Specifying Output Types for Gemini API with Google Apps Script

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Specifying Output Types for Gemini API with Google Apps Script

Abstract

The Gemini API generates different outputs depending on the prompts. This report explains how to use function calling in the new Gemini 1.5 API to control the output format (string, number, etc.) within a script during a chat session. This allows for more flexibility in using the Gemini API’s results.

Introduction

The appearance of Gemini has already brought a wave of innovation to various fields. When the Gemini API returns a response, the format of the response is highly dependent on the input text provided as a prompt. For instance, to retrieve the output value as a JSON object, you need to explicitly include a prompt like “Return JSON” within your input. However, there can be situations where the API doesn’t return the data in the desired format.

Identifying Colored Cell Regions in Google Sheets with Google Apps Script

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Identifying Colored Cell Regions in Google Sheets with Google Apps Script

Overview

This Google Apps Script helps identify and analyze regions of colored cells in a Google Sheet.

Description

Recently, I encountered a situation where I needed to identify colored cell regions in Google Sheets. For instance, consider the following spreadsheet:

Identifying Colored Cell Regions in Google Sheets with Google Apps Script

The region enclosed by the red cells (B2:D4) is a rectangle. In this case, the closed region can be easily identified using a simple script in Google Sheets. However, the region enclosed by the blue cells (H3, I2, J2,,,) is more complex. It consists of multiple disconnected cells that form a single shape. Identifying such irregular shapes using a script can be challenging.

Parsing Invoices using Gemini 1.5 API with Google Apps Script

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Parsing Invoices using Gemini 1.5 API with Google Apps Script

Abstract

This report explores using Gemini, a new AI model, to parse invoices in Gmail attachments. Traditional text searching proved unreliable due to invoice format variations. Gemini’s capabilities can potentially overcome this inconsistency and improve invoice data extraction.

Introduction

After Gemini, a large language model from Google AI, has been released, it has the potential to be used for modifying various situations, including information extraction from documents. In my specific case, I work with invoices in PDF format. Until now, I relied on the direct search by a Google Apps Script to achieve this task. The script’s process involved:

Convert Soft Breaks to Hard Breaks on Google Documents using Google Apps Script

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Description

This script converts soft breaks to hard breaks in a Google Document using Google Apps Script.

Usage

Follow these steps:

1. Create a New Google Document

Create a new Google Document and open it. Go to “View” -> “Show non-printing characters” in the top menu to see line breaks in the document body (as shown in the image below).

2. Sample Script

Copy and paste the following script into the script editor of your Google Document.

Technique for Appending Values to Specific Columns on Google Spreadsheet using Google Apps Script

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Technique for Appending Values to Specific Columns on Google Spreadsheet using Google Apps Script

Abstract

This report addresses the challenge of appending values to specific columns in Google Sheets when columns have uneven last rows. It offers a Google Apps Script solution with a sample script and demonstration image, enabling efficient and flexible data manipulation.

Introduction

Google Apps Script is a versatile tool that allows for seamless management of various Google Workspace applications, including Docs, Sheets, Slides, Forms, and APIs. Its ability to automate tasks within Google Sheets is particularly powerful.

Analyzing Trends of Google Apps Script from Questions on Stackoverflow using Gemini 1.5 API

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Analyzing Trends of Google Apps Script from Questions on Stackoverflow using Gemini 1.5 API

Abstract

A new large language model (LLM) called Gemini with an API is now available, allowing developers to analyze vast amounts of data. This report explores trends in Google Apps Script by using the Gemini 1.5 API to analyze questions on Stack Overflow.

Introduction

The release of the LLM model Gemini as an API on Vertex AI and Google AI Studio has opened a world of possibilities. Ref The Gemini API significantly expands the potential of various scripting languages, paving the way for diverse applications. Additionally, Gemini 1.5 has recently been released in AI Studio. Ref We can expect the Gemini 1.5 API to follow suit soon.

