Add Databricks ML flow api endpoints

csharp/Microsoft.Azure.Databricks.Client.Sample/SampleProgram .MachineLearning.cs

@@ -0,0 +1,20 @@
+using Microsoft.Azure.Databricks.Client.Models.UnityCatalog;
+using System;
+using System.Linq;
+using System.Threading.Tasks;
+
+namespace Microsoft.Azure.Databricks.Client.Sample;
+
+internal static partial class SampleProgram
+{
+    private static async Task TestExperimentApiClient(DatabricksClient client)
+    {
+        string run_id = "sample_run_id";
+        PrintDelimiter();
+        Console.WriteLine("Listing metastores");
+        var data = await client.MachineLearning.Experiments.GetRun(run_id);
+        Console.WriteLine($"\t{data.Info.RunId}");
+        PrintDelimiter();
+
+    }
+}

csharp/Microsoft.Azure.Databricks.Client.Sample/SampleProgram.UnityCatalog.cs

@@ -73,5 +73,22 @@ private static async Task TestUnityCatalogApi(DatabricksClient client)
         Console.WriteLine($"Deleting created catalog {catalog.Name}...");
         await client.UnityCatalog.Catalogs.Delete(catalog.Name);
         Console.WriteLine("Catalog deleted");
+
+        Console.WriteLine("Listing Regsitered Models");
+        var registeredModels = await client.UnityCatalog.RegisteredModels.ListRegisteredModels();
+        foreach (var model in registeredModels)
+        {
+            Console.WriteLine($"\t{model.MetastoreId}, {model.Name}");
+        }
+        PrintDelimiter();
+
+        var fullName = "main.default.revenue_forecasting";
+        Console.WriteLine("Listing Regsitered Models");
+        var modelVersionsList = await client.UnityCatalog.ModelVersion.ListModelVersions(fullName);
+        foreach (var model in modelVersionsList)
+        {
+            Console.WriteLine($"\t{model.MetastoreId}, {model.CatalogName}");
+        }
+        PrintDelimiter();
     }
 }

csharp/Microsoft.Azure.Databricks.Client.Test/MachineLearning/ExperimentApiClientTest.cs

@@ -0,0 +1,100 @@
+
+
+using Microsoft.Azure.Databricks.Client.MachineLearning;
+using Moq.Contrib.HttpClient;
+using System.Net;
+using System.Text.Json;
+using System.Text.Json.Nodes;
+using Microsoft.Azure.Databricks.Client.Models.MachineLearning.Experiment;
+
+namespace Microsoft.Azure.Databricks.Client.Test.MachineLearning;
+
+[TestClass]
+public class ExperimentApiClientTests : MachineLearningApiClientTest
+{
+    [TestMethod]
+    public async Task GetRunTest()
+    {
+        var run_id = "19d13cbfa8134b699f8b41fdab0cdd4c";
+        var requestUri = $"{MlflowBaseUri}/runs/get?run_id={run_id}";
+        var expectedResponse = @"
+        {
+          ""run"": {
+            ""info"": {
+              ""run_id"": ""string"",
+              ""run_uuid"": ""string"",
+              ""experiment_id"": ""string"",
+              ""user_id"": ""string"",
+              ""status"": ""RUNNING"",
+              ""start_time"": 0,
+              ""end_time"": 0,
+              ""artifact_uri"": ""string"",
+              ""lifecycle_stage"": ""string""
+            },
+            ""data"": {
+              ""metrics"": [
+                {
+                  ""key"": ""string"",
+                  ""value"": 0.1,
+                  ""timestamp"": 0,
+                  ""step"": ""0""
+                }
+              ],
+              ""params"": [
+                {
+                  ""key"": ""string"",
+                  ""value"": ""string""
+                }
+              ],
+              ""tags"": [
+                {
+                  ""key"": ""string"",
+                  ""value"": ""string""
+                }
+              ]
+            },
+            ""inputs"": {
+              ""dataset_inputs"": [
+                {
+                  ""tags"": [
+                    {
+                      ""key"": ""string"",
+                      ""value"": ""string""
+                    }
+                  ],
+                  ""dataset"": {
+                    ""name"": ""string"",
+                    ""digest"": ""string"",
+                    ""source_type"": ""string"",
+                    ""source"": ""string"",
+                    ""schema"": ""string"",
+                    ""profile"": ""string""
+                  }
+                }
+              ]
+            }
+          }
+        }";
+
+        var handler = CreateMockHandler();
+        handler
+        .SetupRequest(HttpMethod.Get, requestUri)
+        .ReturnsResponse(HttpStatusCode.OK, expectedResponse, "application/json");
+
+        var mockClient = handler.CreateClient();
+        mockClient.BaseAddress = BaseApiUri;
+
+        using var client = new ExperimentApiClient(mockClient);
+        var response = await client.GetRun(run_id);
+
+        var expected = JsonNode.Parse(expectedResponse)?["run"].Deserialize<Run>(Options);
+
+        Assert.IsNotNull(expected, "Expected object is null.");
+        Assert.IsNotNull(response, "Response object is null.");
+
+        if (response != null && expected != null)
+        {
+            Assert.AreEqual(expected.ToString(), response.ToString());
+        }
+    }
+}

