Google Sheets Q&A Chatbot

An intelligent chatbot assistant that answers user questions strictly using data from a provided Google Sheets file. Perfect for analysts, operations, auditors, and educators needing precise, document-grounded insights without external data or guesswork.

Flows

How the AI Flow works

User Provides Question and Google Sheet.: User submits their question and attaches a Google Sheets document.
Retrieve Google Sheet Data.: The workflow fetches the content of the provided Google Sheet for analysis.
Maintain Chat History.: Chat history is managed to support context-aware interactions.
AI Agent Answers Based on Sheet.: An AI agent analyzes the sheet content and formulates answers strictly based on the data inside the Google Sheet.
Display Answer to User.: The assistant presents the answer to the user in a chat interface.

Prompts used in this flow

Welcome Message

Displays a welcome message to the user explaining the assistant's purpose and instructions for document upload.

👋 Welcome to the Google Docs-Based AI Assistant!
I'm here to help you find accurate answers strictly based on the document you provide 📄. I’ll extract only the most relevant information—no assumptions, no outside sources—just clear, document-grounded responses.

Please upload your document or paste the text you'd like me to work with, and I’ll get started! 🔍📚

Tool Calling Agent System Instructions

Provides the language model with strict instructions to only answer questions using the provided Google Sheet, without external knowledge, and to handle missing...

You are an AI assistant specialized in answering questions based *strictly* on a provided document. Your primary goal is to extract relevant information from the text given to you and formulate an accurate answer.

**Instructions:**

1. **Source Restriction:** Base your answer *solely* on the content of the Google sheets provided in the google sheet retriever tool. Do *not* access or incorporate any external websites, prior knowledge, or information not present in the text.
2. **Accuracy:** Ensure your answer directly reflects the information stated in the document. Avoid making assumptions or interpretations beyond what is written.
3. **Completeness:** If the document contains the answer, provide it as completely as possible based on the text.
4. **Handling Missing Information:** If the answer to the user's question cannot be found within the provided document text, explicitly state "Based on the provided document, I could not find the answer to your question." or a similar phrase. Do not attempt to guess or synthesize an answer.
5. **Quoting (Optional but Recommended):** When possible, briefly quote the relevant sentence(s) from the document that support your answer.

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.

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

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

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

Tool Calling Agent

Explore the Tool Calling Agent in FlowHunt—an advanced workflow component that enables AI agents to intelligently select and use external tools to answer complex queries. Perfect for building smart AI solutions that require dynamic tool usage, iterative reasoning, and integration with multiple resources.

See Tool Calling Agent

Google Sheets Retriever

Integrate your Google Sheets with FlowHunt workflows using the Google Sheets Retriever component. Effortlessly fetch and utilize spreadsheet data as part of your automation, enabling dynamic data-driven processes and advanced workflow logic.

See Google Sheets Retriever

Flow description

Purpose and benefits

This workflow creates an intelligent Q&A assistant that can answer user questions strictly based on the data found in a provided Google Sheets file. It is especially useful for data analysts, operations teams, project managers, auditors, and educators who need quick, accurate, and source-grounded answers from spreadsheet data—without relying on external information or manual searching.

How It Works

1. User Interaction

Welcome Message: When a user enters the Playground, they are greeted by a message explaining the assistant’s capabilities and inviting them to upload a Google Sheets document or paste the text they want to query.
Chat Inputs: Users can input their questions and attach the relevant Google Sheets file directly into the chat interface.

2. Data Retrieval

Google Sheets Retriever: Upon receiving a file, the workflow uses a Google Sheets Retriever tool to access and extract the sheet’s content. This tool converts the spreadsheet into a format suitable for question answering.

3. Contextual Memory

Chat History: The system maintains an in-memory history of the conversation, enabling context-aware follow-up questions and more natural interactions.

4. Intelligent Answer Generation

Specialized AI Agent: An AI agent is configured with strict instructions to only use the content from the uploaded Google Sheet:
- No External Knowledge: The agent is barred from using any information outside the provided document.
- Accurate Extraction: Answers are generated solely from the spreadsheet content, quoting directly from it when possible.
- Handling Missing Data: If the answer is not present in the sheet, the agent will explicitly state that it cannot find the answer—never guessing or fabricating information.

5. Response Delivery

Chat Output: The assistant’s answers are displayed back to the user in the chat interface, maintaining a clear and conversational format.

Workflow Structure (Simplified Table)

Step	Component	Purpose
User Input	Chat Input	Collects user questions and file uploads
Welcome Message	Message Widget	Greets user and explains assistant’s function
Data Fetching	Google Sheets Retriever	Extracts data from the uploaded Google Sheets document
Memory Management	Chat History	Stores conversation history for context
Q&A Processing	Tool Calling Agent (AI)	Processes questions, uses only sheet data to answer
Response Output	Chat Output	Presents answers and messages to the user

Why This Workflow Is Useful

Scalable Q&A: It automates the extraction of information from spreadsheets, allowing many users to query complex data without specialized knowledge.
Source-grounded: By restricting answers to the uploaded document, it avoids hallucinations or irrelevant information, critical for auditing, compliance, or data-sensitive scenarios.
Efficient & Accurate: Reduces manual searching and enables quick turnaround for operational, analytical, and educational queries.
Natural Interaction: The conversational interface and memory make it easy for users to ask follow-up questions or refine their queries.

Example Use Cases

Data Analysts: Instantly ask questions about large datasets without manual filtering.
Project Managers: Check project milestones, deadlines, or budget data directly from reports.
Auditors & Compliance: Verify entries or spot inconsistencies based solely on official sheets.
Educators: Let students or staff interact with data sheets in a controlled, source-limited way.

Overall, this workflow provides a robust, user-friendly, and secure way to interact with Google Sheets data via natural language, ensuring answers are always based on the facts contained in the uploaded document. This makes it highly valuable for organizations aiming to scale and automate spreadsheet-based knowledge work.

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