first commit

.gitignore

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+wwwroot/*.js
+node_modules
+typings
+dist

.npmignore

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+README.md

.openapi-generator-ignore

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+# OpenAPI Generator Ignore
+# Generated by openapi-generator https://github.com/openapitools/openapi-generator
+
+# Use this file to prevent files from being overwritten by the generator.
+# The patterns follow closely to .gitignore or .dockerignore.
+
+# As an example, the C# client generator defines ApiClient.cs.
+# You can make changes and tell OpenAPI Generator to ignore just this file by uncommenting the following line:
+#ApiClient.cs
+
+# You can match any string of characters against a directory, file or extension with a single asterisk (*):
+#foo/*/qux
+# The above matches foo/bar/qux and foo/baz/qux, but not foo/bar/baz/qux
+
+# You can recursively match patterns against a directory, file or extension with a double asterisk (**):
+#foo/**/qux
+# This matches foo/bar/qux, foo/baz/qux, and foo/bar/baz/qux
+
+# You can also negate patterns with an exclamation (!).
+# For example, you can ignore all files in a docs folder with the file extension .md:
+#docs/*.md
+# Then explicitly reverse the ignore rule for a single file:
+#!docs/README.md
+
+src/runtime.ts

.openapi-generator/FILES

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+.gitignore
+.npmignore
+.openapi-generator-ignore
+README.md
+package.json
+src/apis/MixedbreadAiApi.ts
+src/apis/index.ts
+src/index.ts
+src/models/Embeddings200Response.ts
+src/models/Embeddings200ResponseDataInner.ts
+src/models/Embeddings200ResponseUsage.ts
+src/models/EmbeddingsRequest.ts
+src/models/ErrorResponse.ts
+src/models/index.ts
+src/runtime.ts
+tsconfig.esm.json
+tsconfig.json

.openapi-generator/VERSION

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+7.2.0

README.md

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+## @mixedbread-ai/sdk@1.0.0
+
+This generator creates TypeScript/JavaScript client that utilizes [Fetch API](https://fetch.spec.whatwg.org/). The generated Node module can be used in the following environments:
+
+Environment
+* Node.js
+* Webpack
+* Browserify
+
+Language level
+* ES5 - you must have a Promises/A+ library installed
+* ES6
+
+Module system
+* CommonJS
+* ES6 module system
+
+It can be used in both TypeScript and JavaScript. In TypeScript, the definition should be automatically resolved via `package.json`. ([Reference](http://www.typescriptlang.org/docs/handbook/typings-for-npm-packages.html))
+
+### Building
+
+To build and compile the typescript sources to javascript use:
+```
+npm install
+npm run build
+```
+
+### Publishing
+
+First build the package then run ```npm publish```
+
+### Consuming
+
+navigate to the folder of your consuming project and run one of the following commands.
+
+_published:_
+
+```
+npm install @mixedbread-ai/sdk@1.0.0 --save
+```
+
+_unPublished (not recommended):_
+
+```
+npm install PATH_TO_GENERATED_PACKAGE --save
+# typescript-sdk

dist/apis/MixedbreadAiApi.d.ts

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+/**
+ * mixedbread-ai
+ * Discover how to convert text into embeddings with the Embeddings API. Ideal for NLP tasks like text similarity and clustering. Use top open source models or your own fine-tuned models.
+ *
+ * The version of the OpenAPI document: 1.0.0
+ *
+ *
+ * NOTE: This class is auto generated by OpenAPI Generator (https://openapi-generator.tech).
+ * https://openapi-generator.tech
+ * Do not edit the class manually.
+ */
+import * as runtime from '../runtime';
+import type { Embeddings200Response, EmbeddingsRequest } from '../models/index';
+export interface EmbeddingsOperationRequest {
+    embeddingsRequest: EmbeddingsRequest;
+}
+/**
+ *
+ */
+export declare class MixedbreadAiApi extends runtime.BaseAPI {
+    /**
+     * This endpoint allows you to post text data and receive embeddings in response. The embeddings are generated using the model specified in the request body.
+     * Create embeddings
+     */
+    embeddingsRaw(requestParameters: EmbeddingsOperationRequest, initOverrides?: RequestInit | runtime.InitOverrideFunction): Promise<runtime.ApiResponse<Embeddings200Response>>;
+    /**
+     * This endpoint allows you to post text data and receive embeddings in response. The embeddings are generated using the model specified in the request body.
+     * Create embeddings
+     */
+    embeddings(embeddingsRequest: EmbeddingsRequest, initOverrides?: RequestInit | runtime.InitOverrideFunction): Promise<Embeddings200Response>;
+}

