Baserow campaign database to Shopify with image upload & dynamic template update
Automating your marketing campaign management process can streamline your workflow and save you valuable time. With the combination of Baserow and n8n, you can efficiently handle your campaign data and seamlessly publish content to your Shopify store. In this workflow template, I demonstrate how to leverage Baserow as a centralized platform for organizing your marketing campaign assets, including copy and images. By utilizing n8n, we automate the process of fetching images and campaign descriptions from Baserow and uploading them directly to your Shopify store. With this automated solution, you can expedite the publishing process, ensuring that your campaigns are launched swiftly across your sales channels. Additionally, this workflow serves as a foundational step towards further automation in campaign management, allowing you to dynamically generate and upload content to your Shopify store with ease. This template will help you: Use n8n to get images for marketing campaigns from Baserow and upload them to your Shopify media library Dynamically inject data from Baserow into a template file Upload a template file to your Shopify theme This template will demonstrate the follwing concepts in n8n: use the Webhook node use the IF node to control the execution flow of the workflow do time calculation using expressions and javascript use the GraphQL node to upload images to your Shopify media files create a dynamic template file for your Shopify theme use the HTTP Reqest node to upload your template file to your Shopify store How to get started? Create a custom app in Shopify get the credentials needed to connect n8n to Shopify This is needed for the Shopify Trigger Create Shopify Acces Token API credentials n n8n for the Shopify trigger node Create Header Auth credentials: Use X-Shopify-Access-Token as the name and the Acces-Token from the Shopify App you created as the value. The Header Auth is neccessary for the GraphQL nodes. You will need a running Baserow instance for this. You can also sign up for a free account at https://baserow.io/ Please make sure to read the notes in the template. For a detailed explanation please check the corresponding video: https://youtu.be/Ky-dYlljGiY
By SaschaAutomate X-ray analysis with VLM Orion and distribute to Gmail, Telegram & Drive
📌 Overview This workflow provides an automated pipeline for processing medical X-ray images using VLM Run (model: vlmrun-orion-1:auto), and distributing the AI-generated analysis to multiple channels—email, Telegram, and Google Drive. --- ⚙️ How It Works Upload X-Ray Image A Form Trigger allows the user to upload an X-ray file. Once the image is submitted, the workflow immediately starts processing. --- Automated X-Ray Analysis The uploaded X-ray image is sent to VLM Run (vlmrun-orion-1:auto) via an OpenAI-compatible endpoint. The model returns: A text-based interpretation or description A disease-highlighted output image (if detected) A URL reference pointing to the annotated result image stored in Google Cloud --- Extract Artifact From artifact reference, download file using artifact node. --- Generate Report File The Convert to File node transforms the analysis text into a shareable .txt report. This file is used both for email and Drive storage. --- Send Notifications to Gmail & Telegram The workflow automatically: 📧 Emails the doctor (or configured staff email): The diagnostic description The generated report file The annotated X-ray image 📨 Sends a Telegram message containing: The same report The disease-highlighted X-ray image This ensures instant notification and cross-platform availability. --- Upload to Google Drive The final step uses Google Drive OAuth2 to store: The report file The annotated medical image These files are uploaded to a designated Drive folder for archiving and future reference. --- 🧩 Key Features ✔️ Automated X-ray processing using VLM Run ✔️ Structured extraction of annotated medical images ✔️ Multi-channel notification (Email + Telegram) ✔️ Centralized archive via Google Drive ✔️ Zero manual intervention after upload ✔️ Works with OpenAI-compatible VLM endpoints --- 🔧 Requirements VLM Run API Credentials Required to call vlm-agent-1 for image analysis. Gmail OAuth2 Credentials Needed to automatically email the diagnostic report. Telegram Bot Token Sends analysis results to a Telegram chat or group. Google Drive OAuth2 Stores reports and annotated images in Google Drive. --- 📎 Notes This workflow automates image handling and communication. All AI-generated content must be reviewed by a qualified medical professional before any clinical use.
By Mehedi Ahamed