neuml/mlflow-txtai

MLflow automatic tracing for txtai

39
/ 100
Emerging

This tool helps machine learning engineers and data scientists keep track of how their AI models, specifically those built with txtai, process information. It automatically logs key steps like text extraction, embedding lookups, and how RAG (Retrieval Augmented Generation) pipelines and agents function. You get a detailed record of inputs, outputs, and the model's intermediate decisions, making it easier to understand and debug complex AI workflows.

No commits in the last 6 months. Available on PyPI.

Use this if you are building AI applications with txtai and need a robust way to monitor, debug, and optimize the performance and behavior of your text-based models and pipelines.

Not ideal if you are not using txtai for your AI workflows or if you only need to track high-level model metrics without detailed tracing of each operational step.

AI Development Natural Language Processing Model Observability Experiment Tracking Machine Learning Operations
Stale 6m
Maintenance 2 / 25
Adoption 5 / 25
Maturity 25 / 25
Community 7 / 25

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Stars

11

Forks

1

Language

Python

License

Apache-2.0

Last pushed

Jun 22, 2025

Commits (30d)

0

Dependencies

2

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