Okay, this is a detailed explanation of how telemetry and assertions are handled in two different examples (AgentInspect and Promptfoo) within a larger system likely involving AI agents and tools. Let's break down the key takeaways and summarize the differences.
Overall Context:
The text describes a system designed to test and evaluate AI agents that use tools. A crucial aspect is capturing detailed telemetry data about how the agent operates – which tools are used, in what order, any errors encountered, etc. This allows for automated verification of the agent's behavior against expected patterns.
1. AgentInspect Example:
- Telemetry: Uses automatic instrumentation through an official AI SDK adapter. This likely means a library or framework is automatically adding code to track events within the agent's execution.
- Artifacts: Produces
trace.jsonl(likely JSON lines format for trace data) andeval.json. - Evaluation: Uses built-in checks via
evalRun(), which seems to be a core function for verifying the agent's performance. This function likely incorporates the telemetry data to determine if the run was successful.
2. Promptfoo Example:
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