💬 Website chatbot with Google Drive knowledge base using GPT-4 and Mistral AI

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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: rajeet.nair@digitalbiz.tech
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

HTTP Request, Webhook, Google Drive, AI Agent, OpenAI Chat Model, Simple Memory

📥 Import

Download workflow.json and import into n8n: Workflow menu → Import from File

📖 Importing guide · 🔑 Credential setup