Metadata filtering in RAG application
-
Updated
Apr 16, 2025 - Jupyter Notebook
Metadata filtering in RAG application
Go Client for CyborgDB: The Confidential Vector Database
Python Client SDK for CyborgDB: The Confidential Vector Database
JavaScript & TypeScript Client SDK for CyborgDB: The Confidential Vector Database
An ultra-fast BM25 retriever with support for multiple variants and meta-data filtering.
A production-ready Advanced RAG API featuring background ingestion, schema-driven routing, and dynamic metadata filtering. Built with FastAPI, ChromaDB, and Ollama, it utilizes RabbitMQ workers for scalable, idempotent document processing and autonomous query expansion.
This project is a **production-ready multi-agent AI financial advisory system** designed to deliver **holistic, personalized financial guidance**.
A domain specific multiagentic medical rag on hypertension and diabetics used to generate care plans for the patients.
Add a description, image, and links to the metadata-filtering topic page so that developers can more easily learn about it.
To associate your repository with the metadata-filtering topic, visit your repo's landing page and select "manage topics."