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If you’re not seeing traces in your tracing project or notice traces logged to the wrong project/workspace, the issue might be due to LangSmith’s default environment variable caching. This is especially common when running LangSmith within a Jupyter notebook. Follow these steps to diagnose and resolve the issue:

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1. Verify Your Environment Variables

First, check that the environment variables are set correctly by running: 
import os
print(os.getenv("LANGSMITH_PROJECT"))
print(os.getenv("LANGSMITH_TRACING"))
print(os.getenv("LANGSMITH_ENDPOINT"))
print(os.getenv("LANGSMITH_API_KEY"))
If the output does not match what’s defined in your .env file, it’s likely due to environment variable caching.

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2. Clear the cache

Clear the cached environment variables with the following command: 
utils.get_env_var.cache_clear()

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3. Reload the Environment Variables

Reload your environment variables from the .env file by executing: 
from dotenv import load_dotenv
import os
load_dotenv(<path to .env file>, override=True)
After reloading, your environment variables should be set correctly. If you continue to experience issues, please reach out to us via a shared Slack channel or email support (available for Plus and Enterprise plans), or in the LangChain Forum.
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