https://github.com/stekern/terraform-aws-paper2remarkable-lambda

Terraform module for running paper2remarkable in an AWS Lambda function.
https://github.com/stekern/terraform-aws-paper2remarkable-lambda

aws-lambda remarkable-tablet terraform

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Terraform module for running paper2remarkable in an AWS Lambda function.

• Host: GitHub
• URL: https://github.com/stekern/terraform-aws-paper2remarkable-lambda
• Owner: stekern
• Created: 2020-12-12T13:23:52.000Z (about 4 years ago)
• Default Branch: master
• Last Pushed: 2023-12-15T17:25:47.000Z (about 1 year ago)
• Last Synced: 2023-12-15T18:33:25.974Z (about 1 year ago)
• Topics: aws-lambda, remarkable-tablet, terraform
• Language: Python
• Homepage:
• Size: 11.7 KB
• Stars: 1
• Watchers: 2
• Forks: 1
• Open Issues: 1
• Metadata Files:
  • Readme: README.md

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README

        
# terraform-aws-paper2remarkable-lambda

A Terraform module that creates an AWS Lambda function for calling [paper2remarkable](https://github.com/GjjvdBurg/paper2remarkable).

The Lambda uses a custom Docker image (see [src/Dockerfile](src/Dockerfile)) which comes with paper2remarkable and its dependencies installed.

You can opt-in to receive emails if paper2remarkable fails to process a given input, or if the Lambda function itself times out.

## Set up

You need to first manually create the tokens for [rmapi](https://github.com/juruen/rmapi/), and then store these tokens in the parameter `//rmapi-config` in AWS Parameter Store using the following format:

```json

{"rmapi_device_token": "", "rmapi_user_token": ""}

```

You also need to build the Docker image and host it in ECR, e.g.:

```sh

$ docker build -t ".dkr.ecr..amazonaws.com/-paper2remarkable" ./src

$ aws ecr get-login-password --region  | docker login --username AWS --password-stdin ".dkr.ecr..amazonaws.com"

$ docker push ".dkr.ecr..amazonaws.com/-paper2remarkable"

```

## Usage

After setting up the credentials, you can run the Lambda as such:

```sh

aws lambda invoke \

  --function-name -paper2remarkable \

  --payload '{"inputs": ["https://arxiv.org/abs/1406.2661"]}' \

  output.json

```

You can further integrate the Lambda function with AWS API Gateway to set up a REST API for the function -- allowing you to send files to your reMarkable from anywhere with an internet connection!

## TODOs

- Host the image in a public ECR repository.

- The Lambda somestimes failes due to an error `[Errno 2] No such file or directory ` -- seems to be related to reuse of Lambda execution context. Changing the directory to a known directory seems to fix this, but may need to research this further and see if it can be handled in a more robust manner.

- A normal run takes roughly 60 seconds.

  - May be an idea to use a Fargate task instead of a Lambda, but there's an inherent ~30 sec start-up time here.

- Docker image can probably be simplified and minimized (currently sits at 500 MB).