MLflow
@mlflow.org
An open source machine learning platform for managing the complete ML lifecycle
🔹 𝗪𝗵𝗼 𝘀𝗵𝗼𝘂𝗹𝗱 𝗮𝗽𝗽𝗹𝘆: open source contributors, speakers, and organizers with a track record in MLOps/AI.
🔹 𝗪𝗵𝘆 𝗷𝗼𝗶𝗻: amplify your impact and shape #GenAI practice in your community with MLflow’s evolving toolkit—spanning evaluation, #LLM/agent tracing, and prompt lifecycle management.
#opensource
🔹 𝗪𝗵𝘆 𝗷𝗼𝗶𝗻: amplify your impact and shape #GenAI practice in your community with MLflow’s evolving toolkit—spanning evaluation, #LLM/agent tracing, and prompt lifecycle management.
#opensource
November 28, 2025 at 9:27 PM
🔹 𝗪𝗵𝗼 𝘀𝗵𝗼𝘂𝗹𝗱 𝗮𝗽𝗽𝗹𝘆: open source contributors, speakers, and organizers with a track record in MLOps/AI.
🔹 𝗪𝗵𝘆 𝗷𝗼𝗶𝗻: amplify your impact and shape #GenAI practice in your community with MLflow’s evolving toolkit—spanning evaluation, #LLM/agent tracing, and prompt lifecycle management.
#opensource
🔹 𝗪𝗵𝘆 𝗷𝗼𝗶𝗻: amplify your impact and shape #GenAI practice in your community with MLflow’s evolving toolkit—spanning evaluation, #LLM/agent tracing, and prompt lifecycle management.
#opensource
With that metadata—and MLflow’s MCP features released recently—the judge can make tool calls to MLflow to search spans and query different aspects of the trace.
Office Hours: Wed, Oct 22: luma.com/officehours1...
#mlflow #agenticjudges #llm #genai
Office Hours: Wed, Oct 22: luma.com/officehours1...
#mlflow #agenticjudges #llm #genai
MLflow Office Hours | October 22 · Zoom · Luma
luma.com
October 15, 2025 at 2:15 PM
With that metadata—and MLflow’s MCP features released recently—the judge can make tool calls to MLflow to search spans and query different aspects of the trace.
Office Hours: Wed, Oct 22: luma.com/officehours1...
#mlflow #agenticjudges #llm #genai
Office Hours: Wed, Oct 22: luma.com/officehours1...
#mlflow #agenticjudges #llm #genai
In this mode, the judge gets the MLflow trace info object: input to the call, output, and basically the root span ID for that trace.
October 15, 2025 at 2:15 PM
In this mode, the judge gets the MLflow trace info object: input to the call, output, and basically the root span ID for that trace.