Workflow Templates

This n8n template demonstrates a complete AI-driven content pipeline for social media. It automatically generates captions and hashtags for new product images, collects human approval via Telegram, and publishes approved content to Twitter. It’s ideal for marketers, e-commerce businesses, and creators who want to speed up content creation while keeping human oversight. How it works Trigger: The workflow starts when a new file is added to a specific Google Drive folder. File Analysis: The image is processed to extract product information. AI Captioning: Gemini generates a caption and five relevant hashtags based on the product. Telegram Approval: The image, caption, and hashtags are sent to the user for approval. ✅ If approved → The content is posted to Twitter and a confirmation is sent back via Telegram. 🔄 If regenerate → Gemini creates a new caption and hashtags, and the approval loop repeats. ❌ If discard → A message is sent on Telegram and the workflow ends. Requirements Google Drive account Gemini API credentials for captioning and hashtags Telegram bot for approvals Twitter Developer Account with API credentials Customising this workflow Swap Google Drive with Dropbox, Notion, or Airtable as the content source. Extend publishing to LinkedIn, Instagram, or multiple platforms. Add multi-user approval flows in Telegram for team-based decisions.

Automatically extract job listings from any website URL, format them with AI, and publish directly to WordPress. Just send a URL via Telegram, and watch as the workflow scrapes the job details, enhances the content with GPT, and creates a polished post on your site. 💡 Why Use Job Repost? ⏰ Save countless hours Automatically extract, process, and publish job offers from any website, freeing your time from repetitive tasks. ✅ Eliminate human errors Say goodbye to typos and missed fields — every job post is validated before going live. 📈 Boost engagement Fresh, well-structured job listings attract more candidates, improving your site's reach and authority. 🚀 Stay ahead Leveraging AI with GPT means your content is not just automated but polished and SEO-friendly — the digital assistant you never knew you needed. ⚡ Perfect For Job board managers:** Want to aggregate listings from multiple sources with minimal effort Recruiters & HR teams:** Who need to streamline job posting workflows without technical hassles Content creators & marketers:** Looking to automate publishing while maintaining style and SEO standards 🔧 How It Works | Step | Process | Description | |------|---------|-------------| | 📱 | Trigger | Send a job URL via Telegram bot to initiate the process | | 🔥 | Extract | Firecrawl API scrapes and extracts clean content from the provided URL | | 📎 | Process | Job data is extracted via AI, text split and cleaned, job categories and types mapped to your system | | 🤖 | Smart Logic | GPT crafts formatted job posts, intelligent validation ensures all key data is present, default values fill in the blanks if necessary | | 💌 | Output | Posts automatically published to WordPress with company logos uploaded, and success or error notifications sent via Telegram | | 🗂 | Storage | Uses Supabase vector store for managing document embeddings, ensuring quick lookup and reference compliance | 🔐 Quick Setup Import the provided JSON file into your n8n instances Add credentials: Firecrawl API key Google Drive OAuth2 (for RAG storage) OpenAI API WordPress API Telegram API Supabase Customize: Telegram bot token WordPress URLs Default images and category mappings if needed Update: URLs and API tokens where placeholders are used Test: Send a job URL to your Telegram bot to verify accurate extraction and posting 🧩 You'll Need ✅ Active n8n instances ✅ Firecrawl account with API access ✅ Google Drive account for RAG document storage ✅ OpenAI account with GPT API access ✅ WordPress site with autojob plugin and API enabled ✅ Telegram bot for URL submission and notifications ✅ Supabase account for vector store management 🛠️ Level Up Ideas 🌍 Add multi-language support to expand global reach 🔗 Support batch URL processing for multiple jobs at once 💬 Integrate Slack or email notifications for wider team alerts 🎯 Use more AI nodes to summarize or rate job offers for quality control 🔄 Schedule periodic cleanup of vector store for performance optimization 📊 Add analytics tracking for published jobs performance 🧠 Nodes Used Core Components: Firecrawl HTTP Request** (Web scraping and content extraction) Google Drive** (RAG document storage) Supabase Vector Store** OpenAI** (Embeddings, GPT Extraction) Code Nodes** for mapping categories Telegram Trigger & Message** HTTP Request** (for WordPress API and image uploads) Made by: Khaisa Studio Tags: automation recruitment job-posting wordpress AI web-scraping firecrawl Category: Human Resources, Recruitment, Wordpress, Scrapping Need a custom? contact me on LinkedIn or Web

