MLflow 2.21.3

MLflow 2.21.3 includes a few bug fixes and feature updates.

Features:

• [Tracing] Add return_type argument to mlflow.search_traces() API (#15085, @B-Step62)

Bug fixes:

• [Tracking] Fix spark ML save model error in Databricks shared or serverless cluster (#15198, @WeichenXu123)
• [Tracking] Fix Spark model logging / loading in Databricks shared cluster and serverless (#15075, @WeichenXu123)

Documentation updates:

• [Docs] Add document page for DSPy optimizer tracking (#15143, @TomeHirata)

Small bug fixes and documentation updates:

#15205, @mlflow-app[bot]; #15184, #15157, #15137, @TomeHirata; #15118, @bbqiu; #15172, @harupy

MLflow 2.21.2

MLflow 2.21.2 is a patch release that introduces minor features and bug fixes.

• Fix connection exhausting when exporting traces to Databricks (#15124, @B-Step62)
• Add logging of result table for DSPy optimizer tracking (#15061, @TomeHirata)

MLflow 2.21.1

MLflow 2.21.1 is a patch release that introduces minor features and addresses some minor bugs.

Features:

• [Tracking] Introduce support for logging evaluations within DSPy (#14962, @TomeHirata)
• [Tracking] Add support for run creation when DSPy compile is executed (#14949, @TomeHirata)
• [Docker / Sagemaker] Add support for building a SageMaker serving container that does not contain Java via the --install-java option (#14868, @rgangopadhya)

Bug fixes:

• [Tracing] Fix an issue with trace ordering due to a timestamp conversion timezone bug (#15094, @orm011)
• [Tracking] Fix a typo in the environment variable OTEL_EXPORTER_OTLP_PROTOCOL definition (#15008, @gabrielfu)
• [Tracking] Fix an issue in shared and serverless clusters on Databricks when logging Spark Datasources when using the evaluate API (#15077, @WeichenXu123)
• [UI] Fix a rendering issue with displaying images from within the metric tab in the UI (#15034, @TomeHirata)

Documentation updates:

• [Docs] Add additional contextual information within the set_retriever_schema API docs (#15099, @smurching)

Small bug fixes and documentation updates:

#15009, #14995, #15039, #15040, @TomeHirata; #15010, #15053, @B-Step62; #15014, #15025, #15030, #15050, #15070, @Gumichocopengin8; #15035, #15064, @joelrobin18; #15058, @serena-ruan; #14945, @turbotimon

MLflow 2.21.0

We are excited to announce the release of MLflow 2.21.0! This release includes a number of significant features, enhancements, and bug fixes.

Major New Features

• 📚 Documentation Redesign: MLflow documentation is fully revamped with a new MDX-based website that provides better navigation and makes it easier to find the information you need! (#13645, @daniellok-db)
• 🤖 Prompt Registry: MLflow Prompt Registry is a powerful tool that streamlines prompt engineering and management in your GenAI applications. It enables you to version, track, and reuse prompts across your organization. (#14795, #14834, #14936, @B-Step62, #14960, #14984, @daniellok-db, #14909, @hubertzub-db)
• ⚡️ FastAPI Scoring Server: The MLflow inference serverhas been migrated from Flask to FastAPI, enabling ASGI-based scalable inference for improved performance and throughput. (#14307, @TomeHirata)
• 🔍 Enhanced Tracing Capabilities: MLflow Tracing now supports synchronous/asynchronous generators and auto-tracing for Async OpenAI, providing more flexible and comprehensive tracing options. (#14459, #14400, #14793, @14792, @B-Step62)

Features:

• [Tracking] Support OpenAI Agent SDK Auto Tracing (#14987, @B-Step62)
• [Sqlalchemy / Tracking] Support mysql ssl connections with client certs (#14839, @aksylumoed)
• [Artifacts] Supports ADLS artifact repo (#14723, @serena-ruan)
• [Tracking] Add import and docs for txtai integration (#14712, @B-Step62)
• [Models] Introduce User Auth Policy for Pyfunc Models (#14538, @aravind-segu)
• [Tracking] Support new Google GenAI SDK (#14576, @TomeHirata)
• [Tracking] Support generating traces from DSPy built-in compilation and evaluation (#14400, @B-Step62)
• [Tracking] Add mlflow.log_trace API (#14418, @TomeHirata)
• [Models] ChatAgent LangGraph and LangChain Connectors (#14215, @bbqiu)

