Azure-AI-RAG-Architecture-React-FastAPI-and-Cosmos-DB-Vector-Store and LangChain-RAG-Pattern-with-React-FastAPI-and-Cosmos-DB-Vector-Store
These are **ecosystem siblings** — both demonstrate the same RAG architecture pattern on Azure using identical core components (React frontend, FastAPI backend, Cosmos DB vector store), with one example using LangChain as an abstraction layer while the other implements RAG more directly.
About Azure-AI-RAG-Architecture-React-FastAPI-and-Cosmos-DB-Vector-Store
jonathanscholtes/Azure-AI-RAG-Architecture-React-FastAPI-and-Cosmos-DB-Vector-Store
This project demonstrates deploying a secure, scalable Generative AI (GenAI) solution on Azure using a Retrieval-Augmented Generation (RAG) architecture and Azure best practices. Leveraging CosmosDB, Azure OpenAI, and a React + Python FastAPI framework, it ensures efficient data retrieval, security, and an intuitive user experience.
This project guides you through setting up a secure and scalable AI assistant on Azure. You provide your documents, and the system uses them to answer questions and generate responses, ensuring the information is always based on your specific data. It's designed for organizations that need a robust, enterprise-grade AI solution for their employees or customers, built on Azure.
About LangChain-RAG-Pattern-with-React-FastAPI-and-Cosmos-DB-Vector-Store
jonathanscholtes/LangChain-RAG-Pattern-with-React-FastAPI-and-Cosmos-DB-Vector-Store
Complete project (web, api, data) covering the implementation of the RAG (Retrieval Augmented Generation) pattern using Azure Cosmos DB for MongoDB vCore and LangChain. The RAG pattern combines leverages the new vector search capabilities for Azure Cosmos DB.
This project helps developers integrate Retrieval Augmented Generation (RAG) capabilities into their applications. It takes your existing data, stores it in a vector database, and uses it to generate contextually relevant, 'grounded' answers to user questions. This is for software developers looking to build AI-powered conversational interfaces or knowledge retrieval systems.
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