Use Gemini and Imagen 3 on Vertex AI to create the images you envision. Generate tailored images from reference sources with Apps Script.
Have you ever generated an image using Gemini in Google Workspace and wished you could easily tweak or iterate on it? While Gemini for Workspace is great for initial creation, iterating on those images directly isn’t currently straightforward. A recent post by Stéphane Giron highlights a programmatic approach using Google Apps Script, Vertex AI (with Imagen 3 and Gemini models) to achieve the goal of generating image variations based on a source image.
Stéphane’s method uses a source image (which could be one previously generated or found elsewhere) which is provided to the Vertex AI API for Gemini (e.g., gemini-2.0-pro) along with text instructions for the required changes. The Gemini model analyzes the image and the request to generate a new prompt. This new prompt is then used with the Imagen 3 model (e.g., imagen-3.0-generate-001) via Vertex AI to generate the final image variation.
It’s interesting to contrast this with another solution we’ve previously featured from Kanshi Tanaike on ‘Iterative Image Generation with the Gemini API and Google Apps Script‘. While Tanaike’s method uses the Gemini API’s chat history to iteratively build an image from sequential text prompts, Stéphane’s focuses on reinterpreting a source image with specific modifications via a newly generated prompt.
You can check out Stéphane Giron’s source post for the complete code and setup instructions.
Last week at Google Cloud Next ’25 was packed with announcements, but one that particularly grabbed my attention was the unveiling of Google Workspace Flows. As Google Apps Script developers, many of us are familiar with automating simple tasks. However, the Flows demo hinted at a more accessible approach for tackling complex business processes.
Think about those workflows that go beyond basic if-this-then-that and into a world where you can easily configure Gemini to be your virtual assistant. Updating specific spreadsheet entries based on nuanced analysis, or finding and summarising information scattered across different files before replying to a customer. Traditional automation often hits a wall here because these tasks require context, reasoning, and sometimes even creative generation – capabilities standard automation tools lack.
Workspace Flows: AI Agents Joining the Workflow
What Google presented with Flows is a new solution for Google Workspace designed to automate these kinds of multi-step processes with AI providing assistance. Instead of just triggering actions, Flows uses AI models, including Gemini, as agents within the loop. This means the AI isn’t just kicking off a process; it’s actively participating – researching, analysing, creating, and reasoning to help get work done more efficiently and intelligently.
Having used tools like IFTTT it feels like a conceptual shift from simple automation to building intelligent, agentic workflows directly within the Workspace environment, without writing a single line of code.
Why Flows Looks Interesting for Developers: Current Capabilities and Future Vision
Beyond the core AI capabilities shown in the demo, Google outlined a vision for Flows that is particularly relevant for developers, indicating where the platform is heading:
No-Code/Low-Code Interface (Current): The initial preview allows configuring triggers (like new emails, form responses, etc.) and actions across core Workspace apps and integrating Gemini and Gems for AI-driven steps, removing the need to find alternative solutions (code you write or third party solutions).
Apps Script Extensibility (Future Vision): Google announced plans to allow developers to build their own custom triggers and actions using Apps Script. This creates the opportunity to integrate your own systems or add specific logic to get more out of Flows. The presentation briefly showed an example appsscript.json manifest snippet for declaring these elements around 13:08).
Workspace Connectors Platform (Future Vision): A dedicated platform for third-party integrations was also announced in the presentation as part of the roadmap. The plan is to enable connections to tools like Jira, Asana, Salesforce, HubSpot, etc., allowing them to be used as triggers or actions. The stated goal is to include the ability to build end-to-end workflows spanning beyond Google Workspace, with connectors built once potentially working in both Flows and Gemini Extensions.
Bring Your Own Models via Vertex AI (Future Vision): For advanced AI needs, Google shared the vision for integrating your own custom or fine-tuned models hosted on Google Cloud’s Vertex AI. The concept shown involved an ‘Ask an LLM’ step where you could select a ‘Custom Model’ directly within the flow builder, pointing towards future capabilities for incorporating highly specialized AI into Workspace automations.
Looking Ahead
Google Workspace Flows is definitely a platform I’ll be watching closely. The initial preview, focusing on AI agents-in-the-loop and core Workspace automation, is already compelling. But the announced roadmap for developer extensibility – adding Apps Script support, a robust connector platform, and the ability to call custom Vertex AI models – is what makes Flows truly exciting from a development perspective.
Flows is currently in alpha with its initial feature set. If this vision sounds as interesting to you as it did to me, you can sign up for the early access waitlist.
