Mlflow

Bug fixes:

- [Models] Fix params and model_config handling for llm/v1/xxx Transformers model (12401, B-Step62)
- [UI] Fix dark mode user preference (12386, daniellok-db)
- [Docker] Fix docker image failing to build with `install_mlflow=False` (12388, daniellok-db)

Documentation updates:

- [Docs] Add link to langchain autologging page in doc (12398, xq-yin)
- [Docs] Add documentation for Models from Code (12381, BenWilson2)

Small bug fixes and documentation updates:

12415, 12396, 12394, harupy; 12403, 12382, BenWilson2; 12397, B-Step62

Major features:

- **MLflow Tracing**: Tracing is powerful tool designed to enhance your ability to monitor, analyze, and debug GenAI applications by allowing you to inspect the intermediate outputs generated as your application handles a request. This update comes with an automatic LangChain integration to make it as easy as possible to get started, but we've also implemented high-level fluent APIs, and low-level client APIs for users who want more control over their trace instrumentation. For more information, check out the [guide in our docs](https://mlflow.org/docs/latest/llms/tracing/index.html)!
- **Unity Catalog Integration**: The MLflow Deployments server now has an integration with Unity Catalog, allowing you to leverage registered functions as tools for enhancing your chat application. For more information, check out [this guide](https://mlflow.org/docs/latest/llms/deployments/uc_integration.html)!
- **OpenAI Autologging**: Autologging support has now been added for the OpenAI model flavor. With this feature, MLflow will automatically log a model upon calling the OpenAI API. Each time a request is made, the inputs and outputs will be logged as artifacts. Check out [the guide](https://mlflow.org/docs/latest/llms/openai/guide/index.html#openai-autologging) for more information!

Other Notable Features:

- [Models] Support input images encoded with b64.encodebytes (12087, MadhuM02)
- [Tracking] Support async logging per X seconds (12324, chenmoneygithub)
- [Tracking] Provide a way to set urllib's connection number and max size (12227, chenmoneygithub)
- [Projects] Make MLflow project runner supporting submit spark job to databricks runtime >= 13 (12139, WeichenXu123)
- [UI] Add the "description" column to the runs table (11996, zhouyou9505)

Bug fixes:

- [Model Registry] Handle no headers presigned url (12349, artjen)
- [Models] Fix docstring order for ChatResponse class and make object field immutable (12305, xq-yin)
- [Databricks] Fix root user checking in get_databricks_nfs_temp_dir and get_databricks_local_temp_dir (12186, WeichenXu123)
- [Tracking] fix _init_server process terminate hang (12076, zhouyou9505)
- [Scoring] Fix MLflow model container and slow test CI failure (12042, WeichenXu123)

Documentation updates:

- [Docs] Enhance documentation for autologging supported libraries (12356, xq-yin)
- [Tracking, Docs] Adding Langchain as a code example and doc string (12325, sunishsheth2009)
- [Tracking, Docs] Adding Pyfunc as a code example and doc string (12336, sunishsheth2009)
- [Docs] Add FAQ entry for viewing trace exceptions in Docs (12309, BenWilson2)
- [Docs] Add note about 'fork' vs 'spawn' method when using multiprocessing for parallel runs (12337, B-Step62)
- [Docs] Fix type error in tracing example for function wrapping (12338, B-Step62)
- [Docs] Add example usage of "extract_fields" for mlflow.search_traces in documentation (12319, xq-yin)
- [Docs] Update LangChain Autologging docs (12306, B-Step62)
- [Docs] Add Tracing documentation (12191, BenWilson2)

Small bug fixes and documentation updates:

12359, 12308, 12350, 12284, 12345, 12316, 12287, 12303, 12291, 12288, 12265, 12170, 12248, 12263, 12249, 12251, 12239, 12241, 12240, 12235, 12242, 12172, 12215, 12228, 12216, 12164, 12225, 12203, 12181, 12198, 12195, 12192, 12146, 12171, 12163, 12166, 12124, 12106, 12113, 12112, 12074, 12077, 12058, harupy; 12355, 12326, 12114, 12343, 12328, 12327, 12340, 12286, 12310, 12200, 12209, 12189, 12194, 12201, 12196, 12174, 12107, serena-ruan; 12364, 12352, 12354, 12353, 12351, 12298, 12297, 12220, 12155, daniellok-db; 12311, 12357, 12346, 12312, 12339, 12281, 12283, 12282, 12268, 12236, 12247, 12199, 12232, 12233, 12221, 12229, 12207, 12212, 12193, 12167, 12137, 12147, 12148, 12138, 12127, 12065, B-Step62; 12289, 12253, 12330 xq-yin; 11771, lababidi; 12280, 12275, BenWilson2; 12246, 12244, 12211, 12066, 12061, WeichenXu123; 12278, sunishsheth2009; 12136, kriscon-db; 11911, jessechancy; 12169, hubertzub-db

features.

