chore(deps): update dependency mlflow to v3#22
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This PR contains the following updates:
==2.21.3->==3.1.4Release Notes
mlflow/mlflow (mlflow)
v3.1.4Compare Source
MLflow 3.1.4 includes several major features and improvements
Small bug fixes and documentation updates:
#16835, #16820, @daniellok-db
v3.1.3Compare Source
MLflow 3.1.3 includes several major features and improvements
Features:
Bug fixes:
MLFLOW_DEPLOYMENT_PREDICT_TIMEOUTto databricks-sdk (#16783, @bbqiu)Small bug fixes and documentation updates:
#16786, #16692, @daniellok-db; #16594, @ngoduykhanh; #16475, @harupy
v3.1.2Compare Source
MLflow 3.1.2 is a patch release that includes several bug fixes.
Bug fixes:
download_artifactsignoringtracking_uriparameter (#16461, @harupy)Small fixes and documentation updates:
#16568, #16454, #16617, #16605, #16569, #16553, #16625, @B-Step62; #16571, #16552, #16452, #16395, #16446, #16420, #16447, #16554, #16515, @frontsideair; #16558, #16443, #16457, @16442, #16449, @harupy; #16509, #16512, #16524, #16514, #16607, @TomeHirata; #16541, @copilot-swe-agent; #16427, @bbqiu; #16573, @daniellok-db; #16470, #16281, @BenWilson2
v3.1.1Compare Source
MLflow 3.1.1 includes several major features and improvements
Features:
Bug fixes:
Documentation updates:
Small bug fixes and documentation updates:
#16261, @rohitarun-db; #16411, #16352, #16327, #16324, #16279, #16193, #16197, @harupy; #16409, #16348, #16347, #16290, #16286, #16283, #16271, #16223, @TomeHirata; #16326, @mohammadsubhani; #16364, @BenWilson2; #16308, #16218, @serena-ruan; #16262, @raymondzhou-db; #16191, @copilot-swe-agent; #16212, @B-Step62; #16208, @frontsideair; #16205, #16200, #16198, @daniellok-db
v3.1.0: 3️⃣ MLflow 3 3️⃣Compare Source
MLflow 3: Redefining MLOps for the GenAI Era
MLflow 3 is now available to everyone, marking the biggest evolution in the best open-source MLOps platform's history and transforming how millions of developers build, deploy, AI applications. While previous versions focused on traditional ML workflows, MLflow 3 fundamentally reimagines the platform for the GenAI era. This isn't just an update, but a complete paradigm shift that brings enterprise-grade GenAI capabilities to the open source community for the first time.
🎯 Improved Model Tracking for GenAI
MLflow 3 introduces a refined architecture with the new LoggedModel entity as a first-class citizen, moving beyond the traditional run-centric approach. This enables better organization and comparison of GenAI models. agents, deep learning checkpoints, and model variants across experiments.
🔗 Comprehensive Performance Tracking & Observability
Enhanced model tracking provides comprehensive lineage between models, runs, traces, prompts, and evaluation metrics. The new model-centric design allows you to group traces and metrics from different development environments and production, enabling rich comparisons across model versions.
📊 Production-Grade GenAI Evaluation
MLflow's evaluation and monitoring capabilities help you systematically measure, improve, and maintain the quality of your GenAI applications throughout their lifecycle. From development through production, use the same quality scorers to ensure your applications deliver accurate, reliable responses while managing cost and latency. Visit documentation for more details.
👥 Human-in-the-Loop Feedback
Real-world GenAI applications need human oversight. MLflow 3 now tracks human annotations and feedback for model predictions, enabling streamlined human-in-the-loop evaluation cycles. This creates a collaborative environment where data scientists, domain experts, and stakeholders can efficiently improve model quality together.
(Note: Currently available in Databricks Managed MLflow. Open source release coming in the next few months.)
