A complete LangGraph guide for PhD students and researchers. From zero to multi-agent systems with Python examples (chatbots, ReAct agents, supervisor patterns, research pipelines).

📝 Create a robust Reflection Agent in Java 21 using Spring AI 2.0, simplifying complex patterns for generating and improving tweets efficiently.

A robust Java implementation of an AI Reflection Agent using Spring AI 2.0. Demonstrates 'Code as Orchestration' strategies to build resilient agents without the complexity of graph DSLs like LangGraph.

Agentic Q&A System leveraging LangGraph and IBM Watsonx for multi-agent orchestration. Features autonomous routing, reflection loops, and self-correction to ensure verified outputs. Includes high-fidelity parsing via Docling and hybrid retrieval (BM25 + ChromaDB) for sophisticated, enterprise-ready document intelligence.

LangGraph Reflection Agent — LinkedIn post generator that iteratively generates, critiques & refines content through self-improvement loops using IBM Watsonx foundation models

LangGraph Orchestrator-Worker + Reflection patterns — parallel meal planning with chef agents & iterative investment advisory using Cathie Wood, Ray Dalio & Warren Buffett AI personas

Build AI chatbots that analyze PDFs, answer questions, and visualize LangGraph workflows using Azure OpenAI and Gradio.