dist/apis/MixedbreadAiApi.js

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+"use strict";
+/* tslint:disable */
+/* eslint-disable */
+/**
+ * mixedbread-ai
+ * Discover how to convert text into embeddings with the Embeddings API. Ideal for NLP tasks like text similarity and clustering. Use top open source models or your own fine-tuned models.
+ *
+ * The version of the OpenAPI document: 1.0.0
+ *
+ *
+ * NOTE: This class is auto generated by OpenAPI Generator (https://openapi-generator.tech).
+ * https://openapi-generator.tech
+ * Do not edit the class manually.
+ */
+var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
+    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
+    return new (P || (P = Promise))(function (resolve, reject) {
+        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
+        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
+        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
+        step((generator = generator.apply(thisArg, _arguments || [])).next());
+    });
+};
+Object.defineProperty(exports, "__esModule", { value: true });
+exports.MixedbreadAiApi = void 0;
+const runtime = require("../runtime");
+const index_1 = require("../models/index");
+/**
+ *
+ */
+class MixedbreadAiApi extends runtime.BaseAPI {
+    /**
+     * This endpoint allows you to post text data and receive embeddings in response. The embeddings are generated using the model specified in the request body.
+     * Create embeddings
+     */
+    embeddingsRaw(requestParameters, initOverrides) {
+        return __awaiter(this, void 0, void 0, function* () {
+            if (requestParameters.embeddingsRequest === null || requestParameters.embeddingsRequest === undefined) {
+                throw new runtime.RequiredError('embeddingsRequest', 'Required parameter requestParameters.embeddingsRequest was null or undefined when calling embeddings.');
+            }
+            const queryParameters = {};
+            const headerParameters = {};
+            headerParameters['Content-Type'] = 'application/json';
+            if (this.configuration && this.configuration.apiKey) {
+                headerParameters["Authorization"] = this.configuration.apiKey("Authorization"); // MIXEDBREADAI_API_KEY authentication
+            }
+            const response = yield this.request({
+                path: `/v1/embeddings/`,
+                method: 'POST',
+                headers: headerParameters,
+                query: queryParameters,
+                body: (0, index_1.EmbeddingsRequestToJSON)(requestParameters.embeddingsRequest),
+            }, initOverrides);
+            return new runtime.JSONApiResponse(response, (jsonValue) => (0, index_1.Embeddings200ResponseFromJSON)(jsonValue));
+        });
+    }
+    /**
+     * This endpoint allows you to post text data and receive embeddings in response. The embeddings are generated using the model specified in the request body.
+     * Create embeddings
+     */
+    embeddings(embeddingsRequest, initOverrides) {
+        return __awaiter(this, void 0, void 0, function* () {
+            const response = yield this.embeddingsRaw({ embeddingsRequest: embeddingsRequest }, initOverrides);
+            return yield response.value();
+        });
+    }
+}
+exports.MixedbreadAiApi = MixedbreadAiApi;

dist/apis/index.d.ts

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+export * from './MixedbreadAiApi';

