Release 0.0.2-1

voyage-ai · Dec 9, 2024 · 6622f88 · 6622f88
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diff --git a/.mock/definition/endpoints.yml b/.mock/definition/endpoints.yml
diff --git a/.mock/openapi/openapi.yml b/.mock/openapi/openapi.yml
diff --git a/README.md b/README.md
@@ -1,6 +1,6 @@
 # Voyage TypeScript Library
 
-[![fern shield](https://img.shields.io/badge/%F0%9F%8C%BF-SDK%20generated%20by%20Fern-brightgreen)](https://github.com/fern-api/fern)
+[![fern shield](https://img.shields.io/badge/%F0%9F%8C%BF-Built%20with%20Fern-brightgreen)](https://buildwithfern.com?utm_source=github&utm_medium=github&utm_campaign=readme&utm_source=https%3A%2F%2Fgithub.com%2Fvoyage-ai%2Ftypescript-sdk)
 [![npm shield](https://img.shields.io/npm/v/voyageai)](https://www.npmjs.com/package/voyageai)
 
 The Voyage TypeScript library provides convenient access to the Voyage API from TypeScript.
@@ -51,7 +51,7 @@ following namespace:
 ```typescript
 import { VoyageAI } from "voyageai";
 
-const request: VoyageAI.EmbedRequest = {
+const request: VoyageAI.MultimodalembeddingsApiRequest = {
     ...
 };
 ```

diff --git a/package.json b/package.json
@@ -1,6 +1,6 @@
 {
     "name": "voyageai",
-    "version": "0.0.1-5",
+    "version": "0.0.2-1",
     "private": false,
     "repository": "https://github.com/voyage-ai/typescript-sdk",
     "main": "./index.js",

diff --git a/reference.md b/reference.md
@@ -68,3 +68,71 @@ await client.rerank({
 </details>
 
 ##
+
+## Endpoints
+
+<details><summary><code>client.endpoints.<a href="/src/api/resources/endpoints/client/Client.ts">multimodalembeddingsApi</a>({ ...params }) -> VoyageAI.MultimodalembeddingsApiResponse</code></summary>
+<dl>
+<dd>
+
+#### 📝 Description
+
+<dl>
+<dd>
+
+<dl>
+<dd>
+
+The Voyage multimodal embedding endpoint returns vector representations for a given list of multimodal inputs consisting of text, images, or an interleaving of both modalities.
+
+</dd>
+</dl>
+</dd>
+</dl>
+
+#### 🔌 Usage
+
+<dl>
+<dd>
+
+<dl>
+<dd>
+
+```typescript
+await client.endpoints.multimodalembeddingsApi({
+    inputs: [{}],
+    model: "model",
+});
+```
+
+</dd>
+</dl>
+</dd>
+</dl>
+
+#### ⚙️ Parameters
+
+<dl>
+<dd>
+
+<dl>
+<dd>
+
+**request:** `VoyageAI.MultimodalembeddingsApiRequest`
+
+</dd>
+</dl>
+
+<dl>
+<dd>
+
+**requestOptions:** `Endpoints.RequestOptions`
+
+</dd>
+</dl>
+</dd>
+</dl>
+
+</dd>
+</dl>
+</details>
diff --git a/src/Client.ts b/src/Client.ts
@@ -8,6 +8,7 @@ import * as VoyageAI from "./api/index";
 import * as serializers from "./serialization/index";
 import urlJoin from "url-join";
 import * as errors from "./errors/index";
+import { Endpoints } from "./api/resources/endpoints/client/Client";
 
 export declare namespace VoyageAIClient {
     interface Options {
@@ -55,8 +56,8 @@ export class VoyageAIClient {
                 Authorization: await this._getAuthorizationHeader(),
                 "X-Fern-Language": "JavaScript",
                 "X-Fern-SDK-Name": "voyageai",
-                "X-Fern-SDK-Version": "0.0.1-5",
-                "User-Agent": "voyageai/0.0.1-5",
+                "X-Fern-SDK-Version": "0.0.2-1",
+                "User-Agent": "voyageai/0.0.2-1",
                 "X-Fern-Runtime": core.RUNTIME.type,
                 "X-Fern-Runtime-Version": core.RUNTIME.version,
             },
@@ -126,8 +127,8 @@ export class VoyageAIClient {
                 Authorization: await this._getAuthorizationHeader(),
                 "X-Fern-Language": "JavaScript",
                 "X-Fern-SDK-Name": "voyageai",
-                "X-Fern-SDK-Version": "0.0.1-5",
-                "User-Agent": "voyageai/0.0.1-5",
+                "X-Fern-SDK-Version": "0.0.2-1",
+                "User-Agent": "voyageai/0.0.2-1",
                 "X-Fern-Runtime": core.RUNTIME.type,
                 "X-Fern-Runtime-Version": core.RUNTIME.version,
             },
@@ -170,6 +171,12 @@ export class VoyageAIClient {
         }
     }
 
