Documentation Index
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Phoenix has first-class support for LangChain applications.
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
