lilysaas

• what are the core database schema "things"
• what is the plan for taking payments?
• what are the key actions?

entities

• auth
  • use keycloak
• model
  • json file to start with
  • a list of things that lilypad can run
• job
  • inference
  • training (fine tunings)
    • starts with an existing model
    • produces a new model

plan

This is to have a hello world that you can login to.

• docker compose stack
  • keycloak
  • frontend (react & vite)
  • api (go)
  • postgres

dev

You need the following installed:

• docker
• docker-compose
• abigen
• bacalhau

You also need the lilypad repo cloned alongside this one.

smart contract interface

When the smart contract in lilypad changes - checkout latest main of lilypad and then:

./stack generate-golang-bindings

This will re-create the api/pkg/contract/Modicum.go

running alongside lilypad in local dev

Make sure that you have cloned lilypad at the same level as this repo.

export RUN_LILYPAD=1
./stack start

This will boot a fresh lilypad and lilysaas stack and link everything together using tmux.

To run each part manually here are the guides:

lilypad

First start lilypad and then bacalhau:

cd lilypad
./stack boot

Then we start bacalhau:

NOTE you will require the correct version of bacalhau - run through this guide:

./stack bacalhau-serve

Now we need 3 other terminals each with LOG_LEVEL=debug

./stack solver --server-url http://172.17.0.1:8080

so it reports an address accessible from inside docker (the default docker bridge ip - this will probably only work on linux? on mac maybe you can use host.docker.internal)

./stack mediator

./stack resource-provider

Now we switch to lilysaas and get it booted alongside lilypad.

lilysaas

We need to create an top level .env file like so

export WEB3_PRIVATE_KEY=XXX

You can get the WEB3_PRIVATE_KEY value with this command:

cat ../lilypad/.env | grep JOB_CREATOR_PRIVATE_KEY

Copy the value of this to be the WEB3_PRIVATE_KEY value in the .env file - the other values should be as shown.

docker-compose up -d

Then we exec into the api container and run the api server:

docker-compose exec api bash
go run . serve

port forwarding for local web development on a remote GPU machine

If you want to run the stack on a GPU machine and access it via browser on another machine, the following might be useful:

sudo ssh -L 80:localhost:80 <user>@<gpu-node>

and in another terminal:

ssh -L 8081:localhost:8081 <gpu-node>

Then open http://localhost in the browser

of course, VS code remote via SSH is useful in this scenario as well