Change the interval (e.g., every 6 hours, daily) Swap avatar/voice in HeyGen to fit your brand Expand to post the video directly to social media Add image background or B-roll overlays using Creatomate This is a fast, automated pipeline to create explainer-style AI news updates using real-time data and generative video tools.
by Tarek Mustafa
Who is this for? Jira users who want to automate the generation of a Lessons Learned or Retrospective report after an Epic is Done. What problem is this workflow solving? / use case Lessons Learned / Retrospective reports are often omitted in Agile teams because they take time to write. With the use of n8n and AI this process can be automated. What is this workflow doing Triggers automatically upon an Epic reaching the "Done" status in Jira. Collects all related tasks and comments associated with the completed Epic. Intelligently filters the gathered data to provide the LLM with the most relevant information. Utilizes an LLM with a structured System Message to generate insightful reports. Delivers the finalized report directly to your specified Google Docs document. Setup Create a Jira API key and follow the Credentials Setup in the Jira trigger node. Create credentials for Google Docs and paste your document ID into the Node. How to customize this workflow to your needs Change the System Message in the AI Agent to fit your needs.
by David Roberts
AI evaluation in n8n This is a template for n8n's evaluation feature. Evaluation is a technique for getting confidence that your AI workflow performs reliably, by running a test dataset containing different inputs through the workflow. By calculating a metric (score) for each input, you can see where the workflow is performing well and where it isn't. How it works This template shows how to calculate a workflow evaluation metric: whether an output matches an expected output (i.e. has the same meaning). The workflow takes questions about the causes of historical events and compares them with the reference answers in the dataset. We use an evaluation trigger to read in our dataset It is wired up in parallel with the regular chat trigger so that the workflow can be started from either one. More info If we're evaluating (i.e. the execution started from the evaluation trigger), we calculate the correctness metric using AI We pass this information back to n8n as a metric If we're not evaluating we avoid calculating the metric, to reduce cost
by Alex
This workflow contains community nodes that are only compatible with the self-hosted version of n8n. How It Works This template orchestrates a multi-step workflow that constructs a comprehensive four-zone automation matrix—Green, Yellow, Red, and White—grounded in the Human Agency Scale (HAS). When a user sends a job title via Telegram, the workflow routes both text and voice messages appropriately. Voice messages are transcribed via OpenAI's Whisper, while text inputs bypass transcription. Both streams merge into a single data flow. The AI Agent node, powered by GPT-4, analyzes the user's profession and core tasks. It also leverages live context by calling the Tavily search tool, ensuring the analysis incorporates up-to-date information. After the evaluation, the workflow formats and returns the completed matrix, with detailed task examples and rationales for each zone, back to the user via Telegram. Setup Instructions Create an OpenAI credential in n8n (model: GPT-4.1 mini). Add a Tavily credential with your API key (FREE plan available). Configure a Telegram Bot credential: API bot token. Import this JSON as a new workflow in n8n and map credentials in each node. Activate the workflow; test by sending sample job titles; adjust node timeouts and webhook settings as needed. Requirements n8n v1.0.0 or higher Active OpenAI API key (GPT-4.1 mini access) Tavily API key for web context search Telegram Bot token with correctly configured webhook Stable internet connectivity Audience & Problem This template is designed for consultants, HR professionals, and analysts who need a scalable, standardized approach to evaluate which routine tasks in a given profession can be automated, which require human oversight, and which should remain manual to preserve strategic judgment, creativity, and expertise.
