LangChain Tracing

How to use the python LangChainInstrumentor to trace LangChain

Phoenix has first-class support for LangChain applications.

Launch Phoenix

Install

pip install openinference-instrumentation-langchain langchain_openai

Setup

Use the register function to connect your application to Phoenix:

from phoenix.otel import register

# configure the Phoenix tracer
tracer_provider = register(
  project_name="my-llm-app", # Default is 'default'
  auto_instrument=True # Auto-instrument your app based on installed OI dependencies
)

Run LangChain

By instrumenting LangChain, spans will be created whenever a chain is run and will be sent to the Phoenix server for collection.

from langchain_core.prompts import ChatPromptTemplate
from langchain_openai import ChatOpenAI

prompt = ChatPromptTemplate.from_template("{x} {y} {z}?").partial(x="why is", z="blue")
chain = prompt | ChatOpenAI(model_name="gpt-3.5-turbo")
chain.invoke(dict(y="sky"))

Observe

Now that you have tracing setup, all invocations of chains will be streamed to your running Phoenix for observability and evaluation.

Resources

• Example notebook

• OpenInference package

• Working examples