Automate Exam Question Generation from Google Docs with AI & Qdrant
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This n8n workflow automates the crucial first step in generating exam questions: transforming your Google Docs content into a searchable, AI-ready knowledge base. It leverages OpenAI embeddings and Qdrant vector storage to semantically prepare your learning materials for intelligent question generation.
About This Workflow
Streamline your content preparation for educational assessments with this robust n8n workflow. Designed for educators, trainers, and content creators, this automation takes your raw Google Docs content, converts it into structured Markdown, and then processes it using OpenAI's advanced embeddings. The resulting semantic vectors are efficiently stored in a Qdrant vector database, creating a rich, retrievable knowledge base. This foundational setup is ideal for subsequent Retrieval Augmented Generation (RAG) processes, enabling a Large Language Model (LLM) to accurately generate diverse exam questions directly from your source material. Say goodbye to manual content parsing and hello to intelligent, automated question-making.
Key Features
- Google Docs Integration: Directly fetch and process content from your existing Google Docs.
- Automated Markdown Conversion: Flawlessly transform complex document structures into clean, standardized Markdown.
- Advanced AI Embeddings: Utilize OpenAI to generate high-quality vector embeddings for semantic understanding of your content.
- Scalable Vector Storage: Store and manage your vectorized knowledge base efficiently with Qdrant.
- RAG-Ready Foundation: Establish the perfect data pipeline for integrating LLMs to generate contextually relevant exam questions.
How To Use
- Set up Qdrant: Ensure your Qdrant instance is accessible. Update
QDRANT_URLandCOLLECTIONplaceholders in the "Create collection" and "Refresh collection" HTTP Request nodes, as well as the "Qdrant Vector Store" nodes. - Configure Google Docs: Provide your Google Docs OAuth2 credentials and update the
documentURLplaceholder in the "Get Doc" node with the URL of your source document. - Add OpenAI Credentials: Input your OpenAI API credentials into the "Embeddings OpenAI" node.
- Run Ingestion: Execute the workflow to ingest your Google Doc content, convert it to Markdown, generate embeddings, and store them in Qdrant.
- Connect for Generation: Once the knowledge base is populated, you can extend this workflow by connecting an LLM node (not included in this snippet) to the "Vector Store Retriever" to start generating exam questions based on queries against your vectorized content.
Apps Used
Workflow JSON
{
"id": "446168fc-79a4-4791-b214-f7f3e6248c53",
"name": "Automate Exam Question Generation from Google Docs with AI & Qdrant",
"nodes": 27,
"category": "Operations",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
Get This Workflow
ID: 446168fc-79a4...
About the Author
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