smallville

Smallville is a javascript library to create custom generative agent simulations in web browsers. Generative Agents use LLM's to create realistic NPC charcters and are most useful for research and video games.

Install the necessary files

Start a new javascript project

npm init

npm i smallville

Download the compiled jar from releases

Example

const sim = new Smallville({
        host: "http://localhost:8080", // host of the server
        stateHandler: function(state) {
                //in here you would update the location of the agent using your own pathfinding algorithm
                const currentLocation = state.agents[0].getCurrentLocation()
                const newLocation = state.agents[0].getNextLocation()
                const emoji = state.agents[0].getEmoji()
                const activity = state.agents[0].getCurrentActivity()
                
                const updatedLocations = state.locations;
                
                const conversations = state.conversations;
                
                console.log('[State Change]: The simulation has been updated')
    },
});

Create new location trees

sim.createLocation({
   name: 'Barn',
})

sim.createObject({
   name: 'Hay Pile',
   state: 'Full',
   parent: 'Barn'    
})

Add new agents and initialize their memory stream with starting memories

sim.createAgent({
  name: 'John',
  location: 'Barn',
  memories: [
    "John is a farmer at the Barn",
    "John is a nice and outgoing person"
  ]
})

Increment the time clock. The simulation will get the current time and update the agents state

sim.updateState();

Keep calling sim.updateState whenever you want to update the simulation step

To add new observations to the agent which they will prompt a reaction to use the following method

sim.addObservation({name: "Full Agent Name", observation: "memory description", reactable: true})

Such observations such as encountering another agent or discovering a location should make use of this

For observatonal purposes, you can also ask an agent a question which will use their relevant memories to answer the question

sim.askQuestion("John", "What do you do in your free time")

This will not store the question in the agents memory unless you call sim.addObservation()

Furthermore, locations should be given as a full tree. ex)

location: "Island: Red House: desk"

And the leaf node (in this example desk), should have a state, although it is not necessary. Adding states to leaf locations enables the agents to interact with the world. To get the leaf location and move the agent to the location you can use our utility function getLeafLocation(location) or make your own method.