feat(community): add ByteDance Doubao Embeddings

docs/core_docs/docs/integrations/text_embedding/bytedance_doubao.mdx

@@ -0,0 +1,33 @@
+---
+sidebar_class_name: node-only
+---
+
+# ByteDance Doubao
+
+The `ByteDanceDoubaoEmbeddings` class uses the ByteDance Doubao API to generate embeddings for a given text.
+
+## Setup
+
+You'll need to sign up for an ByteDance API key and set it as an environment variable named `ARK_API_KEY`.
+
+Then, you'll need to install the [`@langchain/community`](https://www.npmjs.com/package/@langchain/community) package:
+
+import IntegrationInstallTooltip from "@mdx_components/integration_install_tooltip.mdx";
+
+<IntegrationInstallTooltip></IntegrationInstallTooltip>
+
+```bash npm2yarn
+npm install @langchain/community @langchain/core
+```
+
+## Usage
+
+import CodeBlock from "@theme/CodeBlock";
+import ByteDanceDoubaoExample from "@examples/embeddings/bytedance_doubao.ts";
+
+<CodeBlock language="typescript">{ByteDanceDoubaoExample}</CodeBlock>
+
+## Related
+
+- Embedding model [conceptual guide](/docs/concepts/embedding_models)
+- Embedding model [how-to guides](/docs/how_to/#embedding-models)

examples/.env.example

@@ -84,7 +84,8 @@ HANA_HOST=HANA_DB_ADDRESS
 HANA_PORT=HANA_DB_PORT
 HANA_UID=HANA_DB_USER
 HANA_PWD=HANA_DB_PASSWORD
+ARK_API_KEY=ADD_YOURS_HERE # https://console.volcengine.com/
 JIRA_HOST=ADD_YOURS_HERE
 JIRA_USERNAME=ADD_YOURS_HERE
 JIRA_ACCESS_TOKEN=ADD_YOURS_HERE
-JIRA_PROJECT_KEY=ADD_YOURS_HERE
+JIRA_PROJECT_KEY=ADD_YOURS_HERE

examples/src/embeddings/bytedance_doubao.ts

@@ -0,0 +1,9 @@
+import { ByteDanceDoubaoEmbeddings } from "@langchain/community/embeddings/bytedance_doubao";
+
+const model = new ByteDanceDoubaoEmbeddings({
+  modelName: 'ep-xxx-xxx'
+});
+const res = await model.embedQuery(
+  "What would be a good company name a company that makes colorful socks?"
+);
+console.log({ res });

libs/langchain-community/.gitignore

@@ -146,6 +146,10 @@ embeddings/bedrock.cjs
 embeddings/bedrock.js
 embeddings/bedrock.d.ts
 embeddings/bedrock.d.cts
+embeddings/bytedance_doubao.cjs
+embeddings/bytedance_doubao.js
+embeddings/bytedance_doubao.d.ts
+embeddings/bytedance_doubao.d.cts
 embeddings/cloudflare_workersai.cjs
 embeddings/cloudflare_workersai.js
 embeddings/cloudflare_workersai.d.ts

libs/langchain-community/langchain.config.js

@@ -72,6 +72,7 @@ export const config = {
     "embeddings/alibaba_tongyi": "embeddings/alibaba_tongyi",
     "embeddings/baidu_qianfan": "embeddings/baidu_qianfan",
     "embeddings/bedrock": "embeddings/bedrock",
+    "embeddings/bytedance_doubao": "embeddings/bytedance_doubao",
     "embeddings/cloudflare_workersai": "embeddings/cloudflare_workersai",
     "embeddings/cohere": "embeddings/cohere",
     "embeddings/deepinfra": "embeddings/deepinfra",

libs/langchain-community/package.json

@@ -1056,6 +1056,15 @@
       "import": "./embeddings/bedrock.js",
       "require": "./embeddings/bedrock.cjs"
     },
+    "./embeddings/bytedance_doubao": {
+      "types": {
+        "import": "./embeddings/bytedance_doubao.d.ts",
+        "require": "./embeddings/bytedance_doubao.d.cts",
+        "default": "./embeddings/bytedance_doubao.d.ts"
+      },
+      "import": "./embeddings/bytedance_doubao.js",
+      "require": "./embeddings/bytedance_doubao.cjs"
+    },
     "./embeddings/cloudflare_workersai": {
       "types": {
         "import": "./embeddings/cloudflare_workersai.d.ts",
@@ -3332,6 +3341,10 @@
     "embeddings/bedrock.js",
     "embeddings/bedrock.d.ts",
     "embeddings/bedrock.d.cts",
+    "embeddings/bytedance_doubao.cjs",
+    "embeddings/bytedance_doubao.js",
+    "embeddings/bytedance_doubao.d.ts",
+    "embeddings/bytedance_doubao.d.cts",
     "embeddings/cloudflare_workersai.cjs",
     "embeddings/cloudflare_workersai.js",
     "embeddings/cloudflare_workersai.d.ts",