dist/apis/index.js

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+"use strict";
+var __createBinding = (this && this.__createBinding) || (Object.create ? (function(o, m, k, k2) {
+    if (k2 === undefined) k2 = k;
+    var desc = Object.getOwnPropertyDescriptor(m, k);
+    if (!desc || ("get" in desc ? !m.__esModule : desc.writable || desc.configurable)) {
+      desc = { enumerable: true, get: function() { return m[k]; } };
+    }
+    Object.defineProperty(o, k2, desc);
+}) : (function(o, m, k, k2) {
+    if (k2 === undefined) k2 = k;
+    o[k2] = m[k];
+}));
+var __exportStar = (this && this.__exportStar) || function(m, exports) {
+    for (var p in m) if (p !== "default" && !Object.prototype.hasOwnProperty.call(exports, p)) __createBinding(exports, m, p);
+};
+Object.defineProperty(exports, "__esModule", { value: true });
+/* tslint:disable */
+/* eslint-disable */
+__exportStar(require("./MixedbreadAiApi"), exports);

dist/esm/apis/MixedbreadAiApi.d.ts

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+/**
+ * mixedbread-ai
+ * Discover how to convert text into embeddings with the Embeddings API. Ideal for NLP tasks like text similarity and clustering. Use top open source models or your own fine-tuned models.
+ *
+ * The version of the OpenAPI document: 1.0.0
+ *
+ *
+ * NOTE: This class is auto generated by OpenAPI Generator (https://openapi-generator.tech).
+ * https://openapi-generator.tech
+ * Do not edit the class manually.
+ */
+import * as runtime from '../runtime';
+import type { Embeddings200Response, EmbeddingsRequest } from '../models/index';
+export interface EmbeddingsOperationRequest {
+    embeddingsRequest: EmbeddingsRequest;
+}
+/**
+ *
+ */
+export declare class MixedbreadAiApi extends runtime.BaseAPI {
+    /**
+     * This endpoint allows you to post text data and receive embeddings in response. The embeddings are generated using the model specified in the request body.
+     * Create embeddings
+     */
+    embeddingsRaw(requestParameters: EmbeddingsOperationRequest, initOverrides?: RequestInit | runtime.InitOverrideFunction): Promise<runtime.ApiResponse<Embeddings200Response>>;
+    /**
+     * This endpoint allows you to post text data and receive embeddings in response. The embeddings are generated using the model specified in the request body.
+     * Create embeddings
+     */
+    embeddings(embeddingsRequest: EmbeddingsRequest, initOverrides?: RequestInit | runtime.InitOverrideFunction): Promise<Embeddings200Response>;
+}

