🤖 AI Powered RAG Chatbot for Your Docs + Google Drive + Gemini + Qdrant — Flujo de trabajo n8n

Alta complejidad Disparador35 nodos AI👁 65,428 vistaspor Joseph LePage

Descripción general

🤖 AI-Powered RAG Chatbot with Google Drive Integration

This workflow creates a powerful RAG (Retrieval-Augmented Generation) chatbot that can process, store, and interact with documents from Google Drive using Qdrant vector storage and Google's Gemini AI.

How It Works

Document Processing & Storage 📚 Retrieves documents from a specified Google Drive folder Processes and splits documents into manageable chunks Extracts metadata using AI for enhanced search capabilities Stores document vectors i

Nodos utilizados

TelegramGoogle DriveGoogle DocsAI AgentLangChain CodeEmbeddings OpenAIOpenAI Chat ModelSimple MemoryToken SplitterDefault Data LoaderQdrant Vector StoreGoogle Gemini Chat ModelInformation Extractor

Vista previa del flujo de trabajo

Prepare Qdrant Vector Store
Perform Qdrant Vector Store Operations
🌟Workflow Config
- Google Drive Folder Id
- Qdrant Collection Name
- List of Google Drive File Id's
Extract Metadata for Qdrant Hybrid Search
Google Drive
✨ Save Documents to Qdrant Vector Store
Delete From Qdrant Vector Store
This operation can not be undone!!!
Human In The Loop
User must verify deletion of points from Qdrant vector
👍Start Here!
🤖Retrieve Content from Qdrant Vector Store
🗣️ Chat with Your Documents
Step 1 - Save Documents to Qdrant Vector Stor
Step 2 - Chat with Your Documents from Qdrant
Save Chat History
🤖 AI-Powered RAG Chatbot with Google Drive I
This workflow creates a powerful RAG (Retrieval-Augment
docmodelmemoryembedmodeltoolembedmodel
Data Loader
Token Splitter
Qdrant Vector Store
L
Loop Over Items
W
Wait
W
When clicking ‘Test work…
Google Gemini Chat Model
M
Merge
Extract Meta Data
G
Get File Contents
Download File From Googl…
Find File Ids in Google …
text-embeddings-3-large
G
Google Folder ID
gpt-4o-mini1
Delete Qdrant Points by …
Q
Qdrant Collection Name
F
File Id List
M
Merge1
M
Merge2
Confirm Qdrant Delete Po…
I
If
Send Declined Message
W
Webhook
AI Agent
Window Buffer Memory
W
When chat message received
Google Gemini Chat Model1
text-embeddings-3-large1
Google Drive
R
Respond to User
Update Chat History
Qdrant Vector Store Tool
OpenAI Chat Model
Send Completed Message
35 nodes35 edges

Cómo funciona

  1. 1

    Disparador

    El flujo de trabajo comienza con un disparador disparador.

  2. 2

    Procesamiento

    Los datos fluyen a través de 35 nodos, connecting agent, chattrigger, code.

  3. 3

    Salida

    El flujo de trabajo completa su automatización y entrega el resultado al destino configurado.

Detalles de nodos (35)

TE

Telegram

telegram

#1
GO

Google Drive

googleDrive

#2
GO

Google Docs

googleDocs

#3
AI

AI Agent

n8n-nodes-langchain.agent

#4
LA

LangChain Code

n8n-nodes-langchain.code

#5
EM

Embeddings OpenAI

n8n-nodes-langchain.embeddingsOpenAi

#6
OP

OpenAI Chat Model

n8n-nodes-langchain.lmChatOpenAi

#7
SI

Simple Memory

n8n-nodes-langchain.memoryBufferWindow

#8
TO

Token Splitter

n8n-nodes-langchain.textSplitterTokenSplitter

#9
DE

Default Data Loader

n8n-nodes-langchain.documentDefaultDataLoader

#10
QD

Qdrant Vector Store

n8n-nodes-langchain.vectorStoreQdrant

#11
GO

Google Gemini Chat Model

n8n-nodes-langchain.lmChatGoogleGemini

#12
IN

Information Extractor

n8n-nodes-langchain.informationExtractor

#13

Cómo importar este flujo de trabajo

  1. 1Haz clic en el botón Descargar JSON a la derecha para guardar el archivo del flujo de trabajo.
  2. 2Abre tu instancia de n8n. Ve a Flujos de trabajo → Nuevo → Importar desde archivo.
  3. 3Selecciona el archivo ai-powered-rag-chatbot-for-your-docs-google-drive-gemini-qdrant descargado y haz clic en Importar.
  4. 4Configura las credenciales para cada nodo de servicio (claves API, OAuth, etc.).
  5. 5Haz clic en Probar flujo de trabajo para verificar que todo funcione, luego actívalo.

O pega directamente en n8n → Importar desde JSON:

{ "name": "🤖 AI Powered RAG Chatbot for Your Docs + Google Drive + Gemini + Qdrant", "nodes": [...], ...}

Integraciones

agentchattriggercodedocumentdefaultdataloaderembeddingsopenaiextractfromfilegoogledocsgoogledriveifinformationextractorlmchatgooglegeminilmchatopenaimanualtriggermemorybufferwindowmergesetsplitinbatchessummarizetelegramtextsplittertokensplitter

Obtener este flujo de trabajo

Descarga e importa con un solo clic

Descargar JSONVer en n8n.io
Nodos35
Complejidadhigh
Disparadortrigger
Vistas65,428
CategoríaAI

Creado por

Joseph LePage

Joseph LePage

@joe

Etiquetas

agentchattriggercodedocumentdefaultdataloaderembeddingsopenaiextractfromfilegoogledocsgoogledriveifinformationextractor

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