+    protected _endpoints: Endpoints | undefined;
+
+    public get endpoints(): Endpoints {
+        return (this._endpoints ??= new Endpoints(this._options));
+    }
+
     protected async _getAuthorizationHeader(): Promise<string> {
         const bearer = (await core.Supplier.get(this._options.apiKey)) ?? process?.env["VOYAGE_API_KEY"];
         if (bearer == null) {

diff --git a/src/api/index.ts b/src/api/index.ts
@@ -1,2 +1,3 @@
+export * from "./resources";
 export * from "./types";
 export * from "./client";
diff --git a/src/api/resources/endpoints/client/Client.ts b/src/api/resources/endpoints/client/Client.ts
@@ -0,0 +1,112 @@
+/**
+ * This file was auto-generated by Fern from our API Definition.
+ */
+
+import * as environments from "../../../../environments";
+import * as core from "../../../../core";
+import * as VoyageAI from "../../../index";
+import * as serializers from "../../../../serialization/index";
+import urlJoin from "url-join";
+import * as errors from "../../../../errors/index";
+
+export declare namespace Endpoints {
+    interface Options {
+        environment?: core.Supplier<environments.VoyageAIEnvironment | string>;
+        apiKey?: core.Supplier<core.BearerToken | undefined>;
+        fetcher?: core.FetchFunction;
+    }
+
+    interface RequestOptions {
+        /** The maximum time to wait for a response in seconds. */
+        timeoutInSeconds?: number;
+        /** The number of times to retry the request. Defaults to 2. */
+        maxRetries?: number;
+        /** A hook to abort the request. */
+        abortSignal?: AbortSignal;
+    }
+}
+
+export class Endpoints {
+    constructor(protected readonly _options: Endpoints.Options = {}) {}
+
+    /**
+     * The Voyage multimodal embedding endpoint returns vector representations for a given list of multimodal inputs consisting of text, images, or an interleaving of both modalities.
+     *
+     * @param {VoyageAI.MultimodalembeddingsApiRequest} request
+     * @param {Endpoints.RequestOptions} requestOptions - Request-specific configuration.
+     *
+     * @example
+     *     await client.endpoints.multimodalembeddingsApi({
+     *         inputs: [{}],
+     *         model: "model"
+     *     })
+     */
+    public async multimodalembeddingsApi(
+        request: VoyageAI.MultimodalembeddingsApiRequest,
+        requestOptions?: Endpoints.RequestOptions
+    ): Promise<VoyageAI.MultimodalembeddingsApiResponse> {
+        const _response = await (this._options.fetcher ?? core.fetcher)({
+            url: urlJoin(
+                (await core.Supplier.get(this._options.environment)) ?? environments.VoyageAIEnvironment.Default,
+                "multimodalembeddings"
+            ),
+            method: "POST",
+            headers: {
+                Authorization: await this._getAuthorizationHeader(),
+                "X-Fern-Language": "JavaScript",
+                "X-Fern-SDK-Name": "voyageai",
+                "X-Fern-SDK-Version": "0.0.2-1",
+                "User-Agent": "voyageai/0.0.2-1",
+                "X-Fern-Runtime": core.RUNTIME.type,
+                "X-Fern-Runtime-Version": core.RUNTIME.version,
+            },
+            contentType: "application/json",
+            requestType: "json",
+            body: serializers.MultimodalembeddingsApiRequest.jsonOrThrow(request, { unrecognizedObjectKeys: "strip" }),
+            timeoutMs: requestOptions?.timeoutInSeconds != null ? requestOptions.timeoutInSeconds * 1000 : 60000,
+            maxRetries: requestOptions?.maxRetries,
+            abortSignal: requestOptions?.abortSignal,
+        });
+        if (_response.ok) {
+            return serializers.MultimodalembeddingsApiResponse.parseOrThrow(_response.body, {
+                unrecognizedObjectKeys: "passthrough",
+                allowUnrecognizedUnionMembers: true,
+                allowUnrecognizedEnumValues: true,
+                skipValidation: true,
+                breadcrumbsPrefix: ["response"],
+            });
+        }
+
+        if (_response.error.reason === "status-code") {
+            throw new errors.VoyageAIError({
+                statusCode: _response.error.statusCode,
+                body: _response.error.body,
+            });
+        }
+
