Workflow Templates

Setup & Instructions — fluidX: Create Session, Analyze & Notify Goal: This workflow demonstrates the full fluidX THE EYE integration — starting a live session, inviting both the customer (via SMS) and the service agent (via email), and then accessing the media (photos and videos) created during the session. Captured images are automatically analyzed with AI, uploaded to an external storage (such as Google Drive), and a media summary for the session is generated at the end. The agent receives an email with a link to join the live session. The customer receives an SMS with a link to start sharing their camera. Once both are connected, the agent can view the live feed, and the system automatically stores uploaded images and videos in Google Drive. When the session ends, the workflow collects all media and creates a complete AI-powered session summary (stored and updated in Google Drive). Below is an example screenshot from the customer’s phone: Prerequisites Developer account:* https://live.fluidx.digital (activate the *TEST plan**, €0) API docs (Swagger):** fluidX.digital API 🔐 Required Credentials 1️⃣ fluidX API key (HTTP Header Auth) • Credential name in n8n: fluidx API key • Header name: x-api-key • Header value: YOUR_API_KEY 2️⃣ SMTP account (for outbound email) • Credential name in n8n: SMTP account • Configure host, port, username, and password according to your provider • Enable TLS/SSL as required 3️⃣ Google Drive account • Used to store photos, videos, and automatically update the session summary files. 4️⃣ OpenAI API (for AI analysis & summary) •Used in the Analyze Images (AI) and Generate Summary parts of the workflow. • Credential type: OpenAI • Credential name (suggested): OpenAI account • API Key: your OpenAI API key • Model: e.g. gpt-4.1, gpt-4o, or similar (choose in the OpenAI node settings) ⚙️ Configuration (in the “Set Config” node) BASE_URL: https://live.fluidx.digital company / project / billingcode / sku: adjust as needed emailAgent: set before running (empty in template) phoneNumberUser: set before running (empty in template) Flow Overview Form Trigger → Create Session → Set Session Vars → Send SMS (User) → Send Email (Agent) → Monitor Media → Analyze Images (AI) → Upload Files to Google Drive → Generate Summary → Update Summary File The workflow starts automatically when a Form submission is received. Users enter the customer’s phone number and agent’s email, and the system creates a new fluidX THE EYE session. As media is uploaded during the session, the workflow automatically retrieves, stores, analyzes, and summarizes it — providing a complete end-to-end automation example for remote inspection, support, or field-service use cases. Notes Do not store real personal data inside the template. Manage API keys and secrets via n8n Credentials or environment variables. Log out of https://live.fluidx.digital in the agent’s browser before testing, to ensure a clean invite flow and session creation.

🎨 Instagram Carousel & Caption Generator on Autopilot (GPT-5 + Nano Banana + Blotato + Google Sheets) Description Watch the full step-by-step tutorial on YouTube: https://youtu.be/id22R7iBTjo Disclaimer (self-hosted requirement): This template assumes you have valid API credentials for OpenAI, Wavespeed/Nano Banana, Blotato, and Google. If using n8n Self-Hosted, ensure HTTPS access and credentials are set in your instance. How It Works Chat Trigger – Receive a topic/idea (e.g. “5 best podcast tips”). Image Prompt Generator (GPT-5) – Creates 5 prompts using the “Hook → Problem → Insight → Solution → CTA” framework. Structured Output Parser – Formats output into a JSON array. Generate Images (Nano Banana) – Converts prompts into high-quality visuals. Wait for Render – Ensures image generation completes. Fetch Rendered Image URLs – Retrieves image links. Upload to Blotato – Hosts and prepares images for posting. Collect Media URLs – Gathers all uploaded image URLs. Log to Google Sheets – Stores image URLs + timestamps for tracking. Caption Generator (GPT-5) – Writes an SEO-friendly caption. Merge Caption + Images – Combines data. Post Carousel (Blotato) – Publishes directly to Instagram. Step-by-Step Setup Instructions 1) Prerequisites n8n (Cloud or Self-Hosted) OpenAI API Key (GPT-5) Wavespeed API Key (Nano Banana) Blotato API credentials (connected to Instagram) Google Sheets OAuth credentials 2) Add Credentials in n8n OpenAI: Settings → Credentials → Add “OpenAI API” Wavespeed: HTTP Header Auth (e.g. Authorization: Bearer <API_KEY>) Blotato: Add “Blotato API” Google Sheets: Add “Google Sheets OAuth2 API” 3) Configure & Test Run with an idea like “Top 5 design hacks”. Check generated images, caption, and logged sheet entry. Confirm posting works via Blotato. 4) Optional Add a Schedule Trigger for weekly automation. Insert a Slack approval loop before posting. Customization Guide ✏️ Change design style: Modify adjectives in the Image Prompt Generator. 📑 Adjust number of slides: Change Split node loop count. 💬 Tone of captions: Edit Caption Generator’s system prompt. ⏱️ Adjust render wait time: If image generation takes longer, increase the Wait node duration from 30 seconds to 60 seconds or more. 🗂️ Log extra data: Add columns in Google Sheets for campaign or topic. 🔁 Swap posting tool: Replace Blotato with your scheduler or email node. Requirements OpenAI API key (GPT-5 or compatible) Wavespeed API key (Nano Banana) Blotato API credentials Google Sheets OAuth credentials n8n account (Cloud or Self-Hosted)