libs/langchain-community/src/embeddings/bytedance_doubao.ts

@@ -0,0 +1,175 @@
+import { getEnvironmentVariable } from "@langchain/core/utils/env";
+import { Embeddings, type EmbeddingsParams } from "@langchain/core/embeddings";
+import { chunkArray } from "@langchain/core/utils/chunk_array";
+
+export interface ByteDanceDoubaoEmbeddingsParams extends EmbeddingsParams {
+  /** Model name to use */
+  modelName: string;
+
+  /**
+   * Timeout to use when making requests to ByteDanceDoubao.
+   */
+  timeout?: number;
+
+  /**
+   * The maximum number of documents to embed in a single request. This is
+   * limited by the ByteDanceDoubao API to a maximum of 2048.
+   */
+  batchSize?: number;
+
+  /**
+   * Whether to strip new lines from the input text.
+   */
+  stripNewLines?: boolean;
+}
+
+interface EmbeddingCreateParams {
+  model: ByteDanceDoubaoEmbeddingsParams["modelName"];
+  input: string[];
+  encoding_format?: "float";
+}
+
+interface EmbeddingResponse {
+  data: {
+    index: number;
+    embedding: number[];
+  }[];
+
+  usage: {
+    prompt_tokens: number;
+    total_tokens: number;
+  };
+
+  id: string;
+}
+
+interface EmbeddingErrorResponse {
+  type: string;
+  code: string;
+  param: string;
+  message: string;
+}
+
+export class ByteDanceDoubaoEmbeddings
+  extends Embeddings
+  implements ByteDanceDoubaoEmbeddingsParams {
+  modelName: ByteDanceDoubaoEmbeddingsParams["modelName"] = "";
+
+  batchSize = 24;
+
+  stripNewLines = true;
+
+  apiKey: string;
+
+  constructor(
+    fields?: Partial<ByteDanceDoubaoEmbeddingsParams> & {
+      verbose?: boolean;
+      apiKey?: string;
+    }
+  ) {
+    const fieldsWithDefaults = { maxConcurrency: 2, ...fields };
+    super(fieldsWithDefaults);
+
+    const apiKey =
+      fieldsWithDefaults?.apiKey ?? getEnvironmentVariable("ARK_API_KEY");
+
+    if (!apiKey) throw new Error("ByteDanceDoubao API key not found");
+
+    this.apiKey = apiKey;
+
+    this.modelName = fieldsWithDefaults?.modelName ?? this.modelName;
+    this.batchSize = fieldsWithDefaults?.batchSize ?? this.batchSize;
+    this.stripNewLines =
+      fieldsWithDefaults?.stripNewLines ?? this.stripNewLines;
+  }
+
+  /**
+   * Method to generate embeddings for an array of documents. Splits the
+   * documents into batches and makes requests to the ByteDanceDoubao API to generate
+   * embeddings.
+   * @param texts Array of documents to generate embeddings for.
+   * @returns Promise that resolves to a 2D array of embeddings for each document.
+   */
+  async embedDocuments(texts: string[]): Promise<number[][]> {
+    const batches = chunkArray(
+      this.stripNewLines ? texts.map((t) => t.replace(/\n/g, " ")) : texts,
+      this.batchSize
+    );
+    const batchRequests = batches.map((batch) => {
+      const params = this.getParams(batch);
+
+      return this.embeddingWithRetry(params);
+    });
+
+    const batchResponses = await Promise.all(batchRequests);
+    const embeddings: number[][] = [];
+
+    for (let i = 0; i < batchResponses.length; i += 1) {
+      const batch = batches[i];
+      const batchResponse = batchResponses[i] || [];
+      for (let j = 0; j < batch.length; j += 1) {
+        embeddings.push(batchResponse[j]);
+      }
+    }
+
+    return embeddings;
+  }
+
+  /**
+   * Method to generate an embedding for a single document. Calls the
+   * embeddingWithRetry method with the document as the input.
+   * @param text Document to generate an embedding for.
+   * @returns Promise that resolves to an embedding for the document.
+   */
+  async embedQuery(text: string): Promise<number[]> {
+    const params = this.getParams([
+      this.stripNewLines ? text.replace(/\n/g, " ") : text,
+    ]);
+
+    const embeddings = (await this.embeddingWithRetry(params)) || [[]];
+    return embeddings[0];
+  }
+
+  /**
+   * Method to generate an embedding params.
+   * @param texts Array of documents to generate embeddings for.
+   * @returns an embedding params.
+   */
+  private getParams(
+    texts: EmbeddingCreateParams["input"]
+  ): EmbeddingCreateParams {
+    return {
+      model: this.modelName,
+      input: texts,
+    };
+  }
+
+  /**
+   * Private method to make a request to the OpenAI API to generate
+   * embeddings. Handles the retry logic and returns the response from the
+   * API.
+   * @param request Request to send to the OpenAI API.
+   * @returns Promise that resolves to the response from the API.
+   */
+  private async embeddingWithRetry(body: EmbeddingCreateParams) {
+    return fetch("https://ark.cn-beijing.volces.com/api/v3/embeddings", {
+      method: "POST",
+      headers: {
+        "Content-Type": "application/json",
+        Authorization: `Bearer ${this.apiKey}`,
+      },
+      body: JSON.stringify(body),
+    }).then(async (response) => {
+      const embeddingData: EmbeddingResponse | EmbeddingErrorResponse =
+        await response.json();
+
+      if ("code" in embeddingData && embeddingData.code) {
+        throw new Error(`${embeddingData.code}: ${embeddingData.message}`);
+      }
+
+      return (embeddingData as EmbeddingResponse).data.map(
+        ({ embedding }) => embedding
+      );
+    });
+  }
+}

