i ran the deepagent on my machine, works perfectly but once deployed and with a paid seat:
TypeError(‘“Could not resolve authentication method. Expected either api_key or auth_token to be set. Or for one of the X-Api-Key or Authorization headers to be explicitly omitted”’)Traceback (most recent call last):
File “/usr/local/lib/python3.11/site-packages/langgraph/pregel/main.py”, line 2971, in astream
async for _ in runner.atick(…
And no documentation of any help would work, its own Studio failed repeatedly the ai help in langchain keeps on insisting to add anthropic key, langsmith secret key and so on .
Not a single success api call and test for hours trying to unravel what should have been a too making agent deployment easier.
yup i set it in the settings → workspace → secrets
ANTHROPIC_API_KEY
In fact i done this twice by deleting and setting it again in case the first one has a typo on the value.
Ah I see the misunderstanding. LangSmith observability secrets are entirely different than the environment for a given agent server / LangGraph app you’re deploying.
You need to configure environment for a specific deployment. You can do so by clicking “New revision” and adding the relevant variables.
can u kindly provide also a simple script in python or curl where i could send a “hello world” to my deployed agent and get back some response. the docs don’t even have this example. The “assistand id” isnt even obvious or copyable anywhere in the deployment screen and not an id that was needed in the console version, i dont get why the deploy version is just so drastically diff and difficult.
If you would like to invoke the agent via python, I recommend using the langsmith deployment sdk. Here is a good example: Manage assistants - Docs by LangChain . As mentioned in that section, you can pass either a graph ID or assistant ID when running your graph.
