Hybrid RAG AI Agent built with MongoDB, Pydantic AI, and Docling - combines semantic and text search with reciprocal rank fusion.

An interactive RAG agent built with LangChain and MongoDB Atlas. Manage your knowledge base, switch embedding models, and tune retrieval parameters on-the-fly through a conversational interface.

Production-ready RAG framework for Python — multi-tenant chatbots with streaming, tool calling, agent mode (LangGraph), vector search (FAISS), and persistent MongoDB memory. Built on LangChain.

An advanced Multi-Agent RAG system using Python, LangChain, and LangGraph to query diverse databases like SQLite, MongoDB, Neo4j, and MeiliSearch.

A production-ready AI Agent API with advanced RAG (Retrieval-Augmented Generation) capabilities, built with Node.js, TypeScript, MongoDB Atlas, Redis, and Google Gemini integration. This API provides intelligent question-answering based on trained knowledge from various sources including documents, websites, YouTube videos, audio, and video files.

Podcast Summarizer Agent will have LLMs, RAGs, MongoDB, Chatbot, Flutter Mobile app

A hybrid system combining Legal RAG for Vietnamese law retrieval with an AI-powered observability agent for monitoring and analyzing system health. Built with FastAPI, Airflow, MongoDB, Redis, Qdrant, Kubernetes, and LLMs, deployed on cloud with Helm & ArgoCD.

Enhancing Text Retrieval with Metadata Filters using MongoDB and LangChain Agent

Backend API powered by MongoDB Atlas, showcasing intelligent document processing through multi-agent orchestration, agentic RAG with vector search, and automated report generation.

Hack(H)er413 Winner - Best Use of MongoDB. Multi Agentic RAG Platform to simplify all you complex documents so you never miss a clause!

(2nd Place American Airlines Track · 1st Place Vultr Use, TAMUHack26) Developed Aria, an agentic AI airport concierge with a vector-driven backend leveraging LangGraph orchestration, MongoDB Atlas Vector Search, and Vultr LLM inference to support biometric identity resolution, RAG-based knowledge retrieval, and fault-tolerant real-time interactions

CBT&SFBT therapy AGENT with RAG and mongodb mood

MongoDB 3D Asset Metadata Services for 3D Agentic RAG

Python RAG agents using LangChain + CrewAI, Ollama (llama3), Weaviate vector DB, Pydantic schemas, MongoDB; ingestion & search tools

Intelligent travel booking with RAG retrieval & Multi-Agent AI (Search, Recommend, Booking). 768-dim semantic search, 5-factor pricing, conversation memory. Next.js 13, TypeScript, Gemini Pro, Supabase, MongoDB.

Resume Chat Agent API 🤖 A FastAPI-based RAG (Retrieval-Augmented Generation) application that provides intelligent Q&A about resume information using LangChain, MongoDB Atlas Vector Search, and Anthropic Claude.

A distributed Kayak-inspired travel booking system with microservices, Kafka event streaming, Redis caching, MySQL, MongoDB, and an AI concierge agent powered by Gemini 2.5, RAG pipeline, and QLoRA fine-tuning.

cloud-lensShort Description: > A self-healing, AI-native AWS infrastructure auditor. Uses Multi-threaded Discovery, Semantic RAG (MongoDB), and ReAct Agents to bridge the gap between complex cloud architecture and natural language reasoning.

This repository presents a production-ready RAG system combining LangGraph agent with Model Context Protocol (MCP) integration. Features hybrid search using Reciprocal Rank Fusion (RRF) via MongoDB vector and text searches, grounded responses using COSTAR prompting, and automated RAGAS-based evaluation for building reliable, context-aware AI agents

A structured collection of my AI engineering, backend development, and practical project work, including agentic AI experiments, FastAPI projects, POCs, technical articles, and notes. This repository showcases my hands-on learning, real-world implementations, and exploration across LLMs, Python, FastAPI, MongoDB, RAG, and AI tools

A production-ready Retrieval-Augmented Generation (RAG) platform

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A simple RAG application where embeddings are stored in MongoDB Atlas

Agentic RAG system with MongoDB Atlas Vector Search, Pydantic AI, and FastAPI

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A langchain/langgraph RAG agent with mongodb vector store using vector index, gemini as the llm and gemini embedding model.

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sample agent with rag using mongodb atlas