(G) LineChatBot + Google Sheets (as a memory)
For LineChatBot, this automated workflow seamlessly integrates with Google Sheets to store and retrieve chat history, enhancing user interactions by providing contextually relevant responses. It leverages AI to generate personalized replies based on past conversations, ensuring a friendly and helpful experience. The system efficiently manages conversation history, preventing data overflow while maintaining accessibility, ultimately improving user engagement and satisfaction.
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Workflow Overview
For LineChatBot, this automated workflow seamlessly integrates with Google Sheets to store and retrieve chat history, enhancing user interactions by providing contextually relevant responses. It leverages AI to generate personalized replies based on past conversations, ensuring a friendly and helpful experience. The system efficiently manages conversation history, preventing data overflow while maintaining accessibility, ultimately improving user engagement and satisfaction.
Target Audience
- Businesses: Companies looking to automate customer interactions via LINE messaging.
- Developers: Tech-savvy individuals who want to integrate AI chat functionalities with Google Sheets.
- Marketers: Professionals aiming to enhance customer engagement and retention through personalized responses.
- Educators: Teachers or trainers who wish to provide automated support to students via chat platforms.
Problem Solved
This workflow addresses the challenge of managing customer inquiries and interactions efficiently. It automates the response process, ensuring that users receive timely and relevant replies while maintaining a record of chat history in Google Sheets. This helps in:
- Reducing response time to customer queries.
- Keeping track of user interactions for better service.
- Leveraging AI to provide contextually relevant answers.
Workflow Steps
- Webhook Trigger: The workflow begins with a webhook that listens for incoming messages on LINE.
- Edit Fields: The incoming message is parsed to extract essential details like the message text and user ID.
- Get History: The user's chat history is retrieved from Google Sheets based on their user ID.
- Prepare Prompt: A prompt is constructed for the AI agent, incorporating the user's history and the latest message.
- AI Agent: The prompt is sent to the AI agent, which generates a response based on the context provided.
- Split History: The chat history is updated with the new exchange, ensuring it does not exceed character limits.
- Save History: The updated history is saved back to Google Sheets, maintaining a record of interactions.
- HTTP Request: The AI's response is sent back to LINE for the user to see.