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.

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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

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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

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