+        switch (_response.error.reason) {
+            case "non-json":
+                throw new errors.VoyageAIError({
+                    statusCode: _response.error.statusCode,
+                    body: _response.error.rawBody,
+                });
+            case "timeout":
+                throw new errors.VoyageAITimeoutError();
+            case "unknown":
+                throw new errors.VoyageAIError({
+                    message: _response.error.errorMessage,
+                });
+        }
+    }
+
+    protected async _getAuthorizationHeader(): Promise<string> {
+        const bearer = (await core.Supplier.get(this._options.apiKey)) ?? process?.env["VOYAGE_API_KEY"];
+        if (bearer == null) {
+            throw new errors.VoyageAIError({
+                message: "Please specify VOYAGE_API_KEY when instantiating the client.",
+            });
+        }
+
+        return `Bearer ${bearer}`;
+    }
+}
diff --git a/src/api/resources/endpoints/client/index.ts b/src/api/resources/endpoints/client/index.ts
@@ -0,0 +1 @@
+export * from "./requests";
diff --git a/src/api/resources/endpoints/client/requests/MultimodalembeddingsApiRequest.ts b/src/api/resources/endpoints/client/requests/MultimodalembeddingsApiRequest.ts
@@ -0,0 +1,106 @@
+/**
+ * This file was auto-generated by Fern from our API Definition.
+ */
+
+import * as VoyageAI from "../../../../index";
+
+/**
+ * @example
+ *     {
+ *         inputs: [{}],
+ *         model: "model"
+ *     }
+ */
+export interface MultimodalembeddingsApiRequest {
+    /**
+     * A list of multimodal inputs to be vectorized.
+     * A single input in the list is a dictionary containing a single key "content", whose value represents a sequence of text and images.
+     * <ul><p></p>
+     *   <li> The value of&nbsp;<code class="rdmd-code lang- theme-light" data-lang="" name="" tabindex="0"><span class="cm-s-neo" data-testid="SyntaxHighlighter">"content"</span></code>&nbsp;is a list of dictionaries, each representing a single piece of text or image. The dictionaries have four possible keys:
+     *       <ol class="nested-ordered-list">
+     *           <li> <b>type</b>: Specifies the type of the piece of the content. Allowed values are <code class="rdmd-code lang- theme-light" data-lang="" name="" tabindex="0"><span class="cm-s-neo" data-testid="SyntaxHighlighter">text</span></code>, <code class="rdmd-code lang- theme-light" data-lang="" name="" tabindex="0"><span class="cm-s-neo" data-testid="SyntaxHighlighter">image_url</span></code>, or <code class="rdmd-code lang- theme-light" data-lang="" name="" tabindex="0"><span class="cm-s-neo" data-testid="SyntaxHighlighter">image_base64</span></code>.</li>
+     *           <li> <b>text</b>: Only present when <code class="rdmd-code lang- theme-light" data-lang="" name="" tabindex="0"><span class="cm-s-neo" data-testid="SyntaxHighlighter">type</span></code> is <code class="rdmd-code lang- theme-light" data-lang="" name="" tabindex="0"><span class="cm-s-neo" data-testid="SyntaxHighlighter">text</span></code>. The value should be a text string.</li>
+     *           <li> <b>image_base64</b>: Only present when <code class="rdmd-code lang- theme-light" data-lang="" name="" tabindex="0"><span class="cm-s-neo" data-testid="SyntaxHighlighter">type</span></code> is <code class="rdmd-code lang- theme-light" data-lang="" name="" tabindex="0"><span class="cm-s-neo" data-testid="SyntaxHighlighter">image_base64</span></code>. The value should be a Base64-encoded image in the <a target="_blank" href="https://developer.mozilla.org/en-US/docs/Web/URI/Schemes/data">data URL</a> format <code class="rdmd-code lang- theme-light" data-lang="" name="" tabindex="0"><span class="cm-s-neo" data-testid="SyntaxHighlighter">data:[&lt;mediatype&gt;];base64,&lt;data&gt;</span></code>. Currently supported <code class="rdmd-code lang- theme-light" data-lang="" name="" tabindex="0"><span class="cm-s-neo" data-testid="SyntaxHighlighter">mediatypes</span></code> are: <code class="rdmd-code lang- theme-light" data-lang="" name="" tabindex="0"><span class="cm-s-neo" data-testid="SyntaxHighlighter">image/png</span></code>, <code class="rdmd-code lang- theme-light" data-lang="" name="" tabindex="0"><span class="cm-s-neo" data-testid="SyntaxHighlighter">image/jpeg</span></code>, <code class="rdmd-code lang- theme-light" data-lang="" name="" tabindex="0"><span class="cm-s-neo" data-testid="SyntaxHighlighter">image/webp</span></code>, and <code class="rdmd-code lang- theme-light" data-lang="" name="" tabindex="0"><span class="cm-s-neo" data-testid="SyntaxHighlighter">image/gif</span></code>.</li>