Automate video creation: AI generates ideas, Vertex AI renders videos, and auto-uploads to Google Drive with complete tracking. What You Get Gemini AI for creative prompts Vertex AI video generation Auto-upload to Google Drive Complete Google Sheets logging Smart retry logic Base64 to MP4 conversion Setup Enable Vertex AI in Google Cloud Get Gemini API key Run gcloud auth print-access-token for ACCESS TOKEN Import workflow & configure credentials Add prompts & test Flow Schedule → Gemini AI → Vertex AI → Wait → Convert → Upload → Log Resources Google Sheets Template ⚠️ Note: ACCESS TOKEN expires hourly - refresh using gcloud auth print-access-token 📧 LinkedIn: linkedin.com/in/yourprofile 🔗 More n8n Products: Click here

Overview This workflow automates financial reconciliation across multiple data sources such as bank statements, invoices, ERP systems, and CSV uploads. It standardizes all incoming data, performs rule-based matching, enhances results with AI-powered fuzzy matching, and assigns confidence scores. High-confidence matches are auto-reconciled, while uncertain ones are flagged for human review. How It Works Data Ingestion Receives financial data via webhook from different sources. Source Detection & Routing Identifies the data type and routes it to the correct normalization flow. Data Normalization Converts all records into a unified schema with consistent fields like ID, amount, date, and description. Data Merging Combines all normalized records into a single dataset for matching. Deterministic Matching Matches records using exact field combinations such as ID, amount, and date to generate initial confidence. Match Quality Check Filters low-confidence matches for further analysis. AI Fuzzy Matching Uses AI to identify near matches based on descriptions, amount tolerance, and date proximity. Confidence Scoring Combines deterministic and AI results into a final confidence score with a detailed audit trail. Decision Routing High confidence → auto-reconciled Low confidence → flagged for human review Reporting Logs reconciliation results into Google Sheets. Notifications Sends a summary report to Slack for visibility. Setup Instructions Configure webhook to receive financial data Set matching keys and confidence thresholds Connect OpenAI for fuzzy matching Connect Google Sheets for reporting Connect Slack for notifications Ensure input data follows expected formats Test with sample financial data Activate the workflow Use Cases Bank statement vs invoice reconciliation ERP vs accounting system matching Financial audit automation Detecting missing or duplicate transactions Reducing manual reconciliation effort Requirements n8n instance with webhook support OpenAI API access Google Sheets account Slack workspace Structured financial datasets (CSV/API) Notes Deterministic matching ensures accuracy for exact matches. AI fuzzy matching improves coverage for ambiguous records. Confidence scoring provides transparency and auditability. Human review ensures control over uncertain reconciliations.

