MIRA

Project Overview

MIRA (Memory-Integrated Retrieval Assistant) is a conversational AI backend that leverages Retrieval-Augmented Generation (RAG) to provide context-aware responses with long-term memory. The system uses LangChain to orchestrate document processing, embedding generation, and retrieval workflows, while Pinecone serves as the vector database for semantic search. OpenAI's language models power the conversational interface, enhanced by retrieved context from the knowledge base. Built with Flask and Celery, the backend handles asynchronous document processing, embedding generation, and maintains conversation history for personalized interactions. The system demonstrates understanding of modern LLM architectures, vector databases, and production-ready AI application design.