langchain-core

Let's Debate LLM-Scientist with LLM-Philosopher... and decide winner by LLM-Judge

Successfully developed a state-of-the-art AI-driven credit underwriting engine using LangGraph and FastMCP that orchestrates multiple specialized agents to evaluate risk, detect fraud, and generate explainable credit decisions, delivering transparent, auditable, and tailored financial solutions with unmatched efficiency.

AI Research Agent 🔍 secure Academic Research Assistant with AI Integration. A full-stack web application leveraging OpenAI and LangChain to provide authenticated users with AI-powered research capabilities. Features secure JWT authentication, real-time web/Wikipedia integration, Markdown report generation, and Docker deployment.

ResuMind AI is an LLM-powered resume analysis system that processes bulk PDF and DOCX resumes from ZIP files and converts unstructured content into structured CSV data. Built with LangChain, Gemini, and Streamlit, it enables automated, scalable, and schema-driven resume intelligence.

A simple langchain chatbot

Successfully developed a Healthcare AI Clinical Decision Support System, leveraging LangGraph, GPT-4o-mini, and PubMed to deliver real-time patient risk stratification, evidence-based treatment recommendations, and personalized clinical road maps with integrated drug safety validations.

Build an application that performs real-time currency conversion using an LLM and external API.

A Streamlit web application that lets you upload PDF documents and have a conversational Q&A session with their content. Built using Retrieval-Augmented Generation (RAG) with LangChain, Groq, and ChromaDB.

Successfully developed an AI-powered Investment Portfolio Optimization Workflow using LangGraph that infers user risk profiles, selects tickers, fetches market data, and simulates & optimizes portfolios with actionable recommendations. It integrates advanced financial metrics, risk assessment, and dynamic portfolio management for decision-making.

A hands-on project exploring LangChain's core capabilities through two interactive Jupyter notebooks: a conversational chatbot with session memory and a retrieval-augmented generation (RAG) pipeline using vector stores.

Successfully developed AdAstra Marketing Intelligence Campaign Optimization Engine, a next-generation AI system using LangGraph that transforms raw campaign data into strategic, revenue-driven decisions. It blends KPI diagnostics, CVXPY optimization, and intelligent budget reallocation to deliver measurable lift in ROAS, efficiency, and growth.

An intelligent CLI tool that converts unstructured text into a validated SQL database using a self-correcting LangChain and Pydantic pipeline.

AI agent that performs revenue calculations and generates business analysis (via CLI or chat platform integration such as Slack)

An AI Agent that uses Wikipedia to research userinput depending on user role (student, researcher)

This repository demonstrates Retrieval-Augmented Generation (RAG) with two knowledge sources: Wikipedia and a research paper about RAG.

Successfully developed a cutting-edge, intelligent, and adaptive learning platform using LangGraph that personalizes lessons, exercises, and assessments in real-time, seamlessly integrating AI-driven insights to optimize mastery, engagement, and retention for learners of all levels.

A project that dwells into the concept of LLM , RAG and Langchain