TypeScript SDK for the Unstructured API

This is a HTTP client for the Unstructured Platform API. You can sign up here and process 1000 free pages per day for 14 days.

Please refer to the our documentation for a full guide on integrating the Partition Endpoint into your JavaScript/TypeScript code. Support for the Workflow Endpoint is coming soon.

SDK Installation

NPM

npm install unstructured-client --include=dev

Yarn

yarn add unstructured-client --dev

Model Context Protocol (MCP) Server

This SDK is also an installable MCP server where the various SDK methods are exposed as tools that can be invoked by AI applications.

Node.js v20 or greater is required to run the MCP server.

Claude installation steps

Add the following server definition to your claude_desktop_config.json file:

{
  "mcpServers": {
    "Unstructured": {
      "command": "npx",
      "args": [
        "-y", "--package", "unstructured-client",
        "--",
        "mcp", "start",
      ]
    }
  }
}

Cursor installation steps

Go to Cursor Settings > Features > MCP Servers > Add new MCP server and use the following settings:

• Name: Unstructured
• Type: command
• Command:

npx -y --package unstructured-client -- mcp start

For a full list of server arguments, run:

npx -y --package unstructured-client -- mcp start --help

SDK Example Usage

Example

import { UnstructuredClient } from "unstructured-client";
import { PartitionResponse } from "unstructured-client/sdk/models/operations";
import { Strategy } from "unstructured-client/sdk/models/shared";
import * as fs from "fs";

const unstructuredClient = new UnstructuredClient({
    security: {
        apiKeyAuth: "YOUR_API_KEY",
    },
});

const filename = "./sample-file";
const data = fs.readFileSync(filename);

unstructuredClient.general.partition({
    partitionParameters: {
        files: {
            content: data,
            fileName: filename,
        },
	strategy: Strategy.Auto,
    }
}).then((res: PartitionResponse) => {
    if (res.statusCode == 200) {
        console.log(res.elements);
    }
}).catch((e) => {
    console.log(e.statusCode);
    console.log(e.body);
});

Refer to the API parameters page for all available parameters.

Change the base URL

If you are self hosting the API, or developing locally, you can change the server URL when setting up the client.

const client = new UnstructuredClient({
    serverURL: "http://localhost:8000",
    security: {
        apiKeyAuth: key,
    },
});

// OR

const client = new UnstructuredClient({
    serverURL: "https://my-server-url",
    security: {
        apiKeyAuth: key,
    },
});

Custom HTTP Client

The TypeScript SDK makes API calls using an HTTPClient that wraps the native Fetch API. This client is a thin wrapper around fetch and provides the ability to attach hooks around the request lifecycle that can be used to modify the request or handle errors and response.

The HTTPClient constructor takes an optional fetcher argument that can be used to integrate a third-party HTTP client or when writing tests to mock out the HTTP client and feed in fixtures.

The following example shows how to use the "beforeRequest" hook to to add a custom header and a timeout to requests and how to use the "requestError" hook to log errors:

import { UnstructuredClient } from "unstructured-client";
import { HTTPClient } from "unstructured-client/lib/http";

const httpClient = new HTTPClient({
  // fetcher takes a function that has the same signature as native `fetch`.
  fetcher: (request) => {
    return fetch(request);
  }
});

httpClient.addHook("beforeRequest", (request) => {
  const nextRequest = new Request(request, {
    signal: request.signal || AbortSignal.timeout(5000)
  });

  nextRequest.headers.set("x-custom-header", "custom value");

  return nextRequest;
});

httpClient.addHook("requestError", (error, request) => {
  console.group("Request Error");
  console.log("Reason:", `${error}`);
  console.log("Endpoint:", `${request.method} ${request.url}`);
  console.groupEnd();
});

const sdk = new UnstructuredClient({ httpClient });

Retries

Some of the endpoints in this SDK support retries. If you use the SDK without any configuration, it will fall back to the default retry strategy provided by the API. However, the default retry strategy can be overridden on a per-operation basis, or across the entire SDK.

To change the default retry strategy for a single API call, simply provide a retryConfig object to the call:

import { openAsBlob } from "node:fs";
import { UnstructuredClient } from "unstructured-client";
import {
  VLMModel,
  VLMModelProvider,
} from "unstructured-client/sdk/models/shared";

const unstructuredClient = new UnstructuredClient();

async function run() {
  const result = await unstructuredClient.general.partition({
    partitionParameters: {
      chunkingStrategy: "by_title",
      files: await openAsBlob("example.file"),
      splitPdfPageRange: [
        1,
        10,
      ],
      vlmModel: VLMModel.Gpt4o,
      vlmModelProvider: VLMModelProvider.Openai,
    },
  }, {
    retries: {
      strategy: "backoff",
      backoff: {
        initialInterval: 1,
        maxInterval: 50,
        exponent: 1.1,
        maxElapsedTime: 100,
      },
      retryConnectionErrors: false,
    },
  });

