> ## Documentation Index
> Fetch the complete documentation index at: https://langwatch.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Tracking Custom DSPy Optimizer

> Track custom DSPy optimizer logic in LangWatch to visualize optimization steps and improve AI agent testing workflows.

If you are building a custom DSPy optimizer, then LangWatch won't support tracking it out of the box, but adding track to any custom optimizer is also very simple.

## 1. Initialize LangWatch DSPy with optimizer=None

Before the compilation step, explicitly provide `None` on the `optimizer` parameter to be able to track the steps manually:

```python  theme={null}
langwatch.dspy.init(experiment="dspy-custom-optimizer-example", optimizer=None)

compiled_rag = my_awesome_optimizer.compile(RAG(), trainset=trainset)
```

## 2. Track the metric function

Either before instantiating your optimizer, or inside the compilation step, don't forget to wrap the metric function with `langwatch.dspy.track_metric` so that it's tracked:

```python  theme={null}
metric = langwatch.dspy.track_metric(metric)
```

## 3. Track each step

Now at each step your optimizer progresses, call `langwatch.dspy.log_step` to capture the score at the current step index, optimizer info and predictors being used on this step evaluation:

```python  theme={null}
langwatch.dspy.log_step(
    optimizer=DSPyOptimizer(
        name="MyAwesomeOptimizer",
        parameters={
            "hyperparam": 1,
        },
    ),
    index="1", # step index
    score=0.5,
    label="score",
    predictors=candidate_program.predictors(),
)
```

The LLM calls and examples being evaluated with be tracked automatically and logged in together with calling `log_step`.

## Wrapping up

That's it! You should see the steps of the optimizer in the LangWatch dashboard now.

For any questions or issues, feel free to contact our support, join our channel on [Discord](https://discord.com/invite/kT4PhDS2gH) or [open an issue](https://github.com/langwatch/langwatch/issues) on our GitHub.