Automated Daily Student Motivation with RAG and Weaviate
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This n8n workflow automates daily student motivation by leveraging a Retrieval Augmented Generation (RAG) agent. It uses Weaviate as a vector store to retrieve relevant context and a chat model to generate personalized motivational messages.
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About This Workflow
Overview
This n8n workflow is designed to automate the delivery of daily motivational messages to students. It employs a RAG (Retrieval Augmented Generation) agent that integrates with Weaviate, a vector database, to provide contextually relevant information. The workflow starts with a Webhook Trigger, which can be used to initiate the process. The incoming data is then processed using a Text Splitter and Embeddings (OpenAI) to prepare it for storage in Weaviate. The Weaviate Insert node stores these embeddings, allowing for efficient retrieval later. A Weaviate Query node retrieves relevant information based on a query, which is then used by the Vector Tool. This tool, along with Window Memory and a Chat Model (OpenAI), powers the RAG Agent. The RAG Agent processes the retrieved context and user input to generate a motivational message. Finally, the output is logged to a Google Sheet using the Append Sheet node, and a Slack Alert is configured for error handling. This workflow automates the generation and logging of motivational content, saving time and ensuring consistent engagement.
Key Features
- Automated Message Generation: Creates daily motivational messages for students.
- RAG Implementation: Utilizes Retrieval Augmented Generation for context-aware responses.
- Vector Database Integration: Uses Weaviate to store and retrieve embeddings for efficient context retrieval.
- Scalable Processing: Employs Text Splitter for efficient data handling.
- Comprehensive Logging: Records generated messages to a Google Sheet for tracking.
- Error Alerting: Sends Slack notifications in case of workflow failures.
How To Use
- Set up Webhook: Configure a webhook to trigger the workflow. This could be a scheduled trigger or an external event.
- Configure Credentials: Ensure your OpenAI API and Weaviate API credentials are set up in n8n.
- Populate Weaviate: The initial run will require data to be split, embedded, and inserted into Weaviate. You might need a separate process to initially load your motivational content into the vector store or configure the workflow to ingest new data periodically.
- Define Google Sheet: Specify the ID of your Google Sheet and the name of the log sheet (e.g., 'Log').
- Set up Slack Alert: Configure your Slack API credentials and the channel for error alerts.
- Trigger the Workflow: Initiate the workflow via the configured webhook.
Apps Used
Workflow JSON
{
"id": "92017095-96b9-49dd-b05e-822053736797",
"name": "Automated Daily Student Motivation with RAG and Weaviate",
"nodes": 0,
"category": "Education Automation",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
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ID: 92017095-96b9...
About the Author
DevOps_Master_X
Infrastructure Expert
Specializing in CI/CD pipelines, Docker, and Kubernetes automations.
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