MLflow
Learn how to trace your Haystack pipelines with MLflow.
| How to enable | mlflow.haystack.autolog() |
| Content tracing | Captured automatically, including latencies, token usage, cost, and exceptions |
| Package | mlflow |
| Integration guide | https://haystack.deepset.ai/integrations/mlflow |
Overview
MLflow is an open-source platform for managing the end-to-end machine learning and AI lifecycle. MLflow provides native tracing support for Haystack, so you can capture traces from all your pipelines and components with a single line of code.
Installation
Install MLflow:
Usage
Enable automatic tracing for all Haystack pipelines and components:
python
import mlflow
mlflow.haystack.autolog()
# Optionally set an experiment name
mlflow.set_experiment("Haystack")
This automatically captures traces from all Haystack pipelines and components, including latencies, token usage, cost, and any exceptions.
info
Check out the MLflow Haystack integration guide for a full walkthrough with examples.