I've developed a framework for multimodal semantic search (RAG), which orchestrates MongoDB, Pinecone, S3 bucket, LLM API, etc.
If you are not too familiar with "semantic search," think of it as RAG.
To enable semantic search for text, image, etc, we need to pre-process our data before sending it to the database.
My framework works as a middle layer between your app and existing databases, where all the processings happen.
The key differentiator is its MongoDB-compatible NoSQL interface: you interact with this RAG engine exactly as you would with MongoDB, while benefiting from powerful vector search and document-augmentation capabilities.
It's open source: https://github.com/onenodehq/onenode
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Open Source Multimodal Semantic Search · HackerTrans
If you are not too familiar with "semantic search," think of it as RAG.
To enable semantic search for text, image, etc, we need to pre-process our data before sending it to the database.
My framework works as a middle layer between your app and existing databases, where all the processings happen.
The key differentiator is its MongoDB-compatible NoSQL interface: you interact with this RAG engine exactly as you would with MongoDB, while benefiting from powerful vector search and document-augmentation capabilities.
It's open source: https://github.com/onenodehq/onenode