csharp/Microsoft.Azure.Databricks.Client.Test/MachineLearning/MachineLearningApiClientTest.cs

@@ -0,0 +1,7 @@
+namespace Microsoft.Azure.Databricks.Client.Test.MachineLearning;
+
+[TestClass]
+public class MachineLearningApiClientTest : ApiClientTest
+{
+    protected static readonly Uri MlflowBaseUri = new(BaseApiUri, "2.0/mlflow");
+}

csharp/Microsoft.Azure.Databricks.Client.Test/UnityCatalog/ModelVersionApiClientTests.cs

@@ -0,0 +1,172 @@
+using Microsoft.Azure.Databricks.Client.Models.UnityCatalog;
+using Microsoft.Azure.Databricks.Client.UnityCatalog;
+using Moq.Contrib.HttpClient;
+using System.Net;
+using System.Text.Json;
+using System.Text.Json.Nodes;
+
+namespace Microsoft.Azure.Databricks.Client.Test.UnityCatalog;
+
+[TestClass]
+public class ModelVersionApiClientTests : UnityCatalogApiClientTest
+{
+    [TestMethod]
+    public async Task ListModelVersionsTest()
+    {
+        var full_name = "main.default.revenue_forecasting";
+        var requestUri = $"{BaseApiUri}models/{full_name}/versions";
+
+        var expectedResponse = @"
+        {
+             ""model_versions"": [
+            {
+              ""model_name"": ""revenue_forecasting_model"",
+              ""catalog_name"": ""main"",
+              ""schema_name"": ""default"",
+              ""comment"": ""This model version forecasts future revenue given historical data, using classic ML techniques"",
+              ""source"": ""dbfs:/databricks/mlflow-tracking/1234567890/abcdef/artifacts/model"",
+              ""run_id"": ""abcdef"",
+              ""run_workspace_id"": 6051234418418567,
+              ""version"": 1,
+              ""status"": ""READY"",
+              ""id"": ""9876543-21zy-abcd-3210-abcdef456789"",
+              ""metastore_id"": ""11111111-1111-1111-1111-111111111111"",
+              ""created_at"": 1666369196203,
+              ""created_by"": ""[email protected]"",
+              ""updated_at"": 1666369196203,
+              ""updated_by"": ""[email protected]"",
+              ""storage_location"": ""s3://my-bucket/hello/world/models/2222-2222/versions/9876543-21zy-abcd-3210-abcdef456789""
+            },
+            {
+              ""model_name"": ""revenue_forecasting_model"",
+              ""catalog_name"": ""main"",
+              ""schema_name"": ""default"",
+              ""comment"": ""This model version forecasts future revenue given historical data, using deep learning"",
+              ""source"": ""dbfs:/databricks/mlflow-tracking/1234567890/abcdef/artifacts/model"",
+              ""run_id"": ""abcdef"",
+              ""run_workspace_id"": 6051234418418567,
+              ""version"": 2,
+              ""status"": ""READY"",
+              ""id"": ""01234567-89ab-cdef-0123-456789abcdef"",
+              ""metastore_id"": ""11111111-1111-1111-1111-111111111111"",
+              ""created_at"": 1666369196907,
+              ""created_by"": ""[email protected]"",
+              ""updated_at"": 1666369196907,
+              ""updated_by"": ""[email protected]"",
+              ""storage_location"": ""s3://my-bucket/hello/world/models/2222-2222/versions/01234567-89ab-cdef-0123-456789abcdef""
+            }
+          ],
+          ""next_page_token"": ""some-page-token""
+        }";
+        var expected = JsonNode.Parse(expectedResponse)?["model_versions"].Deserialize<IEnumerable<ModelVersion>>(Options);
+
+        var handler = CreateMockHandler();
+        handler
+            .SetupRequest(HttpMethod.Get, requestUri)
+            .ReturnsResponse(HttpStatusCode.OK, expectedResponse, "application/json");
+
+        var mockClient = handler.CreateClient();
+        mockClient.BaseAddress = ApiClientTest.BaseApiUri;
+
+        using var client = new ModelVersionApiClient(mockClient);
+        var response = await client.ListModelVersions(full_name);
+
+        var responseJson = JsonSerializer.Serialize(response, Options);
