A hands-on learning repository for LangGraph fundamentals — building stateful, multi-actor LLM applications. Covers state graphs, conversational agents, tool-calling, ReAct agent patterns, streaming responses, and debugging workflows.
- State graph fundamentals — building and traversing stateful graphs
- Conversational agents — persistent, context-aware chat interactions
- Tool calling integration — connecting LLMs to external tools and APIs
- ReAct agent patterns — reasoning and acting loop implementations
- Streaming responses — real-time token-by-token output
- Debugging workflows — graph visualization and execution tracing
- Production patterns — error handling, persistence, and checkpointing
- Python 3 — Core programming language
- LangGraph — Stateful orchestration framework for LLM applications
- LangChain — LLM integration and tool-calling infrastructure
- Jupyter Notebook — Interactive learning and experimentation
git clone https://github.com/giovanniromero-dev/langgraph-foundations.git
cd langgraph-foundations
pip install -r requirements.txt
jupyter notebookBuilt with dedication by Giovanni Romero