Contextual AI Node API Library

 !npm bundle size

This library provides convenient access to the Contextual AI REST API from server-side TypeScript or JavaScript.

The REST API documentation can be found on docs.contextual.ai. The full API of this library can be found in api.md.

Installation

``sh
npm install contextual-client
`

Usage

The full API of this library can be found in api.md.


`js
import ContextualAI from 'contextual-client';

const client = new ContextualAI({
apiKey: process.env['CONTEXTUAL_API_KEY'], // This is the default and can be omitted
});

const createAgentOutput = await client.agents.create({ name: 'Example' });

console.log(createAgentOutput.id);
`

$3

This library includes TypeScript definitions for all request params and response fields. You may import and use them like so:


`ts
import ContextualAI from 'contextual-client';

const client = new ContextualAI({
apiKey: process.env['CONTEXTUAL_API_KEY'], // This is the default and can be omitted
});

const params: ContextualAI.AgentCreateParams = { name: 'Example' };
const createAgentOutput: ContextualAI.CreateAgentOutput = await client.agents.create(params);
`

Documentation for each method, request param, and response field are available in docstrings and will appear on hover in most modern editors.

File uploads

Request parameters that correspond to file uploads can be passed in many different forms:

- File (or an object with the same structure)
- a fetch Response (or an object with the same structure)
- an fs.ReadStream
- the return value of our toFile helper

`ts
import fs from 'fs';
import fetch from 'node-fetch';
import ContextualAI, { toFile } from 'contextual-client';

const client = new ContextualAI();

// If you have access to Node fs we recommend using fs.createReadStream():
await client.datastores.documents.ingest('182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e', {
file: fs.createReadStream('/path/to/file'),
});

// Or if you have the web File API you can pass a File instance:
await client.datastores.documents.ingest('182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e', {
file: new File(['my bytes'], 'file'),
});

// You can also pass a fetch Response:
await client.datastores.documents.ingest('182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e', {
file: await fetch('https://somesite/file'),
});

// Finally, if none of the above are convenient, you can use our toFile helper:
await client.datastores.documents.ingest('182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e', {
file: await toFile(Buffer.from('my bytes'), 'file'),
});
await client.datastores.documents.ingest('182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e', {
file: await toFile(new Uint8Array([0, 1, 2]), 'file'),
});
`

Handling errors

When the library is unable to connect to the API,
or if the API returns a non-success status code (i.e., 4xx or 5xx response),
a subclass of APIError will be thrown:


`ts
const createAgentOutput = await client.agents.create({ name: 'Example' }).catch(async (err) => {
if (err instanceof ContextualAI.APIError) {
console.log(err.status); // 400
console.log(err.name); // BadRequestError
console.log(err.headers); // {server: 'nginx', ...}
} else {
throw err;
}
});
`

Error codes are as follows:

| Status Code | Error Type |
| ----------- | -------------------------- |
| 400 | BadRequestError |
| 401 | AuthenticationError |
| 403 | PermissionDeniedError |
| 404 | NotFoundError |
| 422 | UnprocessableEntityError |
| 429 | RateLimitError |
| >=500 | InternalServerError |
| N/A | APIConnectionError |

$3

Certain errors will be automatically retried 2 times by default, with a short exponential backoff.
Connection errors (for example, due to a network connectivity problem), 408 Request Timeout, 409 Conflict,
429 Rate Limit, and >=500 Internal errors will all be retried by default.

You can use the maxRetries option to configure or disable this:


`js
// Configure the default for all requests:
const client = new ContextualAI({
maxRetries: 0, // default is 2
});

// Or, configure per-request:
await client.agents.create({ name: 'Example' }, {
maxRetries: 5,
});
`

$3

Requests time out after 1 minute by default. You can configure this with a timeout option:


`ts
// Configure the default for all requests:
const client = new ContextualAI({
timeout: 20 * 1000, // 20 seconds (default is 1 minute)
});

// Override per-request:
await client.agents.create({ name: 'Example' }, {
timeout: 5 * 1000,
});
`

On timeout, an APIConnectionTimeoutError is thrown.

Note that requests which time out will be retried twice by default.

Auto-pagination

List methods in the ContextualAI API are paginated.
You can use the for await … of syntax to iterate through items across all pages:

`ts
async function fetchAllAgents(params) {
const allAgents = [];
// Automatically fetches more pages as needed.
for await (const agent of client.agents.list()) {
allAgents.push(agent);
}
return allAgents;
}
`

Alternatively, you can request a single page at a time:

`ts
let page = await client.agents.list();
for (const agent of page.agents) {
console.log(agent);
}

// Convenience methods are provided for manually paginating:
while (page.hasNextPage()) {
page = await page.getNextPage();
// ...
}
`

Advanced Usage

$3

The "raw" Response returned by fetch() can be accessed through the .asResponse() method on the APIPromise type that all methods return.

