Update CHANGELOG (#1118)

Co-authored-by: adriangonz <adriangonz@users.noreply.github.com>

CHANGELOG.md

@@ -1,47 +1,151 @@
 # Changelog
 
-<a name="1.2.4"></a>
 
+<a name="1.3.1"></a>
+## [1.3.1](https://github.com/SeldonIO/MLServer/releases/tag/1.3.1) - 27 Apr 2023
+
+### What's Changed
+
+- Move OpenAPI schemas into Python package ([#1095](https://github.com/SeldonIO/MLServer/issues/1095))
+
+[Changes][1.3.1]
+
+
+<a name="1.3.0"></a>
+## [1.3.0](https://github.com/SeldonIO/MLServer/releases/tag/1.3.0) - 27 Apr 2023
+
+> WARNING :warning: : The `1.3.0` has been yanked from PyPi due to a packaging issue. This should have been now resolved in `>= 1.3.1`. 
+
+### What's Changed
+
+#### Custom Model Environments
+
+More often that not, your custom runtimes will depend on external 3rd party dependencies which are not included within the main MLServer package - or different versions of the same package (e.g. `scikit-learn==1.1.0` vs `scikit-learn==1.2.0`). In these cases, to load your custom runtime, MLServer will need access to these dependencies.
+
+In MLServer `1.3.0`, it is now [possible to load this custom set of dependencies by providing them](https://mlserver.readthedocs.io/en/latest/user-guide/custom.html#loading-a-custom-python-environment), through an [environment tarball](https://mlserver.readthedocs.io/en/latest/examples/conda/README.html), whose path can be specified within your `model-settings.json` file. This custom environment will get provisioned on the fly after loading a model - alongside the default environment and any other custom environments.
+
+Under the hood, each of these environments will run their own separate pool of workers.
+
+![image](https://user-images.githubusercontent.com/1577620/234797983-aa52c353-2d2f-4261-a078-06bfe62cae87.png)
+
+#### Custom Metrics
+
+The MLServer framework now includes a simple interface that allows you to register and keep track of any [custom metrics](https://mlserver.readthedocs.io/en/latest/user-guide/metrics.html#custom-metrics):
+
+- `[mlserver.register()](https://mlserver.readthedocs.io/en/latest/reference/api/metrics.html#mlserver.register)`: Register a new metric.
+- `[mlserver.log()](https://mlserver.readthedocs.io/en/latest/reference/api/metrics.html#mlserver.log)`: Log a new set of metric / value pairs.
+
+Custom metrics will generally be registered in the `[load()](https://mlserver.readthedocs.io/en/latest/reference/api/model.html#mlserver.MLModel.load)` method and then used in the `[predict()](https://mlserver.readthedocs.io/en/latest/reference/api/model.html#mlserver.MLModel.predict)` method of your [custom runtime](https://mlserver.readthedocs.io/en/latest/user-guide/custom.html). These metrics can then be polled and queried via [Prometheus](https://mlserver.readthedocs.io/en/latest/user-guide/metrics.html#settings).
+
+![image](https://user-images.githubusercontent.com/1577620/234798211-9e538439-4914-4aa6-9c3f-539a66e3ce54.png)
+
+#### OpenAPI
+
+MLServer `1.3.0` now includes an autogenerated Swagger UI which can be used to interact dynamically with the Open Inference Protocol.
+
+The autogenerated Swagger UI can be accessed under the `/v2/docs` endpoint.
+
+![https://mlserver.readthedocs.io/en/latest/_images/swagger-ui.png](https://mlserver.readthedocs.io/en/latest/_images/swagger-ui.png)
+
+Alongside the [general API documentation](https://mlserver.readthedocs.io/en/latest/user-guide/openapi.html#Swagger-UI), MLServer also exposes now a set of API docs tailored to individual models, showing the specific endpoints available for each one.
+
+The model-specific autogenerated Swagger UI can be accessed under the following endpoints:
+
+- `/v2/models/{model_name}/docs`
+- `/v2/models/{model_name}/versions/{model_version}/docs`
+
+#### HuggingFace Improvements
+
+MLServer now includes improved Codec support for all the main different types that can be returned by HugginFace models - ensuring that the values returned via the Open Inference Protocol are more semantic and meaningful.
+
+Massive thanks to [@pepesi](https://github.com/pepesi)  for taking the lead on improving the HuggingFace runtime!
+
+#### Support for Custom Model Repositories
+
+Internally, MLServer leverages a Model Repository implementation which is used to discover and find different models (and their versions) available to load. The latest version of MLServer will now allow you to swap this for your own model repository implementation - letting you integrate against your own model repository workflows. 
+
+This is exposed via the [model_repository_implementation](https://mlserver.readthedocs.io/en/latest/reference/settings.html#mlserver.settings.Settings.model_repository_implementation) flag of your `settings.json` configuration file. 
+
+Thanks to [@jgallardorama](https://github.com/jgallardorama)  (aka [@jgallardorama-itx](https://github.com/jgallardorama-itx) ) for his effort contributing this feature!
+
+#### Batch and Worker Queue Metrics
+
+MLServer `1.3.0` introduces a [new set of metrics](https://mlserver.readthedocs.io/en/latest/user-guide/metrics.html#default-metrics) to increase visibility around two of its internal queues:
+
+- [Adaptive batching](https://mlserver.readthedocs.io/en/latest/user-guide/adaptive-batching.html) queue: used to accumulate request batches on the fly.
+- [Parallel inference](https://mlserver.readthedocs.io/en/latest/user-guide/parallel-inference.html) queue: used to send over requests to the inference worker pool.
+
+Many thanks to [@alvarorsant](https://github.com/alvarorsant)  for taking the time to implement this highly requested feature!
+
+#### Image Size Optimisations
+
+The latest version of MLServer includes a few optimisations around image size, which help reduce the size of the official set of images by more than ~60% - making them more convenient to use and integrate within your workloads. In the case of the full `seldonio/mlserver:1.3.0` image (including all runtimes and dependencies), this means going from 10GB down to ~3GB.
+
+#### Python API Documentation
+
+Alongside its built-in inference runtimes, MLServer also exposes a Python framework that you can use to extend MLServer and write your own codecs and inference runtimes. The MLServer official docs now include a [reference page](https://mlserver.readthedocs.io/en/latest/reference/api/index.html) documenting the main components of this framework in more detail.
+
+### New Contributors
+* [@rio](https://github.com/rio) made their first contribution in https://github.com/SeldonIO/MLServer/pull/864
+* [@pepesi](https://github.com/pepesi) made their first contribution in https://github.com/SeldonIO/MLServer/pull/692
+* [@jgallardorama](https://github.com/jgallardorama) made their first contribution in https://github.com/SeldonIO/MLServer/pull/849
+* [@alvarorsant](https://github.com/alvarorsant) made their first contribution in https://github.com/SeldonIO/MLServer/pull/860
+* [@gawsoftpl](https://github.com/gawsoftpl) made their first contribution in https://github.com/SeldonIO/MLServer/pull/950
+* [@stephen37](https://github.com/stephen37) made their first contribution in https://github.com/SeldonIO/MLServer/pull/1033
+* [@sauerburger](https://github.com/sauerburger) made their first contribution in https://github.com/SeldonIO/MLServer/pull/1064
+
+[Changes][1.3.0]
+
+
+<a name="1.2.4"></a>
 ## [1.2.4](https://github.com/SeldonIO/MLServer/releases/tag/1.2.4) - 10 Mar 2023
 
