Auto-update knowledge base with Drive, LlamaIndex & Azure OpenAI embeddings

This Workflow auto-ingests Google Drive documents, parses them with LlamaIndex, and stores Azure OpenAI embeddings in an in-memory vector store—cutting manual update time from ~30 minutes to under 2 minutes per doc. Last updated: September 2026. Why Use This Workflow? Cost Reduction: No monthly cloud fees just to store knowledge. Ideal For Knowledge Managers / Documentation Teams: Automatically keep product docs and SOPs in sync when source files change on Google Drive. Support Teams: Ensure the searchable KB is always up-to-date after doc edits, speeding agent onboarding and resolution time. Developer / AI Teams: Populate an in-memory vector store for experiments, rapid prototyping, or loca

Help me set up the n8n workflow "Auto-update knowledge base with Drive, LlamaIndex & Azure OpenAI embeddings" (https://n8n.io/workflows/9174). It uses: HTTP Request, Google Drive, Simple Vector Store, Default Data Loader, Embeddings Azure OpenAI. Import the template JSON into my n8n instance, list every credential I need to create, and walk me through testing it.