Website Chatbot with Google Drive Knowledge Base using GPT-4 and Mistral AI

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Built by DIGITAL BIZ TECH DIGITAL BIZ TECH
Created on June 06, 2026

Description

AI-Powered Website Chatbot with Google Drive Knowledge Base

Overview
This workflow combines website chatbot intelligence with automated document ingestion and vectorization — enabling live Q&A from both chat input and processed Google Drive files.
It uses Mistral AI for OCR + embeddings, and Qdrant for vector search.

Chatbot Flow
Trigger:** When chat message received or webhook based upon deployed chatbot
Model:** OpenAI gpt-4.1-mini
Memory:** Simple Memory (Buffer Window)
Vector Search Tool:** Qdrant Vector Store
Embeddings:** Mistral Cloud
Agent:** website chat agent
Responds based on chatdbtai Supabase content
Enforces brand tone and informative documents.
Integratration with both:
Embedded chat UI
Webhook

Document → Knowledge Base Pipeline
Triggered manually to keep vector store up-to-date.

Steps
Google Drive (brand folder)
→ Fetch files from folder Website kb (ID: 1o3DK9Ceka5Lqb8irvFSfEeB8SVGG_OL7)
Loop Over Items
→ For each file:
Set metadata
Download file
Upload to Mistral for OCR
Get Signed URL
Run OCR extraction (mistral-ocr-latest)
If OCR success
→ Pass to chunking pipeline
Else → skip and continue
Chunking Logic (Code node)
Splits document into 1,000-character JSON chunks
Adds metadata (source, char positions, file ID)
Default Data Loader + Text Splitter
→ Prepares chunks for embedding
Embeddings (Mistral Cloud)
→ Generates embeddings for text chunks
Qdrant Vector Store (Insert mode)
→ Saves embeddings into docragtestkb collection
Wait
→ Optional delay between batches

Integrations Used
| Service | Purpose | Credential |
|----------|----------|------------|
| Google Drive | File source | Google Drive account 6 rn dbt |
| Mistral Cloud | OCR + embeddings | Mistral Cloud account 2 dbt rn |
| Qdrant | Vector storage | QdrantApi account |
| OpenAI | Chat model | OpenAi account 8 dbt digi |

Agent System Prompt Summary
> “You are the official AI assistant for this website.
Use chatdbtai only as your knowledge source.
Respond conversationally, list offerings clearly, link blogs, and say
‘I couldn’t find that on this site’ if no match.”

Key Features
✅ Automated OCR + chunking → vectorization
✅ Persistent memory for chat sessions
✅ Multi-channel (Webhook + Embedded Chat)
✅ Fully brand-guided, structured responses
✅ Live data retrieval from Qdrant vector store

Summary
> A unified workflow that turns brand files + web content into a knowledge base that powers a intelligent chatbot — capable of responding to visitors in real time, powered by Mistral, OpenAI, and Qdrant.

Need Help or More Workflows?
Want to customize this workflow for your business or integrate it with your existing tools?
Our team at Digital Biz Tech can tailor it precisely to your use case from automation logic to AI-powered enhancements.

💡 We can help you set it up for free — from connecting credentials to deploying it live.

Contact: [email protected]
Website: https://www.digitalbiz.tech
LinkedIn: https://www.linkedin.com/company/digital-biz-tech/
You can also DM us on LinkedIn for any help.

Nodes Used (10)

AI Agent
@n8n/n8n-nodes-langchain.agent
Character Text Splitter
@n8n/n8n-nodes-langchain.textSplitterCharacterTextSplitter
Code
n8n-nodes-base.code
Default Data Loader
@n8n/n8n-nodes-langchain.documentDefaultDataLoader
Embeddings Mistral Cloud
@n8n/n8n-nodes-langchain.embeddingsMistralCloud
Google Drive
n8n-nodes-base.googleDrive
HTTP Request
n8n-nodes-base.httpRequest
OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi
Qdrant Vector Store
@n8n/n8n-nodes-langchain.vectorStoreQdrant
Simple Memory
@n8n/n8n-nodes-langchain.memoryBufferWindow