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Interact with OpenAI from Kestra.
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package io.kestra.plugin.openai;
import com.theokanning.openai.image.CreateImageRequest;
import com.theokanning.openai.image.ImageResult;
import com.theokanning.openai.service.OpenAiService;
import io.kestra.core.models.annotations.Example;
import io.kestra.core.models.annotations.Plugin;
import io.kestra.core.models.property.Property;
import io.kestra.core.models.tasks.RunnableTask;
import io.kestra.core.runners.RunContext;
import io.swagger.v3.oas.annotations.media.Schema;
import lombok.*;
import lombok.experimental.SuperBuilder;
import org.apache.commons.io.FileUtils;
import java.io.File;
import java.io.IOException;
import java.net.URI;
import java.util.ArrayList;
import java.util.Base64;
import java.util.List;
import java.util.UUID;
import jakarta.validation.constraints.NotNull;
import static io.kestra.core.utils.Rethrow.throwConsumer;
@SuperBuilder
@ToString
@EqualsAndHashCode
@Getter
@NoArgsConstructor
@Schema(
title = "Given a prompt, create an image.",
description = "For more information, refer to the [OpenAI Image Generation API docs](https://platform.openai.com/docs/api-reference/images/create)."
)
@Plugin(
examples = {
@Example(
full = true,
code = """
id: openai
namespace: company.team
tasks:
- id: create_image
type: io.kestra.plugin.openai.CreateImage
prompt: A funny cat in a black suit
apiKey:
download: true
n: 5
"""
)
}
)
public class CreateImage extends AbstractTask implements RunnableTask {
@Schema(
title = "Message to send to the API as prompt."
)
@NotNull
private Property prompt;
@Schema(
title = "The number of images to generate. Must be between 1 and 10."
)
private Integer n;
@Schema(
title = "The size of the generated images."
)
@Builder.Default
private Property size = Property.of(SIZE.LARGE);
@Schema(
title = "Whether to download the generated image",
description = "If enable, the generated image will be downloaded inside Kestra's internal storage. Else, the URL of the generated image will be available as task output."
)
@Builder.Default
private Property download = Property.of(Boolean.FALSE);
@Override
public CreateImage.Output run(RunContext runContext) throws Exception {
OpenAiService client = this.client(runContext);
String user = runContext.render(this.user == null ? null : this.user.as(runContext, String.class));
String prompt = runContext.render(this.prompt == null ? null : this.prompt.as(runContext, String.class));
ImageResult imageResult = client.createImage(CreateImageRequest.builder()
.prompt(prompt)
.size(this.size.as(runContext, SIZE.class).getSize())
.n(this.n)
.responseFormat(this.download.as(runContext, Boolean.class) ? "b64_json" : "url")
.user(user)
.build()
);
List files = new ArrayList<>();
imageResult.getData().forEach(throwConsumer(image -> {
if (this.download.as(runContext, Boolean.class)) {
files.add(runContext.storage().putFile(this.downloadB64Json(image.getB64Json())));
} else {
files.add(URI.create(image.getUrl()));
}
}));
return Output.builder().images(files).build();
}
@Builder
@Getter
public static class Output implements io.kestra.core.models.tasks.Output {
@Schema(
title = "Generated images."
)
private List images;
}
private File downloadB64Json(String encodedImage) throws IOException {
File image = File.createTempFile("openai-" + UUID.randomUUID(), ".png");
byte[] decodedBytes = Base64.getDecoder().decode(encodedImage);
FileUtils.writeByteArrayToFile(image, decodedBytes);
return image;
}
protected enum SIZE {
SMALL("256x256"),
MEDIUM("512x512"),
LARGE("1024x1024");
private final String value;
SIZE(String value) {
this.value = value;
}
public String getSize() {
return value;
}
}
}
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