Library / RAG & Knowledge Bases
RAG & Knowledge Bases
RAG Agent with Milvus, Cohere and OpenAI for Drive Files
When new files appear in Google Drive they are embedded with Cohere into Milvus, and when a chat message arrives an OpenAI agent answers from them.
What it does
## Why Milvus Based on comparisons and user feedback, Milvus is often considered a more performant and scalable vector database solution compared to Supabase, particularly for demanding use cases involving large datasets, high-volume vector search operations, and multilingual support. ### Requirements - Create an account on Zilliz to generate the Milvus cluster. - There is no need to create docker containers or your own instance, Zilliz provides the cloud infraestructure to build it easily - Get your credentials ready from Drive, Milvus (Zilliz), and Cohere ### Usage Every time a new pdf is added into the Drive folder, it will be inserted into the Milvus Vector Store, allowing for the interaction with the RAG agent in seconds. ## Calculate your company's RAG costs Want to run Milvus on your own server on n8n? Zilliz provides a great cost calculator ### Get in touch with us Want to implement a RAG AI agent for your company? Shoot us a message
The steps
- Default Data Loader
- Embeddings Cohere
- When chat message received
- Watch New Files
- Download New
- Insert into Milvus
- RAG Agent
- Retrieve from Milvus
- OpenAI 4o
- Memory
- Cohere embeddings
- Set Chunks
- Extract from File
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