Bug fixes:

• [Models] Fix infinite recursion error with warning handler module (#14954, @BenWilson2)
• [Model Registry] Fix invalid type issue for ModelRegistry RestStore (#14980, @B-Step62)
• [Tracking] Fix: ExperimentViewRunsControlsActionsSelectTags doesn't set loading state to false when set-tag request fails. (#14907, @harupy)
• [Tracking] Fix a bug in tag creation where tag values containing ": " get truncated (#14896, @harupy)
• [Tracking] Fix false alert from AMD GPU monitor (#14884, @B-Step62)
• [Tracking] Fix mlflow.doctor to fall back to mlflow-skinny when mlflow is not found (#14782, @harupy)
• [Models] Handle LangGraph breaking change (#14794, @B-Step62)
• [Tracking] Fix DSPy tracing in serving (#14743, @B-Step62)
• [Tracking] Add limit to the length of experiment artifact locations (#14416, @daniellok-db)
• [Build] Fix build.py to restore specific files #14444 (#14448, @arunkothari84)
• [Models] Fix false alert for ChatModel type hint (#14343, @B-Step62)
• [Model Registry] use aes256 to talk to s3 (#14354, @artjen)
• [Tracking] Fix LiteLLM autologging (#14340, @B-Step62)
• [Models] Fix ChatCompletionResponse for model serving Pydantic 1.x (#14332, @BenWilson2)

Documentation updates:

• [Tracking] Add guide about using MLflow tracing across thread (#14881, @B-Step62)
• [Docs] Add guide for tracing deepseek (#14826, @B-Step62)
• [Docs] Update llama Jupyter notebook source (#14754, @emmanuel-ferdman)
• [Docs] Replace Databricks Community Edition with Lighthouse [1] (#14642, @TomeHirata)
• [Docs] Update models from code guide and chat model guide to always recommend models from code (#14370, @smurching)
• [Artifacts] [DOC-FIX #14183] Improve documentation for 'artifact_uri' in 'download_artifacts' (#14225, @vinayakkgarg)

Small bug fixes and documentation updates:

#14994, #14992, #14990, #14979, #14964, #14969, #14944, #14948, #14957, #14958, #14942, #14940, #14935, #14929, #14805, #14876, #14833, #14748, #14744, #14666, #14668, #14664, #14667, #14580, #14475, #14439, #14397, #14363, #14361, #14377, #14378, #14337, #14324, #14339, #14259, @B-Step62; #14981, #14943, #14914, #14930, #14924, #14927, #14786, #14910, #14859, #14891, #14883, #14863, #14852, #14788, @Gumichocopengin8; #14946, #14978, #14956, #14906, #14903, #14854, #14860, #14857, #14824, #14830, #14767, #14772, #14770, #14766, #14651, #14629, #14636, #14572, #14498, #14328, #14265, @serena-ruan; #14989, #14895, #14880, #14878, #14866, #14821, #14817, #14815, #14765, #14803, #14773, #14783, #14784, #14776, #14759, #14541, #14553, #14540, #14499, #14495, #14481, #14479, #14456, #14022, #14411, #14407, #14408, #14315, #14346, #14325, #14322, #14326, #14310, #14309, #14320, #14308, @daniellok-db; #14986, #14904, #14898, #14893, #14861, #14870, #14853, #14849, #14813, #14822, #14818, #14802, #14804, #14814, #14779, #14796, #14735, #14731, #14728, #14734, #14727, #14726, #14721, #14719, #14716, #14692, #14683, #14687, #14684, #14674, #14673, #14662, #14652, #14650, #14648, #14647, #14646, #14639, #14637, #14635, #14634, #14633, #14630, #14628, #14624, #14623, #14621, #14619, #14615, #14613, #14603, #14601, #14600, #14597, #14570, #14564, #14554, #14551, #14550, #14515, #14529, #14528, #14525, #14516, #14514, #14486, #14476, #14472, #14477, #14364, #14431, #14414, #14398, #14412, #14399, #14359, #14369, #14381, #14349, #14350, #14347, #14348, #14342, #14329, #14250, #14318, #14323, #14306, #14280, #14279, #14272, #14270, #14263, #14222, @harupy; #14985, #14850, #14800, #14799, #14671, #14665, #14594, #14506, #14457, #14395, #14371, #14360, #14327, @TomeHirata; #14755, #14567, #14367, @bbqiu; #14892, @brilee; #14941, #14932, @hubertzub-db; #14913, @joelrobin18; #14756, @jiewpeng; #14701, @jaceklaskowski; #14568, #14450, @BenWilson2; #14535, @njbrake; #14507, @arunprd; #14489, @RuchitAgrawal; #14467, @seal07; #14460, @ManzoorAhmedShaikh; #14374, @wasup-yash; #14333, @singh-kristian; #14362, #14353, #14296, #13789, @dsuhinin; #14358, @apoxnen; #14335, @Fresnel-Fabian; #14178, @emmanuel-ferdman