Getting started with generative AI in your Google Apps Script projects just got a whole lot easier! Google AI Studio has introduced a handy new feature allowing you to directly export your AI interactions as ready-to-use Apps Script code. If you’re new to Apps Script or integrating AI, this is a fantastic way to quickly add powerful features to your automations. Here’s how you can grab the code:
Click the Get code icon (</>) above the chat prompt.
In the ‘Get code’ window, click the language dropdown (this might initially show ‘Python’).
Select Apps Script from the dropdown list.
Click the Copy button to copy the generated Apps Script code to your clipboard.
If you are using AI Studio with your enterprise data, make sure you’re using a billable account so that your data is protected. This addition is perfect for rapid prototyping and understanding the basic API interaction. However, for applications needing more features essential for production environments, including robust error handling like exponential back-off, then you might want to look at my open source GeminiApp library.
Gemini API now generates images via Flash Experimental and Imagen 3. This report introduces image evolution within conversations using Gemini API with Google Apps Script.
The Gemini API recently gained the ability to generate images. Taking this a step further, Kanshi Tanaike has explored how to create evolving images within a conversation using Google Apps Script.
Often, you might want to generate an image and then iteratively add or modify elements in subsequent steps. Kanshi’s approach cleverly uses the chat functionality of the Gemini API (gemini-2.0-flash-exp model). By sending prompts sequentially within a chat, the API uses the conversation history, allowing each new image to build upon the previous one. This enables the generation of images that evolve step-by-step based on your prompts, as demonstrated in the original post with examples like drawing successive items on a whiteboard.
This technique is particularly useful because, as noted in the post, using chat history provides better results for this kind of sequential image generation compared to generating images from isolated prompts.
Kanshi Tanaike’s original post includes a detailed explanation, setup instructions (including API key usage and library installation ), and complete sample code snippets that you can adapt for your own Google Workspace projects.
I’ve created a small (pseudo) class that more easily clears and creates conditional formatting rules in a Google Sheet tab with Google Apps Script. Why? Well in Google Apps Script, conditional formatting rules are all or nothing. You can only ever set, get or clear ALL rules in a specified Google Sheet tab.
Conditional formatting in Google Sheets can be a powerful tool. However, Google Apps Script’s native setConditionalFormatRules() method replaces the entire set of rules, requiring the retrieval and reconstruction of the complete rule array to add, modify, or remove a single rule. This can be cumbersome and inefficient.
Fortunately Scott Donald has developed Range_ConditionalFormatting(), a valuable utility that simplifies conditional formatting management. This includes a SetRule method that allows you to add new rules without overwriting existing ones, and the position parameter provides precise control over rule order, which is crucial as conditional formatting rules are applied sequentially.
Scott’s post includes all the code you need to get this working in your own project along with a number of example snippets. This makes managing conditional formatting much more efficient and manageable.
Today I had the task of implementing a newsletter for internal updates and decided to use Google Apps Script since I was already using it for managing the project data. Based upon past experiences with emails using HTML I need this area was full of landmines and I didn’t want to navigate through it. 💣
So I decided to use MJML with Google Apps Script.
Sending emails using Google Apps Script is a common task, however, creating HTML emails that render consistently across different email clients and that look visually appealing can be challenging.
Justin Poehnelt’s post on DEV Community, “Using MJML in Google Apps Script to Send Beautiful Emails,” offers a solution to this problem. MJML is a markup language that makes it easy to create responsive HTML emails. It removes some of the complexities of HTML email development, allowing users to focus on the content of their emails.
In the post, Justin explains how to use MJML with Google Apps Script to send beautiful, responsive emails. He also mentions that he has published a library, MJMLApp, that “hides the gnarly bits” of using MJML with Google Apps Script. This library is available on GitHub in the mjml-apps-script repo where you can find the library ID and basic usage information.
As a Google Workspace Developer Advocate, I’m always exploring innovative ways to leverage technology. I’m thrilled to share my new Jupyter Notebook that showcases the power of Gemini and the Google Calendar API for productivity coaching. 🚀✨
This notebook dives into:
– Using Gemini’s multimodal capabilities to analyze calendar data. 📅
– Leveraging function calling to connect Gemini with Google Workspace APIs. 🔗
– Developing a personalized AI productivity coach. 🧑🏫
It’s amazing to see how generative AI can transform the way we work and optimize our time. ⏳
Explore the notebook on GitHub and discover how to build your own AI-powered productivity tools! 🛠️
Are you struggling to manage your time effectively? Mohammad Al-Ansari, Google Developer Advocate, has recently shared how the Gemini API can act as a personal productivity coach. The solution uses a Google Colab notebook, which is connected to the Google Calendar API. The Gemini API is used to provide personalized insights and recommendations to boost your productivity and improve your work/life balance. For those who don’t know, Google Colab is a free cloud-based platform for running Jupyter Notebooks, which are interactive coding environments that allow users to write and execute code and can be a useful tool to have in the toolbox when exploring data.
