Vision RAG & Image Embeddings with Cohere Command-A and Embed v4

Creates a Vision RAG agent using Cohere's multimodal models to embed document images, store in Qdrant, and retrieve relevant scans for vision model queries.

This workflow leverages Cohere's new multimodal models (Command-A-vision and Embed v4) to build a Vision RAG system for efficient document scan retrieval and analysis. It downloads page extracts from reports with graphs/charts, converts them to base64, generates embeddings, and stores them with original URLs in a Qdrant vector database using the community node. The agent splits into a regular chat AI for conversation and a specialized Q&A branch powered by Command-A-vision. On relevant queries,
Platform
n8n
Category
File & Document Management
Price
$24.99
Creator
Quentin Andersen

How to import this workflow into n8n

  1. 1Purchase or download the workflow to get the n8n workflow JSON file.
  2. 2In your n8n instance, open Workflows and choose "Import from File" (or paste the JSON with Ctrl+V on the canvas).
  3. 3Open each node marked with a credential warning and connect your own accounts and API keys.
  4. 4Run the workflow once manually to verify the data flow, then toggle it to Active.

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