libs/langchain-community/src/embeddings/tests/bytedance_doubao.int.test.ts

@@ -0,0 +1,40 @@
+import { test, expect } from "@jest/globals";
+import { ByteDanceDoubaoEmbeddings } from "../bytedance_doubao.js";
+
+const modelName = 'ep-xxx-xxx';
+test.skip("Test ByteDanceDoubaoEmbeddings.embedQuery", async () => {
+  const embeddings = new ByteDanceDoubaoEmbeddings({
+    modelName,
+  });
+  const res = await embeddings.embedQuery("Hello world");
+  expect(typeof res[0]).toBe("number");
+});
+
+test.skip("Test ByteDanceDoubaoEmbeddings.embedDocuments", async () => {
+  const embeddings = new ByteDanceDoubaoEmbeddings({
+    modelName,
+  });
+  const res = await embeddings.embedDocuments(["Hello world", "Bye bye"]);
+  expect(res).toHaveLength(2);
+  expect(typeof res[0][0]).toBe("number");
+  expect(typeof res[1][0]).toBe("number");
+});
+
+test.skip("Test ByteDanceDoubaoEmbeddings concurrency", async () => {
+  const embeddings = new ByteDanceDoubaoEmbeddings({
+    modelName,
+    batchSize: 1,
+  });
+  const res = await embeddings.embedDocuments([
+    "Hello world",
+    "Bye bye",
+    "Hello world",
+    "Bye bye",
+    "Hello world",
+    "Bye bye",
+  ]);
+  expect(res).toHaveLength(6);
+  expect(res.find((embedding) => typeof embedding[0] !== "number")).toBe(
+    undefined
+  );
+});

libs/langchain-community/src/load/import_map.ts

@@ -27,6 +27,7 @@ export * as agents__toolkits__base from "../agents/toolkits/base.js";
 export * as agents__toolkits__connery from "../agents/toolkits/connery/index.js";
 export * as embeddings__alibaba_tongyi from "../embeddings/alibaba_tongyi.js";
 export * as embeddings__baidu_qianfan from "../embeddings/baidu_qianfan.js";
+export * as embeddings__bytedance_doubao from "../embeddings/bytedance_doubao.js";
 export * as embeddings__deepinfra from "../embeddings/deepinfra.js";
 export * as embeddings__fireworks from "../embeddings/fireworks.js";
 export * as embeddings__minimax from "../embeddings/minimax.js";