Generating Texts using Files Uploaded by Gemini 1.5 API

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Generating Texts using Files Uploaded by Gemini 1.5 API

Abstract

The Gemini API allows the generating of text from uploaded files using Google Apps Script. It expands the potential of various scripting languages for diverse applications.

Introduction

With the release of the LLM model Gemini as an API on Vertex AI and Google AI Studio, a world of possibilities has opened up. Ref The Gemini API significantly expands the potential of various scripting languages and paves the way for diverse applications. Also, recently, Gemini 1.5 in AI Studio has been released. Ref In the near future, Gemini 1.5 API will be also released soon.

Crafting Bespoke Output Formats with Gemini API

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Crafting Bespoke Output Formats with Gemini API

Abstract

The Gemini API unlocks potential for diverse applications but requires consistent output formatting. This report proposes a method using question phrasing and API calls to craft a bespoke output, enabling seamless integration with user applications. Examples include data categorization and obtaining multiple response options.

Introduction

With the release of the LLM model Gemini as an API on Vertex AI and Google AI Studio, a world of possibilities has opened up. Ref The Gemini API significantly expands the potential of various scripting languages and paves the way for diverse applications. However, leveraging the Gemini API smoothly requires consistent output formatting, which can be tricky due to its dependence on the specific question asked.

Attempting Reverse Engineering with Gemini API and Google Apps Script

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Abstract

Gemini API on Vertex AI/Studio unlocks new applications with data retrieval and content generation through function calls. This report explores using the API for reverse engineering with a sample interpreter in Google Apps Script.

Introduction

The recent release of the LLM model Gemini as an API on Vertex AI and Google AI Studio unlocks a vast potential for new applications and methodologies. It significantly expands capabilities across diverse situations, paving the way for groundbreaking applications. Notably, the Gemini API allows data retrieval and content generation through function calls. In my recent report, “Guide to Function Calling with Gemini and Google Apps Script”, I explore function calls as a launchpad for various applications. This report showcases reverse engineering using the Gemini API, with a sample interpreter for creating sample values from a given regex using Google Apps Script.

Google OAuth Verification & Application Privacy Policy

Registered Application Name: Workspace & Gemini AI Orchestration Engine

Application Purpose & Core Functionality:

This web page serves as the official homepage and privacy compliance interface for the application "Workspace & Gemini AI Orchestration Engine". This specialized developer utility is designed to research, benchmark, and optimize advanced integrations between Google Workspace services, the Google Apps Script API, and Gemini AI models (via Google Vertex AI / Gemini API endpoints).

The application facilitates automated multi-agent scaffolding, programmatic script deployment, project resource management, and structural analysis of Google Apps Script projects. It allows developers and autonomous AI agents (operating via Model Context Protocol / MCP) to securely evaluate execution performance, implement high-performance batch requests, and test agent-to-agent (A2A) workflows within a controlled and structured environment.

Google User Data Policy Compliance Statements:

1. Data Access & Specific Usage

Our application explicitly requests access to specific Google user accounts through OAuth scopes required strictly for interacting with the Google Apps Script API and Google Workspace endpoints. This access is utilized solely to execute user-initiated or agent-orchestrated programmatic operations—such as creating, modifying, deploying, or benchmarking script projects and executing automated workflows. No background automated extraction occurs without explicit session initiation.

2. Data Storage & Zero-Retention Policy

Adhering to a strict Zero-Retention Model, this application does not store, log, or persist any personal data, OAuth tokens, script source codes, or Google account configurations on any external server, database, or persistent storage medium. All data processing and API responses are handled entirely in-memory or securely on the client side within the active session context, ensuring complete cryptographic transient isolation.

3. Data Sharing & Third-Party Non-Disclosure

We maintain absolute data privacy. No data accessed via Google OAuth scopes is shared, sold, rented, or transferred to third-party entities, advertising networks, or data brokers. All data transmissions are strictly point-to-point, encrypted in transit using industry-standard protocols, and limited entirely to the direct channel between the execution environment and Google's official API gateways.

For inquiries regarding this developer application, technical benchmarks, or verification compliance, please refer to the official documentation and repositories linked on this homepage (tanaikech.github.io).