Do you work with large sets of documents? Build AI apps that rely on external content? Or just love automation?
Then you’ll love CalBot — a smart workflow I built using n8n that automates everything from file ingestion to vector storage.
It’s a plug-and-play solution for document processing, semantic search, and RAG-based applications.
What is CalBot?
CalBot is an automated pipeline that does the following:
- Watches a Google Drive folder for new files
- Downloads and processes each file into text chunks
- Embeds those chunks using Google Gemini (PaLM API)
- Stores the embeddings in a Pinecone vector store
All of this is done using n8n — no manual steps, no complex setup.
Ideal for developers building AI assistants, search engines, chatbots, or internal knowledge bases.
The Tech Stack
- n8n for workflow automation
- Google Drive API (file monitoring + download)
- Google Gemini (PaLM) for text embeddings
- Pinecone for fast vector search
- Recursive Text Splitter for clean chunking
- JSON-based workflow that’s easy to import and extend
Use Cases
- Retrieval-Augmented Generation (RAG)
- Internal document search
- FAQ bots
- AI-driven content understanding
- Knowledge base enrichment
Watch the Full Demo
Watch on YouTube – A complete walkthrough of the CalBot workflow, how it works, and how to set it up.
Let’s Collaborate
Want to use this in your project?
Have a custom AI idea you want to automate?
Need help modifying the workflow?
Let’s connect — I love building automation tools for real-world problems.
Feel free to fork the project, comment below, or reach out.
Tags
#n8n #automation #pinecone #googleai #semanticsearch #rag #nocode #workflowautomation