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Documentation Index

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Neo4j is a leading graph database platform that enables organizations to build intelligent applications that extract business value from connections in their data. Langtrace’s Neo4j integration lets you monitor and trace all your Neo4j database operations, including cypher queries, transaction processing, and GraphRAG operations.

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Setup

  1. Install the Langtrace’s SDK and initialize the SDK in your code.
pip install langtrace-python-sdk
  1. Install the Neo4j python driver.
pip install neo4j
  1. Setup environment variables:
export LANGTRACE_API_KEY=YOUR_LANGTRACE_API_KEY

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Usage

Initialize Langtrace before creating your Phidata agent:
Python
from langtrace_python_sdk import langtrace  # Must precede other imports
from langtrace_python_sdk.utils.with_root_span import with_langtrace_root_span

from neo4j import GraphDatabase

# Create a driver instance
driver = GraphDatabase.driver(NEO4J_URI, auth=(NEO4J_USERNAME, NEO4J_PASSWORD))

# Execute a query
records, summary, keys = driver.execute_query(
    "MATCH (p:Person {age: $age}) RETURN p.name AS name",
    age=42,
    database_="neo4j",
)

# Access results
for person in records:
    print(person["name"])

# Print summary information
print("The query returned {} records in {} ms.".format(
    len(records), summary.result_available_after
))

# Don't forget to close the driver
driver.close()

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What’s being traced?

With Langtrace, the following operations are automatically traced: Query Execution
  • Query text and parameters
  • Execution time and timestamps
  • Query result, counts and metadata
  • Database and routing information
View all these trace details in the Langtrace dashboard: traces traces

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Resources