dist/esm/apis/MixedbreadAiApi.js

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+/* tslint:disable */
+/* eslint-disable */
+/**
+ * mixedbread-ai
+ * Discover how to convert text into embeddings with the Embeddings API. Ideal for NLP tasks like text similarity and clustering. Use top open source models or your own fine-tuned models.
+ *
+ * The version of the OpenAPI document: 1.0.0
+ *
+ *
+ * NOTE: This class is auto generated by OpenAPI Generator (https://openapi-generator.tech).
+ * https://openapi-generator.tech
+ * Do not edit the class manually.
+ */
+var __awaiter = (this && this.__awaiter) || function (thisArg, _arguments, P, generator) {
+    function adopt(value) { return value instanceof P ? value : new P(function (resolve) { resolve(value); }); }
+    return new (P || (P = Promise))(function (resolve, reject) {
+        function fulfilled(value) { try { step(generator.next(value)); } catch (e) { reject(e); } }
+        function rejected(value) { try { step(generator["throw"](value)); } catch (e) { reject(e); } }
+        function step(result) { result.done ? resolve(result.value) : adopt(result.value).then(fulfilled, rejected); }
+        step((generator = generator.apply(thisArg, _arguments || [])).next());
+    });
+};
+import * as runtime from '../runtime';
+import { Embeddings200ResponseFromJSON, EmbeddingsRequestToJSON, } from '../models/index';
+/**
+ *
+ */
+export class MixedbreadAiApi extends runtime.BaseAPI {
+    /**
+     * This endpoint allows you to post text data and receive embeddings in response. The embeddings are generated using the model specified in the request body.
+     * Create embeddings
+     */
+    embeddingsRaw(requestParameters, initOverrides) {
+        return __awaiter(this, void 0, void 0, function* () {
+            if (requestParameters.embeddingsRequest === null || requestParameters.embeddingsRequest === undefined) {
+                throw new runtime.RequiredError('embeddingsRequest', 'Required parameter requestParameters.embeddingsRequest was null or undefined when calling embeddings.');
+            }
+            const queryParameters = {};
+            const headerParameters = {};
+            headerParameters['Content-Type'] = 'application/json';
+            if (this.configuration && this.configuration.apiKey) {
+                headerParameters["Authorization"] = this.configuration.apiKey("Authorization"); // MIXEDBREADAI_API_KEY authentication
+            }
+            const response = yield this.request({
+                path: `/v1/embeddings/`,
+                method: 'POST',
+                headers: headerParameters,
+                query: queryParameters,
+                body: EmbeddingsRequestToJSON(requestParameters.embeddingsRequest),
+            }, initOverrides);
+            return new runtime.JSONApiResponse(response, (jsonValue) => Embeddings200ResponseFromJSON(jsonValue));
+        });
+    }
+    /**
+     * This endpoint allows you to post text data and receive embeddings in response. The embeddings are generated using the model specified in the request body.
+     * Create embeddings
+     */
+    embeddings(embeddingsRequest, initOverrides) {
+        return __awaiter(this, void 0, void 0, function* () {
+            const response = yield this.embeddingsRaw({ embeddingsRequest: embeddingsRequest }, initOverrides);
+            return yield response.value();
+        });
+    }
+}

dist/esm/apis/index.d.ts

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+export * from './MixedbreadAiApi';

dist/esm/apis/index.js

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+/* tslint:disable */
+/* eslint-disable */
+export * from './MixedbreadAiApi';

dist/esm/index.d.ts

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+export * from './runtime';
+export * from './apis/index';
+export * from './models/index';

dist/esm/index.js

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+/* tslint:disable */
+/* eslint-disable */
+export * from './runtime';
+export * from './apis/index';
+export * from './models/index';

dist/esm/models/Embeddings200Response.d.ts

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+/**
+ * mixedbread-ai
+ * Discover how to convert text into embeddings with the Embeddings API. Ideal for NLP tasks like text similarity and clustering. Use top open source models or your own fine-tuned models.
+ *
+ * The version of the OpenAPI document: 1.0.0
+ *
+ *
+ * NOTE: This class is auto generated by OpenAPI Generator (https://openapi-generator.tech).
+ * https://openapi-generator.tech
+ * Do not edit the class manually.
+ */
+import type { Embeddings200ResponseDataInner } from './Embeddings200ResponseDataInner';
+import type { Embeddings200ResponseUsage } from './Embeddings200ResponseUsage';
+/**
+ *
+ * @export
+ * @interface Embeddings200Response
+ */
+export interface Embeddings200Response {
+    /**
+     * The embeddings model used.
+     * @type {string}
+     * @memberof Embeddings200Response
+     */
+    model: string;
+    /**
+     *
+     * @type {Array<Embeddings200ResponseDataInner>}
+     * @memberof Embeddings200Response
+     */
+    data: Array<Embeddings200ResponseDataInner>;
+    /**
+     *
+     * @type {Embeddings200ResponseUsage}
+     * @memberof Embeddings200Response
+     */
+    usage: Embeddings200ResponseUsage;
+}
+/**
+ * Check if a given object implements the Embeddings200Response interface.
+ */
+export declare function instanceOfEmbeddings200Response(value: object): boolean;
+export declare function Embeddings200ResponseFromJSON(json: any): Embeddings200Response;
+export declare function Embeddings200ResponseFromJSONTyped(json: any, ignoreDiscriminator: boolean): Embeddings200Response;
+export declare function Embeddings200ResponseToJSON(value?: Embeddings200Response | null): any;