DSPy

Wrap a DSPy module with neatlogs.wrap() and its module runs (CHAIN), LM calls (LLM), and retrieval (RETRIEVER) are captured. Wrapping a dspy.Module self-roots — the module run becomes the trace root — so a single run renders in the dashboard with no extra code.

Prerequisites

pip install -U "neatlogs[dspy]" dspy

Usage

import os
import neatlogs
import dspy

neatlogs.init(api_key=os.environ["NEATLOGS_API_KEY"], workflow_name="dspy-demo")

dspy.configure(lm=dspy.LM("openai/gpt-4o"))

class QA(dspy.Module):
    def __init__(self):
        super().__init__()
        self.answer = dspy.Predict("question -> answer")

    def forward(self, question: str):
        return self.answer(question=question)

program = neatlogs.wrap(QA())

result = program(question="In one sentence, what is DSPy?")
print(result.answer)

neatlogs.flush()
neatlogs.shutdown()

wrap() works on any DSPy version. If you call a bare predictor (e.g. dspy.Predict(...)) outside a dspy.Module, the LM span self-roots on its own; wrap a dspy.Module (as above) to group a multi-step program under one root.

A runnable end-to-end example lives at examples/sdk_examples/dspy_basic.py in the SDK repo.