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Available via: OpenTelemetry auto-instrumentation (Python). This is not a Zespan SDK wrapper — see Send traces from any OTel-instrumented app for how the underlying endpoint works.
OpenInference’s openinference-instrumentation-dspy package instruments DSPy’s module and predictor calls (Predict, ChainOfThought, ReAct, and DSPy’s own LM calls underneath) so every step of a DSPy pipeline — including compiled/optimized programs — shows up as a span, no changes to your DSPy code.

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Installation

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Setup

Use BatchSpanProcessor instead of SimpleSpanProcessor in production — the example above uses SimpleSpanProcessor (synchronous, one export per span) since it’s simpler for a first run, but it adds latency to every call at real traffic volume.

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What gets captured

Each DSPy module invocation and its underlying LM call become spans in the same trace, so a compiled multi-step pipeline (retrieval, reasoning, self-refinement) shows up as one flame graph rather than disconnected calls. Fields map through the standard OpenTelemetry GenAI semantic conventions Zespan reads — model, tokens, prompts, and completions per step.