Audio transcription & chat bot with AssemblyAI, Gemini, and Pinecone RAG
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 18 nodes and runs when someone submits an n8n form (“upload files”) (plus 1 other trigger). Along the way it connects Pinecone Vector Store, Embeddings Google Gemini, Google Sheets and Google Gemini Chat Model. It also calls api.assemblyai.com over HTTP.
How it runs
Trigger: When someone submits an n8n form (“upload files”) (plus 1 other trigger).
- HTTP Request: calls api.assemblyai.com (POST)
- AI Agent: runs an AI agent, with model: Google Gemini Chat Model; 1 tool (Pinecone Vector Store); memory: Simple Memory
- HTTP Request: calls api.assemblyai.com (POST)
- Wait: pauses before continuing
- HTTP Request: calls an HTTP API
- If: checks a condition and branches into true / false
- Convert to File: converts data to a file (to text)
- Pinecone Vector Store: stores documents in the Pinecone vector store, with embeddings: Embeddings Google Gemini; document loader: Default Data Loader
- Append row in sheet (Google Sheets): append
Services it uses
HTTP calls to: api.assemblyai.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)
- n8n Form Trigger
n8n-nodes-base.formTrigger - HTTP Request
n8n-nodes-base.httpRequest - Wait
n8n-nodes-base.wait - If
n8n-nodes-base.if - Convert to File
n8n-nodes-base.convertToFile - Pinecone Vector Store
@n8n/n8n-nodes-langchain.vectorStorePinecone - Embeddings Google Gemini
@n8n/n8n-nodes-langchain.embeddingsGoogleGemini - Recursive Character Text Splitter
@n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter - Default Data Loader
@n8n/n8n-nodes-langchain.documentDefaultDataLoader - Google Sheets
n8n-nodes-base.googleSheets - Chat Trigger
@n8n/n8n-nodes-langchain.chatTrigger - AI Agent
@n8n/n8n-nodes-langchain.agent - Google Gemini Chat Model
@n8n/n8n-nodes-langchain.lmChatGoogleGemini - Simple Memory
@n8n/n8n-nodes-langchain.memoryBufferWindow
From the author
Who’s it for This template is designed for podcasters, researchers, educators, product teams, and support teams who work with audio content and want to turn it into searchable knowledge. It is especially useful for users who need automated transcription,…