docs(aiplatform): Add PredictTextClassificationSample #2396 (#2407)

aiplatform/api/AIPlatform.Samples.Tests/PredictTextClassificationTest.cs

@@ -0,0 +1,37 @@
+/*
+ * Copyright 2023 Google LLC
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *     https://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+using Xunit;
+
+[Collection(nameof(AIPlatformFixture))]
+public class PredictTextClassificationTest
+{
+    private readonly AIPlatformFixture _fixture;
+    private readonly PredictTextClassificationSample _sample;
+
+    public PredictTextClassificationTest(AIPlatformFixture fixture)
+    {
+        _fixture = fixture;
+        _sample = new PredictTextClassificationSample();
+    }
+
+    [Fact]
+    public void TestPredictTextClassification()
+    {
+        var response = _sample.PredictTextClassification(_fixture.ProjectId);
+        Assert.NotNull(response);
+    }
+}

aiplatform/api/AIPlatform.Samples/PredictTextClassificationSample.cs

@@ -0,0 +1,103 @@
+/*
+ * Copyright 2023 Google LLC
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *     https://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+// [START aiplatform_sdk_classify_news_items]
+
+using Google.Cloud.AIPlatform.V1;
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using Value = Google.Protobuf.WellKnownTypes.Value;
+
+// Text Classification with a Large Language Model
+public class PredictTextClassificationSample
+{
+    public string PredictTextClassification(
+        string projectId = "your-project-id",
+        string locationId = "us-central1",
+        string publisher = "google",
+        string model = "text-bison@001")
+    {
+        // Initialize client that will be used to send requests.
+        // This client only needs to be created once,
+        // and can be reused for multiple requests.
+        var client = new PredictionServiceClientBuilder
+        {
+            Endpoint = $"{locationId}-aiplatform.googleapis.com"
+        }.Build();
+
+        // Configure the parent resource.
+        var endpoint = EndpointName.FromProjectLocationPublisherModel(projectId, locationId, publisher, model);
+
+        // Initialize request argument(s).
+        var content = @"What is the topic for a given news headline?
+- business
+- entertainment
+- health
+- sports
+- technology
+
+Text: Pixel 7 Pro Expert Hands On Review, the Most Helpful Google Phones.
+The answer is: technology
+
+Text: Quit smoking?
+The answer is: health
+
+Text: Roger Federer reveals why he touched Rafael Nadals hand while they were crying
+The answer is: sports
+
+Text: Business relief from Arizona minimum-wage hike looking more remote
+The answer is: business
+
+Text: #TomCruise has arrived in Bari, Italy for #MissionImpossible.
+The answer is: entertainment
+
+Text: CNBC Reports Rising Digital Profit as Print Advertising Falls
+The answer is:";
+
+        var instances = new List<Value>
+        {
+            Value.ForStruct(new()
+            {
+                Fields =
+                {
+                    ["content"] = Value.ForString(content),
+                }
+            })
+        };
+
+        var parameters = Value.ForStruct(new()
+        {
+            Fields =
+            {
+                { "temperature", new Value { NumberValue = 0 } },
+                { "maxDecodeSteps", new Value { NumberValue = 5 } },
+                { "topP", new Value { NumberValue = 0 } },
+                { "topK", new Value { NumberValue = 1 } }
+            }
+        });
+
+        // Make the request.
+        var response = client.Predict(endpoint, instances, parameters);
+
+        // Parse and return the content.
+        var responseContent = response.Predictions.First().StructValue.Fields["content"].StringValue;
+        Console.WriteLine($"Content: {responseContent}");
+        return responseContent;
+    }
+}
+
+// [END aiplatform_sdk_classify_news_items]