Run Bunker Guard NPC chat and RAG lore checks with Google Gemini and 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 19 nodes and runs when a chat message arrives (plus 2 other triggers). Along the way it connects Google Gemini Chat Model, Vector Store Question Answer, Embeddings Google Gemini and Google Drive.
How it runs
Trigger: When a chat message arrives (plus 2 other triggers).
- AI Agent: runs an AI agent, with model: Google Gemini Chat Model; 1 tool (Database_Bunker); memory: Window Buffer Memory
- Download File From Google Drive (Google Drive): download
- Switch: routes items into 3 branches
- Simple Vector Store: stores documents in the Simple vector store, with embeddings: Embeddings Google Gemini; document loader: Default Data Loader
- DayClue creator (AI Agent): runs an AI agent, with model: Google Gemini Chat Model; 1 tool (Database_Bunker)
- npc creator (AI Agent): runs an AI agent, with model: Google Gemini Chat Model; memory: Simple Memory
- Chat Generator (AI Agent): runs an AI agent, with model: Google Gemini Chat Model; 1 tool (Database_Bunker); memory: Simple Memory
- Respond to Webhook: sends the response back to the webhook caller
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 Chat Generator (v1.8): replace with Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent.
| Removed in 3.0 | Replace with |
|---|---|
| AI Agent v1 (old agent modes) Chat Generator (v1.8) | Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent. |
Nodes used (14)
- Webhook
n8n-nodes-base.webhook - Google Gemini Chat Model
@n8n/n8n-nodes-langchain.lmChatGoogleGemini - AI Agent
@n8n/n8n-nodes-langchain.agent - Switch
n8n-nodes-base.switch - Respond to Webhook
n8n-nodes-base.respondToWebhook - Simple Memory
@n8n/n8n-nodes-langchain.memoryBufferWindow - Default Data Loader
@n8n/n8n-nodes-langchain.documentDefaultDataLoader - Recursive Character Text Splitter
@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter - Simple Vector Store
@n8n/n8n-nodes-langchain.vectorStoreInMemory - Vector Store Question Answer Tool
@n8n/n8n-nodes-langchain.toolVectorStore - Embeddings Google Gemini
@n8n/n8n-nodes-langchain.embeddingsGoogleGemini - Google Drive
n8n-nodes-base.googleDrive - Chat Trigger
@n8n/n8n-nodes-langchain.chatTrigger - Manual Trigger
n8n-nodes-base.manualTrigger
From the author
Quick overview This workflow powers dynamic character interactions for investigative games. It ingests lore from Google Drive into a vector database, using Google Gemini agents to generate daily briefings, spawn NPCs, and roleplay interrogations via a…