fx

examples/ai-core/src/generate-image/openai.ts

@@ -0,0 +1,15 @@
+import { openai } from '@ai-sdk/openai';
+import { generateImage } from 'ai';
+import 'dotenv/config';
+
+async function main() {
+  const { images } = await generateImage({
+    model: openai.image('dall-e-3'),
+    prompt: 'Santa Claus driving a Cadillac',
+    maxRetries: 0,
+  });
+
+  console.log(images);
+}
+
+main().catch(console.error);

packages/ai/core/generate-image/generate-image.ts

@@ -35,7 +35,7 @@ The prompt that should be used to generate the image.
   /**
 Number of images to generate.
    */
-  n: number;
+  n?: number;
 
   /**
 Maximum number of retries per embedding model call. Set to 0 to disable retries.
@@ -58,7 +58,12 @@ Only applicable for HTTP-based providers.
   const { retry } = prepareRetries({ maxRetries: maxRetriesArg });
 
   const { images } = await retry(() =>
-    model.doGenerate({ prompt, n, abortSignal, headers }),
+    model.doGenerate({
+      prompt,
+      n: n ?? 1,
+      abortSignal,
+      headers,
+    }),
   );
 
   return new DefaultGenerateImageResult({ images });

packages/openai/src/openai-image-model.ts

@@ -56,11 +56,13 @@ export class OpenAIImageModel implements ImageModelV1 {
     });
 
     return {
-      images: response.map(item => item.b64_json),
+      images: response.data.map(item => item.b64_json),
     };
   }
 }
 
 // minimal version of the schema, focussed on what is needed for the implementation
 // this approach limits breakages when the API changes and increases efficiency
-const openaiImageResponseSchema = z.array(z.object({ b64_json: z.string() }));
+const openaiImageResponseSchema = z.object({
+  data: z.array(z.object({ b64_json: z.string() })),
+});