release: 4.91.0

.release-please-manifest.json

@@ -1,3 +1,3 @@
 {
-  ".": "4.90.0"
+  ".": "4.91.0"
 }

.stats.yml

@@ -1,4 +1,4 @@
 configured_endpoints: 82
 openapi_spec_url: https://storage.googleapis.com/stainless-sdk-openapi-specs/openai%2Fopenai-6663c59193eb95b201e492de17dcbd5e126ba03d18ce66287a3e2c632ca56fe7.yml
 openapi_spec_hash: 7996d2c34cc44fe2ce9ffe93c0ab774e
-config_hash: 9351ea829c2b41da3b48a38c934c92ee
+config_hash: e25e31d8446b6bc0e3ef7103b6993cce

CHANGELOG.md

@@ -1,5 +1,18 @@
 # Changelog
 
+## 4.91.0 (2025-03-31)
+
+Full Changelog: [v4.90.0...v4.91.0](https://github.com/openai/openai-node/compare/v4.90.0...v4.91.0)
+
+### Features
+
+* **api:** add `get /responses/{response_id}/input_items` endpoint ([ef0e0ac](https://github.com/openai/openai-node/commit/ef0e0acd469379ae6f2745c83e6c6813ff7b4edc))
+
+
+### Performance Improvements
+
+* **embedding:** default embedding creation to base64 ([#1312](https://github.com/openai/openai-node/issues/1312)) ([e54530e](https://github.com/openai/openai-node/commit/e54530e4f6f00d7d74fc8636bbdb6f6280548750)), closes [#1310](https://github.com/openai/openai-node/issues/1310)
+
 ## 4.90.0 (2025-03-27)
 
 Full Changelog: [v4.89.1...v4.90.0](https://github.com/openai/openai-node/compare/v4.89.1...v4.90.0)

jsr.json

@@ -1,6 +1,6 @@
 {
   "name": "@openai/openai",
-  "version": "4.90.0",
+  "version": "4.91.0",
   "exports": {
     ".": "./index.ts",
     "./helpers/zod": "./helpers/zod.ts",

package.json

@@ -1,6 +1,6 @@
 {
   "name": "openai",
-  "version": "4.90.0",
+  "version": "4.91.0",
   "description": "The official TypeScript library for the OpenAI API",
   "author": "OpenAI <support@openai.com>",
   "types": "dist/index.d.ts",

src/core.ts

@@ -1287,6 +1287,27 @@ export const toBase64 = (str: string | null | undefined): string => {
   throw new OpenAIError('Cannot generate b64 string; Expected `Buffer` or `btoa` to be defined');
 };
 
+/**
+ * Converts a Base64 encoded string to a Float32Array.
+ * @param base64Str - The Base64 encoded string.
+ * @returns An Array of numbers interpreted as Float32 values.
+ */
+export const toFloat32Array = (base64Str: string): Array<number> => {
+  if (typeof Buffer !== 'undefined') {
+    // for Node.js environment
+    return Array.from(new Float32Array(Buffer.from(base64Str, 'base64').buffer));
+  } else {
+    // for legacy web platform APIs
+    const binaryStr = atob(base64Str);
+    const len = binaryStr.length;
+    const bytes = new Uint8Array(len);
+    for (let i = 0; i < len; i++) {
+      bytes[i] = binaryStr.charCodeAt(i);
+    }
+    return Array.from(new Float32Array(bytes.buffer));
+  }
+};
+
 export function isObj(obj: unknown): obj is Record<string, unknown> {
   return obj != null && typeof obj === 'object' && !Array.isArray(obj);
 }

src/resources/embeddings.ts

@@ -9,9 +9,47 @@ export class Embeddings extends APIResource {
    */
   create(
     body: EmbeddingCreateParams,
-    options?: Core.RequestOptions,
+    options?: Core.RequestOptions<EmbeddingCreateParams>,
   ): Core.APIPromise<CreateEmbeddingResponse> {
-    return this._client.post('/embeddings', { body, ...options });
+    const hasUserProvidedEncodingFormat = !!body.encoding_format;
+    // No encoding_format specified, defaulting to base64 for performance reasons
+    // See https://github.com/openai/openai-node/pull/1312
+    let encoding_format: EmbeddingCreateParams['encoding_format'] =
+      hasUserProvidedEncodingFormat ? body.encoding_format : 'base64';
+
+    if (hasUserProvidedEncodingFormat) {
+      Core.debug('Request', 'User defined encoding_format:', body.encoding_format);
+    }
+
+    const response: Core.APIPromise<CreateEmbeddingResponse> = this._client.post('/embeddings', {
+      body: {
+        ...body,
+        encoding_format: encoding_format as EmbeddingCreateParams['encoding_format'],
+      },
+      ...options,
+    });
+
+    // if the user specified an encoding_format, return the response as-is
+    if (hasUserProvidedEncodingFormat) {
+      return response;
+    }
+
+    // in this stage, we are sure the user did not specify an encoding_format
+    // and we defaulted to base64 for performance reasons
+    // we are sure then that the response is base64 encoded, let's decode it
+    // the returned result will be a float32 array since this is OpenAI API's default encoding
+    Core.debug('response', 'Decoding base64 embeddings to float32 array');
+
+    return (response as Core.APIPromise<CreateEmbeddingResponse>)._thenUnwrap((response) => {
+      if (response && response.data) {
+        response.data.forEach((embeddingBase64Obj) => {
+          const embeddingBase64Str = embeddingBase64Obj.embedding as unknown as string;
+          embeddingBase64Obj.embedding = Core.toFloat32Array(embeddingBase64Str);
+        });
+      }
+
+      return response;
+    });
   }
 }
 

src/version.ts

@@ -1 +1 @@
-export const VERSION = '4.90.0'; // x-release-please-version
+export const VERSION = '4.91.0'; // x-release-please-version

tests/api-resources/embeddings.test.ts

@@ -32,4 +32,35 @@ describe('resource embeddings', () => {
       user: 'user-1234',
     });
   });
+
+  test('create: encoding_format=float should create float32 embeddings', async () => {
+    const response = await client.embeddings.create({
+      input: 'The quick brown fox jumped over the lazy dog',
+      model: 'text-embedding-3-small',
+    });
+
+    expect(response.data?.at(0)?.embedding).toBeInstanceOf(Array);
+    expect(Number.isFinite(response.data?.at(0)?.embedding.at(0))).toBe(true);
+  });
+
+  test('create: encoding_format=base64 should create float32 embeddings', async () => {
+    const response = await client.embeddings.create({
+      input: 'The quick brown fox jumped over the lazy dog',
+      model: 'text-embedding-3-small',
+      encoding_format: 'base64',
+    });
+
+    expect(response.data?.at(0)?.embedding).toBeInstanceOf(Array);
+    expect(Number.isFinite(response.data?.at(0)?.embedding.at(0))).toBe(true);
+  });
+
+  test('create: encoding_format=default should create float32 embeddings', async () => {
+    const response = await client.embeddings.create({
+      input: 'The quick brown fox jumped over the lazy dog',
+      model: 'text-embedding-3-small',
+    });
+
+    expect(response.data?.at(0)?.embedding).toBeInstanceOf(Array);
+    expect(Number.isFinite(response.data?.at(0)?.embedding.at(0))).toBe(true);
+  });
 });