I’m working with LangChain and LangSmith for testing different LLM prompts. Everything was running smoothly until I had to regenerate my OpenAI API key.
I updated the new key in my environment variables file and confirmed it works by testing with OpenAI’s chat completion directly. I also manually updated the key in LangSmith through the playground settings and verified it appears correctly in my organization’s secret management section.
But when I execute the arun_on_dataset method, I get this authentication error:
AuthenticationError: Error code: 401 - {'error': {'message': 'Incorrect API key provided: sk-O6ZSB***************************************TNxS. You can find your API key at https://platform.openai.com/account/api-keys.'
The error shows my old API key prefix, which means something is still referencing the outdated key. My code hasn’t changed and worked fine before the key rotation.
Where else might the old API key be cached or stored that I need to update?
First, search your project files for any hardcoded OpenAI keys. I’ve seen devs accidentally commit API keys directly in code or config files - these’ll override your environment variables every time. Run echo $OPENAI_API_KEY in your terminal to make sure your shell actually picked up the new variable. Sometimes you need to refresh the environment after updating your .env file. Also check if you’re using wrapper libraries or custom API clients - they might be caching the old key or need a restart to pick up changes.
Had the same headache a few months ago with multiple API integrations. The problem? You’re dealing with different systems that all cache credentials their own way.
Skip hunting down every cache location. I built automation that handles all my API key rotations at once. When I update keys, it pushes new credentials to everything - LangSmith, environment configs, project settings, all of it.
It also restarts services and clears caches automatically. No more detective work when old key prefixes show up in errors.
Quick fix: check for Docker containers or background services still running with the old key. But seriously, proper key rotation automation saves massive time.
I use Latenode for this workflow automation. Connects to different APIs and handles credential updates across platforms. Way better than manually updating keys in 5 places every time.
Check your LangSmith project settings specifically. The playground settings are separate from where arun_on_dataset actually pulls its keys.
I hit this exact issue last year when rotating keys. LangSmith stores API keys in multiple places and project settings don’t always sync with playground updates.
Go to your project dashboard, click the settings gear for that specific project, and update the OpenAI key there. Evaluation methods like arun_on_dataset read from project configs, not playground settings.
Also check for .langchain or .langsmith config files in your home directory. These hidden files can override everything and are easy to miss.
Restart your Python process after making changes. The LangChain client sometimes caches the initial key it loaded.
Same thing happened to me. LangSmith was caching the old key even after I updated it in playground settings. The evaluation runs kept using the cached version. I fixed it by logging out completely, clearing browser cache, then logging back in. Also restart any Jupyter kernels you’ve got running - they might still have the old key in memory. That key prefix in your error message is a dead giveaway that something’s still holding the old credentials.
ya, I had the same problem b4. just make sure any scripts or services that use the key are also restarted or refreshed. sometimes, they keep the old key in memory or a cache. gl!