⚡️ State-of-the-Art Prompt Optimization
Transform prompt engineering from art to science. The MLflow Prompt Registry now includes prompt optimization capabilities built on top of the state-of-the-art research, allowing you to automatically improve prompts using evaluation feedback and labeled datasets. This includes versioning, tracking, and systematic prompt engineering workflows.
📚 Revamped Website and Documentation
The MLflow documentation and website has been fully redesigned to support two main user journeys: GenAI development and classic machine learning workflows. The new structure offers dedicated sections for GenAI features (including LLMs, prompt engineering, and tracing), and traditional ML capabilities such as experiment tracking, model registry, deployment, and evaluation.
▶︎▶︎▶︎ Ready to Get Started? ▶︎▶︎▶︎
Get up and running with MLflow 3 in minutes:
Resources:
🌐 New Website | 📖 Documentation | 🎉:Release Notes
🏎️ The Road Ahead 🏎️
It is just the beginning. The open source community continues driving innovation toward the world's best open-source MLOps/LLMOps platform. Here's how you can be part of the journey:
How to Get Involved:
The future of AI development is unified, observable, and reliable. MLflow 3.0 brings that future to the open source community today.
Ready to transform your GenAI workflow? Get started now →
Changelog
mlflow[databricks](#16097, @dbrx-euirim)MlflowSparkStudy(#15418, @lu-wang-dl)spark_udfsupport DBConnect + DBR 15.4 / DBR dedicated cluster (#15968, @WeichenXu123)uv(#15875, @harupy)mlflow.genai.optimize_promptto optimize prompts (#15861, @TomeHirata)ResponsesAgent.predict_stream(#15762, @bbqiu)LogLoggedModelParams(#15717, @artjen)predict_streamin DSPy flavor (#15678, @TomeHirata)search_promptsfunction to list all the prompts registered (#15445, @joelrobin18)DATABRICKS_CONFIG_PROFILEenvironment variable. (#15587, @WeichenXu123)smolagents(#15574, @y-okt)allow_missingparameter inload_prompt(#15371, @joelrobin18)mlflow.get_artifact_uri()usage outside active run (#12902, @Shashank1202)Bug fixes:
mlflow gc(#11773, @oleg-z)include_spans=False(#15634, @dbczumar)global_guideline_adherence(#15572, @artjen)ResourcesfromSystemAuthPolicyinCreateModelVersion(#15485, @aravind-segu)ResponsesAgentinterface update (#15601, #15741, @bbqiu)Breaking changes:
mlflow.genai.promptsnamespace (#16174, @B-Step62)mlflow.evaluate(#15827, @harupy)mlflow.search_trace()to be V3 format (#15643, @B-Step62)Documentation updates:
Small bug fixes and documentation updates:
#16193, #16192, #16171, #16119, #16036, #16130, #16081, #16101, #16047, #16086, #16077, #16045, #16065, #16067, #16063, #16061, #16058, #16050, #16043, #16034, #16033, #15966, #16025, #16015, #16002, #15970, #16001, #15999, #15942, #15960, #15955, #15951, #15939, #15885, #15883, #15890, #15887, #15874, #15869, #15846, #15845, #15826, #15834, #15822, #15830, #15796, #15821, #15818, #15817, #15805, #15804, #15798, #15793, #15797, #15782, #15775, #15772, #15790, #15773, #15776, #15756, #15767, #15766, #15765, #15746, #15747, #15748, #15751, #15743, #15731, #15720, #15722, #15670, #15614, #15715, #15677, #15708, #15673, #15680, #15686, #15671, #15657, #15669, #15664, #15675, #15667, #15666, #15668, #15651, #15649, #15647, #15640, #15638, #15630, #15627, #15624, #15622, #15558