+     *           <li> <b>image_url</b>: Only present when <code class="rdmd-code lang- theme-light" data-lang="" name="" tabindex="0"><span class="cm-s-neo" data-testid="SyntaxHighlighter">type</span></code> is <code class="rdmd-code lang- theme-light" data-lang="" name="" tabindex="0"><span class="cm-s-neo" data-testid="SyntaxHighlighter">image_url</span></code>. The value should be a URL linking to the image. We support PNG, JPEG, WEBP, and GIF images.</li>
+     *       </ol>
+     *   </li>
+     *   <li> <b>Note</b>: Only one of the keys, <code class="rdmd-code lang- theme-light" data-lang="" name="" tabindex="0"><span class="cm-s-neo" data-testid="SyntaxHighlighter">image_base64</span></code> or <code class="rdmd-code lang- theme-light" data-lang="" name="" tabindex="0"><span class="cm-s-neo" data-testid="SyntaxHighlighter">image_url</span></code>, should be present in each dictionary for image data. Consistency is required within a request, meaning each request should use either <code class="rdmd-code lang- theme-light" data-lang="" name="" tabindex="0"><span class="cm-s-neo" data-testid="SyntaxHighlighter">image_base64</span></code> or <code class="rdmd-code lang- theme-light" data-lang="" name="" tabindex="0"><span class="cm-s-neo" data-testid="SyntaxHighlighter">image_url</span></code> exclusively for images, not both.<br>
+     *   <br>
+     *   <details> <summary> Example payload where <code class="rdmd-code lang- theme-light" data-lang="" name="" tabindex="0"><span class="cm-s-neo" data-testid="SyntaxHighlighter">inputs</span></code>&nbsp;contains an image as a URL </summary>
+     *       <br>
+     *       The <code class="rdmd-code lang- theme-light" data-lang="" name="" tabindex="0"><span class="cm-s-neo" data-testid="SyntaxHighlighter">inputs</span></code> list contains a single input, which consists of a piece of text and an image (which is provided via a URL).
+     *       <pre><code class="rdmd-code lang- theme-light" data-lang="" name="" tabindex="0"><span class="cm-s-neo" data-testid="SyntaxHighlighter">
+     *       {
+     *         "inputs": [
+     *           {
+     *             "content": [
+     *               {
+     *                 "type": "text",
+     *                 "text": "This is a banana."
+     *               },
+     *               {
+     *                 "type": "image_url",
+     *                 "image_url": "https://raw.githubusercontent.com/voyage-ai/voyage-multimodal-3/refs/heads/main/images/banana.jpg"
+     *               }
+     *             ]
+     *           }
+     *         ],
+     *         "model": "voyage-multimodal-3"
+     *       }
+     *       </span></code></pre>
+     *   </details>
+     *   <details> <summary> Example payload where <code class="rdmd-code lang- theme-light" data-lang="" name="" tabindex="0"><span class="cm-s-neo" data-testid="SyntaxHighlighter">inputs</span></code>&nbsp;contains a Base64 image </summary>
+     *       <br>
+     *       Below is an equivalent example to the one above where the image content is a Base64 image instead of a URL. (Base64 images can be lengthy, so the example only shows a shortened version.)
+     *       <pre><code class="rdmd-code lang- theme-light" data-lang="" name="" tabindex="0"><span class="cm-s-neo" data-testid="SyntaxHighlighter">
+     *       {
+     *         "inputs": [
+     *           {
+     *             "content": [
+     *               {
+     *                 "type": "text",
+     *                 "text": "This is a banana."
+     *               },
+     *               {
+     *                 "type": "image_base64",
+     *                 "image_base64": "data:image/jpeg;base64,/9j/4AAQSkZJRgABAQAA..."
+     *               }
+     *             ]
+     *           }
+     *         ],
+     *         "model": "voyage-multimodal-3"
+     *       }