TalentFlow AI – Bulk Resume Screening with JD Matching Automatically extract, evaluate, and shortlist multiple resumes against a selected job description using GPT-4. This smart, scalable n8n workflow helps HR/TA teams streamline hiring decisions while keeping results structured, auditable, and easy to share. 👤 Who’s it for This workflow is designed for: HR or Talent Acquisition (TA) teams handling multiple candidates per role Recruiters who want AI-assisted resume screening to save time and reduce bias Organizations that want to automatically log evaluations and keep stakeholders updated in real-time via Slack or Sheets ⚙️ How it works / What it does HR/TA uploads multiple candidate resumes and selects a job role Each resume is: Uploaded to Google Drive Parsed with GPT-4 to extract structured profile data The job description for the selected role is: Retrieved from Google Sheets Downloaded from Drive and parsed The profile + JD are sent to an AI agent to generate: Fit score Strengths & gaps Final recommendation Results are: Appended to the evaluation tracking sheet Optionally shared with the hiring team on Slack Used to trigger emails to qualified or unqualified candidates 🛠️ How to set up Clone or import the workflow into your n8n instance Connect your integrations: Google Sheets (positions & evaluation form) Google Drive (CV & JD folders) OpenAI API (GPT-4) Slack (for notifications) (Optional) SendGrid or SMTP for email notifications Update Google Sheets structure: Positions sheet: maps Job Role → JD file link Evaluation form: stores evaluation results Prepare Drive folders: /cv folder for uploaded resumes /jd folder for job description PDFs 📋 Requirements ✅ n8n (hosted or self-hosted) ✅ OpenAI GPT-4 account (used in Profile & JD evaluator agents) ✅ Google Drive + Google Sheets access ✅ Slack workspace + bot token (Optional) SendGrid or email credentials for candidate follow-up 🎨 How to customize the workflow Change the fit score threshold in the Candidate qualified? node Edit Slack message content/formatting to match your company tone Add additional candidate metadata to Sheets or Slack messages Use a webhook trigger to integrate with your ATS or job board Swap GPT-4 with Claude or Gemini if you prefer other AI services Expand to include multi-position batch screening logic Happy Hiring! 🚀 Automated with love using n8n

Say goodbye to endless applications and hello to more time for perfecting your interview skills! The JOB Hunter Agent uses the power of Google Gemini and SerpAPI to find the perfect job match and generate a personalized cover letter. Result example: 💡 Why Use JOB Hunter Agent? Save Precious Time: Stop sifting through countless job boards; this agent does the heavy lifting, saving you hours every week. Land Your Dream Job Faster: Get laser-focused job matches and a custom-crafted cover letter that speaks directly to the hiring manager, increasing your chances of getting noticed. Never Miss an Opportunity: Your personal AI assistant works 24/7, ensuring you're always on top of the latest openings, even while you sleep! Stand Out from the Crowd: A perfectly tailored cover letter generated on the fly gives you an edge over generic applications, making you look like a superstar. ⚡ Perfect For Job Seekers: Anyone actively looking for a new role who wants to streamline their application process. Busy Professionals: Those with limited time who need an efficient way to find relevant opportunities. Career Changers: Individuals exploring new industries who need a helping hand in crafting compelling applications. 🔧 How It Works ⏱ Trigger: You submit your CV and job preferences through a simple n8n form. 📎 Process: Your CV is extracted from the PDF, and your preferences (location, job type, salary, email) are neatly organized. 🤖 Smart Logic: The "Job Hunter Agent" uses Google Gemini and SerpAPI to find the single best job match for you and then drafts a bespoke cover letter based on your CV and the job description. It's like magic, but with more code! 💌 Output: A beautifully formatted HTML email containing your profile summary, the best job match, your personalized cover letter, and handy application tips is sent straight to your inbox. 🗂 Storage: All the initial data from your form submission is processed and used to craft your perfect job application package. 🔐 Quick Setup Import JSON file to your n8n instances Add credentials: Google Gemini (Gemini 2.5 Pro model) and SerpAPI Customize: Adjust the system prompt in the "Job Hunter Agent" to fine-tune the cover letter tone or length, update the email footer, and expand job filters. Update: Ensure your Gmail OAuth2 credentials are valid for sending emails. Test: Run the workflow with your own CV and preferences to see the magic happen! 🧩 You'll Need Active n8n instances Google Gemini API key (for Gemini 2.5 Pro) SerpAPI account for Google Jobs search results A Gmail account for sending personalized job match emails 🛠️ Level Up Ideas Integrate with LinkedIn, Jobstreet, or Indeed APIs for a wider range of job sources. Allow the agent to find multiple job matches and present them as a curated list. Add an option to attach a parsed CV summary as a PDF to the email for quick reference. Made by: khaisa Studio Tags: AI, Gemini, Google Jobs, Job Search, Automation, Cover Letter Category: job hunter Need custom work? Contact me