by Stefan
Automate LinkedIn engagement without sounding like a bot. This workflow: 🌍 Detects language & tone (German / English) 👍 Chooses the right reaction (like / celebrate / support …) 🗣 Generates a personalised comment in your voice and mentions the author 📲 Optional Telegram review – approve ✅ or regenerate ❌ before posting 💸 Runs on cost-efficient GPT-4o mini or Claude 3.5 Haiku ☁️ Publishes comment + reaction via the Unipile API Setup (≈ 15-30 min) Unipile – connect LinkedIn → copy account_id, dsn, then create an Access-Token (X-API-KEY). Telegram (optional) – create a bot, add a credential named YOUR TELEGRAM ACCOUNT. OpenAI / Anthropic – add your API key and keep one LLM node (delete the other). Open the “Defining guardrails” node and replace the credential placeholders. (Optional) Tweak role, comment_length and openers_example_1-3 for your brand voice. Security: no live keys included – all secrets are placeholders. Best for: solopreneurs, marketing teams, personal-branding consultants.
by Xiaoyuan Zhang
Description This workflow creates a sophisticated bilingual dictionary that provides literary-style definitions and examples for English and German words. The system automatically detects the input language, generates comprehensive definitions in Chinese, creates three literary-style example sentences with translations, and stores everything in a Supabase database for future reference. Who Is This For? Language Learners & Students: Perfect for those studying English or German who want to understand words in literary contexts with Chinese translations. Writers & Content Creators: Ideal for bilingual writers working with English, German, and Chinese who need rich, literary examples for their work. Educators & Translators: Excellent tool for language teachers and professional translators who need comprehensive word definitions with contextual examples. Literary Enthusiasts: Great for readers of literature who encounter unfamiliar words and want to understand their poetic or literary usage. What Problem Does This Workflow Solve? Traditional dictionaries often provide basic definitions without literary context or cross-language examples. This workflow addresses several key challenges: Limited Literary Context: Most dictionaries lack poetic, expressive, or literary-style examples that help understand how words are used in sophisticated writing. Cross-Language Learning: Provides seamless translation between English/German and Chinese with culturally appropriate examples. Data Persistence: Automatically saves all lookups to a database, creating a personalized vocabulary collection over time. API Accessibility: Provides a clean webhook interface that can be integrated into apps, websites, or other tools. How It Works Main Dictionary Lookup Flow Input Processing: Receives a word via webhook POST request and automatically detects if it's English or German AI Analysis: Uses OpenAI GPT-4o-mini to generate comprehensive definitions with literary context Response Formatting: Processes the AI response to extract structured data (word, meaning, examples) Quality Control: Validates the response and handles unclear or invalid inputs gracefully Database Storage: Saves the word, Chinese meaning, and examples to Supabase for future reference API Response: Returns formatted JSON with the complete dictionary entry Data Storage Flow Parallel Processing: Simultaneously returns the dictionary data to the user and saves it to the database Structured Storage: Organizes data in Supabase with fields for words, Chinese meanings, and example arrays Success Confirmation: Provides confirmation when data is successfully stored Setup Instructions Prerequisites & Accounts You'll need accounts and API access for: n8n (Cloud or self-hosted) OpenAI (API key required) Supabase (Database and API credentials) Webhook Configuration The workflow uses two webhook endpoints with the same path for different operations Note the webhook URL provided by n8n for API integration Test the webhook endpoints to ensure they're accessible approach Customization Options Extend to support additional input languages by modifying the AI prompt Add support for other target languages beyond Chinese Customize the literary style for different cultural contexts This workflow transforms simple word lookups into rich, contextual learning experiences while building a personalized vocabulary database over time.
