Skip to main content

Prevent logging of inputs and outputs in traces

In some situations, you may need to prevent the inputs and outputs of your traces from being logged for privacy or security reasons. LangSmith provides a way to filter the inputs and outputs of your traces before they are sent to the LangSmith backend.

If you want to completely hide the inputs and outputs of your traces, you can set the following environment variables when running your application:

LANGCHAIN_HIDE_INPUTS=true
LANGCHAIN_HIDE_OUTPUTS=true

This works for both the LangSmith SDK (Python and TypeScript) and LangChain.

You can also customize and override this behavior for a given Client instance. This can be done by setting the hide_inputs and hide_outputs parameters on the Client object. For the example below, we will simply return an empty object for both hide_inputs and hide_outputs, but you can customize this to your needs.

import openai
from langsmith import Client
from langsmith.wrappers import wrap_openai

openai_client = wrap_openai(openai.Client())
langsmith_client = Client(
hide_inputs=lambda inputs: {}, hide_outputs=lambda outputs: {}
)

# The trace produced will have its metadata present, but the inputs will be hidden
openai_client.chat.completions.create(
model="gpt-3.5-turbo",
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Hello!"},
],
langsmith_extra={"client": langsmith_client},
)

# The trace produced will not have hidden inputs and outputs
openai_client.chat.completions.create(
model="gpt-3.5-turbo",
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Hello!"},
],
)

Was this page helpful?


You can leave detailed feedback on GitHub.