v1.0.4 (April 13, 2024)
You can see the detail information here https://github.com/tanaikech/UtlApp
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.
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.
This Google Apps Script helps identify and analyze regions of colored cells in a Google Sheet.
Recently, I encountered a situation where I needed to identify colored cell regions in Google Sheets. For instance, consider the following spreadsheet:
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.
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.
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:
This script converts soft breaks to hard breaks in a Google Document using Google Apps Script.
Follow these steps:
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).
Copy and paste the following script into the script editor of your Google Document.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.