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KuzuQAChain

This notebook shows how to use LLMs to provide a natural language interface to Kùzu database.

Kùzu is an in-process property graph database management system. You can simply install it with pip:

pip install kuzu

Once installed, you can simply import it and start creating a database on the local machine and connect to it:

import kuzu

db = kuzu.Database("test_db")
conn = kuzu.Connection(db)

First, we create the schema for a simple movie database:

conn.execute("CREATE NODE TABLE Movie (name STRING, PRIMARY KEY(name))")
conn.execute(
    "CREATE NODE TABLE Person (name STRING, birthDate STRING, PRIMARY KEY(name))"
)
conn.execute("CREATE REL TABLE ActedIn (FROM Person TO Movie)")
    <kuzu.query_result.QueryResult at 0x1066ff410>

Then we can insert some data.

conn.execute("CREATE (:Person {name: 'Al Pacino', birthDate: '1940-04-25'})")
conn.execute("CREATE (:Person {name: 'Robert De Niro', birthDate: '1943-08-17'})")
conn.execute("CREATE (:Movie {name: 'The Godfather'})")
conn.execute("CREATE (:Movie {name: 'The Godfather: Part II'})")
conn.execute(
    "CREATE (:Movie {name: 'The Godfather Coda: The Death of Michael Corleone'})"
)
conn.execute(
    "MATCH (p:Person), (m:Movie) WHERE p.name = 'Al Pacino' AND m.name = 'The Godfather' CREATE (p)-[:ActedIn]->(m)"
)
conn.execute(
    "MATCH (p:Person), (m:Movie) WHERE p.name = 'Al Pacino' AND m.name = 'The Godfather: Part II' CREATE (p)-[:ActedIn]->(m)"
)
conn.execute(
    "MATCH (p:Person), (m:Movie) WHERE p.name = 'Al Pacino' AND m.name = 'The Godfather Coda: The Death of Michael Corleone' CREATE (p)-[:ActedIn]->(m)"
)
conn.execute(
    "MATCH (p:Person), (m:Movie) WHERE p.name = 'Robert De Niro' AND m.name = 'The Godfather: Part II' CREATE (p)-[:ActedIn]->(m)"
)
    <kuzu.query_result.QueryResult at 0x107016210>

Creating KuzuQAChain​

We can now create the KuzuGraph and KuzuQAChain. To create the KuzuGraph we simply need to pass the database object to the KuzuGraph constructor.

from langchain.chat_models import ChatOpenAI
from langchain.graphs import KuzuGraph
from langchain.chains import KuzuQAChain
graph = KuzuGraph(db)
chain = KuzuQAChain.from_llm(ChatOpenAI(temperature=0), graph=graph, verbose=True)

Refresh graph schema information​

If the schema of database changes, you can refresh the schema information needed to generate Cypher statements.

# graph.refresh_schema()
print(graph.get_schema)
    Node properties: [{'properties': [('name', 'STRING')], 'label': 'Movie'}, {'properties': [('name', 'STRING'), ('birthDate', 'STRING')], 'label': 'Person'}]
    Relationships properties: [{'properties': [], 'label': 'ActedIn'}]
    Relationships: ['(:Person)-[:ActedIn]->(:Movie)']

Querying the graph​

We can now use the KuzuQAChain to ask question of the graph

chain.run("Who played in The Godfather: Part II?")
    
    
    > Entering new  chain...
    Generated Cypher:
    MATCH (p:Person)-[:ActedIn]->(m:Movie {name: 'The Godfather: Part II'}) RETURN p.name
    Full Context:
    [{'p.name': 'Al Pacino'}, {'p.name': 'Robert De Niro'}]
    
    > Finished chain.





    'Al Pacino and Robert De Niro both played in The Godfather: Part II.'
chain.run("Robert De Niro played in which movies?")
    
    
    > Entering new  chain...
    Generated Cypher:
    MATCH (p:Person {name: 'Robert De Niro'})-[:ActedIn]->(m:Movie)
    RETURN m.name
    Full Context:
    [{'m.name': 'The Godfather: Part II'}]
    
    > Finished chain.





    'Robert De Niro played in The Godfather: Part II.'
chain.run("Robert De Niro is born in which year?")
    
    
    > Entering new  chain...
    Generated Cypher:
    MATCH (p:Person {name: 'Robert De Niro'})-[:ActedIn]->(m:Movie)
    RETURN p.birthDate
    Full Context:
    [{'p.birthDate': '1943-08-17'}]
    
    > Finished chain.





    'Robert De Niro was born on August 17, 1943.'
chain.run("Who is the oldest actor who played in The Godfather: Part II?")
    
    
    > Entering new  chain...
    Generated Cypher:
    MATCH (p:Person)-[:ActedIn]->(m:Movie{name:'The Godfather: Part II'})
    WITH p, m, p.birthDate AS birthDate
    ORDER BY birthDate ASC
    LIMIT 1
    RETURN p.name
    Full Context:
    [{'p.name': 'Al Pacino'}]
    
    > Finished chain.





    'The oldest actor who played in The Godfather: Part II is Al Pacino.'