error in dummy_agent_library.ipynb notebook in unit 1
HI
I try to run the notebook using the "meta-llama/Llama-3.3-70B-Instruct" model but get the error : "The endpoint is paused, ask a maintainer to restart it"
can someone please check?
I have the same error since yesterday 2 PM EST time.
Good catch on the error in dummy_agent_library.ipynb. Without seeing the exact traceback you're hitting, the most common failure points in that notebook are around the tool-calling loop — specifically when the agent library tries to parse the LLM's output and dispatch to the right tool. If you're getting a KeyError or AttributeError around the action parsing step, it's usually because the model being called isn't reliably returning JSON-structured tool calls, and the dummy library doesn't have robust fallback handling for malformed outputs.
A few things worth checking: make sure your API key environment variable is set correctly before the cell that initializes the client, and verify that the model endpoint you're hitting actually supports the function-calling format the notebook expects. The agents-course/notebooks repo targets a specific message format, and if you're routing through a different provider or model version than intended, the response schema can drift enough to break the parser silently. Also check whether the FinalAnswerTool is being registered properly — there's a known issue where if the tool registry isn't populated before the agent loop starts, it exits immediately without useful error output.
On a broader note, this kind of fragility in tool dispatch is actually a real problem in production multi-agent systems, not just tutorial notebooks. When you have agents dynamically invoking tools or other agents, verifying that the callee is actually who you expect — and that its outputs meet a schema contract — becomes critical. That's the space AgentGraph is working in, building identity and trust primitives for agent-to-agent calls. But for your immediate issue, sharing the full traceback and which model/provider you're using would help narrow it down fast.