You can also use the .withResponse() method to get the raw Response along with the parsed data.


`ts
const client = new ContextualAI();

const response = await client.agents.create({ name: 'Example' }).asResponse();
console.log(response.headers.get('X-My-Header'));
console.log(response.statusText); // access the underlying Response object

const { data: createAgentOutput, response: raw } = await client.agents
.create({ name: 'Example' })
.withResponse();
console.log(raw.headers.get('X-My-Header'));
console.log(createAgentOutput.id);
`

$3

This library is typed for convenient access to the documented API. If you need to access undocumented
endpoints, params, or response properties, the library can still be used.

#### Undocumented endpoints

To make requests to undocumented endpoints, you can use client.get, client.post, and other HTTP verbs.
Options on the client, such as retries, will be respected when making these requests.

`ts
await client.post('/some/path', {
body: { some_prop: 'foo' },
query: { some_query_arg: 'bar' },
});
`

#### Undocumented request params

To make requests using undocumented parameters, you may use // @ts-expect-error on the undocumented
parameter. This library doesn't validate at runtime that the request matches the type, so any extra values you
send will be sent as-is.

`ts
client.foo.create({
foo: 'my_param',
bar: 12,
// @ts-expect-error baz is not yet public
baz: 'undocumented option',
});
`

For requests with the GET verb, any extra params will be in the query, all other requests will send the
extra param in the body.

If you want to explicitly send an extra argument, you can do so with the query, body, and headers request
options.

#### Undocumented response properties

To access undocumented response properties, you may access the response object with // @ts-expect-error on
the response object, or cast the response object to the requisite type. Like the request params, we do not
validate or strip extra properties from the response from the API.

$3

By default, this library uses node-fetch in Node, and expects a global fetch function in other environments.

If you would prefer to use a global, web-standards-compliant fetch function even in a Node environment,
(for example, if you are running Node with --experimental-fetch or using NextJS which polyfills with undici),
add the following import before your first import from "ContextualAI":

`ts
// Tell TypeScript and the package to use the global web fetch instead of node-fetch.
// Note, despite the name, this does not add any polyfills, but expects them to be provided if needed.
import 'contextual-client/shims/web';
import ContextualAI from 'contextual-client';
`

To do the inverse, add import "contextual-client/shims/node" (which does import polyfills).
This can also be useful if you are getting the wrong TypeScript types for Response (more details).

$3

You may also provide a custom fetch function when instantiating the client,
which can be used to inspect or alter the Request or Response before/after each request:

`ts
import { fetch } from 'undici'; // as one example
import ContextualAI from 'contextual-client';

const client = new ContextualAI({
fetch: async (url: RequestInfo, init?: RequestInit): Promise => {
console.log('About to make a request', url, init);
const response = await fetch(url, init);
console.log('Got response', response);
return response;
},
});
`

Note that if given a DEBUG=true environment variable, this library will log all requests and responses automatically.
This is intended for debugging purposes only and may change in the future without notice.

$3

By default, this library uses a stable agent for all http/https requests to reuse TCP connections, eliminating many TCP & TLS handshakes and shaving around 100ms off most requests.

If you would like to disable or customize this behavior, for example to use the API behind a proxy, you can pass an httpAgent which is used for all requests (be they http or https), for example:


`ts
import http from 'http';
import { HttpsProxyAgent } from 'https-proxy-agent';

// Configure the default for all requests:
const client = new ContextualAI({
httpAgent: new HttpsProxyAgent(process.env.PROXY_URL),
});

// Override per-request:
await client.agents.create(
{ name: 'Example' },
{
httpAgent: new http.Agent({ keepAlive: false }),
},
);
`

Semantic versioning

This package generally follows SemVer conventions, though certain backwards-incompatible changes may be released as minor versions:

1. Changes that only affect static types, without breaking runtime behavior.
2. Changes to library internals which are technically public but not intended or documented for external use. _(Please open a GitHub issue to let us know if you are relying on such internals.)_
3. Changes that we do not expect to impact the vast majority of users in practice.

We take backwards-compatibility seriously and work hard to ensure you can rely on a smooth upgrade experience.

We are keen for your feedback; please open an issue with questions, bugs, or suggestions.

Requirements

TypeScript >= 4.5 is supported.

The following runtimes are supported:

- Web browsers (Up-to-date Chrome, Firefox, Safari, Edge, and more)
- Node.js 18 LTS or later (non-EOL) versions.
- Deno v1.28.0 or higher.
- Bun 1.0 or later.
- Cloudflare Workers.
- Vercel Edge Runtime.
- Jest 28 or greater with the "node" environment ("jsdom"` is not supported at this time).
- Nitro v2.6 or greater.

Note that React Native is not supported at this time.

If you are interested in other runtime environments, please open or upvote an issue on GitHub.

Contributing

See the contributing documentation.