What is UpTrain used for?

UpTrain is a free, Apache-licensed, open-source platform for evaluating and improving generative AI applications with preconfigured checks and root-cause analysis on failures. It is a good fit for evaluating LLM output quality before release and monitoring generative AI apps for failures.

Is UpTrain open source?

Yes. UpTrain is open source under the Apache-2.0 licence. Its source code is on GitHub at uptrain-ai/uptrain and is written mainly in Python.

Yes. UpTrain is open source, so the software itself is free to use.

Can I self-host UpTrain?

Yes. UpTrain can be self-hosted on your own server or infrastructure.

What is UpTrain an alternative to?

UpTrain is an open-source alternative to Weights & Biases, Braintrust and Galileo. Other open-source alternatives to Weights & Biases include Opik, Laminar and Langfuse.

Is UpTrain actively maintained?

The most recent commit to UpTrain was on 18 August 2024, and the latest release is v0.7.1, published on 14 May 2024. The project has 2.4k stars on GitHub.

UpTrain: open-source alternative to Weights & Biases

About UpTrain

UpTrain is an open-source platform aimed at teams building generative AI applications who need a structured way to evaluate output quality rather than eyeballing responses manually. It targets common LLM reliability problems such as hallucination and jailbreak attempts, alongside more general prompt and output quality checks.

It provides grades for more than 20 preconfigured checks covering language, code and embedding-based use cases, and when a check fails, it performs root cause analysis on the failure case and gives insights on how to resolve it, rather than just reporting a pass/fail score. Its topics also cover experimentation, prompt engineering support, and comparisons to tools such as OpenAI Evals, positioning it within the broader LLMOps evaluation space.

UpTrain is written in Python and released under the Apache-2.0 license, so it can be run and self-hosted as part of an existing ML or LLM pipeline. It is aimed at developers integrating evaluation directly into their generative AI development and monitoring workflow.

Key features

20-plus preconfigured LLM evaluation checks
Hallucination and jailbreak detection
Root cause analysis on failing checks
Embedding, language and code use-case coverage
Self-hosted LLMOps evaluation pipeline

Good fit for

→Evaluating LLM output quality before release
→Monitoring generative AI apps for failures

Built with: Python
Tags: llmops; ai-evaluation; hallucination-detection; python; monitoring; prompt-engineering; self-hosted

UpTrain: questions and answers

What is UpTrain used for?: UpTrain is a free, Apache-licensed, open-source platform for evaluating and improving generative AI applications with preconfigured checks and root-cause analysis on failures. It is a good fit for evaluating LLM output quality before release and monitoring generative AI apps for failures.
Is UpTrain open source?: Yes. UpTrain is open source under the Apache-2.0 licence. Its source code is on GitHub at uptrain-ai/uptrain and is written mainly in Python.
Is UpTrain free?: Yes. UpTrain is open source, so the software itself is free to use.
Can I self-host UpTrain?: Yes. UpTrain can be self-hosted on your own server or infrastructure.
What is UpTrain an alternative to?: UpTrain is an open-source alternative to Weights & Biases, Braintrust and Galileo. Other open-source alternatives to Weights & Biases include Opik, Laminar and Langfuse.
Is UpTrain actively maintained?: The most recent commit to UpTrain was on 18 August 2024, and the latest release is v0.7.1, published on 14 May 2024. The project has 2.4k stars on GitHub.