Graph nodes and edges in LangChain - Mini Project: Build & Apply

Graph nodes and edges

📖 Scenario: You are building a simple graph structure using LangChain to represent connections between places in a city. Each place is a node, and the roads between them are edges.

🎯 Goal: Create a graph with nodes and edges using LangChain's graph components. You will first set up nodes, then configure a threshold for edge weights, add edges based on that threshold, and finally complete the graph setup.

📋 What You'll Learn

Create a dictionary called nodes with these exact entries: 'Library': 'A place with books', 'Cafe': 'A place to drink coffee', 'Park': 'A place to relax'

Create a variable called min_weight and set it to 5

Create a list called edges that includes tuples of (start_node, end_node, weight) for edges with weight greater than or equal to min_weight

Create a LangChain Graph object called city_graph using the nodes and edges

💡 Why This Matters

🌍 Real World

Graphs are used to model networks like social connections, maps, or recommendation systems.

💼 Career

Understanding graph structures is important for roles in data science, AI, and software engineering working with complex data relationships.

1

Create the nodes dictionary

Create a dictionary called nodes with these exact entries: 'Library': 'A place with books', 'Cafe': 'A place to drink coffee', 'Park': 'A place to relax'

LangChain

# Create the nodes dictionary with exact entries
# Your code here

Need a hint?

Use curly braces {} to create a dictionary with the exact keys and values.

2

Set the minimum edge weight

Create a variable called min_weight and set it to 5

LangChain

nodes = {
    'Library': 'A place with books',
    'Cafe': 'A place to drink coffee',
    'Park': 'A place to relax'
}
# Create a variable min_weight and set it to 5
# Your code here

Need a hint?

Just assign the number 5 to the variable min_weight.

3

Create edges with weight filter

Create a list called edges that includes tuples of (start_node, end_node, weight) for these connections: ('Library', 'Cafe', 7), ('Cafe', 'Park', 3), ('Library', 'Park', 5). Include only edges with weight greater than or equal to min_weight.

LangChain

nodes = {
    'Library': 'A place with books',
    'Cafe': 'A place to drink coffee',
    'Park': 'A place to relax'
}

min_weight = 5
# Create edges list with tuples (start_node, end_node, weight) where weight >= min_weight
# Your code here

Need a hint?

Use a list comprehension to filter edges by weight.

4

Create the LangChain Graph object

Create a LangChain Graph object called city_graph using the nodes and edges variables.

LangChain

nodes = {
    'Library': 'A place with books',
    'Cafe': 'A place to drink coffee',
    'Park': 'A place to relax'
}

min_weight = 5

all_edges = [
    ('Library', 'Cafe', 7),
    ('Cafe', 'Park', 3),
    ('Library', 'Park', 5)
]

edges = [edge for edge in all_edges if edge[2] >= min_weight]

# Import Graph from langchain.graphs and create city_graph with nodes and edges
# Your code here

Need a hint?

Import Graph from langchain.graphs and create city_graph with the nodes and edges.