Oscar is a sassy, connected chatbot who enables you to easily interact with GitHub projects, all out of Slack!
Check the Quick Start Guide to get access to Oscar on our Slack Channel - oscar-bot.slack.com. Also check out The AWS Chatbot Challenge.
The fastest way to try out Oscar is to request an invite to the OscarBot Slack Channel. Then checkout the Quick Start Guide.
Oscar can provide all sorts of information about repositories, as well as doing things like opening issues. Some example interations are:
- "How many issues does {Repository} have?"
- "I would like to open an issue"
- "List the top issues for my project"
There's a more detailed list in the [Quick Start Guide](Quick Start Guide).
The project structure is:
├── aws # some aws resources used in setup
├── docs # internal docs/images
├── lex # slots and intent json files
├── oscar-cli # the oscar cli
├── oscarbot # lamba function and tests
└── scripts # scripts used by the makefile
This diagram shows the key steps for setup and development:
Install:
Ensure you are logged into the AWS CLI as a user with permissions to create Lambda Functions, Buckets, Roles, Policies and Lex Models.
Set the following environment variables:
| Variable | Usage |
|---|---|
OSCAR_BUCKET |
A name to use for the S3 bucket for Oscar. This must be unique across AWS, so try something like oscarbot-<your name> |
OSCAR_GITHUB_USERNAME |
The GitHub user to login as when performing queries. |
OSCAR_GITHUB_PASSWORD |
The GitHub password to login with when performing queries. |
DEBUG=oscar |
Optional. Enables debug output (we use the debug module. |
You can now call:
make setupWhich will build the lambda function, bucket and policies.
If you change the lambda function, slots, intents or bot, just call:
make deployThis will rebuild the lambda function and redeploy it. It will also rebuild and publish all slots, intents and the bot. ``
Here are some commands you can run to help work with the project:
| Command | Usage |
|---|---|
make build |
Builds the lamba function and zips it up locally. |
make test |
Runs the unit tests. |
make lint |
Lints the code. |
make setup |
Sets up your AWS resources. First time setup only. |
make deploy |
Deploys the code, slots and intents. |
make utterances |
Helper to print out all supported utterances. Useful when building docs. |
npm run test:debug |
Runs tests with the Chrome Inspector. |
npm run coverage |
Runs tests, generating a coverage report. |
If you have the AWS CLI setup with access to the bot, you can actually chat using the CLI. First, build and link the CLI with:
make cliThen just run the oscar command to chat!
$ oscar
Hello, I am Oscar 🤖
You chat to me about your GitHub project!
oscar > Hi! What can I help you with?
me > What projects am I working on?
circle.yml will build changes on master and deploy to AWS (make sure you have set the Circle AWS key in the console).
The bulk of the tests work by creating a chat event and passing it to the lambda function. This means it will test the intent but not the natural language understanding.
A good example test to get learn from is intentDescribeLastCommit.js.
If you want to provide some simple flavour text or a one-line response to a statement, you can use the snappyResponses.js file.
Please note that even a one-line response will still need an intent. Put these intents in the intents/conversational folder to distinguish them from functional intents.
It is possible that intents are limited, and it is the case that a large number of intents can actually make it harder to determine intent, so be careful to to add too many.