Features:

- [Tracking] Provide a way to set `urllib`'s connection number and max size (12227, chenmoneygithub)
- [Tracking] Support UC directory as MLflow MetaDataset (12224, chenmoneygithub)

Bug fixes:

- [Models] Fix inferring `mlflow[gateway]` as dependency when using `mlflow.deployment` module (12264, B-Step62)
- [Tracking] Flatten the model_config with `/` before logging as params (12190, sunishsheth2009)

Small bug fixes and documentation updates:

12268, 12210, B-Step62; 12214, harupy; 12223, 12226, annzhang-db; 12260, 12237, prithvikannan; 12261, BenWilson2; 12231, serena-ruan; 12238, sunishsheth2009

MLflow 2.13.1 is a patch release that includes several bug fixes and integration improvements to existing features. New features that are introduced in this patch release are intended to provide a foundation to further major features that will be released in the next release.

Features:

- [MLflow] Add `mlflow[langchain]` extra that installs recommended versions of langchain with MLflow (12182, sunishsheth2009)
- [Tracking] Adding the ability to override the model_config in langchain flavor if loaded as pyfunc (12085, sunishsheth2009)
- [Model Registry] Automatically detect if Presigned URLs are required for Unity Catalog (12177, artjen)

Bug fixes:
- [Tracking] Use `getUserLocalTempDir` and `getUserNFSTempDir` to replace `getReplLocalTempDir` and `getReplNFSTempDir` in databricks runtime (12105, WeichenXu123)
- [Model] Updating chat model to take default input_example and predict to accept json during inference (12115, sunishsheth2009)
- [Tracking] Automatically call `load_context` when inferring signature in pyfunc (12099, sunishsheth2009)

Small bug fixes and documentation updates:

12180, 12152, 12128, 12126, 12100, 12086, 12084, 12079, 12071, 12067, 12062, serena-ruan; 12175, 12167, 12137, 12134, 12127, 12123, 12111, 12109, 12078, 12080, 12064, B-Step62; 12142, 2maz; 12171, 12168, 12159, 12153, 12144, 12104, 12095, 12083, harupy; 12160, aravind-segu; 11990, kriscon-db; 12178, 12176, 12090, 12036, sunishsheth2009; 12162, 12110, 12088, 11937, 12075, daniellok-db; 12133, 12131, prithvikannan; 12132, 12035, annzhang-db; 12121, 12120, liangz1; 12122, 12094, dbczumar; 12098, 12055, mparkhe

With this release, we're happy to introduce several features that enhance the usability of MLflow broadly across a range of use cases.

Major Features and Improvements:

- **Streamable Python Models**: The newly introduced `predict_stream` API for Python Models allows for custom model implementations that support the return of a generator object, permitting full customization for GenAI applications.

- **Enhanced Code Dependency Inference**: A new feature for automatically inferrring code dependencies based on detected dependencies within a model's implementation. As a supplement to the `code_paths` parameter, the introduced `infer_model_code_paths` option when logging a model will determine which additional code modules are needed in order to ensure that your models can be loaded in isolation, deployed, and reliably stored.

- **Standardization of MLflow Deployment Server**: Outputs from the Deployment Server's endpoints now conform to OpenAI's interfaces to provide a simpler integration with commonly used services.

Features:

- [Deployments] Update the MLflow Deployment Server interfaces to be OpenAI compatible (12003, harupy)
- [Deployments] Add `Togetherai` as a supported provider for the MLflow Deployments Server (11557, FotiosBistas)
- [Models] Add `predict_stream` API support for Python Models (11791, WeichenXu123)
- [Models] Enhance the capabilities of logging code dependencies for MLflow models (11806, WeichenXu123)
- [Models] Add support for RunnableBinding models in LangChain (11980, serena-ruan)
- [Model Registry / Databricks] Add support for renaming models registered to Unity Catalog (11988, artjen)
- [Model Registry / Databricks] Improve the handling of searching for invalid components from Unity Catalog registered models (11961, artjen)
- [Model Registry] Enhance retry logic and credential refresh to mitigate cloud provider token expiration failures when uploading or downloading artifacts (11614, artjen)
- [Artifacts / Databricks] Add enhanced lineage tracking for models loaded from Unity Catalog (11305, shichengzhou-db)
- [Tracking] Add resourcing metadata to Pyfunc models to aid in model serving environment configuration (11832, sunishsheth2009)
- [Tracking] Enhance LangChain signature inference for models as code (11855, sunishsheth2009)

Bug fixes:

