Automated book summarization with DeepSeek AI, Qdrant Vector DB & Google Drive
Needs changesNeeds changes. This template uses 1 thing(s) that n8n 3.0 removes: AI Agent v1 (old agent modes). 1 breaking item(s) found. Static check, last run 2026-10-19.
What this workflow does
This AI workflow has 21 nodes and runs on Google Drive events. Along the way it connects Qdrant Vector Store, Google Drive, Embeddings Cohere and DeepSeek Chat Model.
How it runs
Trigger: On Google Drive events.
- Google Drive: uses Google Drive
- input (Code): runs custom JavaScript code
- Qdrant Vector Store: uses the Qdrant vector store, with embeddings: Embeddings Cohere; document loader: Default Data Loader
- Code: runs custom JavaScript code
- Question and Answer Chain: answers questions over your documents (RAG), with model: DeepSeek Chat Model; retriever: Vector Store Retriever
- Information Extractor: extracts structured fields from text with AI, with model: DeepSeek Chat Model
- Split Out: splits a list into separate items
- AI Agent: runs an AI agent, with model: DeepSeek Chat Model; 1 tool (qdrant_search); memory: Simple Memory
- Response (Code): runs custom JavaScript code
- Delete Collection (HTTP Request): calls an HTTP API
…plus 2 more steps. See the full node list below.
Services it uses
Before you upgrade to n8n 3.0
1 thing in this workflow is removed in n8n 3.0. Fix it before you upgrade:
- AI Agent v1 (old agent modes) in AI Agent (v1.8): replace with Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent.
Rather not rewrite it? Many of these flows can be rebuilt in Make (free plan).
| Removed in 3.0 | Replace with |
|---|---|
| AI Agent v1 (old agent modes) AI Agent (v1.8) | Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent. |
Nodes used (15)
- Qdrant Vector Store
@n8n/n8n-nodes-langchain.vectorStoreQdrant - Recursive Character Text Splitter
@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter - Default Data Loader
@n8n/n8n-nodes-langchain.documentDefaultDataLoader - AI Agent
@n8n/n8n-nodes-langchain.agent - Simple Memory
@n8n/n8n-nodes-langchain.memoryBufferWindow - Code
n8n-nodes-base.code - Google Drive
n8n-nodes-base.googleDrive - HTTP Request
n8n-nodes-base.httpRequest - Question and Answer Chain
@n8n/n8n-nodes-langchain.chainRetrievalQa - Vector Store Retriever
@n8n/n8n-nodes-langchain.retrieverVectorStore - Embeddings Cohere
@n8n/n8n-nodes-langchain.embeddingsCohere - Information Extractor
@n8n/n8n-nodes-langchain.informationExtractor - Split Out
n8n-nodes-base.splitOut - Google Drive Trigger
n8n-nodes-base.googleDriveTrigger - DeepSeek Chat Model
@n8n/n8n-nodes-langchain.lmChatDeepSeek
From the author
📚 AI Book Summarizer with Vector Search – n8n Automation Overview This n8n workflow automates the process of summarizing uploaded books from Google Drive using vector databases and LLMs. It uses Cohere for embeddings, Qdrant for storage and retrieval, and…