, #15610, #15577, #15575, #15545, #15576, #15559, #15563, #15555, #15557, #15548, #15551, #15547, #15542, #15536, #15524, #15531, #15525, #15520, #15521, #15502, #15499, #15442, #15426, #15315, #15392, #15397, #15399, #15394, #15358, #15352, #15349, #15328, #15336, #15335, @harupy; #16196, #16191, #16093, #16114, #16080, #16088, #16053, #15856, #16039, #15987, #16009, #16014, #16007, #15996, #15993, #15991, #15989, #15978, #15839, #15953, #15934, #15929, #15926, #15909, #15900, #15893, #15889, #15881, #15879, #15877, #15865, #15863, #15854, #15852, #15848, @copilot-swe-agent; #16178, #16153, #16155, #15823, #15754, #15794, #15800, #15799, #15615, #15777, #15726, #15752, #15745, #15753, #15738, #15681, #15684, #15682, #15702, #15679, #15623, #15645, #15612, #15533, #15607, #15522, @serena-ruan; #16177, #16167, #16168, #16166, #16152, #16144, #15920, #16134, #16128, #16098, #16059, #16024, #15974, #15917, #15676, #15750, @dbczumar; #16162, #16161, #16137, #16126, #16127, #16099, #16074, #16041, #16040, #16010, #15945, #15697, #15588, #15602, #15581, @rohitarun-db; #16150, #15984, #16125, #16102, #16062, #16060, #15986, #15985, #15983, #15982, #15980, #15763, @smoorjani; #16160, #16149, #16103, #15538, #16055, #16054, #16048, #16012, #16029, #16003, #15940, #15956, #15950, #15906, #15922, #15932, #15930, #15905, #15910, #15902, #15901, #15840, #15896, #15898, #15895, #15850, #15833, #15824, #15819, #15816, #15806, #15803, #15795, #15759, #15791, #15792, #15774, #15769, #15768, #15770, #15755, #15771, #15737, #15690, #15733, #15730, #15687, #15660, #15735, #15688, #15705, #15590, #15663, #15665, #15658, #15594, #15620, #15644, #15648, #15605, #15639, #15642, #15619, #15618, #15611, #15597, #15589, #15580, #15593, #15437, #15584, #15582, #15448, #15351, #15317, #15353, #15320, #15319, @B-Step62; #16151, #16142, #16111, #16106, #16051, #16046, #16044, #15971, #15957, #15810, #15749, #15706, #15683, #15728, #15732, #15707, #15621, #15567, #15566, #15523, #15479, #15404, #15400, #15378, @TomeHirata; #16026, #16072, @AveshCSingh; #15967, @euirim; #15884, #15924, #15395, #15393, #15390, @daniellok-db; #15786, @rahuja23; #15734, @lhrotk; #15809, #15739, #15695, #15654, #15694, #15655, #15653, #15608, #15543, #15573, @dhruyads; #15596, @mrharishkumar; #15742, #15723, #15633, #15606, @ShaylanDias; #15703, #15637, #15613, #15473, @joelrobin18; #15636, #15659, #15616, #15617, @raymondzhou-db; #15674, #15598, #15357, #15586, @WeichenXu123; #15691, @artjen; #15698, @prithvikannan; #15631, @hubertzub-db; #15569, @Anand1923; #15578, @y-okt; #14790, @singh-kristian; #14129, @jamblejoe; #15552, @BenWilson2; #14197, @clarachristiansen; #15505, @Conor0Callaghan; #15509, @tr33k; #15507, @vzamboulingame; #15459, @UnMelow; #13991, @abhishekpawar1060; #12161, @zhouyou9505; #15293, @tornikeo
v3.0.1Compare Source
MLflow 3.0.1 includes several major features and improvements
Features:
Bug fixes:
Small bug fixes and documentation updates:
#16364, @BenWilson2; #16347, @TomeHirata; #16279, #15835, @harupy; #16182, @B-Step62
v3.0.0Compare Source
See https://github.com/mlflow/mlflow/releases/tag/v3.1.0.
v2.22.1Compare Source
MLflow 2.22.1 includes several major features and improvements
Features:
Bug fixes:
Configuration
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