Quick overview Youtube Video: https://youtu.be/WMB_6WwJayc This workflow collects PDF CVs via an n8n form, screens them twice with Gemini (text extraction and vision on a rendered image), and compares the results to detect hidden-text, prompt-injection attempts, then quarantines suspicious files in GDrive and logs outcomes to Sheets with Telegram. How it works Receives a job application submission via an n8n form with the candidate’s name, selected role, and a PDF CV upload. Validates that the uploaded file is a PDF and returns a rejection form response if the format is incorrect. Extracts raw text from the PDF and sends it to Google Gemini to produce a structured verdict (qualified flag, score, years of experience, and one-sentence reason). Converts the PDF to a JPG via ConvertAPI, converts the returned base64 to an image file, and sends the image to Google Gemini vision to generate the same structured verdict (and reports via Telegram if this vision path fails). Compares the text and vision verdicts to compute score and experience gaps and flags the CV as suspicious if the verdicts disagree or diverge beyond the configured thresholds. If flagged, uploads the original CV to a Google Drive quarantine folder and sends a detailed Telegram alert; otherwise, sends a “clean result” Telegram message using the vision-based reason. Appends a row to a Google Sheets “Applications” tab with the submission metadata, both scores, divergence metrics, the suspicion flag, and the trusted reason. Setup Configure the n8n form trigger and publish the form so candidates can submit their name, role, and a PDF file in the binary field named "CV". Add Google Gemini (PaLM) credentials and ensure the selected Gemini model supports both text and multimodal inputs. Set up ConvertAPI and replace the placeholder Secret in the PDF-to-JPG HTTP request URL. Add Google Drive OAuth2 credentials and set the target quarantine folder ID. Add Google Sheets OAuth2 credentials and update the spreadsheet ID and ensure the “Applications” tab has the expected headers. Add Telegram bot credentials and replace the placeholder chat ID(s) for the flagged, clean, and vision-failure notifications.

AI-Powered Viral Video Factory 🚀 This workflow automates the entire process of creating short, cinematic, fact-based videos ready for social media. It takes a single concept, generates a script and visuals, creates video clips, adds a voiceover, and assembles a final video, which is then uploaded directly to your Google Drive. It's perfect for content creators and marketing agencies looking to scale video production with minimal manual effort. How It Works 🎬 Generate a Viral Idea 💡: The workflow begins with the Create New Idea1 (OpenAI) node, which generates a viral-ready video concept, including a punchy title, hashtags, and a brief description based on a core theme (e.g., space, black holes). This idea is then logged in a Google Sheet. Create a Cinematic Script & Voiceover 📜: An OpenAI node (Generating scenes1) creates a detailed 12-scene script, outlining the visuals for a 60-second video. The script text for all scenes is combined and prepared for voiceover generation by another OpenAI node (Generate Voiceover). Generate Scene-by-Scene Visuals ✨: The workflow loops through each of the 12 scenes to create an animated clip: Image Generation: An HTTP Request node sends the scene's prompt to the fal-ai/flux model to create a photorealistic still image. Animation Prompting: The Video Prompts1 (OpenAI Vision) node analyzes the generated image and creates a new, specific prompt to animate it cinematically. Image-to-Video: Another HTTP Request node uses the fal-ai/kling-video model to turn the still image into a 5-second animated video clip based on the new animation prompt. Assemble the Final Video 🎞️: Stitch Clips: Once all 12 clips are generated, the Merge Clips node uses the fal-ai/ffmpeg-api to concatenate them into a single, seamless 60-second video. Add Audio: The Combine Voice and Video node then layers the AI-generated voiceover onto the stitched video. Deliver to Google Drive 📂: Finally, the completed video is converted from a URL to a file and automatically uploaded to your specified Google Drive folder for easy access and publishing. Key Technologies Used n8n**: For orchestrating the entire automated workflow. OpenAI (GPT-4.1 & GPT-4o)**: For idea generation, scriptwriting, voiceover, and vision analysis. Fal.ai**: For high-performance, API-based image generation (Flux), video animation (Kling), and video processing (FFMPEG API). Google Drive & Sheets**: For logging ideas and storing the final video output. Setup Instructions Add Credentials: In n8n, add your OpenAI API key. Connect your Google account for Google Sheets and Google Drive access. You will need a Fal.ai API Key. Configure Fal.ai API Key: Crucially, you must replace the placeholder API key in all HTTP Request nodes that call the fal.run URL. Find the Authorization header in each of these nodes and replace the existing key with your own Key YOUR_FAL_AI_KEY_HERE. Nodes to update: Create Images1, Get Images1, Create Video1, Get Video1, Merge Clips, Get Final video, Combine Voice and Video. Configure OpenAI Nodes: Select each OpenAI node (e.g., Create New Idea1, Generating scenes1) and choose your OpenAI credential. You can customize the main prompt in the Create New Idea1 node to change the theme of the videos you want to generate. Configure Google Sheets & Drive: In the Organise idea, caption etc1 node, select your Google Sheets credential and specify the Spreadsheet and Sheet ID you want to use for logging ideas. In the Upload file to drive node, select your Google Drive credential and choose the destination folder for your final videos.

