Trace with Anthropic

The Anthropic wrapper methods in Python (wrap_anthropic) and Typescript (wrapAnthropic) allow you to wrap your Anthropic client in order to log traces automatically. Using the wrapper ensures that messages, including tool calls and multimodal content blocks will be rendered nicely in LangSmith. The wrapper works seamlessly alongside the @traceable decorator (Python) or traceable function (TypeScript), so you can trace your Anthropic calls with the wrapper and trace other parts of your application with the decorator or function.

The LANGSMITH_TRACING environment variable must be set to 'true' in order for traces to be logged to LangSmith, even when using wrap_anthropic or wrapAnthropic. This allows you to toggle tracing on and off without changing your code.

Additionally, you will need to set the LANGSMITH_API_KEY environment variable to your API key (see Setup for more information).

If your LangSmith API key is linked to multiple workspaces, set the LANGSMITH_WORKSPACE_ID environment variable to specify which workspace to use.

By default, the traces will be logged to a project named default. To log traces to a different project, see this section.

Python

import anthropic
from langsmith import traceable
from langsmith.wrappers import wrap_anthropic

client = wrap_anthropic(anthropic.Anthropic())

@traceable(run_type="tool", name="Retrieve Context")
def my_tool(question: str) -> str:
  return "During this morning's meeting, we solved all world conflict."

@traceable(name="Chat Pipeline")
def chat_pipeline(question: str):
  context = my_tool(question)
  messages = [
      { "role": "user", "content": f"Question: {question}\nContext: {context}"}
  ]
  message = client.messages.create(
      model="claude-sonnet-4-5-20250929",
      messages=messages,
      max_tokens=1024,
      system="You are a helpful assistant. Please respond to the user's request only based on the given context."
  )
  return message

chat_pipeline("Can you summarize this morning's meetings?")

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