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.

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.

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.

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

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

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