by Yang
🧾 What this workflow does This workflow takes a reference ad image and brand website, then uses GPT-4, LangChain, and Dumpling AI to generate 10 high-quality image variations for ad testing. These image variations are visually consistent but subtly different in background, mood, lighting, and tone — perfect for performance testing on platforms like Meta Ads or TikTok. 👤 Who is this for DTC marketers and brand designers testing ad creatives Creative teams automating visual experimentation Content agencies using AI for fast ad mockups Performance marketers running multivariate testing ⚙️ How to set up ✅ Requirements You’ll need the following tools set up in n8n: Google Drive (OAuth2 credential) Google Sheets (OAuth2 credential) OpenAI API (for GPT-4 or GPT-4o) Dumpling AI API (via HTTP header authentication) 🛠️ Steps to configure Google Sheet Setup Create a sheet with one column: Image URL Update the Sheet ID and tab name in the final Google Sheets node. Drive Setup Create a folder in Google Drive for storing the reference image. Replace the folderId in the “Upload Ad Image to Google Drive” node. Dumpling AI API Key Use n8n’s credential manager (HTTP Header Auth) — do not hardcode the key. OpenAI API Key Required for both image description and LangChain agent prompt generation. Form Inputs Required Brand Name Brand Website Ad Image (upload field) 🧠 How it works A user submits the brand name, website, and a reference ad image through a form. The image is uploaded to Google Drive. GPT-4o describes the image’s visual style (e.g., mood, lighting, composition). GPT-4 analyzes the brand’s website to define its visual aesthetic. A LangChain agent uses both analyses to create 10 tightly scoped variation prompts. Dumpling AI generates a new image for each prompt using its “FLUX.1-pro” model. Each new image’s link is logged into Google Sheets. 🛠️ How to customize 🧪 Change prompt logic to experiment with different variations (e.g., theme, season). 🎨 Switch image model in Dumpling AI to one that supports your desired style. 🔗 Log additional metadata (prompt, timestamp) to Google Sheets. 📤 Connect output images to Airtable, Notion, or a review tool like Figma. 🎯 Modify GPT system message to reflect a different tone or brand strategy. This workflow gives creative teams and marketers an instant, AI-powered ad image testing system — built on real brand visuals, not generic stock content.
by SamirLiu
📝 What this workflow does Every morning at 8 a.m., this workflow fetches the latest AI-related articles from both GNews and NewsAPI. It merges up to 40 new articles daily, selects the 15 most relevant ones on AI technology and applications, and uses GPT-4.1 to generate concise summaries in accurate Traditional Chinese (while preserving essential English technical terms). Each summary also includes the article link for easy referral. The compiled digest is then posted to your designated Telegram account or group. 👥 Who is this for? AI enthusiasts, professionals, and anyone interested in artificial intelligence news Individuals and teams wanting a concise daily digest of AI developments in Traditional Chinese Telegram users who prefer automated information delivery 🎯 What problem does this workflow solve? With the rapid evolution of AI technology, it can be overwhelming to keep up with new developments. This workflow addresses information overload by automatically collecting, summarizing, and translating the most important AI news each morning — all delivered conveniently to your chosen Telegram channel or group. ⚙️ Setup 🔑 Add NewsAPI and GNews API Keys Register for accounts on NewsAPI.org and GNews to obtain your API keys. Input your NewsAPI key directly into the Fetch NewsAPI articles node. Input your GNews API key into the Fetch GNews articles node. 🤖 Set up your Telegram Bot Create a Telegram Bot via BotFather and copy the generated Bot Token. In n8n, create Telegram Bot credentials using this token. In the Send summary to Telegram node, enter the chat ID of your target user, group, or channel to receive the messages. 🧠 Configure OpenAI Credentials In n8n, create a new credential using your OpenAI API key. Assign this credential to the GPT-4.1 Model node (or equivalent OpenAI/AI nodes). After completing these steps, your workflow is fully configured to fetch, summarize, and deliver daily AI news to your selected Telegram chat automatically. 🛠️ How to customize this workflow 🔍 Change the topic:** Update the keywords in the NewsAPI and GNews nodes for other subjects (e.g., "blockchain", "quantum computing"). ⏰ Adjust delivery time:** Modify the scheduled trigger to your preferred hour. ✍️ Tweak summary style or language:** Refine the prompt in the AI summarizer node for different tones or translate into other languages as needed. 📦 Dependencies NewsAPI account GNews account Telegram Bot OpenAI API access (for GPT-4.1) or compatible AI model for Langchain agent
by Leonard
