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https://github.com/unstructured-io/unstructured-js-client

A JavaScript/Typescript client for the Unstructured Platform API
https://github.com/unstructured-io/unstructured-js-client

Last synced: 9 months ago
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A JavaScript/Typescript client for the Unstructured Platform API

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README 

          


  






    






  
TypeScript SDK for the Unstructured API



This is a HTTP client for the [Unstructured Platform API](https://docs.unstructured.io/platform-api/overview). You can sign up [here](https://unstructured.io/developers) 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](https://docs.unstructured.io/platform-api/partition-api/sdk-jsts) into your JavaScript/TypeScript code. Support for the [Workflow Endpoint](https://docs.unstructured.io/platform-api/api/overview) is coming soon. 



## SDK Installation



### NPM



```bash

npm install unstructured-client --include=dev

```



### Yarn



```bash

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:



```json

{

  "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:

```sh

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

```



For a full list of server arguments, run:



```sh

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

```



## SDK Example Usage



### Example



```typescript

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](https://docs.unstructured.io/api-reference/api-services/api-parameters) 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.



```typescript

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](https://developer.mozilla.org/en-US/docs/Web/API/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:



```typescript

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: 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:

```typescript

import { openAsBlob } from "node:fs";

import { UnstructuredClient } from "unstructured-client";

import {

  Strategy,

  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,

      ],

      strategy: Strategy.Auto,

      vlmModel: VLMModel.Gpt4o,

      vlmModelProvider: VLMModelProvider.Openai,

    },

  }, {

    retries: {

      strategy: "backoff",

      backoff: {

        initialInterval: 1,

        maxInterval: 50,

        exponent: 1.1,

        maxElapsedTime: 100,

      },

      retryConnectionErrors: false,

    },

  });



  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:

```typescript

import { openAsBlob } from "node:fs";

import { UnstructuredClient } from "unstructured-client";

import {

  Strategy,

  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,

      ],

      strategy: Strategy.Auto,

      vlmModel: VLMModel.Gpt4o,

      vlmModelProvider: VLMModelProvider.Openai,

    },

  });



  console.log(result);

}



run();



```



### Splitting PDF by pages



See [page splitting](https://docs.unstructured.io/api-reference/api-services/sdk#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.



```typescript

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-installation)

  * [SDK Example Usage](#sdk-example-usage)

  * [Change the base URL](#change-the-base-url)

  * [Custom HTTP Client](#custom-http-client)

  * [Retries](#retries)

  * [Requirements](#requirements)

  * [Standalone functions](#standalone-functions)

  * [File uploads](#file-uploads)

  * [Debugging](#debugging)



## Requirements



For supported JavaScript runtimes, please consult [RUNTIMES.md](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](./FUNCTIONS.md).



Available standalone functions



- [`generalPartition`](docs/sdks/general/README.md#partition) - 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`](https://nodejs.org/docs/latest-v20.x/api/fs.html#fsopenasblobpath-options).

> - **Bun:** The native [`Bun.file`](https://bun.sh/docs/api/file-io#reading-files-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`](https://developer.mozilla.org/en-US/docs/Web/API/File) when reading the value from an `` element.

> - **Node.js v18:** A file stream can be created using the `fileFrom` helper from [`fetch-blob/from.js`](https://www.npmjs.com/package/fetch-blob).



```typescript

import { openAsBlob } from "node:fs";

import { UnstructuredClient } from "unstructured-client";

import {

  Strategy,

  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,

      ],

      strategy: Strategy.Auto,

      vlmModel: VLMModel.Gpt4o,

      vlmModelProvider: VLMModelProvider.Openai,

    },

  });



  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.



```typescript

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](https://docs.speakeasyapi.dev/docs/using-speakeasy/client-sdks)