Clean up the mlflow trace for tool calling #47
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| # messages should be returned back to the Review App (or any other front end app) and stored there so it can be passed back to this stateless agent with the next turns of converastion. | ||
| "messages": messages_log_with_tool_calls, | ||
| } | ||
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| @mlflow.trace(span_type="AGENT") | ||
| @mlflow.trace(span_type="CHAIN") |
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QQ, why change from agent to chain?
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Mostly asking since this does still seem like the core agentic loop logic
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(same thinking as below)
| + tool_messages | ||
| ) | ||
| i += 1 | ||
| with mlflow.start_span(name=f"iteration_{i}", span_type="CHAIN") as span: |
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Same question here RE "CHAIN" vs "AGENT"
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I mirrored what LangGraph traces looked like here - they use a CHAIN for this type of logic. My thinking: this span represents logic that is actually a deterministic chain of steps.
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Got it, thanks! Do you have a pointer to a LangGraph "CHAIN" tracing example? i'm wondering if LangGraph uses that span name mostly writing a fixed chain, since the logic in this function calling agent thing looks similar to the Python equivalent of a LangGraph agent (e.g. if you translated something like LangGraph create_react_agent into Python code)
Related Issues/PRs
What changes are proposed in this pull request?
Clean up the Mlflow trace from the openai SDK function calling agent. Goal was to make the inputs/outputs + how the iterations run + how the tool function is called more clear in the trace / the code easier to read.
How is this PR tested?