langgraph-quick-start-py

LangGraph Quick Start Agent in Python

Overview

This is an example LangGraph Python agent using the OpenAI LLM to answer questions about cryptocurrencies. This agent is A2A-compatible.

You can run this code locally and extend it to build your own Agent, as shown in this guide:

• Get Started with Python LangGraph agents

What the Agent Does

This agent is a crypto-focused single-node chatbot that receives a message, calls an OpenAI model, and returns an assistant response.

How It Works

Nodes and Graphs

In LangGraph, a graph is a map of how your agent thinks and acts. It defines what steps the agent can take and how those steps connect.

Each node is one of those steps—for example:

• calling an AI model
• fetching data from an API
• deciding what to do next

When you build a LangGraph agent, you're basically creating a small workflow made of these nodes. The graph handles how messages move between them—so your agent can reason, make calls, and respond in a structured way.

In this example, there is only one node, which calls OpenAI.

The Agent's Main Logic

The agent logic is defined in src/agent/graph.py:

• The code imports the langgraph.graph and langgraph.runtime components for building and running the agent.
• Context is a class defining configurable parameters accessible to the runtime.
• State is a dataclass defining the agent's working memory (a list of message objects forming the conversation).
• call_model is a node responsible for interacting with the LLM (gpt-4o-mini from OpenAI). It receives the current conversation state and runtime context, sends the latest user message to the model, an updated message list that includes the assistant's response.
• graph defines the graph. StateGraph describes the workflow, with one node (call_model) that runs as soon as the graph starts. The compile() function finalizes the workflow into an executable runtime graph.
• The agent follows the A2A protocol, meaning it can receive and send structured conversational messages to other agents. The State and Context schemas make it interoperable with other A2A-compatible components