jrmccluskey commented on code in PR #36623:
URL: https://github.com/apache/beam/pull/36623#discussion_r2470662909
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sdks/java/ml/remoteinference/src/main/java/org/apache/beam/sdk/ml/remoteinference/openai/OpenAiModelHandler.java:
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@@ -0,0 +1,44 @@
+package org.apache.beam.sdk.ml.remoteinference.openai;
+
+import com.openai.client.OpenAIClient;
+import com.openai.client.okhttp.OpenAIOkHttpClient;
+import com.openai.models.responses.ResponseCreateParams;
+import org.apache.beam.sdk.ml.remoteinference.base.BaseModelHandler;
+
+import java.util.stream.Collectors;
+
+public class OpenAiModelHandler
Review Comment:
Stylize this as `OpenAIModelHandler` (this goes for all of the other classes
as well)
##########
sdks/java/ml/remoteinference/src/main/java/org/apache/beam/sdk/ml/remoteinference/RemoteInference.java:
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@@ -0,0 +1,91 @@
+package org.apache.beam.sdk.ml.remoteinference;
+
+import org.checkerframework.checker.nullness.qual.Nullable;
+
+import org.apache.beam.sdk.ml.remoteinference.base.BaseInput;
+import org.apache.beam.sdk.ml.remoteinference.base.BaseModelHandler;
+import org.apache.beam.sdk.ml.remoteinference.base.BaseModelParameters;
+import org.apache.beam.sdk.ml.remoteinference.base.BaseResponse;
+import org.apache.beam.sdk.transforms.DoFn;
+import org.apache.beam.sdk.transforms.PTransform;
+import org.apache.beam.sdk.transforms.ParDo;
+import org.apache.beam.sdk.values.PCollection;
+
+
+import com.google.auto.value.AutoValue;
+
+@SuppressWarnings({ "rawtypes", "unchecked" })
+public class RemoteInference {
+
+ public static <InputT extends BaseInput, OutputT extends BaseResponse>
Invoke<InputT, OutputT> invoke() {
+ return new AutoValue_RemoteInference_Invoke.Builder<InputT,
OutputT>().setParameters(null)
+ .build();
+ }
+
+ private RemoteInference() {
+ }
+
+ @AutoValue
+ public abstract static class Invoke<InputT extends BaseInput, OutputT
extends BaseResponse>
+ extends PTransform<PCollection<InputT>, PCollection<OutputT>> {
+
+ abstract @Nullable Class<? extends BaseModelHandler> handler();
+
+ abstract @Nullable BaseModelParameters parameters();
+
+ abstract Builder<InputT, OutputT> builder();
+
+ @AutoValue.Builder
+ abstract static class Builder<InputT extends BaseInput, OutputT extends
BaseResponse> {
+
+ abstract Builder<InputT, OutputT> setHandler(Class<? extends
BaseModelHandler> modelHandler);
+
+ abstract Builder<InputT, OutputT> setParameters(BaseModelParameters
modelParameters);
+
+ abstract Invoke<InputT, OutputT> build();
+ }
+
+ public Invoke<InputT, OutputT> handler(Class<? extends BaseModelHandler>
modelHandler) {
+ return builder().setHandler(modelHandler).build();
+ }
+
+ public Invoke<InputT, OutputT> withParameters(BaseModelParameters
modelParameters) {
+ return builder().setParameters(modelParameters).build();
+ }
+
+ @Override
Review Comment:
From the Python implementation (as well as the cross-language implementation
in Java) we're generally trying to return input-output pairs to make it easier
to process the results downstream.
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sdks/java/ml/build.gradle:
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@@ -0,0 +1,32 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you 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
+ *
+ * http://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.
+ */
Review Comment:
The Apache license header needs to be at the top of every new file (this is
what the RAT pre-commit check is)
##########
sdks/java/ml/remoteinference/src/test/java/Example.java:
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@@ -0,0 +1,43 @@
+import org.apache.beam.runners.direct.DirectRunner;
+import org.apache.beam.sdk.Pipeline;
+import org.apache.beam.sdk.ml.remoteinference.RemoteInference;
+import org.apache.beam.sdk.ml.remoteinference.openai.OpenAiModelHandler;
+import org.apache.beam.sdk.ml.remoteinference.openai.OpenAiModelInput;
+import org.apache.beam.sdk.ml.remoteinference.openai.OpenAiModelParameters;
+import org.apache.beam.sdk.ml.remoteinference.openai.OpenAiModelResponse;
+import org.apache.beam.sdk.options.PipelineOptions;
+import org.apache.beam.sdk.options.PipelineOptionsFactory;
+import org.apache.beam.sdk.transforms.Create;
+import org.apache.beam.sdk.transforms.DoFn;
+import org.apache.beam.sdk.transforms.MapElements;
+import org.apache.beam.sdk.transforms.ParDo;
+import org.apache.beam.sdk.values.TypeDescriptor;
+
+public class Example {
Review Comment:
I'd like to see this written as an integration test rather than just an
example
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