MLflow 2.21.0rc0

Release Candidate

MLflow 2.21.0rc0 is a pre-release for testing out major features planned in the stable release. To install, run the following command:

pip install mlflow==2.21.0rc0

Please try it out and report any issues on the issue tracker!

Major New Features

• 📚 Documentation Redesign: MLflow documentation is fully revamped with a new MDX-based website that provides better navigation and makes it easier to find the information you need!
• ⚡️ FastAPI Scoring Server: The MLflow inference server has been migrated from Flask to FastAPI, enabling ASGI-based scalable inference for improved performance and throughput.
• 🔍 Enhanced Tracing Capabilities: MLflow Tracing now supports synchronous/asynchronous generators and auto-tracing for Async OpenAI, providing more flexible and comprehensive tracing options.

Deprecations

The following features are marked for deprecation:

• MLflow Recipes
• fastai and f2o flavors

MLflow 2.20.3

MLflow 2.20.3 is a patch release includes several major features and improvements

Features:

• Implemented GPU metrics for AMD/HIP GPUs (#12694, @evenmn)
• Add txtai tracing integration (#14712, @B-Step62)
• Support new Google GenAI SDK (#14576, @TomeHirata)
• Support the new thinking content block in Anthropic Claude 3.7 models (#14733, @B-Step62)

Bug fixes:

• Resolve LangGraph tracing bug with astream_event API (#14598, @B-Step62)

Small bug fixes and documentation updates:

#14640, #14574, #14593, @serena-ruan; #14338, #14693, #14664, #14663, #14377, @B-Step62; #14680, @JulesLandrySimard; #14388, #14685, @harupy; #14704, @brilee; #14698, #14658, @bbqiu; #14660, #14659, #14632, #14616, #14594, @TomeHirata; #14535, @njbrake

MLflow 2.20.2

MLflow 2.20.2 is a patch release includes several bug fixes and features

Features:

• [Tracing] Support tracing sync/async generator function with @mlflow.trace (#14459, @B-Step62)
• [Tracing] Support generating traces from DSPy built-in compilation and evaluation (#14400, @B-Step62)
• [Models] ChatAgent interface enhancements and Langgraph connectors updates (#14368, #14567, @bbqiu)
• [Models] VariantType support in spark_udf (#14317, @serena-ruan)

Bug fixes:

• [Models] DSPy thread issue fix (#14471, @chenmoneygithub)

Documentation updates:

• [Docs] ChatAgent documentation updates (#14367, @bbqiu)

Small bug fixes and documentation updates:

#14410, #14569, #14440, @harupy; #14510, #14544, #14491, #14488, @bbqiu; #14518, @serena-ruan; #14517, #14500, #14461, #14478, @TomeHirata; #14512, @shaikmoeed; #14496, #14473, #14475, @B-Step62; #14467, @seal07; #14022, #14453, #14539, @daniellok-db; #14450, @BenWilson2; #14449, @SaiMadhavanG

