https://github.com/chialab/math-api

➗ Serverless API to render maths using MathJax for Node.
https://github.com/chialab/math-api

aws-apigateway aws-lambda docker hacktoberfest latex mathml nodejs serverless

Last synced: 2 months ago
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➗ Serverless API to render maths using MathJax for Node.

• Host: GitHub
• URL: https://github.com/chialab/math-api
• Owner: chialab
• License: mit
• Created: 2017-03-14T11:27:11.000Z (almost 8 years ago)
• Default Branch: master
• Last Pushed: 2022-12-10T17:24:17.000Z (about 2 years ago)
• Last Synced: 2024-03-26T20:15:42.966Z (10 months ago)
• Topics: aws-apigateway, aws-lambda, docker, hacktoberfest, latex, mathml, nodejs, serverless
• Language: JavaScript
• Homepage:
• Size: 241 KB
• Stars: 39
• Watchers: 5
• Forks: 7
• Open Issues: 14
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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  Math API • Render LaTeX and MathML formulas as SVG or PNG.



---

A REST API to do fancy things with formulas, like rendering LaTeX or MathML to

SVG or PNG on the server side using [MathJax for Node](https://github.com/mathjax/MathJax-node),

while leveraging expensive computations on the client.

## As a Serverless application

You can deploy this repository as a serverless application using an AWS CloudFormation

Template to create an AWS API Gateway that invokes Lambda functions to serve requests.

> [**Launch this stack on AWS**](https://console.aws.amazon.com/cloudformation/home#/stacks/new?stackName=MathApi&templateURL=https://chialab-cloudformation-templates.s3-eu-west-1.amazonaws.com/chialab/math-api/master/template.yml)

## As a Docker image

You can pull and run a Docker container to deploy the API on your local machine,

server, Kubernetes cluster, whatever!

To start the container (it will bind on ):

```sh

docker run --name math-api -d -p 3000:3000 chialab/math-api

```

## Endpoints

- [`GET /render`](#get-render)

- [`POST /render`](#post-render)

### `GET /render`

> An endpoint to render LaTeX and MathML formulas to SVG or PNG.

**Query parameters**:

- `input` (**required**): the format of math in input.  

   **Valid values**: `latex`, `mathml`

- `inline` (_optional_): when `input` is `latex`, optionally enable "inline" mode.  

   **Valid values**: `0`, `1`

- `source` (**required**): the math to be rendered.  

   **Valid values**: _string, depends on the input type_

- `output` (**required**): the output format.  

   **Valid values**: `mathml`, `png`, `svg`

- `width`, `height` (_optional_): when `output` is `png`, specify the dimensions of the image to return.  

   **Valid values**: _positive integers_

**Examples**:

```http

GET /render?input=latex&output=svg&source=x^2 HTTP/1.1

Accept: image/svg+xml

```

```http

GET /render?input=latex&inline=1&output=png&source=x^2&width=512 HTTP/1.1

Accept: image/png

```

### `POST /render`

> An endpoint to render LaTeX and MathML formulas to SVG or PNG.

**Request body (JSON)**:

- `input` (**required**): the format of math in input.  

   **Valid values**: `latex`, `mathml`

- `inline` (_optional_): when `input` is `latex`, optionally enable "inline" mode.  

   **Valid values**: _boolean_

- `source` (**required**): the math to be rendered.  

   **Valid values**: _string, depends on the input type_

- `output` (**required**): the output format.  

   **Valid values**: `mathml`, `png`, `svg`

- `width`, `height` (_optional_): when `output` is `png`, specify the dimensions of the image to return.  

   **Valid values**: _positive integers_

**Examples**:

```http

POST /render

Accept: image/svg+xml

Content-Type: application/json

{

    "input": "latex",

    "output": "svg",

    "source": "e^{i \\pi} + 1 = 0"

}

```

```http

POST /render

Accept: image/png

Content-Type: application/json

{

    "input": "latex",

    "inline": true,

    "output": "png",

    "source": "e^{i \\pi} + 1 = 0",

    "width": 512

}

```

## Development

_All the following instructions assume you have at least [NodeJS](https://nodejs.org/) and [Yarn](https://yarnpkg.com/) installed._

**Start the application locally**:

> `yarn start`

**Run unit tests**:

> `yarn run test`

**Start a simulated AWS API Gateway** (_provided you have AWS SAM Local and Docker installed_):

> `yarn run api-gateway`

**Validate CloudFormation template** (_provided you have AWS CLI installed_)

> `make validate`

**Package CloudFormation template** (_provided you have AWS CLI and Docker installed_)

> `make layers` (_this is needed only the first time, then when updating MathJax version_)

> `make package`

**Deploy CloudFormation template** (_provided you have AWS CLI and Docker installed_)

> `make deploy`

> `make deploy ENVIRONMENT=Production`

---

## License

Math API is released under the [MIT](https://github.com/chialab/math-api/blob/master/LICENSE) license.