  // Handle the result
  console.log(result);
}

run();

If you'd like to override the default retry strategy for all operations that support retries, you can provide a retryConfig at SDK initialization:

import { openAsBlob } from "node:fs";
import { UnstructuredClient } from "unstructured-client";
import {
  VLMModel,
  VLMModelProvider,
} from "unstructured-client/sdk/models/shared";

const unstructuredClient = new UnstructuredClient({
  retryConfig: {
    strategy: "backoff",
    backoff: {
      initialInterval: 1,
      maxInterval: 50,
      exponent: 1.1,
      maxElapsedTime: 100,
    },
    retryConnectionErrors: false,
  },
});

async function run() {
  const result = await unstructuredClient.general.partition({
    partitionParameters: {
      chunkingStrategy: "by_title",
      files: await openAsBlob("example.file"),
      splitPdfPageRange: [
        1,
        10,
      ],
      vlmModel: VLMModel.Gpt4o,
      vlmModelProvider: VLMModelProvider.Openai,
    },
  });

  // Handle the result
  console.log(result);
}

run();

Splitting PDF by pages

See page splitting for more details.

In order to speed up processing of large PDF files, the client splits up PDFs into smaller files, sends these to the API concurrently, and recombines the results. splitPdfPage can be set to false to disable this.

The amount of parallel requests is controlled by splitPdfConcurrencyLevel parameter. By default it equals to 5. It can't be more than 15, to avoid too high resource usage and costs. The size of each batch is determined internally and it can vary between 2 and 20 pages per split.

client.general.partition({
    partitionParameters: {
        files: {
            content: data,
            fileName: filename,
        },
        // Set splitPdfPage parameter to false in order to disable splitting PDF
        splitPdfPage: true,
        // Modify splitPdfConcurrencyLevel to change the limit of parallel requests
        splitPdfConcurrencyLevel: 10,
    },
}};

Summary

Table of Contents

• SDK Installation
• SDK Example Usage
• Change the base URL
• Custom HTTP Client
• Retries
• Requirements
• Standalone functions
• File uploads
• Debugging

Requirements

For supported JavaScript runtimes, please consult RUNTIMES.md.

Standalone functions

All the methods listed above are available as standalone functions. These functions are ideal for use in applications running in the browser, serverless runtimes or other environments where application bundle size is a primary concern. When using a bundler to build your application, all unused functionality will be either excluded from the final bundle or tree-shaken away.

To read more about standalone functions, check FUNCTIONS.md.

Available standalone functions

• generalPartition - Summary

File uploads

Certain SDK methods accept files as part of a multi-part request. It is possible and typically recommended to upload files as a stream rather than reading the entire contents into memory. This avoids excessive memory consumption and potentially crashing with out-of-memory errors when working with very large files. The following example demonstrates how to attach a file stream to a request.

Tip

Depending on your JavaScript runtime, there are convenient utilities that return a handle to a file without reading the entire contents into memory:

• Node.js v20+: Since v20, Node.js comes with a native openAsBlob function in node:fs.
• Bun: The native Bun.file function produces a file handle that can be used for streaming file uploads.
• Browsers: All supported browsers return an instance to a File when reading the value from an <input type="file"> element.
• Node.js v18: A file stream can be created using the fileFrom helper from fetch-blob/from.js.

import { openAsBlob } from "node:fs";
import { UnstructuredClient } from "unstructured-client";
import {
  VLMModel,
  VLMModelProvider,
} from "unstructured-client/sdk/models/shared";

const unstructuredClient = new UnstructuredClient();

async function run() {
  const result = await unstructuredClient.general.partition({
    partitionParameters: {
      chunkingStrategy: "by_title",
      files: await openAsBlob("example.file"),
      splitPdfPageRange: [
        1,
        10,
      ],
      vlmModel: VLMModel.Gpt4o,
      vlmModelProvider: VLMModelProvider.Openai,
    },
  });

  // Handle the result
  console.log(result);
}

run();

Debugging

You can setup your SDK to emit debug logs for SDK requests and responses.

You can pass a logger that matches console's interface as an SDK option.

Warning

Beware that debug logging will reveal secrets, like API tokens in headers, in log messages printed to a console or files. It's recommended to use this feature only during local development and not in production.

import { UnstructuredClient } from "unstructured-client";

const sdk = new UnstructuredClient({ debugLogger: console });

Maturity

This SDK is in beta, and there may be breaking changes between versions without a major version update. Therefore, we recommend pinning usage to a specific package version. This way, you can install the same version each time without breaking changes unless you are intentionally looking for the latest version.

Contributions

While we value open-source contributions to this SDK, this library is generated programmatically. Feel free to open a PR or a Github issue as a proof of concept and we'll do our best to include it in a future release!

SDK Created by Speakeasy