The workflow first populates a Pinecone index with vectors from a Bitcoin whitepaper. Then, it waits for a manual chat message. When received, the chat message is turned into a vector and compared to the vectors in Pinecone. The most similar vectors are retrieved and passed to OpenAI for generating a chat response. Note that to use this template, you need to be on n8n version 1.19.4 or later.

💥 Generate AI Music & Publish to YouTube Automatically with Blotato This workflow automatically generates AI music, creates a thumbnail, converts everything into a video, and publishes it directly to YouTube — fully automated. Perfect for building faceless YouTube music channels, AI content automation, or passive content generation pipelines. Who is this for? This template is ideal for: YouTube creators building AI music channels Content creators creating faceless videos Automation enthusiasts using n8n for content pipelines Agencies generating bulk YouTube content Anyone wanting to automate music creation and publishing Whether you're creating lofi music, ambient tracks, meditation sounds, or background music, this workflow removes manual work entirely. What problem is this workflow solving? Creating AI music videos typically involves multiple manual steps: Generating music Creating thumbnails Converting audio into video Uploading to YouTube Writing titles and metadata This process is time-consuming and repetitive. This workflow automates everything into a single end-to-end pipeline, allowing you to: Generate unlimited AI music Automatically create thumbnails Convert audio into video Publish directly to YouTube What this workflow does This workflow performs the following steps: User submits a music request via form AI generates an optimized music prompt ElevenLabs generates AI music AI generates thumbnail prompt Atlas Cloud generates thumbnail image Cloudinary uploads generated assets Shotstack creates video (image + audio) Blotato uploads video to YouTube automatically SEO-optimized YouTube title is generated automatically Final result: AI-generated music video automatically published to YouTube The entire process runs fully automated. Setup To use this workflow, configure the following credentials: Required APIs OpenAI API Key — Prompt generation Elevenlabs** API Key — Music generation AtlasCloud** API Key — Thumbnail generation Cloudinary Account — Media hosting Shotstack API Key — Video creation Blotato** API Key — YouTube publishing Community Node Requirement This workflow uses the Blotato community node. 🎥 Watch This Tutorial 👋 Need help or want to customize this? 📩 Contact: LinkedIn 📺 YouTube: @DRFIRASS 🚀 Workshops: Mes Ateliers n8n Need help customizing? Contact me for consulting and support : Linkedin / Youtube / 🚀 Mes Ateliers n8n

How it works This workflow generates an 8-second product advertising video from a single input image. It downloads the image from Google Drive, converts it to base64 for the API request, analyzes it with Gemini (Creative Visualiser), then turns the description into a short video script/prompt. The prompt + image are sent to Veo to start a long-running video generation job. The workflow polls until a video URI is available, downloads the MP4, and uploads it back to Google Drive. Setup 1) Connect credentials used in this workflow: Google Drive + Google Gemini, and an API key for the Veo HTTP requests. 2) Set the input image file in Download ad image. 3) Set the output folder in Upload to Drive. 4) (Optional) Adjust aspectRatio, resolution, and durationSeconds in Generate Video, then execute the workflow.