- [Artifacts] Prohibit invalid configuration options for multi-part upload on AWS (11975, ian-ack-db)
- [Model Registry] Enforce registered model metadata equality (12013, artjen)
- [Models] Correct an issue with `hasattr` references in `AttrDict` usages (11999, BenWilson2)

Documentation updates:

- [Docs] Simplify the main documentation landing page (12017, BenWilson2)
- [Docs] Add documentation for the expanded code path inference feature (11997, BenWilson2)
- [Docs] Add documentation guidelines for the `predict_stream` API (11976, BenWilson2)
- [Docs] Add support for enhanced Documentation with the `JFrog` MLflow Plugin (11426, yonarbel)

Small bug fixes and documentation updates:

12052, 12053, 12022, 12029, 12024, 11992, 12004, 11958, 11957, 11850, 11938, 11924, 11922, 11920, 11820, 11822, 11798, serena-ruan; 12054, 12051, 12045, 12043, 11987, 11888, 11876, 11913, 11868, sunishsheth2009; 12049, 12046, 12037, 11831, dbczumar; 12047, 12038, 12020, 12021, 11970, 11968, 11967, 11965, 11963, 11941, 11956, 11953, 11934, 11921, 11454, 11836, 11826, 11793, 11790, 11776, 11765, 11763, 11746, 11748, 11740, 11735, harupy; 12025, 12034, 12027, 11914, 11899, 11866, BenWilson2; 12026, 11991, 11979, 11964, 11939, 11894, daniellok-db; 11951, 11974, 11916, annzhang-db; 12015, 11931, 11627, jessechancy; 12014, 11917, prithvikannan; 12012, AveshCSingh; 12001, yunpark93; 11984, 11983, 11977, 11977, 11949, edwardfeng-db; 11973, bbqiu; 11902, 11835, 11775, B-Step62; 11845, lababidi

MLflow 2.12.2 is a patch release that includes several bug fixes and integration improvements to existing features. New features that are introduced in this patch release are intended to provide a foundation to further major features that will be released in the next 2 minor releases.

Features:

- [Models] Add an environment configuration flag to enable raising an exception instead of a warning for failures in model dependency inference (11903, BenWilson2)
- [Models] Add support for the `llm/v1/embeddings` task in the Transformers flavor to unify the input and output structures for embedding models (11795, B-Step62)
- [Models] Introduce model streaming return via `predict_stream()` for custom `pyfunc` models capable of returning a stream response (11791, 11895, WeichenXu123)
- [Evaluate] Add support for overriding the entire model evaluation judgment prompt within `mlflow.evaluate` for GenAI models (11912, apurva-koti)
- [Tracking] Add support for defining deployment resource metadata to configure deployment resources within `pyfunc` models (11832, 11825, 11804, sunishsheth2009)
- [Tracking] Add support for logging `LangChain` and custom `pyfunc` models as code (11855, 11842, sunishsheth2009)
- [Tracking] Modify MLflow client's behavior to read from a global asynchronous configuration state (11778, 11780, chenmoneygithub)
- [Tracking] Enhance system metrics data collection to include a GPU power consumption metric (11747, chenmoneygithub)


Bug fixes:

- [Models] Fix a validation issue when performing signature validation if `params` are specified (11838, WeichenXu123)
- [Databricks] Fix an issue where models cannot be loaded in the Databricks serverless runtime (11758, WeichenXu123)
- [Databricks] Fix an issue with the Databricks serverless runtime where scaled workers do not have authorization to read from the driver NFS mount (11757, WeichenXu123)
- [Databricks] Fix an issue in the Databricks serverless runtime where a model loaded via a `spark_udf` for inference fails due to a configuration issue (11752, WeichenXu123)
- [Server-infra] Upgrade the gunicorn dependency to version 22 to address a third-party security issue (11742, maitreyakv)


Documentation updates:

- [Docs] Add additional guidance on search syntax restrictions for search APIs (11892, BenWilson2)
- [Docs] Fix an issue with the quickstart guide where the Keras example model is defined incorrectly (11848, horw)
- [Docs] Provide fixes and updates to LangChain tutorials and guides (11802, BenWilson2)
- [Docs] Fix the model registry example within the docs for correct type formatting (11789, 80rian)

Small bug fixes and documentation updates:

11928, apurva-koti; 11910, 11915, 11864, 11893, 11875, 11744, BenWilson2; 11913, 11918, 11869, 11873, 11867, sunishsheth2009; 11916, 11879, 11877, 11860, 11843, 11844, 11817, 11841, annzhang-db; 11822, 11861, serena-ruan; 11890, 11819, 11794, 11774, B-Step62; 11880, prithvikannan; 11833, 11818, 11954, harupy; 11831, dbczumar; 11812, 11816, 11800, daniellok-db; 11788, smurching; 11756, IgorMilavec; 11627, jessechancy