🧾 Automated Trip Expense Claim Form With OpenAI Agent & Google Drive Watch the demo video below: > This workflow is designed for employees who need to submit expense claims for business trips. It automates the process of extracting data from receipts/invoices, logging it to a Google Sheet, and notifying the finance team via email. 👤 Who’s it for Ideal users: Employees submitting business trip expense claims HR or Admins reviewing travel-related reimbursements Finance teams responsible for processing claims ⚙️ How it works / What it does Employee submits a form with trip information (name, department, purpose, dates) and uploads one or more receipts/invoices (PDF). Uploaded files are saved to Google Drive for record-keeping. Each PDF is passed to a DocClaim Assistant agent, which uses GPT-4o and a structured parser to extract structured invoice data. The data is transformed and formatted into a standard JSON structure. Two parallel paths are followed: Invoice records are appended to a Google Sheet for centralized tracking. A detailed HTML email summarizing the trip and expenses is generated and sent to the finance department for claim processing. 🛠 How to set up Create a form to capture: Employee Name Department Trip Purpose From Date / To Date Receipt/Invoice File Upload (multiple PDFs) Configure file upload node to store files in a specific Google Drive folder. Set up DocClaim Agent using: GPT-4o or any LLM with document analysis capability Output parser for standardizing extracted receipt data (e.g., vendor, total, tax, date) Transform extracted data into a structured claim record (Code Node). Path 1: Save records to a Google Sheet (one row per expense). Path 2: Format the employee + claim data into a dynamic HTML email Use Send Email node to notify the finance department (e.g., finance@yourcompany.com) ✅ Requirements n8n running with access to: Google Drive API (for file uploads) Google Sheets API (for logging expenses) Email node (SMTP or Gmail for sending) GPT-4o or equivalent LLM with document parsing ability PDF invoices with clear formatting Shared Google Sheet for claim tracking Optional: Shared inbox for finance team 🧩 How to customize the workflow Add approval steps**: route the email to a manager before finance Attach original PDFs**: include uploaded files in the email as attachments Localize for other languages**: adapt form labels, email content, or parser prompts Sync to ERP or accounting system**: replace Google Sheet with QuickBooks, Xero, etc. Set limits/validation**: enforce max claim per trip or required fields before submission Auto-tag expenses**: add categories (e.g., travel, accommodation) for better reporting

Workflow Overview This workflow automates the process of creating and publishing engaging Facebook posts that teach Chinese words to a Thai-speaking audience. It integrates multiple AI models, APIs, and tools to generate content, create visuals, and publish posts seamlessly. Below is a detailed breakdown of the workflow: Who Is This Template For? Social Media Managers: Teams managing Facebook pages and looking for automated, engaging content creation. Content Creators: Professionals who want to streamline the process of generating educational and visually appealing posts. Language Enthusiasts: Individuals or organizations teaching languages (e.g., Chinese) to a Thai-speaking audience. What Problem Does This Workflow Solve? Creating engaging social media content manually can be time-consuming and inconsistent. This workflow solves that by: Automating the generation of educational posts in Thai with Chinese vocabulary. Creating visually appealing images tailored to the post's theme. Publishing posts directly to Facebook using the Pages API. What This Workflow Does Input Handling The workflow starts with an input word (e.g., received via chat or fetched from a Google Sheet). The input is split into two variables (word and input) to ensure data persistence throughout the workflow. Generate Text Content An AI model (OpenRouter Chat Model) generates a structured Facebook post in Thai, including: Engaging hook Core vocabulary (Chinese word, Pinyin, and Thai meaning) Real-world usage examples Pro-tip or fun fact Call-to-action for engagement Relevant hashtags Describe Image Concept Another AI model creates a brief description of the visual theme for the post. This description is used as input for generating an image. Generate Image The workflow uses Recraft.ai to generate an image based on the description. The image is styled consistently using predefined themes (e.g., digital illustration). Publish Post The generated text and image are published to Facebook using the Pages API. The post includes: The educational content as the caption. The generated image as the visual element. Setup Guide Pre-Requisites Access to the following APIs: OpenRouter.ai: For generating text content and image descriptions. Recraft.ai: For generating images. Facebook Graph API: For publishing posts. Step-by-Step Setup Configure Input Source: Replace the chat input node with your preferred source (e.g., Google Sheet, email, or manual input). Set Up OpenRouter.ai: Configure the credentials for OpenRouter.ai in the respective nodes (OpenRouter Chat Model and OpenRouter Chat Model1). Set Up Recraft.ai: Add your API key for Recraft.ai in the Generate Image (Recraft.ai) node. Configure Facebook Graph API: Set up the Facebook Graph API credentials with the required permissions (pages_manage_posts, pages_read_engagement, etc.). Update the page_id and graphApiVersion in the Facebook Graph API node. Test the Workflow: Run the workflow manually to verify that it generates content, creates images, publishes posts, and logs details correctly. How to Customize This Workflow to Your Needs Change Input Source: Replace the chat input with a Google Sheet, email, or database query. Modify Content Style: Adjust the AI prompts to suit your audience (e.g., professional tone, casual language). Use Different Image Styles: Experiment with other styles/themes in Recraft.ai for the generated images. Expand Use Cases: Adapt the workflow to other social media platforms (e.g., Instagram, LinkedIn) by modifying the API calls. Why Use This Template? Efficiency: Automates repetitive tasks like content creation and image generation. Consistency: Ensures posts follow a consistent format and style. Engagement: Creates visually appealing and interactive content to boost audience engagement. Scalability: Easily adaptable for different topics, languages, or platforms. Additional Resources