MLflow 2.20.1

MLflow 2.20.1 is a patch release includes several bug fixes and features:

Features:

• Spark_udf support for the model signatures based on type hints (#14265, @serena-ruan)
• Helper connectors to use ChatAgent with LangChain and LangGraph (#14215, @bbqiu)
• Update classifier evaluator to draw RUC/Lift curves for CatBoost models by default (#14333, @singh-kristian)

Bug fixes:

• Fix Pydantic 1.x incompatibility issue (#14332, @BenWilson2)
• Apply temporary fix for LiteLLM tracing to workaround BerriAI/litellm#8013 (#14340, @B-Step62)
• Fix false alert from type hint based model signature for ChatModel (#14343, @B-Step62)

Other small updates:

#14337, #14382, @B-Step62; #14356, @daniellok-db, #14354, @artjen, #14360, @TomuHirata,

MLflow 2.20.0

We are excited to announce the release of MLflow 2.20.0! This release includes a number of significant features, enhancements, and bug fixes.

Major New Features

• 💡Type Hint-Based Model Signature: Define your model's signature in the most Pythonic way. MLflow now supports defining a model signature based on the type hints in your PythonModel's predict function, and validating input data payloads against it. (#14182, #14168, #14130, #14100, #14099, @serena-ruan)

• 🧠 Bedrock / Groq Tracing Support: MLflow Tracing now offers a one-line auto-tracing experience for Amazon Bedrock and Groq LLMs. Track LLM invocation within your model by simply adding mlflow.bedrock.tracing or mlflow.groq.tracing call to the code. (#14018, @B-Step62, #14006, @anumita0203)

• 🗒️ Inline Trace Rendering in Jupyter Notebook: MLflow now supports rendering a trace UI within the notebook where you are running models. This eliminates the need to frequently switch between the notebook and browser, creating a seamless local model debugging experience. Check out this blog post for a quick demo! (#13955, @daniellok-db)

• ⚡️Faster Model Validation with uv Package Manager: MLflow has adopted uv, a new Rust-based, super-fast Python package manager. This release adds support for the new package manager in the mlflow.models.predict API, enabling faster model environment validation. Stay tuned for more updates! (#13824, @serena-ruan)

• 🖥️ New Chat Panel in Trace UI: THe MLflow Trace UI now shows a unified chat panel for LLM invocations. The update allows you to view chat messages and function calls in a rich and consistent UI across LLM providers, as well as inspect the raw input and output payloads. (#14211, @TomuHirata)

Other Features:

• Introduced ChatAgent base class for defining custom python agent (#13797, @bbqiu)
• Supported Tool Calling in DSPy Tracing (#14196, @B-Step62)
• Applied timeout override to within-request local scoring server for Spark UDF inference (#14202, @BenWilson2)
• Supported dictionary type for inference params (#14091, @serena-ruan)
• Make context parameter optional for calling PythonModel instance (#14059, @serena-ruan)
• Set default task for ChatModel (#14068, @stevenchen-db)

Bug fixes:

• [Tracking] Fix filename encoding issue in log_image (#14281, @TomeHirata)
• [Models] Fix the faithfulness metric for custom override parameters supplied to the callable metric implementation (#14220, @BenWilson2)
• [Artifacts] Update presigned URL list_artifacts to return an empty list instead of an exception (#14203, @arpitjasa-db)
• [Tracking] Fix rename permission model registry (#14139, @MohamedKHALILRouissi)
• [Tracking] Fix hard-dependency to langchain package in autologging (#14125, @B-Step62)
• [Tracking] Fix constraint name for MSSQL in migration 0584bdc529eb (#14146, @daniellok-db)
• [Scoring] Fix uninitialized loaded_model variable (#14109, @yang-chengg)
• [Model Registry] Return empty array when DatabricksSDKModelsArtifactRepository.list_artifacts is called on a file (#14027, @shichengzhou-db)

Documentation updates:

• [Docs] Add a quick guide for how to host MLflow on various platforms (#14289, @B-Step62)
• [Docs] Improve documentation for 'artifact_uri' in 'download_artifacts' (#14225, @vinayakkgarg)
• [Docs] Add a page for search_traces (#14033, @TomeHirata)

