LangChain Tracing

Phoenix has first-class support for LangChain applications.

Install#

pip install openinference-instrumentation-langchain langchain_openai

Setup#

Connect your application to Phoenix with the register function:

from phoenix.otel import register# configure the Phoenix tracertracer_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 ChatPromptTemplatefrom langchain_openai import ChatOpenAIprompt = 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