This n8n workflow implements a version of the Adaptive Retrieval-Augmented Generation (RAG) framework. It recognizes that the best way to retrieve information often depends on the type of question asked. Instead of a one-size-fits-all approach, this workflow adapts its strategy based on the user's query intent. 🌟 How it Works Receive Query: Takes a user query as input (along with context like a chat session ID and Vector Store collection ID if used as sub-workflow). Classify Query: First, the workflow classifies the query into a predefined category. This template uses four examples: Factual: For specific facts. Analytical: For deeper explanations or comparisons. Opinion: For subjective viewpoints. Contextual: For questions relying on specific background. Select & Adapt Strategy: Based on the classification, it selects a corresponding strategy to prepare for information retrieval. The example strategies aim to: Factual: Refine the query for precision. Analytical: Break the query into sub-questions for broad coverage. Opinion: Identify different viewpoints to look for. Contextual: Incorporate implied or user-specific context. Retrieve Info: Uses the output of the selected strategy to search the specified knowledge base (Qdrant vector store - change as needed) for relevant documents. Generate Response: Constructs a response using the retrieved documents, guided by a prompt tailored to the original query type. By adapting the retrieval strategy, this workflow aims to provide more relevant results tailored to the user's intent. ⚙️ Usage & Flexibility Sub-Workflow:** Designed to be called from other n8n workflows, passing user_query, chat_memory_key, and vector_store_id as inputs. Chat Testing:** Can also be triggered directly via the n8n Chat interface for easy testing and interaction. Customizable Framework:** The query categories (Factual, Analytical, etc.) and the associated retrieval strategies are examples. You can modify or replace them entirely to fit your specific domain or requirements. 🛠️ Requirements Credentials:** You will need API credentials configured in your n8n instance for: Google Gemini (AI Models) Qdrant (Vector Store)

Chat with thing This n8n template lets you build a smart AI chat assistant that can handle text, images, and PDFs — using OpenAI's GPT-4o multimodal model. It supports dynamic conversations and file analysis, making it great for AI-driven support bots, personal assistants, or embedded chat widgets. 🔍 How it Works The chat trigger node kicks off a session using n8n's hosted chat UI. Users can send text or upload images or PDFs — the workflow checks if a file was included. If an image is uploaded, the file is converted to base64 and analyzed using GPT-4o's vision capabilities. GPT-4o generates a natural language description of the image and responds to the user's question in context. A memory buffer keeps track of the conversation thread, so follow-up questions are handled intelligently. OpenAI’s chat model handles both text-only and mixed media input seamlessly. 🧪 How to Use You can embed this in a website or use it with your own webhook/chat interface. The logic is modular — just swap out the chatTrigger node for another input (e.g. form or API). To use with documents, you can modify the logic to pass PDF content to GPT-4 directly. You can extend it with action nodes, e.g. saving results to Notion, Airtable, or sending replies via email or Slack. 🔐 Requirements Your OpenAI GPT-4o API key Set File Upload on the chat 🚀 Use Cases PDF explainer bot Internal knowledge chat with media support Personal assistant for mixed content

This workflow contains community nodes that are only compatible with the self-hosted version of n8n. Automated Data-Driven UX Persona Creation – Try It Out!* About You can create personas based on your website, region, and industry. Unlike traditional persona creation, this process uses reliable data sources and can estimate market size for each persona. UX personas have a wide range of applications: use them to better define your target users during product development, align your team around user goals during workshops, or inspire new features and ideas by deeply understanding user needs and behaviors. How It Works The flow is triggered via a web form Perplexity analyzes the market and creates a data foundation for the personas An AI agent transforms the data into detailed persona descriptions and publishes them in a Google Doc We use DALL·E 3 to generate an image for each persona, which is saved to your Google Drive How To Use Import the package into your N8N interface Set up the credentials in each node to access the necessary tools Wait for the process to run (it takes just a few seconds) Check the final output in Google Docs and your Google Drive Requirements Perplexity for research OpenAI for LLM and Image generation Google Doc Google Drive to upload images