💼 Lead Outreach Agent This AI workflow helps you quickly react to new leads with an initial personalized outreach. A great start of your lead nurturing sequence to avoid loosing precious leads that could turn into paying customers. Most importantly it uses gotoHuman so you can review the AI-analysis and the AI-generated editable email draft before it is sent out in your name. How it works We receive a new form submission incl. the email address and company name of the prospect and extract the website URL from the address. We proceed only for company email addresses. We scrape the website using Firecrawl and summarize it with OpenAI Our AI agent runs an analysis based on the lead information and documents describing our own company and the defined Ideal Customer Profiles. It also fetches previously approved examples from gotoHuman so you're effectively creating a self-learning agent. It responds with the analysis and the drafted outreach email. Human Approval in gotoHuman. Allows editing the drafted email. We can now send our email including any edits made during the review and be sure that we are using high-quality content instead of AI slop. How to set up Most importantly, install the gotoHuman node before importing this template! (Just add the node to a blank canvas before importing) Set up your credentials for the different services In gotoHuman, select and create the pre-built review template "Lead Outreach Agent" or import the ID: T873fI1Xli5nt3eh33Rj Select this template in the gotoHuman node Requirements You need accounts for gotoHuman (Human Supervision) OpenAI (AI Agent) Typeform (Lead Form Submissions) Firecrawl (Website Scraping) Gmail Google Docs (Company Wiki) How to customize Replace the Typeform trigger with any other way you might receive or find new leads Provide the AI Sales Agent with more context to properly analyze the lead and create better personalized emails. Consider adding tools that allow the agent to fetch more infos about the prospect's company or personal profile, or to find out more about your specific product/service offerings and how your sales pitches look like.

