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feat(api): OpenAPI spec update via Stainless API (#8)
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.stats.yml

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configured_endpoints: 6
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configured_endpoints: 2

README.md

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### Example: creating a resource
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To create a new inference pipeline data, first use the `InferencePipelineDataStreamParams` builder to specify attributes,
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then pass that to the `stream` method of the `data` service.
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To create a new project, first use the `ProjectCreateParams` builder to specify attributes,
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then pass that to the `create` method of the `projects` service.
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```java
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import com.openlayer.api.models.InferencePipelineDataStreamParams;
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import com.openlayer.api.models.InferencePipelineDataStreamResponse;
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import java.util.List;
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InferencePipelineDataStreamParams params = InferencePipelineDataStreamParams.builder()
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.rows(List.of(InferencePipelineDataStreamParams.Row.builder().build()))
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.config(InferencePipelineDataStreamParams.Config.ofLlmData(InferencePipelineDataStreamParams.Config.LlmData.builder()
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.outputColumnName("output")
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.costColumnName("cost")
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.inputVariableNames(List.of("user_query"))
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.numOfTokenColumnName("tokens")
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.timestampColumnName("timestamp")
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.build()))
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.build();
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InferencePipelineDataStreamResponse inferencePipelineDataStreamResponse = client.inferencePipelines().data().stream(params);
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import com.openlayer.api.models.ProjectCreateParams;
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import com.openlayer.api.models.ProjectCreateResponse;
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ProjectCreateParams params = ProjectCreateParams.builder().build();
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ProjectCreateResponse projectCreateResponse = client.projects().create(params);
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```
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---
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To make a request to the Openlayer API, you generally build an instance of the appropriate `Params` class.
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In [Example: creating a resource](#example-creating-a-resource) above, we used the `InferencePipelineDataStreamParams.builder()` to pass to
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the `stream` method of the `data` service.
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In [Example: creating a resource](#example-creating-a-resource) above, we used the `ProjectCreateParams.builder()` to pass to
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the `create` method of the `projects` service.
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Sometimes, the API may support other properties that are not yet supported in the Java SDK types. In that case,
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you can attach them using the `putAdditionalProperty` method.
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```java
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InferencePipelineDataStreamParams params = InferencePipelineDataStreamParams.builder()
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ProjectCreateParams params = ProjectCreateParams.builder()
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// ... normal properties
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.putAdditionalProperty("secret_param", "4242")
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.build();
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When receiving a response, the Openlayer Java SDK will deserialize it into instances of the typed model classes. In rare cases, the API may return a response property that doesn't match the expected Java type. If you directly access the mistaken property, the SDK will throw an unchecked `OpenlayerInvalidDataException` at runtime. If you would prefer to check in advance that that response is completely well-typed, call `.validate()` on the returned model.
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```java
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InferencePipelineDataStreamResponse inferencePipelineDataStreamResponse = client.inferencePipelines().data().stream().validate();
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ProjectCreateResponse projectCreateResponse = client.projects().create().validate();
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```
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### Response properties as JSON
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Sometimes, the server response may include additional properties that are not yet available in this library's types. You can access them using the model's `_additionalProperties` method:
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```java
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JsonValue secret = inferencePipelineDataStreamResponse._additionalProperties().get("secret_field");
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JsonValue secret = projectCreateResponse._additionalProperties().get("secret_field");
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```
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---

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