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(G) LineChatBot + Google Sheets (as a memory)

This workflow implements the storage and management of user conversation history by building an intelligent chatbot based on the Line platform, ensuring continuity and contextual relevance in conversations. Utilizing Google Sheets as a lightweight database, the chatbot can automatically archive chat records and generate polite and friendly responses through advanced AI models, suitable for customer support and intelligent Q&A in the Thai language environment. This system effectively addresses the shortcomings of traditional chatbots in memory and data management, enhancing the user interaction experience.

Workflow Diagram
(G) LineChatBot + Google Sheets (as a memory) Workflow diagram

Workflow Name

(G) LineChatBot + Google Sheets (as a memory)

Key Features and Highlights

This workflow builds an intelligent chatbot named “ลลิตา” based on the official Line account, utilizing Google Sheets to store and manage users’ chat history, thereby providing contextual memory support for AI conversations. It integrates the Google Gemini language model and LangChain AI Agent, enabling the bot to understand and respond politely and friendly in Thai. Additionally, it features automatic segmentation and archiving of chat history to ensure efficient storage and retrieval of historical data.

Core Problems Addressed

  • Traditional chatbots struggle to remember users’ past conversations, resulting in a lack of continuity and contextual relevance.
  • Limited storage capacity for long-term chat data often leads to loss or overwriting of historical information.
  • Ensuring flexible switching of response languages and timezone settings in multilingual environments.
  • Automated management of chat records to prevent user information confusion and enhance interaction experience.

Application Scenarios

  • Enterprises or individuals building intelligent customer service or assistant bots on Line official accounts to enhance user engagement.
  • Chatbots requiring personalized, context-aware services based on historical conversation data.
  • Customer support, consultation, and intelligent Q&A services in Thai language environments.
  • Users who want to leverage Google Sheets as a lightweight database for managing chat records.

Main Workflow Steps

  1. Webhook Listener: Receive user messages from the Line platform via POST requests.
  2. Field Extraction: Extract and organize key information such as message text, reply tokens, and user IDs.
  3. Retrieve History: Query and return historical conversation data from Google Sheets based on user ID.
  4. Prompt Preparation: Integrate historical records with the latest user input to form a complete contextual prompt.
  5. AI Response Generation: Use the LangChain AI Agent to invoke the Google Gemini model for reply generation, supporting Thai language and local timezone settings.
  6. History Segmentation: Monitor character length thresholds of accumulated chat history and segment/archive to prevent cell capacity overflow.
  7. Save History: Update Google Sheets with the latest conversation and archival information to ensure continuous data accumulation.
  8. Send Reply: Call the Line Messaging API via HTTP request to deliver the AI-generated response back to the user.

Involved Systems and Services

  • Line Messaging API: For receiving and replying to messages.
  • Google Sheets: Serves as persistent storage and management platform for chat history.
  • Google Gemini Chat Model: Provides powerful natural language understanding and generation capabilities.
  • LangChain AI Agent: Handles context prompt processing and language model invocation.
  • n8n Automation Platform: Builds and orchestrates the entire automated workflow.

Target Users and Value

  • Developers and enterprises aiming to create intelligent chatbots on the Line platform with memory and contextual understanding capabilities.
  • Product managers and automation operators seeking no-code/low-code solutions for chat data management and AI conversation generation.
  • Companies and brands providing Thai-language intelligent customer service or virtual assistant solutions.
  • SMEs and individual developers who want to easily manage chat history using Google Sheets to reduce database maintenance costs.

By combining advanced AI conversational models with flexible Google Sheets data management, this workflow delivers an intelligent Line chatbot with persistent memory of user history, significantly enhancing the naturalness and personalization of user interactions.