This project is for the REST API that handles interactions on the feedback widget UI and adds this data to a database, currently Google Sheets. It is deployed to AWS Lambda + API Gateway. For full architecture of feedback system, see "Technical diagram" section below.
This project has been generated using the aws-nodejs-typescript
template from the Serverless framework. For detailed instructions, please refer to the documentation.
For the latest information on the API endpoints maintained, see the functions imported and configured within the serverless.ts
file. Within the src/functions/
folder, each sub-folder corresponds to an API endpoint, and the index.ts
file within it has detail on the type of endpoint. For example, see src/functions/comment/index.ts
and src/functions/comment/schema.ts
for details on the POST /comment
endpoint. For a quick summary, this repo supports the following endpoints:
POST /rating
- saves Yes/No rating to databasePOST /comment
- saves text comment to database (and cleans PII)POST /email
- saves email to databasePOST /summary
- generates summary from list of comments using OpenAI's GPT model
- Clone this repository
- Create
.env
file in root directory, pasting in values from Bitwarden secure note. Note that these values are production keys that will allow for live testing. We hope to create a dev or local stage in the future. - Run
npm install
(on Node 18, as listed in.nvmrc
) to install Node dependencies - Run
npx sls offline
to start the API locally - In another terminal, try calling API endpoints such as the example below. Note that this will actually add data to our live production database (Google Sheets).
curl -d '{"pageURL":"www.test.com","rating":true}' -H "Content-Type: application/json" http://localhost:3000/rating
Deployment is done locally to the AWS account Innov-RES-Dev
and not yet connected to Github version control.
- Make code changes locally
- Test code changes locally
- Log into AWS console, and open "Command line and programmatic access" option under
Innov-RES-Dev
account - Follow instructions in modal to save AWS credentials to
~/.aws/credentials
file - Run
npx sls deploy --aws-profile {INSERT PROFILE NAME HERE}
to deploy this Serverless project to AWS
This template contains a single lambda function triggered by an HTTP request made on the provisioned API Gateway REST API /rating
route with POST
method. The request body must be provided as application/json
. The body structure is tested by API Gateway against src/functions/rating/schema.ts
JSON-Schema definition: it must contain the name
property.
- requesting any other path than
/rating
with any other method thanPOST
will result in API Gateway returning a403
HTTP error code - sending a
POST
request to/rating
with a payload not containing a string property namedname
will result in API Gateway returning a400
HTTP error code - sending a
POST
request to/rating
with a payload containing a string property namedname
will result in API Gateway returning a200
HTTP status code with a message saluting the provided name and the detailed event processed by the lambda
⚠️ As is, this template, once deployed, opens a public endpoint within your AWS account resources. Anybody with the URL can actively execute the API Gateway endpoint and the corresponding lambda. You should protect this endpoint with the authentication method of your choice.
In order to test the rating function locally, run the following command:
npx sls invoke local -f rating --path src/functions/rating/mock.json
if you're using NPMnpx sls offline
to run the API locally onhttps://localhost:3000
Check the sls invoke local command documentation for more information.
Note that to run locally, you need to export any environment variables used in code to your current environment. They can be found in the AWS Lambda configurations.
Copy and replace your url
- found in Serverless deploy
command output - and name
parameter in the following curl
command in your terminal or in Postman to test your newly deployed application.
curl --location --request POST 'https://endpoint.execute-api.region.amazonaws.com/dev/rating' \
--header 'Content-Type: application/json' \
--data-raw '{
"pageURL": "example.com",
"rating": true
}'
The project code base is mainly located within the src
folder. This folder is divided in:
functions
- containing code base and configuration for your lambda functionslibs
- containing shared code base between your lambdas
.
├── src
│ ├── functions # Lambda configuration and source code folder
│ │ ├── rating
│ │ │ ├── handler.ts # `rating` lambda source code
│ │ │ ├── index.ts # `rating` lambda Serverless configuration
│ │ │ ├── mock.json # `rating` lambda input parameter, if any, for local invocation
│ │ │ └── schema.ts # `rating` lambda input event JSON-Schema
│ │ │
│ │ └── index.ts # Import/export of all lambda configurations
│ │
│ └── libs # Lambda shared code
│ └── apiGateway.ts # API Gateway specific helpers
│ └── handlerResolver.ts # Sharable library for resolving lambda handlers
│ └── lambda.ts # Lambda middleware
│
├── package.json
├── serverless.ts # Serverless service file
├── tsconfig.json # Typescript compiler configuration
├── tsconfig.paths.json # Typescript paths
└── webpack.config.js # Webpack configuration
This project also contains a scripts
folder, which contains post-processing Python scripts that help analyze the feedback data.
- json-schema-to-ts - uses JSON-Schema definitions used by API Gateway for HTTP request validation to statically generate TypeScript types in your lambda's handler code base
- middy - middleware engine for Node.Js lambda. This template uses http-json-body-parser to convert API Gateway
event.body
property, originally passed as a stringified JSON, to its corresponding parsed object - @serverless/typescript - provides up-to-date TypeScript definitions for your
serverless.ts
service file
Any tsconfig.json can be used, but if you do, set the environment variable TS_NODE_CONFIG
for building the application, eg TS_NODE_CONFIG=./tsconfig.app.json npx serverless webpack
Below is the latest technical architecture as of November 2024. To update the file, download the docs/Feedback-Widget-Diagram.excalidraw
file, import it on Excalidraw, edit the diagram, and update the corresponding files in this repository with the latest versions.