AppsScriptPulse

Official News, Solutions, AppSheet, No Code

AppSheet Gains Gemini Smarts: Native AI Tasks Simplify Automation (No Apps Script Needed!)

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Image credit: Google

We’re thrilled to announce that Gemini in AppSheet Solutions is now available in Public Preview for Enterprise users! As announced during the AppSheet breakout session at Google Cloud Next 2025 just a few weeks ago, this powerful new capability allows AppSheet Enterprise Plus users to integrate Google’s Gemini models directly into their automation workflows.

Google recently announced some exciting developments for AppSheet, with the news that creators can now directly integrate Gemini AI capabilities into your AppSheet apps. While developers have previously found ways to connect AppSheet to Gemini including using Google Apps Script (like the invoice processing example using the GeminiApp library previously discussed on Pulse), this new update promises to make AI-powered automation accessible to everyone, no coding required.

What This Means for AppSheet Creators

This move significantly lowers the barrier for integrating AI into AppSheet workflows. Instead of setting up API keys, writing Apps Script functions, and managing libraries like GeminiApp to call the Gemini API for tasks like data extraction, creators can now use a native AI Task step within AppSheet automations.

As highlighted in Google’s announcement, this new approach offers several advantages:

  • Simplified AI Integration: The native AI Task aims to handle jobs like extracting specific data from uploaded photos or PDFs and categorising text – directly within AppSheet. This replaces the need for external scripts for many common AI tasks.
  • Build with Confidence: The GA AI Task Step Testing feature allows creators to test and refine AI prompts and configurations directly in the editor using sample data before deployment, a crucial step for reliable AI.
  • No-Code Accessibility: By embedding Gemini capabilities directly, AppSheet makes powerful AI accessible to creators who may not have coding expertise.
  • Controlled Deployment & Oversight: Admins still control feature access, and workflows can still incorporate human review steps alongside the AI Task.

Potential Use Cases

Google suggests the AI task can be used for:

  • Information Extraction: Getting details from images (serial numbers, meter readings) or documents (PO numbers, tracking info, report details).
  • Record Categorisation: Classifying expenses, maintenance requests, or customer feedback automatically.

These are similar goals to what was achievable via Apps Script previously, but now potentially much simpler to implement directly in AppSheet.

A Big Step for No-Code AI

This native integration represents a significant simplification compared to earlier methods requiring Apps Script. By embedding Gemini directly into AppSheet automations, Google is making advanced AI capabilities much more accessible for business users of all levels.

For full details and setup instructions, refer to the official Google announcement and linked resources.

Source: Gemini in AppSheet now in Public Preview for Enterprise users! (And AI task testing is GA!)

Solutions, Drive, Beginner

Streamlining Google Workspace Development: Editing JSON files in Google Drive with Apps Script (and a little help from AI)

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Storing JSON files in Google Drive offers a practical approach for Google Workspace developers, especially when combined with Google Apps Script. While Drive lacks a built-in JSON editor, AI tools like Gemini can rapidly prototype solutions, such as web-based editors. However, creating a robust application requires more than just a quick fix. It involves understanding syntax highlighting, managing dependencies, and navigating the constraints of the Apps Script platform, highlighting the importance of both rapid prototyping and robust engineering skills.

I recently explored how to effectively manage JSON configuration files within Google Drive using Google Apps Script, and the journey from quick AI-assisted prototypes to robust solutions.

As part of this I delve into the benefits of storing JSON in Drive, the challenges of editing, and how AI tools like Gemini can provide a great starting point. However, as I discovered, building a truly polished tool requires deeper technical knowledge and problem-solving.

Check out the article for insights on navigating the development process and, if you want one, an Apps Script powered JSON Editor for Google Drive.

Source: Streamlining Google Workspace Development: Editing JSON files in Google Drive with Apps Script (and a little help from AI)

Solutions, AI, Beginner

Programmatically Iterating on Images with Imagen 3, Vertex AI, and Apps Script

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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.

Source: Similar Image Generation with Imagen 3 on Vertex AI with Google Apps Script

Comment, AI

Google Workspace Flows: A Developer’s First Look After Cloud Next ’25

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Image credit: Google

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.

Image credit: Google

If you would like to see Flows in action I highly recommend you check out the Google Cloud Next session ‘New ways to automate your work and integrate with Google Workspace’.

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.

AI, Beginner

New Feature: Get Apps Script Code Directly from Google AI Studio

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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:

  1. Click the Get code icon (</>) above the chat prompt.
  2. In the ‘Get code’ window, click the language dropdown (this might initially show ‘Python’).
  3. Select Apps Script from the dropdown list.
  4. 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.

Solutions, AI, Intermediate

Iterative Image Generation with the Gemini API and Google Apps Script

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Image credit: Kanshi Tanaike

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.

Source: Generate Growing Images using Gemini API

Solutions, Sheets, Intermediate

Streamlining Conditional Formatting in Google Sheets with Apps Script

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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.

Source: Clear and Set Conditional Formatting Rules to a Specific Range in Google Sheets with Apps Script – Yagisanatode

Library, Solutions, Gmail, Intermediate

Create Responsive Emails Easily with Google Apps Script and MJML

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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.

Source: Using MJML in Google Apps Script to Send Beautiful Emails

Solutions, AI, Calendar, Advanced

Unlock Your Productivity Potential with Gemini and Google Calendar (and other Workspace APIs)

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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! 🛠️

👉 Link: https://lnkd.in/gpTxMMAy

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

Check out the notebook to explore!

Source: generative-ai/gemini/use-cases/productivity/productivity_coaching_with_google_calendar.ipynb at main · GoogleCloudPlatform/generative-ai

Solutions, AI, Intermediate

‘AI Agents’ in Google Apps Script: Automate Google Workspace with Natural Language

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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.

Source: Create AI agents in Google Apps Script with Vertex AI and Gemini