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12. Create agents with LangGraph

This app demonstrates how to implement agents with LangGraph.

Prerequisites

  • Python 3.10 or later
  • Azure OpenAI Service

Overview

What is LangGraph?

LangGraph is a library for building stateful, multi-actor applications with LLMs, used to create agent and multi-agent workflows.

This chapter provides a practical example of how to use LangGraph to create an agent that can interact with users and external tools.

Usage

  1. Get Azure OpenAI Service API key
  2. Copy .env.template to .env in the same directory
  3. Set credentials in .env
  4. Run main.py
# Create a virtual environment
$ python -m venv .venv

# Activate the virtual environment
$ source .venv/bin/activate

# Install dependencies
$ pip install -r requirements.txt

Examples

reflection_agent

react_agent

advanced_rag_flows

# create vector store
python apps/12_langgraph_agent/advanced_rag_flows/ingestion.py

# run main.py
python apps/12_langgraph_agent/advanced_rag_flows/main.py

Advanced RAG Flows

References