Unlock AI-Driven Research with Jina AI (No API Key Needed!) Following the success of Open Deep Research 1.0, we are excited to introduce an improved and fully free version: AI-Powered Research with Jina AI Deep Search. This workflow leverages Jina AI’s Deep Search API, a free and powerful AI research tool that requires no API key. It automates querying, analyzing, and formatting research reports, making AI-driven research accessible to everyone. Key Features No API Keys Required** - Start researching instantly without setup hassle. Automated Deep Search* - Uses Jina AI to fetch *relevant and high-quality information**. Structured AI Reports** - Generates clear, well-formatted research documents in markdown. Flexible and Customizable* - Modify the workflow to fit *your specific research needs**. Ideal for Researchers, Writers & Students** - Speed up your research workflow. Use Cases This workflow is particularly useful for: Researchers** - Quickly gather and summarize academic papers, online sources, and deep web content. Writers & Journalists** - Automate background research for articles, essays, and investigative reports. Students & Educators** - Generate structured reports for assignments, literature reviews, or presentations. Content Creators** - Find reliable sources for blog posts, videos, or social media content. Data Analysts** - Retrieve contextual insights from various online sources for reports and analysis. How It Works The user submits a research query via chat. The workflow sends the query to Jina AI’s Deep Search API. The AI processes and generates a well-structured research report. A code node formats the response into clean markdown. The final output is a structured, easy-to-read AI-generated report. Pre-Conditions & Requirements An n8n instance (self-hosted or cloud). No API keys needed** – Jina AI Deep Search is completely free. Basic knowledge of n8n workflow automation is recommended for customization. Customization Options This workflow is fully modular, allowing users to: Modify the query prompt to refine the research focus. Adjust the report formatting to match personal or professional needs. Expand the workflow by adding additional AI tools or data sources. Integrate it with other workflows in n8n to enhance automation. Users are free to connect it with other workflows, add custom nodes, or tweak existing configurations. Getting Started Setup Time: Less than 5 minutes Import the workflow into n8n. Run the workflow and input a research topic. Receive a fully formatted AI-generated research report. Try It Now! Start your AI-powered research with Jina AI Deep Search today! Get the workflow on n8n.io
by Angel Menendez
Who is this for? This workflow is for professionals and teams who want to automate LinkedIn message replies with intelligent, human-like responses — without losing control over tone or accuracy. Ideal for founders, sales teams, DevRel, or community managers handling high-volume inbound messages. What problem is this workflow solving? Responding to every LinkedIn message manually is slow and inconsistent. Basic AI bots generate replies without context or nuance. This subworkflow solves both problems by using structured message routing from Notion and profile insights from UniPile to craft smart, context-aware responses. What this workflow does This workflow takes the sender’s message and profile (from LinkedIn Auto Message Router with Request Detection) and references your centralized Notion database of message types. It uses that to either match the message to a known response or generate a new one using OpenAI's GPT model — all while following professional tone guidelines. This is the third workflow in a 3-part automation system: Receives data from LinkedIn Auto Message Router with Request Detection Uses UniPile LinkedIn Profile Lookup Subworkflow to enrich responses based on follower count or org data Example Use Case If a message comes from someone with low reach (e.g., under 1,000 followers), the AI politely deflects a meeting request. If an influencer reaches out, the AI immediately offers a booking link. Your team controls this logic by updating the Notion database — no edits to the workflow required. Setup Connect this workflow as a subworkflow in your router or Slack approval flow Store your Notion API key and database ID in n8n Provide the following parent inputs: message – The LinkedIn message text sender – Name of the sender chatid – Session ID (optional for memory) linkedinprofile – Enriched array with LinkedIn context (follower count, connection info, etc.) Add your preferred AI model credentials (supports OpenAI, Gemini, or Ollama) Optional: Customize system prompt to better match your brand voice How to customize this workflow to your needs Update the Notion schema to include industry-specific categories or actions Change the AI tone (e.g., humorous, more corporate, etc.) Add conditional logic for auto-sending messages without Slack approval Extend to support multiple platforms (e.g., email, X/Twitter, Instagram DMs)