 <!-- Release notes generated using configuration in .github/release.yml at 1.2.4 -->
 
+
+
 **Full Changelog**: https://github.com/SeldonIO/MLServer/compare/1.2.3...1.2.4
 
 [Changes][1.2.4]
 
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+<a name="1.2.3"></a>
 ## [1.2.3](https://github.com/SeldonIO/MLServer/releases/tag/1.2.3) - 16 Jan 2023
 
 <!-- Release notes generated using configuration in .github/release.yml at 1.2.3 -->
 
+
+
 **Full Changelog**: https://github.com/SeldonIO/MLServer/compare/1.2.2...1.2.3
 
 [Changes][1.2.3]
 
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+<a name="1.2.2"></a>
 ## [1.2.2](https://github.com/SeldonIO/MLServer/releases/tag/1.2.2) - 16 Jan 2023
 
 <!-- Release notes generated using configuration in .github/release.yml at 1.2.2 -->
 
+
+
 **Full Changelog**: https://github.com/SeldonIO/MLServer/compare/1.2.1...1.2.2
 
 [Changes][1.2.2]
 
-<a name="1.2.1"></a>
 
+<a name="1.2.1"></a>
 ## [1.2.1](https://github.com/SeldonIO/MLServer/releases/tag/1.2.1) - 19 Dec 2022
 
 <!-- Release notes generated using configuration in .github/release.yml at 1.2.1 -->
 
+
+
 **Full Changelog**: https://github.com/SeldonIO/MLServer/compare/1.2.0...1.2.1
 
 [Changes][1.2.1]
 
-<a name="1.2.0"></a>
 
+<a name="1.2.0"></a>
 ## [1.2.0](https://github.com/SeldonIO/MLServer/releases/tag/1.2.0) - 25 Nov 2022
 
 <!-- Release notes generated using configuration in .github/release.yml at 1.2.0 -->
@@ -102,19 +206,19 @@ The `1.2.0` release of MLServer, includes a number of fixes around the parallel
 
 - The main MLServer process won’t load an extra replica of the model anymore. Instead, all computing will occur on the parallel inference pool.
 - The worker pool will now ensure that all requests are executed on each worker’s AsyncIO loop, thus optimising compute time vs IO time.
-- Several improvements around logging from the inference workers.
+- Several improvements around logging from the inference workers. 
 
 #### Dropped support for Python 3.7
 
 MLServer has now dropped support for Python `3.7`. Going forward, only `3.8`, `3.9` and `3.10` will be supported (with `3.8` being used in our official set of images).
 
