Google Sheets Formula Generator

Generate Google Sheets formulas instantly from natural language requests. This AI-powered workflow helps users create accurate spreadsheet formulas by simply describing their needs in plain English, streamlining spreadsheet work for improved productivity.

Flows

How the AI Flow works

User Initiates Chat.: The flow is triggered when a user opens the chat interface.
Welcome Message Displayed.: A welcome message is shown to guide the user to describe the Google Sheets formula they need.
User Enters Request.: The user submits a request describing the desired Google Sheets formula in plain language.
AI Generates Formula.: The request and chat context are used to create an AI prompt, and the AI model generates the appropriate Google Sheets formula.
Formula Delivered to User.: The generated formula is displayed back to the user in the chat.

Prompts used in this flow

Below is a complete list of all prompts used in this flow to achieve its functionality. Prompts are the instructions given to the AI model to generate responses or perform actions. They guide the AI in understanding user intent and generating relevant outputs.

Prompt

Create a prompt template with dynamic variables ({input}, {human_input}, {context}, {chat_history}, {system_message}).

                Generate Google Sheets formula based on {input}. Use {chat_history} to get more information.

Components used in this flow

Below is a complete list of all components used in this flow to achieve its functionality. Components are the building blocks of every AI Flow. They allow you to create complex interactions and automate tasks by connecting various functionalities. Each component serves a specific purpose, such as handling user input, processing data, or integrating with external services.

Chat Opened Trigger

The Chat Opened Trigger component detects when a chat session starts, enabling workflows to respond instantly as soon as a user opens the chat. It initiates flows with the initial chat message, making it essential for building responsive, interactive chatbots.

See Chat Opened Trigger

ChatInput

The Chat Input component in FlowHunt initiates user interactions by capturing messages from the Playground. It serves as the starting point for flows, enabling the workflow to process both text and file-based inputs.

See ChatInput

Message Widget

The Message Widget component displays custom messages within your workflow. Ideal for welcoming users, providing instructions, or showing any important information, it supports Markdown formatting and can be set to appear only once per session.

See Message Widget

Chat History Component

The Chat History component in FlowHunt enables chatbots to remember previous messages, ensuring coherent conversations and improved customer experience while optimizing memory and token usage.

See Chat History Component

Prompt Component in FlowHunt

Learn how FlowHunt's Prompt component lets you define your AI bot’s role and behavior, ensuring relevant, personalized responses. Customize prompts and templates for effective, context-aware chatbot flows.

See Prompt Component in FlowHunt

Generator

Explore the Generator component in FlowHunt—powerful AI-driven text generation using your chosen LLM model. Effortlessly create dynamic chatbot responses by combining prompts, optional system instructions, and even images as input, making it a core tool for building intelligent, conversational workflows.

See Generator

Chat Output

Discover the Chat Output component in FlowHunt—finalize chatbot responses with flexible, multi-part outputs. Essential for seamless flow completion and creating advanced, interactive AI chatbots.

See Chat Output

Flow description

Purpose and benefits

Overview

This workflow, titled Google Sheets Formula Generator, automates the process of generating custom Google Sheets formulas based on user requests. By leveraging chat-based user interaction and a language model, it enables users to describe their spreadsheet needs in plain language and instantly receive the appropriate formula. This flow is especially useful for scaling support, onboarding, or automating formula generation tasks for teams, businesses, or educational platforms.

Workflow Steps

Here’s a step-by-step breakdown of how the workflow operates:

User Initiation and Welcome Message
- When a user opens the chat, a Chat Opened Trigger node activates.
- This trigger sends a message to a Message Widget, which displays a welcoming introduction and instructions:
  “Welcome to the Google Sheets Formula Generator! I’m here to help you create the perfect Google Sheets formula based on your request. Just describe what you need, and I’ll generate the formula to solve your problem.”
Capturing User Input
- The user enters their request or question through a Chat Input node, typically asking for help with a Google Sheets formula (e.g., “How do I sum only visible rows?” or “How do I count unique values in column A?”).
Maintaining Chat History
- The Chat History node keeps track of previous interactions, which helps the system maintain context and provide more accurate or context-aware responses.
Prompt Generation
- The Prompt Template node combines several dynamic variables:
  - {input}: the current user request,
  - {chat_history}: previous chat messages,
  - and other possible context.
- The prompt is framed as:
  “Generate Google Sheets formula based on {input}. Use {chat_history} to get more information.”
- This ensures that the AI model receives both the current question and relevant context from the conversation.
Formula Generation via LLM
- The Generator node takes the prompt and feeds it to a large language model (LLM), which generates a text output—specifically, the requested Google Sheets formula and possibly an explanation.
Delivering the Response
- The generated formula and explanation are sent to a Chat Output node, which displays the answer back to the user in the chat interface.

Data Flow Diagram

Step	Node Type	Purpose
1	Chat Opened Trigger	Initiate chat session
2	Message Widget	Display welcome/instruction message
3	Chat Input	Collect user’s formula request
4	Chat History	Store and provide chat context
5	Prompt Template	Build prompt for the LLM with user input and context
6	Generator	Produce formula using AI model
7	Chat Output	Present the generated formula to the user

Key Features and Benefits

User-Friendly: Users interact in natural language—no coding or formula knowledge required.
Context-Aware: Maintains chat history, enabling follow-up questions and clarifications.
Automated & Scalable: Eliminates manual formula writing, saving time for support agents, trainers, or power users.
Instant Results: Reduces wait times by providing immediate, AI-generated formulas.

Example Use Cases

Internal IT or Support Teams: Quickly answer formula questions for employees.
Educational Platforms: Help students learn Google Sheets formulas interactively.
Business Automation: Enable non-technical staff to build spreadsheet solutions without expert intervention.

Summary

By automating the generation of Google Sheets formulas from simple user descriptions, this workflow streamlines support and training, enhances user experience, and saves significant time and effort across organizations. Its modular, chat-based design makes it a powerful tool for scaling formula support and knowledge sharing.

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