Update RAG documents from Google Drive to Qdrant and re

This automation keeps a RAG system up to date by syncing documents from Google Drive to Qdrant and enables accurate, context-aware responses to user queries via chat using Google Gemini. Designed for developers and AI engineers building dynamic, self-updating knowledge systems.

## Who it´s for
- RAG system developers needing to sync documents from cloud storage to vector databases.
- Support teams using chatbots powered by up-to-date documentation.
- Knowledge base owners integrating Google Drive as a content source.
- AI engineers building scalable QA systems with automatic data refresh.

## What the automation does
- On manual trigger or webhook — scans a Google Drive folder and updates the Qdrant collection (full or incremental).
- On receiving a chat message — retrieves relevant document chunks from Qdrant.
- Generates responses using Google Gemini based on retrieved context.
- Supports text splitting and OpenAI embeddings for accurate vector search.
- Automatically replaces outdated documents in Qdrant when files are updated in Google Drive.

## What´s included
- Ready-to-use n8n workflow with RAG update and chat processing logic.
- Trigger logic: manual, HTTP webhook, and chat message receipt.
- Integrations with Google Drive, Qdrant, Google Gemini, and OpenAI.
- Basic setup and adaptation guide.

## Requirements for setup
- n8n instance with external API access.
- Google Drive account with read permissions.
- Running Qdrant instance with configured collection.
- API keys for OpenAI (embeddings) and Google Gemini.

## Benefits and outcomes
- Continuous knowledge base freshness without manual intervention.
- Higher response accuracy due to real-time document updates.
- Reduced support load — users get correct answers automatically.
- Flexibility: update single files or entire collections.

## Important: template only
Important: you are purchasing a ready-made automation workflow template only. Rollout into your infrastructure, connecting specific accounts and services, 1:1 setup help, custom adjustments for non-standard stacks and any consulting support are provided as a separate paid service at an individual rate. To discuss custom work or 1:1 help, contact via Telegram: @gleb923.