+     *       </span></code></pre>
+     *   </details>
+     *   </li>
+     * </ul>
+     *
+     */
+    inputs: VoyageAI.MultimodalembeddingsApiRequestInputsItem[];
+    /**
+     * Name of the model. Currently, the only supported model is `voyage-multimodal-3`.
+     *
+     */
+    model: string;
+    /**
+     * Type of the input text. Defaults to `null`. Other options: `query`, `document`.
+     * <ul> <li> When <code class="rdmd-code lang- theme-light" data-lang="" name="" tabindex="0"><span class="cm-s-neo" data-testid="SyntaxHighlighter">input_type</span></code> is <code class="rdmd-code lang- theme-light" data-lang="" name="" tabindex="0"><span class="cm-s-neo" data-testid="SyntaxHighlighter">null</span></code>, the embedding model directly converts your input data into numerical vectors. For retrieval/search purposes—where an input (called a "query") is used to search for relevant pieces of information (referred to as "documents")—we recommend specifying whether your inputs are intended as queries or documents by setting <code class="rdmd-code lang- theme-light" data-lang="" name="" tabindex="0"><span class="cm-s-neo" data-testid="SyntaxHighlighter">input_type</span></code> to <code class="rdmd-code lang- theme-light" data-lang="" name="" tabindex="0"><span class="cm-s-neo" data-testid="SyntaxHighlighter">query</span></code> or <code class="rdmd-code lang- theme-light" data-lang="" name="" tabindex="0"><span class="cm-s-neo" data-testid="SyntaxHighlighter">document</span></code>, respectively. In these cases, Voyage prepends a prompt to your input before vectorizing it, helping the model create more effective vectors tailored for retrieval/search tasks. Since inputs can be multimodal, queries and documents can be text, images, or an interleaving of both modalities. Embeddings generated with and without the <code class="rdmd-code lang- theme-light" data-lang="" name="" tabindex="0"><span class="cm-s-neo" data-testid="SyntaxHighlighter">input_type</span></code> argument are compatible. </li> <li> For transparency, the following prompts are prepended to your input. </li><p></p>
+     *   <ul>
+     *     <li> For&nbsp;<code class="rdmd-code lang- theme-light" data-lang="" name="" tabindex="0"><span class="cm-s-neo" data-testid="SyntaxHighlighter">query</span></code>, the prompt is <i>"Represent the query for retrieving supporting documents:&nbsp;".</i> </li>
+     *     <li> For&nbsp;<code class="rdmd-code lang- theme-light" data-lang="" name="" tabindex="0"><span class="cm-s-neo" data-testid="SyntaxHighlighter">document</span></code>, the prompt is <i>"Represent the query for retrieving supporting documents:&nbsp;".</i> </li>
+     *   </ul>
+     * <ul></ul></ul>
+     *
+     */
+    inputType?: VoyageAI.MultimodalembeddingsApiRequestInputType;
+    /**
+     * Whether to truncate the input texts to fit within the context length. Defaults to `true`. <ul>  <li> If `true`, over-length input texts will be truncated to fit within the context length, before vectorized by the embedding model. </li>  <li> If `false`, an error will be raised if any given text exceeds the context length. </li>  </ul>
+     *
+     */
+    truncation?: boolean;
+    /**
+     * Format in which the embeddings are encoded. We support two options:  <ul> <li> If not specified (defaults to `null`): the embeddings are represented as lists of floating-point numbers; </li>  <li> `base64`: the embeddings are compressed to [base64](https://docs.python.org/3/library/base64.html) encodings. </li>  </ul>
+     *
+     */
+    encodingFormat?: "base64";
+}
diff --git a/src/api/resources/endpoints/client/requests/index.ts b/src/api/resources/endpoints/client/requests/index.ts
@@ -0,0 +1 @@
+export { type MultimodalembeddingsApiRequest } from "./MultimodalembeddingsApiRequest";
diff --git a/src/api/resources/endpoints/index.ts b/src/api/resources/endpoints/index.ts
@@ -0,0 +1,2 @@
+export * from "./types";
+export * from "./client";
Original file line number	Diff line number	Diff line change
		@@ -0,0 +1 @@
		export { type MultimodalembeddingsApiRequest } from "./MultimodalembeddingsApiRequest";
Original file line number	Diff line number	Diff line change
		@@ -0,0 +1,2 @@
		export * from "./types";
		export * from "./client";