Automate detection of unreliable LLM outputs by combining MLflow tracing with @CleanlabAI's Trustworthy Language Models (TLM). 🚀 This blog post covers: ✅ Setting up MLflow to capture complete LLM interactions, including system prompts. ✅ Retrieving traces and efficiently batch-evaluating them with TLM to get trustworthiness scores and explanations—without ground truth labels. ✅ Tagging each MLflow trace with its trust score and explanation for ongoing review. ✅ Using MLflow Evaluation with a custom TLM metric to systematically compare model outputs. For the full guide and code samples, read more ➡️ mlflow.org/blog/tlm-tracing #opensource #llm #oss #mlflow #cleanlab

Curious about how to systematically evaluate and improve the trustworthiness of your LLM applications? 🤔 Check out how @CleanlabAI's Trustworthy Language Models (TLM) integrates with #MLflow! TLM analyzes both prompts and responses to flag potentially untrustworthy outputs-no ground truth labels required. ✅ By combining #TLM with MLflow's tracing and evaluation capabilities, you can automatically log, track, and analyze trustworthiness scores for every #LLM interaction. This workflow makes it easy to spot hallucinations and debug your AI applications at scale. Ready to make your LLMs more reliable? 👇 🔗 Dive in: mlflow.org/blog/tlm-tracing #opensource #oss #linuxfoundation

BLOG - Automatically find the bad LLM responses in your LLM Evals with @CleanlabAI: mlflow.org/blog/tlm-tracing

Join us for the next MLflow Community Meetup — Wednesday, April 23 at 4PM PT! 🗓️ 👉 REGISTER: lu.ma/mlflow423 We’re bringing two exciting presentations to the community: 🔹MLflow + #DSPy Integration Discover new features that integrate MLflow with DSPy — including compilation tracking, tracing enhancements, and a preview of expanded capabilities on the way. 🔹 @CleanlabAI + MLflow Learn how Cleanlab can enhance your MLflow workflows by adding automation and trust to every data point and prediction — especially in AI and RAG pipelines. 🎥 The event will be livestreamed on YouTube, LinkedIn, and X. 💬 Bring your questions — we'll be taking them live from the audience! Don’t miss this opportunity to connect with the MLflow community and explore powerful new tooling. #opensource #oss #mlflow #linuxfoundation

🚀 New on the MLflow blog: Automatically find the bad LLM responses in your LLM Evals with @CleanlabAI! Cleanlab’s Trustworthy Language Models (TLM) analyze prompts and responses to calculate a 𝚝𝚛𝚞𝚜𝚝𝚠𝚘𝚛𝚝𝚑𝚒𝚗𝚎𝚜𝚜_𝚜𝚌𝚘𝚛𝚎 — flagging potentially incorrect or hallucinated outputs, no ground truth labels required. In this guide, learn how to: ✅ Apply TLM to LLM responses captured with MLflow tracing ✅ Log, track, and analyze trustworthiness scores and explanations ✅ Use MLflow Evaluation to compare scores across runs 🔗 Check out the full guide: mlflow.org/blog/tlm-tracing #opensource #mlflow #cleanlab #oss #llm