GAS Library - GeminiWithFiles

Overview

This is a Google Apps Script library for Gemini API with files.

A new Google Apps Script library called GeminiWithFiles simplifies using Gemini, a large language model, to process unstructured data like images and PDFs. GeminiWithFiles can upload files, generate content, and create descriptions from multiple images at once. This significantly reduces workload and expands possibilities for using Gemini.

Description

Recently, Gemini, a large language model from Google AI, has brought new possibilities to various tasks by enabling the use of unstructured data as structured data. This is particularly significant because a vast amount of information exists in unstructured formats like text documents, images, and videos.

Batch Processing Powerhouse: Leverage Gemini 1.5 API and Google Apps Script for Efficient Content Workflows

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Batch Processing Powerhouse: Leverage Gemini 1.5 API and Google Apps Script for Efficient Content Workflows

Abstract

A new Google Apps Script library, “GeminiWithFiles”, simplifies using the powerful Gemini 1.5 AI model. It lets users directly upload files for content generation or create descriptions for many images at once, making it much faster than prior methods. This is helpful for tasks involving large amounts of text or images.

Introduction

Recently, Gemini, a family of Google’s most capable AI models, has revolutionized various tasks by allowing unstructured data to be used as structured data. This breakthrough is particularly impactful for tasks involving large amounts of text or images.

Consolidate Scattered A1Notations into Continuous Ranges on Google Spreadsheet using Google Apps Script

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Consolidate Scattered A1Notations into Continuous Ranges on Google Spreadsheet using Google Apps Script

Abstract

Consolidate scattered cell references (A1Notation) in Google Sheets for efficiency. This script helps select cells by background color or update values/formats, overcoming limitations of large range lists.

Introduction

When working with Google Spreadsheets, there might be a scenario where you need to process scattered A1Notations (cell addresses in the format “A1”). This could involve selecting cells with specific background colors, updating cell values, or modifying cell formats.

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.

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).