+        CollectionAssert.AreEqual(expected?.ToList(), response?.ToList());
+    }
+
+
+    [TestMethod]
+    public async Task GetModelVersionTest()
+    {
+        var expectedResponse = @"
+        {
+          ""model_name"": ""revenue_forecasting_model"",
+          ""catalog_name"": ""main"",
+          ""schema_name"": ""default"",
+          ""comment"": ""This model version forecasts future revenue given historical data, using classic ML techniques"",
+          ""source"": ""dbfs:/databricks/mlflow-tracking/1234567890/abcdef/artifacts/model"",
+          ""run_id"": ""abcdef"",
+          ""run_workspace_id"": 6051234418418567,
+          ""version"": 1,
+          ""status"": ""READY"",
+          ""id"": ""01234567-89ab-cdef-0123-456789abcdef"",
+          ""metastore_id"": ""11111111-1111-1111-1111-111111111111"",
+          ""created_at"": 1666369196203,
+          ""created_by"": ""[email protected]"",
+          ""updated_at"": 1666369196203,
+          ""updated_by"": ""[email protected]"",
+          ""storage_location"": ""s3://my-bucket/hello/world/models/2222-2222/versions/01234567-89ab-cdef-0123-456789abcdef""
+        }
+        ";
+
+        var full_name = "main.default.revenue_forecasting_model";
+        var version = 2;
+        var requestUri = $"{BaseApiUri}models/{full_name}/versions/{version}";
+
+        var handler = CreateMockHandler();
+        handler
+            .SetupRequest(HttpMethod.Get, requestUri)
+            .ReturnsResponse(HttpStatusCode.OK, expectedResponse, "application/json");
+
+        var mockClient = handler.CreateClient();
+        mockClient.BaseAddress = ApiClientTest.BaseApiUri;
+
+        using var client = new ModelVersionApiClient(mockClient);
+        var response = await client.GetModelVersion(full_name, version);
+
+        var responseJson = JsonSerializer.Serialize(response, Options);
+        AssertJsonDeepEquals(expectedResponse, responseJson);
+    }
+
+    [TestMethod]
+    public async Task GetModelVersionByAliasTest()
+    {
+        var full_name = "main.default.revenue_forecasting_model";
+        var alias = "champion";
+        var requestUri = $"{BaseApiUri}models/{full_name}/aliases/{alias}";
+
+
+        var expectedResponse = @"
+       {
+          ""model_name"": ""revenue_forecasting_model"",
+          ""catalog_name"": ""main"",
+          ""schema_name"": ""default"",
+          ""comment"": ""This model version forecasts future revenue, given historical data"",
+          ""source"": ""dbfs:/databricks/mlflow-tracking/1234567890/abcdef/artifacts/model"",
+          ""run_id"": ""abcdef"",
+          ""run_workspace_id"": 6051234418418567,
+          ""version"": 1,
+          ""status"": ""PENDING_REGISTRATION"",
+          ""id"": ""01234567-89ab-cdef-0123-456789abcdef"",
+          ""metastore_id"": ""11111111-1111-1111-1111-111111111111"",
+          ""created_at"": 1666369196203,
+          ""created_by"": ""[email protected]"",
+          ""updated_at"": 1666369196203,
+          ""updated_by"": ""[email protected]"",
+          ""storage_location"": ""s3://my-bucket/hello/world/models/2222-2222/versions/01234567-89ab-cdef-0123-456789abcdef"",
+          ""aliases"": [
+            {
+              ""alias_name"": ""champion"",
+              ""version_num"": 1
+            }
+          ]
+        }
+        ";
+
+        var handler = CreateMockHandler();
+        handler
+            .SetupRequest(HttpMethod.Get, requestUri)
+            .ReturnsResponse(HttpStatusCode.OK, expectedResponse, "application/json");
+
+
+        var mockClient = handler.CreateClient();
+        mockClient.BaseAddress = ApiClientTest.BaseApiUri;
+
+        using var client = new ModelVersionApiClient(mockClient);
+
+        var response = await client.GetModelVersionByAlias(full_name, alias);
+        var responseJson = JsonSerializer.Serialize(response, Options);
+        AssertJsonDeepEquals(expectedResponse, responseJson);
+    }
+}