Some of the key features in Mohammad’s ‘Productivity Coach’ are:
Function Calling: This notebook uses Gemini’s ‘function calling’ capabilities, allowing it to dynamically interact with the Google Calendar API and retrieve real-time data. This ensures that the analysis and recommendations are always up-to-date and relevant to your current schedule.
Google Workspace Integration: By integrating with the Google Calendar API, this notebook shows how the Gemini API can be seamlessly integrated with other Google Workspace services. This opens up exciting possibilities for quickly experimenting with other Workspace data sources, such as Google Docs, Sheets or Drive.
Personalized Coaching: As a bonus you can see how Gemini can act as your personal productivity coach, so if nothing else you can get some tailored guidance and support about your own calendar
Imagine that you write in plain English what you want to do in Google Workspace (eg. workflows) and it happens just like magic. Insert text prompt, Gemini will generate the code for you and run it immediately. A dream? No, reality, thanks to my conceptual and practical idea of how to implement AI Agents in Google Apps Scripts to leverage the V8 runtime.
Ivan Kutil has explored the concept of AI Agents in Google Apps Script, enabling Google Workspace automation via plain English descriptions. Users describe their automation needs in natural language, which is then processed by Gemini API to generate the necessary code. The generated code is then executed in your Google Apps Script project.
Ivan’s solution uses the gemini-2.0-flash-thinking-exp-01-21 model, an experimental model within Vertex AI specifically designed to reveal its ‘thinking process’, resulting in more reliable code generation. The enhanced reasoning capabilities of this model are particularly beneficial for complex automation tasks, making it a powerful tool for Google Workspace customisation.
To ensure that the agent is doing the right thing, the clever bit is you can test the execution via a dry-run, where the code created with Gemini Flash Thinking is sent to an internal ‘Tester’ agent, which uses Gemini to comment on the code and summarises it in a log. It’s important to review the script before running it, as Ivan accepts no responsibility for the results of the script. Another nice feature is the generated code is stored in the Cache, so after running a dry-run and then a run, the same version will be executed within the Cache limit (currently set to 5 minutes).
This solution, which mirrors Gemini for Workspace’s ability to generate and execute basic Python code, suggests a future where Gemini for Workspace could write and execute Apps Script code for basic tasks. This has the potential to transform how users interact with and automate their Google Workspace environments.
If you are interested in a version of Ivan’s solution that incorporates my GeminiApp library, follow this link. For additional information on Ivan’s solution including setup instructions follow the source link.
If you have domain-specific knowledge that you want an LLM to leverage, you probably have a use case for fine-tuning. Fine-tuning can significantly improve how well the model understands and responds to your queries, whether it’s legal documents, medical texts, financial reports, or niche industry data.
The most crucial step in this process is structuring your data correctly. If your dataset is well-organized and formatted properly, the rest of the workflow becomes much more manageable. From there, it’s just a matter of setting up a few configurations and automating parts of the process with Apps Script. That’s where things get interesting and surprisingly efficient.
Archive Google Sheet Data with Google Sheets API Advanced Service in Google Apps Script
Keeping your Google Sheets organised can be a chore. A recent tutorial by Scott Donald shows you how to automatically archive old rows based on multi-column parameters using Google Apps Script and the Advanced Sheets API, making data management easier and more efficient. This post highlights Scott’s approach to scripting a solution, including how to set up the Sheets API, the main components of the script, and potential applications.
As always Scott packs in a lot of useful tips and guidance; in particular, the tutorial highlights how to archive data using just five API calls, potentially making it faster than the standard SpreadsheetApp approach. Scott also details how to modify the script to suit different processes and includes details on his SsReq class. It provides a structured way to perform common operations like retrieving data, finding rows based on criteria, copying rows, appending rows, and removing rows, making it a great addition to your personal Apps Script toolbox.
For detailed explanations, code examples, and helpful tips, consult the complete tutorial.
