Example Eval - LangChain

from langchain_openai import ChatOpenAI
from langchain_core.prompts import ChatPromptTemplate

llm = ChatOpenAI(model="gpt-4o-mini", temperature=0)
chain = ChatPromptTemplate.from_messages([
    ("system", "You are a helpful support agent."),
    ("human", "{query}"),
]) | llm

def langchain_agent(case):
    result = chain.invoke({"query": case.query})
    return {"output": result.content, "metadata": {"framework": "langchain"}}

report = (
    client.evaluations
    .run(dataset_id="...", subject={"kind": "custom_agent", "displayName": "LangChain Bot", "framework": "langchain"})
    .execute(langchain_agent)
    .finalize()
    .analyze()
)