This n8n template demonstrates how to create an automated emotional story generation system that produces structured video prompts and generates corresponding images using AI. The workflow creates a complete story with 5 scenes featuring a Pakistani character named Yusra, converts them into Veo 3 video generation prompts, and generates images for each scene. Use cases include: Automated story creation for social media content Video pre-production with AI-generated storyboards Content creation for educational or entertainment purposes Multi-scene narrative development with consistent character design Good to know: Uses Gemini 2.5 Flash Lite for story generation and prompt conversion Uses Gemini 2.0 Flash Exp for image generation The image generation model may be geo-restricted in some regions Workflow includes automatic Google Drive organization and Google Sheets tracking How it works: Story Creation: Gemini AI creates a 5-scene emotional story featuring Yusra, a Pakistani girl aged 20-25 in traditional dress Folder Organization: AI generates a unique folder name with timestamp for project organization Google Sheets Setup: Creates a new sheet to track all scenes and their processing status Scene Processing: Each scene is processed individually with character and action prompts Veo 3 Prompt Conversion: Converts natural language scene descriptions into structured JSON format optimized for Veo 3 video generation, including parameters like: Detailed scene descriptions Camera movements and angles Lighting and mood settings Style and quality specifications Aspect ratios and technical parameters Image Generation: Uses Gemini's image generation model to create visual representations of each scene File Management: Automatically uploads images to Google Drive and organizes them in project folders Status Tracking: Updates Google Sheets with processing status and file URLs Automated Workflow: Includes conditional logic to handle different processing states and file movements How to use: Execute the workflow manually or set up automated triggers The system will automatically create a new story with 5 scenes Each scene gets processed through the AI pipeline Generated images are organized in Google Drive folders Track progress through the Google Sheets interface The workflow handles all file management and status updates automatically Requirements: Gemini API access for both text and image generation Google Drive for file storage and organization Google Sheets for project tracking and management n8n instance with appropriate node access Customizing this workflow: Modify the character description in the Story Creator node Adjust the number of scenes by changing the story prompt Customize the Veo 3 prompt parameters for different video styles Add additional AI models or processing steps Integrate with other content creation tools Modify the folder naming convention or organization structure Technical Features: Automated retry logic for failed operations Conditional processing based on status flags Batch processing for multiple scenes Error handling and status tracking File organization with timestamp-based naming Integration with Google Workspace services This template is perfect for content creators, educators, or anyone looking to automate story-based content creation with AI assistance.

WhatsApp Bulk Message Broadcast via Google Sheets (n8n Workflow) Use Case This workflow enables automated bulk WhatsApp message broadcasting using the WhatsApp Business Cloud API. It pulls recipient and message data from a Google Sheet, sends templated messages (optionally with image headers), and updates the sheet with the message status. It is ideal for marketing teams, support agents, and businesses handling high-volume outreach. Who Is This For? Businesses conducting WhatsApp marketing or outreach campaigns Customer support or notification teams Administrators seeking an automated, no-code message distribution system using Google Sheets What This Workflow Does Triggers automatically every minute to scan for pending messages Fetches unsent entries from a Google Sheet Limits the number of messages processed per execution to comply with API usage guidelines Sanitizes WhatsApp numbers for proper formatting Sends messages using a pre-approved WhatsApp template (text and optional image) Marks the row as "Sent" in the sheet upon successful delivery Workflow Breakdown (Node by Node) 1. Trigger Every 5 Minutes Initiates the workflow every minute using a scheduled trigger to continuously monitor pending rows. 2. Fetch All Pending Queries for Messaging Reads rows from a Google Sheet where the Status column is empty, indicating they haven’t been processed yet. 3. Limit Restricts processing to 2 rows per execution to manage API throughput. 4. Loop Over Items Uses SplitInBatches to iterate through each row individually. 5. Clean WhatsApp Number A code node that strips non-numeric characters from the WhatsApp No field, ensuring the format is valid for the API. 6. Send Message to 300 Phone No Sends a WhatsApp message using the WhatsApp Cloud API and a pre-approved template. Template includes: An image from the Image URL column (as header, optional) Dynamic variables for the recipient's Name and Message fields Template variables must be pre-defined and approved in the Meta Developer Portal, such as {{1}}, {{2}}. 7. Change State of Rows in Sent1 Updates the Status column to Sent for each successfully processed row using the row number as a reference. Google Sheet Format Structure your Google Sheet as shown below: | WhatsApp No | Name | Message | Image URL | Status | |--------------|------------|---------------------------|---------------------|--------| | +8801XXXXXXX | John Doe | Hello, your order shipped | https://.../img.jpg | | Leave the Status column empty for rows that need to be processed. Requirements WhatsApp Business Cloud API access via Meta for Developers A properly structured Google Sheet as described above Active OAuth2 credentials configured in n8n for: googleSheetsOAuth2Api whatsAppApi Customization Options Update the Limit node to control how many rows are processed in each run Adjust the trigger schedule (e.g., change to every 5 minutes) Replace the message template ID with your own custom-approved one from Meta Add error-handling logic (e.g., IF or Try/Catch nodes) to log failures or set Status = Failed Sample Sheet Template View Sample Google Sheet Workflow Highlights Automated execution every 1 minute Reads and processes only pending records Verifies WhatsApp numbers and delivers templated messages Updates Google Sheet after each attempt Support & Community Need help setting up or customizing the workflow? WhatsApp: Contact Support Discord: Join SpaGreen Server Facebook Group: SpaGreen Community Website: Visit SpaGreen Creative