-### Move to UBI Base Images
+#### Move to UBI Base Images
 
-The official set of MLServer images has now moved to use [UBI 9](https://www.redhat.com/en/blog/introducing-red-hat-universal-base-image) as a base image. This ensures support to run MLServer in OpenShift clusters, as well as a well-maintained baseline for our images.
+The official set of MLServer images has now moved to use [UBI 9](https://www.redhat.com/en/blog/introducing-red-hat-universal-base-image) as a base image. This ensures support to run MLServer in OpenShift clusters, as well as a well-maintained baseline for our images. 
 
 #### Support for MLflow 2.0
 
-In line with MLServer’s close relationship with the MLflow team, this release of MLServer introduces support for the recently released MLflow 2.0. This introduces changes to the drop-in MLflow “scoring protocol” support, in the MLflow runtime for MLServer, to ensure it’s aligned with MLflow 2.0.
+In line with MLServer’s close relationship with the MLflow team, this release of MLServer introduces support for the recently released MLflow 2.0. This introduces changes to the drop-in MLflow “scoring protocol” support, in the MLflow runtime for MLServer, to ensure it’s aligned with MLflow 2.0.  
 
 MLServer is also shipped as a dependency of MLflow, therefore you can try it out today by installing MLflow as:
 
@@ -124,31 +228,38 @@ $ pip install mlflow[extras]
 
 To learn more about how to use MLServer directly from the MLflow CLI, check out the [MLflow docs](https://www.mlflow.org/docs/latest/models.html#serving-with-mlserver).
 
-### New Contributors
 
-- [@johnpaulett](https://github.com/johnpaulett) made their first contribution in https://github.com/SeldonIO/MLServer/pull/633
-- [@saeid93](https://github.com/saeid93) made their first contribution in https://github.com/SeldonIO/MLServer/pull/711
-- [@RafalSkolasinski](https://github.com/RafalSkolasinski) made their first contribution in https://github.com/SeldonIO/MLServer/pull/720
-- [@dumaas](https://github.com/dumaas) made their first contribution in https://github.com/SeldonIO/MLServer/pull/742
-- [@Salehbigdeli](https://github.com/Salehbigdeli) made their first contribution in https://github.com/SeldonIO/MLServer/pull/776
-- [@regen100](https://github.com/regen100) made their first contribution in https://github.com/SeldonIO/MLServer/pull/839
+### New Contributors
+* [@johnpaulett](https://github.com/johnpaulett) made their first contribution in https://github.com/SeldonIO/MLServer/pull/633
+* [@saeid93](https://github.com/saeid93) made their first contribution in https://github.com/SeldonIO/MLServer/pull/711
+* [@RafalSkolasinski](https://github.com/RafalSkolasinski) made their first contribution in https://github.com/SeldonIO/MLServer/pull/720
+* [@dumaas](https://github.com/dumaas) made their first contribution in https://github.com/SeldonIO/MLServer/pull/742
+* [@Salehbigdeli](https://github.com/Salehbigdeli) made their first contribution in https://github.com/SeldonIO/MLServer/pull/776
+* [@regen100](https://github.com/regen100) made their first contribution in https://github.com/SeldonIO/MLServer/pull/839
 
 **Full Changelog**: https://github.com/SeldonIO/MLServer/compare/1.1.0...1.2.0
 
 [Changes][1.2.0]
 
-<a name="1.2.0.dev1"></a>
 
+<a name="1.2.0.dev1"></a>
 ## [v1.2.0.dev1](https://github.com/SeldonIO/MLServer/releases/tag/1.2.0.dev1) - 01 Aug 2022
 
+
+
 [Changes][1.2.0.dev1]
 
-<a name="1.1.0"></a>
 
+<a name="1.1.0"></a>
 ## [v1.1.0](https://github.com/SeldonIO/MLServer/releases/tag/1.1.0) - 01 Aug 2022
 
+
+
 [Changes][1.1.0]
 
+
+[1.3.1]: https://github.com/SeldonIO/MLServer/compare/1.3.0...1.3.1
+[1.3.0]: https://github.com/SeldonIO/MLServer/compare/1.2.4...1.3.0
 [1.2.4]: https://github.com/SeldonIO/MLServer/compare/1.2.3...1.2.4
 [1.2.3]: https://github.com/SeldonIO/MLServer/compare/1.2.2...1.2.3
 [1.2.2]: https://github.com/SeldonIO/MLServer/compare/1.2.1...1.2.2
@@ -157,4 +268,4 @@ To learn more about how to use MLServer directly from the MLflow CLI, check out
 [1.2.0.dev1]: https://github.com/SeldonIO/MLServer/compare/1.1.0...1.2.0.dev1
 [1.1.0]: https://github.com/SeldonIO/MLServer/tree/1.1.0
 
-<!-- Generated by https://github.com/rhysd/changelog-from-release v3.7.0 -->
+<!-- Generated by https://github.com/rhysd/changelog-from-release v3.7.1 -->