LangGraph Playground

This repository contains example scripts demonstrating various features of LangGraph.

Installation

It is recommended to use uv for managing dependencies and running the scripts.

1. Install uv if you haven't already: https://github.com/astral-sh/uv#installation

2. Create a virtual environment (optional but recommended):

   uv venv
   source .venv/bin/activate

3. Install required packages (check individual script requirements):

   uv pip install langgraph typing_extensions # Base packages
   uv pip install pyppeteer nest_asyncio     # For PNG visualization
   # Install pyppeteer browser dependencies if needed
   # playwright install --with-deps # Only needed if using playwright backend

Scripts

parallel-execution.py

Purpose: Demonstrates how to define and execute both a linear and a parallel workflow using LangGraph.

Functionality:

1. Defines Nodes: Creates simple placeholder functions (search_web, search_vector_db, aggregate_results) representing tasks.
2. Builds Linear Graph: Constructs a graph where nodes execute sequentially: START -> search_web -> search_vector_db -> aggregate_results -> END.
3. Builds Parallel Graph: Constructs a graph where search_web and search_vector_db execute in parallel after START, with both feeding into aggregate_results before END.
4. Visualizes Graphs: Generates PNG images (linear_graph.png, parallel_graph.png) visualizing the structure of both graphs using draw_mermaid_png. This requires pyppeteer and its Chromium dependency.
5. Invokes Graphs: Runs both the linear and parallel graphs, printing messages to the console indicating which node is executing.

Dependencies:

• langgraph
• typing_extensions
• pyppeteer (for visualization)
• nest_asyncio (often needed with pyppeteer)

To Run:

# Ensure pyppeteer's browser is downloaded (happens automatically on first run)
uv run python parallel-execution.py

Output:

• Console output showing the execution flow of nodes for both graphs.
• linear_graph.png: Visualization of the sequential workflow.
• parallel_graph.png: Visualization of the parallel workflow.