Automate Vision RAG with Cohere and Qdrant for Image Embeddings
Leverage Cohere's multimodal models and Qdrant vector store to create a Vision RAG agent that efficiently processes and queries document scans for relevant information.
This workflow automates the process of embedding and retrieving document scans using Cohere's Embed v4 model and Qdrant's vector store. It enables a Vision RAG agent to handle complex queries by splitting tasks between a chat agent and a Q&A agent, optimizing for graphical content like charts and tables. The workflow is ideal for environments where visual data needs to be queried and interpreted efficiently.
- Platform
- n8n
- Category
- AI
- Price
- $19.99
- Creator
- Aisha Okafor
- if
- set
- noOp
- splitOut
- qdrant
- aggregate
- stickyNote
- httpRequest
- manualTrigger
- chat
How to import this workflow into n8n
- 1Purchase or download the workflow to get the n8n workflow JSON file.
- 2In your n8n instance, open Workflows and choose "Import from File" (or paste the JSON with Ctrl+V on the canvas).
- 3Open each node marked with a credential warning and connect your own accounts and API keys.
- 4Run the workflow once manually to verify the data flow, then toggle it to Active.
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