Website chatbot with Google Drive knowledge base using GPT-4 and Mistral AI
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 -
At a glance
Website chatbot with Google Drive knowledge base using GPT-4 and Mistral AI is a ready-made n8n workflow you import as a workflow JSON file — no build required. It connects OpenAI, Google Drive, LinkedIn. It's free to download. Follow the 5-step import below to go live in minutes.
- Platform
- n8n
- Connects
- OpenAI, Google Drive, LinkedIn
- Modules
- 23
- Price
- Free
- Version
- v1.0

About this workflow
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 1. Google Drive (brand folder) → Fetch files from folder Website kb (ID: 1o3DK9Ceka5Lqb8irvFSfEeB8SVGGOL7) 2. Loop Over Items → For each file: - Set metadata - Download file - Upload to Mistral for OCR - Get Signed URL - Run OCR extraction (mistral-ocr-latest) 3. If OCR success → Pass to chunking pipeline Else → skip and continue 4. Chunking Logic (Code node) - Splits document into 1,000-character JSON chunks - Adds metadata (source, char positions, file ID) 5. Default Data Loader + Text Splitter → Prepares chunks for embedding 6. Embeddings (Mistral Cloud) → Generates embeddings for text chunks 7. Qdrant Vector Store (Insert mode) → Saves embeddings into docragtestkb collection 8. 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: LinkedIn: You can also DM us on LinkedIn for any help. ---
How to import this n8n workflow
- 1
Download the workflow JSON file after purchase.
- 2
Open n8n → click the menu → Import from File.
- 3
Select the downloaded JSON and import.
- 4
Set up credentials for each node that requires them.
- 5
Click Execute Workflow to test, then activate.
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