Tags: Supply Chain, Logistics, AI Agents Context Hey! I’m Samir, a Supply Chain Data Scientist from Paris, and the founder of LogiGreen Consulting. We design tools to help companies improve their logistics processes using data analytics, AI, and automation—to reduce costs and minimize environmental impacts. >Let’s use N8N to improve logistics operations! 📬 For business inquiries, you can add me on LinkedIn Who is this template for? This workflow template is designed for logistics or manufacturing operations that receive orders by email. The example above illustrate the challenge we want to tackle using an AI Agent to parse the information and load them in a Google sheet. If you want to understand how I built this workflow, check my detailed tutorial: 🎥 Step-by-Step Tutorial How does it work? The workflow is connected to a Gmail Trigger to open all the emails that include Inbound Order in their subject. The email is parsed by an AI Agent equipped with OpenAI's GPT to collect all the information. The results are pulled in a Google Sheet. These orderlines can then be transferred to warehouse teams to prepare *order receiving. What do I need to get started? You’ll need: Gmail and Google Drive Accounts** with the API credentials to access it via n8n An OpenAI API key (GPT-4o) for the chat model. A Google Sheet with these columns: PO_NUMBER, EXPECTED_DELIVERY DATE, SKU_ID, QUANTITY Next Steps Follow the sticky notes in the workflow to configure each node and start using AI to support your logistic operations. 🚀 Curious how N8N can transform your logistics operations? 📬 Let’s connect on LinkedIn Notes An example of email is included in the template so you can try it with your mailbox. This workflow was built using N8N version 1.82.1 Submitted: March 28, 2025

Prunaai Flux Schnell Image Generator Description This is a 3x faster FLUX.1 [schnell] model from Black Forest Labs, optimised with pruna with minimal quality loss. Contact us for more at pruna.ai Overview This n8n workflow integrates with the Replicate API to use the prunaai/flux-schnell model. This powerful AI model can generate high-quality image content based on your inputs. Features Easy integration with Replicate API Automated status checking and result retrieval Support for all model parameters Error handling and retry logic Clean output formatting Parameters Required Parameters prompt** (string): Prompt for generated image Optional Parameters seed** (integer, default: None): Random seed. Set for reproducible generation megapixels** (string, default: 1): Approximate number of megapixels for generated image speed_mode** (string, default: Juiced 🔥 (default)): Run faster predictions with model optimized for speed num_outputs** (integer, default: 1): Number of outputs to generate aspect_ratio** (string, default: 1:1): Aspect ratio of the output image output_format** (string, default: jpg): Format of the output images output_quality** (integer, default: 80): Quality when saving the output images, from 0 to 100. 100 is best quality, 0 is lowest quality. Not relevant for .png outputs num_inference_steps** (integer, default: 4): Number of denoising steps. 4 is recommended, and lower number of steps produce lower quality outputs, faster. How to Use Set up your Replicate API key in the workflow Configure the required parameters for your use case Run the workflow to generate image content Access the generated output from the final node API Reference Model: prunaai/flux-schnell API Endpoint: https://api.replicate.com/v1/predictions Requirements Replicate API key n8n instance Basic understanding of image generation parameters

Luma Photon Flash Image Generator Description Accelerated variant of Photon prioritizing speed while maintaining quality Overview This n8n workflow integrates with the Replicate API to use the luma/photon-flash model. This powerful AI model can generate high-quality image content based on your inputs. Features Easy integration with Replicate API Automated status checking and result retrieval Support for all model parameters Error handling and retry logic Clean output formatting Parameters Required Parameters prompt** (string): Text prompt for image generation Optional Parameters seed** (integer, default: None): Random seed. Set for reproducible generation aspect_ratio** (string, default: 16:9): Aspect ratio of the generated image image_reference** (string, default: None): Reference image to guide generation style_reference** (string, default: None): Style reference image to guide generation character_reference** (string, default: None): Character reference image to guide generation image_reference_url** (string, default: None): Deprecated: Use image_reference instead style_reference_url** (string, default: None): Deprecated: Use style_reference instead image_reference_weight** (number, default: 0.85): Weight of the reference image. Larger values will make the reference image have a stronger influence on the generated image. style_reference_weight** (number, default: 0.85): Weight of the style reference image character_reference_url** (string, default: None): Deprecated: Use character_reference instead How to Use Set up your Replicate API key in the workflow Configure the required parameters for your use case Run the workflow to generate image content Access the generated output from the final node API Reference Model: luma/photon-flash API Endpoint: https://api.replicate.com/v1/predictions Requirements Replicate API key n8n instance Basic understanding of image generation parameters