Small bug fixes and documentation updates:

#14294, #14252, #14233, #14205, #14217, #14172, #14188, #14167, #14166, #14163, #14162, #14161, #13971, @TomeHirata; #14299, #14280, #14279, #14278, #14272, #14270, #14268, #14269, #14263, #14258, #14222, #14248, #14128, #14112, #14111, #14093, #14096, #14095, #14090, #14089, #14085, #14078, #14074, #14070, #14053, #14060, #14035, #14014, #14002, #14000, #13997, #13996, #13995, @harupy; #14298, #14286, #14249, #14276, #14259, #14242, #14254, #14232, #14207, #14206, #14185, #14196, #14193, #14173, #14164, #14159, #14165, #14152, #14151, #14126, #14069, #13987, @B-Step62; #14295, #14265, #14271, #14262, #14235, #14239, #14234, #14228, #14227, #14229, #14218, #14216, #14213, #14208, #14204, #14198, #14187, #14181, #14177, #14176, #14156, #14169, #14099, #14086, #13983, @serena-ruan; #14155, #14067, #14140, #14132, #14072, @daniellok-db; #14178, @emmanuel-ferdman; #14247, @dbczumar; #13789, #14108, @dsuhinin; #14212, @aravind-segu; #14223, #14191, #14084, @dsmilkov; #13804, @kriscon-db; #14158, @Lodewic; #14148, #14147, #14115, #14079, #14116, @WeichenXu123; #14135, @brilee; #14133, @manos02; #14121, @LeahKorol; #14025, @nojaf; #13948, @benglewis; #13942, @justsomerandomdude264; #14003, @Ajay-Satish-01; #13982, @prithvikannan; #13638, @MaxwellSalmon

MLflow 2.20.0rc0

Release Candidate

MLflow 2.20.0rc0 is a release candidate for 2.20.0. To install, run the following command:

pip install mlflow==2.20.0rc0

Please try it out and report any issues on the issue tracker!

Major New Features

• 💡Type Hint-Based Model Signature: Define your model's signature in the most Pythonic way. MLflow now supports defining a model signature based on the type hints in your PythonModel's predict function, and validating input data payloads against it. (#14182, #14168, #14130, #14100, #14099, @serena-ruan)

• 🧠 Bedrock / Groq Tracing Support: MLflow Tracing now offers a one-line auto-tracing experience for Amazon Bedrock and Groq LLMs. Track LLM invocation within your model by simply adding mlflow.bedrock.tracing or mlflow.groq.tracing call to the code. (#14018, @B-Step62, #14006, @anumita0203)

• 🗒️ Inline Trace Rendering in Jupyter Notebook: MLflow now supports rendering a trace UI within the notebook where you are running models. This eliminates the need to frequently switch between the notebook and browser, creating a seamless local model debugging experience. (#13955, @daniellok-db)

• ⚡️Faster Model Validation with uv Package Manager: MLflow has adopted uv, a new Rust-based, super-fast Python package manager. This release adds support for the new package manager in the mlflow.models.predict API, enabling faster model environment validation. Stay tuned for more updates! (#13824, @serena-ruan)

• 🖥️ New Chat Panel in Trace UI: THe MLflow Trace UI now shows a unified chat panel for LLM invocations. The update allows you to view chat messages and function calls in a rich and consistent UI across LLM providers, as well as inspect the raw input and output payloads. (#14211, @TomuHirata)

Other Features:

• Introduced ChatAgent base class for defining custom python agent (#13797, @bbqiu)
• Supported Tool Calling in DSPy Tracing (#14196, @B-Step62)
• Added support for invokers rights in Databricks Resources (#14212, @aravind-segu)
• Applied timeout override to within-request local scoring server for Spark UDF inference (#14202, @BenWilson2)
• Supported dictionary type for inference params (#14091, @serena-ruan)
• Make context parameter optional for calling PythonModel instance (#14059, @serena-ruan)
• Set default task for ChatModel (#14068, @stevenchen-db)