Power Placetel voice answers from OneDrive docs with OpenAI and Groq
Ready for 3.0Ready for 3.0. This template uses no nodes that n8n 3.0 removes. No removed nodes, versions or helpers found. Static check, last run 2026-10-19.
What this workflow does
This AI workflow has 16 nodes and runs when an HTTP POST request hits its webhook URL (plus 2 other triggers). Along the way it connects Microsoft OneDrive, Embeddings OpenAI, Supabase Vector Store and Groq Chat Model. It also calls graph.microsoft.com over HTTP.
How it runs
Trigger: When an HTTP POST request hits its webhook URL (plus 2 other triggers).
- Question and Answer Chain: answers questions over your documents (RAG), with model: Groq Chat Model; retriever: Vector Store Retriever
- OneDrive – Dateien auflisten (HTTP Request): calls graph.microsoft.com
- Placetel – Antwort zurückgeben (Respond to Webhook): sends the response back to the webhook caller
- Loop – Jede Datei (Loop Over Items (Split in Batches)): loops over the items in batches
- Supabase – Chunks speichern (Supabase Vector Store): stores documents in the Supabase vector store, with embeddings: OpenAI Embeddings – Indexierung; document loader: Text Loader
- Datei-IDs extrahieren (Code): runs custom JavaScript code
- OneDrive – Datei herunterladen (Microsoft OneDrive): download
Services it uses
HTTP calls to: graph.microsoft.com
Before you upgrade to n8n 3.0
Nothing in this workflow is removed in n8n 3.0, so it should import and run after the upgrade.
Nodes used (14)
- Schedule Trigger
n8n-nodes-base.scheduleTrigger - Manual Trigger
n8n-nodes-base.manualTrigger - HTTP Request
n8n-nodes-base.httpRequest - Code
n8n-nodes-base.code - Loop Over Items (Split in Batches)
n8n-nodes-base.splitInBatches - Microsoft OneDrive
n8n-nodes-base.microsoftOneDrive - Default Data Loader
@n8n/n8n-nodes-langchain.documentDefaultDataLoader - Embeddings OpenAI
@n8n/n8n-nodes-langchain.embeddingsOpenAi - Supabase Vector Store
@n8n/n8n-nodes-langchain.vectorStoreSupabase - Webhook
n8n-nodes-base.webhook - Respond to Webhook
n8n-nodes-base.respondToWebhook - Question and Answer Chain
@n8n/n8n-nodes-langchain.chainRetrievalQa - Vector Store Retriever
@n8n/n8n-nodes-langchain.retrieverVectorStore - Groq Chat Model
@n8n/n8n-nodes-langchain.lmChatGroq
From the author
Quick Overview This workflow indexes text files from Microsoft OneDrive into a Supabase vector store using OpenAI embeddings, then answers incoming webhook questions with a Groq LLM using retrieval-augmented generation (RAG) and returns the response to the…