Automate Course Outline to Vector Database with Google Drive and Pinecone
detail.loadingPreview
This workflow automatically ingests course module outlines from Google Drive, processes them into digestible chunks, and stores them as embeddings in a Pinecone vector database. It's perfect for building knowledge bases for AI-powered educational tools.
About This Workflow
The "Bundle RAG Upload" workflow is designed to seamlessly integrate your course module outlines into a powerful vector database. It begins by monitoring a specified Google Drive folder for new or updated documents. Once detected, it retrieves the files, splits them into manageable text segments, and generates embeddings using OpenAI. These embeddings are then efficiently uploaded to a Pinecone vector store, specifically within the 'Course Outlines' namespace. This automation is a crucial step in building robust Retrieval Augmented Generation (RAG) systems for educational content, enabling sophisticated question-answering and content retrieval capabilities.
Key Features
- Automated Google Drive Monitoring: Triggers automatically when new files are created in a designated Google Drive folder.
- Intelligent Document Processing: Downloads files and utilizes a recursive character text splitter to handle varied content lengths.
- Powerful Embeddings Generation: Leverages OpenAI for high-quality text embeddings.
- Scalable Vector Storage: Integrates with Pinecone for efficient and scalable vector storage and retrieval.
- Configurable Chunking: Allows customization of text chunk size and overlap for optimal embedding quality.
How To Use
- Configure Google Drive Trigger: Set up the 'Google Drive Trigger' node to watch your 'Course Module Outline Folder for n8n'. Ensure it's set to trigger on 'fileCreated'.
- Retrieve Files: Connect the 'Google Drive Trigger' to the 'Google Drive' node to list files in the specified folder. Then, link this to the 'Get Docs' node to download the content of each file.
- Process Documents: Use the 'Loop Over Items' node to process multiple files. Connect the output to the 'Default Data Loader' to prepare the data and then to the 'Recursive Character Text Splitter' to break down content into chunks (adjust
chunkSizeandchunkOverlapas needed). - Generate Embeddings: Connect the output of the text splitter to the 'Embeddings OpenAI' node to create vector representations of your text chunks.
- Store in Pinecone: Link the embeddings and the processed documents to the 'Pinecone Vector Store' node. Ensure your Pinecone index and namespace ('Course Outlines') are correctly configured. Set the mode to 'insert'.
Apps Used
Workflow JSON
{
"id": "c9da4e17-d4d5-4a68-ad98-6e06aac521dd",
"name": "Automate Course Outline to Vector Database with Google Drive and Pinecone",
"nodes": 21,
"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: c9da4e17-d4d5...
About the Author
Crypto_Watcher
Web3 Developer
Automated trading bots and blockchain monitoring workflows.
Statistics
Related Workflows
Discover more workflows you might like
Universal CSV to JSON API Converter
Effortlessly transform CSV data into structured JSON with this versatile n8n workflow. Integrate it into any application as a custom API endpoint, supporting various input methods including file uploads and raw text.
Instant WooCommerce Order Notifications via Telegram
When a new order is placed on your WooCommerce store, instantly receive detailed notifications directly to your Telegram chat. Stay on top of your e-commerce operations with real-time alerts, including order specifics and a direct link to view the order.
On-Demand Microsoft SQL Query Execution
This workflow allows you to manually trigger and execute any SQL query against your Microsoft SQL Server database. Perfect for ad-hoc data lookups, administrative tasks, or quick tests, giving you direct control over your database operations.