DSPy Visualization Quickstart

Quickly visualize DSPy notebooks and optimization experiments in LangWatch to support debugging and agent evaluation.

LangWatch DSPy Visualization tracks your DSPy experiments in real time, so you can follow the progress, track costs and debug each step.

1. Install the Python library

Notebook

!pip install langwatch

Command Line

pip install langwatch

2. Login to LangWatch

Import and authenticate the LangWatch SDK:

import langwatch

langwatch.login()

Be sure to log in or create an account using the displayed link, then provide your API key when prompted.

3. Start tracking

Before your DSPy program compilation starts, initialize langwatch with your experiment name and the optimizer to be tracked:

# Initialize langwatch for this run, to track the optimizer compilation
langwatch.dspy.init(experiment="my-awesome-experiment", optimizer=optimizer)

compiled_rag = optimizer.compile(RAG(), trainset=trainset)

Follow your experiment

Open the link provided when the compilation starts or go to your LangWatch dashboard to follow the progress of your experiments:

Wrapping up

With your experiments tracked on LangWatch, you can explore how the training is going and look at the examples, the LLM calls and the different steps, so you can find where to improve your DSPy program.

When you are ready to deploy your DSPy program, you can monitor the inference traces on LangWatch dashboard as well. Check out the Python Integration Guide for more details.

For any questions or issues, feel free to contact our support, join our channel on Discord or open an issue on our GitHub.