Class: AgentRuntime
Represents the runtime environment for an agent, handling message processing, action registration, and interaction with external services like OpenAI and Supabase.
Constructors
constructor
• new AgentRuntime(opts): AgentRuntime
Creates an instance of AgentRuntime.
Parameters
| Name | Type | Description |
|---|---|---|
opts | Object | The options for configuring the AgentRuntime. |
opts.actions? | Action[] | Optional custom actions. |
opts.agentId? | `${string}-${string}-${string}-${string}-${string}` | Optional ID of the agent. |
opts.conversationLength? | number | The number of messages to hold in the recent message cache. |
opts.databaseAdapter | DatabaseAdapter | The database adapter used for interacting with the database. |
opts.debugMode? | boolean | If true, debug messages will be logged. |
opts.embeddingModel? | string | The model to use for embedding. |
opts.evaluators? | Evaluator[] | Optional custom evaluators. |
opts.fetch? | unknown | Custom fetch function to use for making requests. |
opts.model? | string | The model to use for completion. |
opts.providers? | Provider[] | Optional context providers. |
opts.serverUrl? | string | The URL of the worker. |
opts.token | string | The JWT token, can be a JWT token if outside worker, or an OpenAI token if inside worker. |
Returns
Properties
actions
• actions: Action[] = []
Custom actions that the agent can perform.
agentId
• agentId: `${string}-${string}-${string}-${string}-${string}` = zeroUuid
The ID of the agent
databaseAdapter
• databaseAdapter: DatabaseAdapter
The database adapter used for interacting with the database.
debugMode
• debugMode: boolean
Indicates if debug messages should be logged.
descriptionManager
• descriptionManager: MemoryManager
Store and recall descriptions of users based on conversations.
embeddingModel
• embeddingModel: string = "text-embedding-3-small"
The model to use for embedding.
evaluators
• evaluators: Evaluator[] = []
Evaluators used to assess and guide the agent's responses.
factManager
• factManager: MemoryManager
Manage the fact and recall of facts.
fetch
• fetch: (input: RequestInfo | URL, init?: RequestInit<CfProperties<unknown>>) => Promise<Response>(input: RequestInfo, init?: RequestInit<CfProperties<unknown>>) => Promise<Response>(input: RequestInfo, init?: RequestInit<RequestInitCfProperties>) => Promise<Response> = fetch
Fetch function to use Some environments may not have access to the global fetch function and need a custom fetch override.
Type declaration
▸ (input, init?): Promise<Response>
Fetch function to use Some environments may not have access to the global fetch function and need a custom fetch override.
Parameters
| Name | Type |
|---|---|
input | RequestInfo | URL |
init? | RequestInit<CfProperties<unknown>> |
Returns
Promise<Response>
▸ (input, init?): Promise<Response>
Fetch function to use Some environments may not have access to the global fetch function and need a custom fetch override.
Parameters
| Name | Type |
|---|---|
input | RequestInfo |
init? | RequestInit<CfProperties<unknown>> |
Returns
Promise<Response>
▸ (input, init?): Promise<Response>
Fetch function to use Some environments may not have access to the global fetch function and need a custom fetch override.
Parameters
| Name | Type |
|---|---|
input | RequestInfo |
init? | RequestInit<RequestInitCfProperties> |
Returns
Promise<Response>
loreManager
• loreManager: MemoryManager
Manage the creation and recall of static information (documents, historical game lore, etc)
messageManager
• messageManager: MemoryManager
Store messages that are sent and received by the agent.
model
• model: string = "gpt-3.5-turbo-0125"
The model to use for completion.
providers
• providers: Provider[] = []
Context providers used to provide context for message generation.
serverUrl
• serverUrl: string = "http://localhost:7998"
The base URL of the server where the agent's requests are processed.
token
• token: null | string
Authentication token used for securing requests.
Methods
completion
▸ completion(opts): Promise<string>
Send a message to the OpenAI API for completion.
Parameters
| Name | Type | Default value | Description |
|---|---|---|---|
opts | Object | undefined | The options for the completion request. |
opts.context | undefined | string | "" | The context of the message to be completed. |
opts.frequency_penalty | undefined | number | 0.0 | The frequency penalty to apply to the completion. |
opts.model | undefined | string | undefined | The model to use for completion. |
opts.presence_penalty | undefined | number | 0.0 | The presence penalty to apply to the completion. |
opts.stop | undefined | never[] | [] | A list of strings to stop the completion at. |
opts.temperature | undefined | number | 0.7 | The temperature to apply to the completion. |
Returns
Promise<string>
The completed message.
composeState
▸ composeState(message, additionalKeys?): Promise<{ actionConditions: string ; actionExamples: string ; actionNames: string ; actions: string ; actors: string ; actorsData: Actor[] ; agentId: `${string}-${string}-${string}-${string}-${string}` ; agentName: undefined | string ; evaluatorConditions: string ; evaluatorExamples: string ; evaluatorNames: string ; evaluators: string ; evaluatorsData: Evaluator[] ; goals: string ; goalsData: Goal[] ; lore: string ; loreData: Memory[] ; providers: string ; recentFacts: string ; recentFactsData: Memory[] ; recentMessages: string ; recentMessagesData: Memory[] ; relevantFacts: string ; relevantFactsData: Memory[] ; room_id: `${string}-${string}-${string}-${string}-${string}` ; senderName: undefined | string }>
Compose the state of the agent into an object that can be passed or used for response generation.
Parameters
| Name | Type | Description |
|---|---|---|
message | Message | The message to compose the state from. |
additionalKeys | Object | - |
Returns
Promise<{ actionConditions: string ; actionExamples: string ; actionNames: string ; actions: string ; actors: string ; actorsData: Actor[] ; agentId: `${string}-${string}-${string}-${string}-${string}` ; agentName: undefined | string ; evaluatorConditions: string ; evaluatorExamples: string ; evaluatorNames: string ; evaluators: string ; evaluatorsData: Evaluator[] ; goals: string ; goalsData: Goal[] ; lore: string ; loreData: Memory[] ; providers: string ; recentFacts: string ; recentFactsData: Memory[] ; recentMessages: string ; recentMessagesData: Memory[] ; relevantFacts: string ; relevantFactsData: Memory[] ; room_id: `${string}-${string}-${string}-${string}-${string}` ; senderName: undefined | string }>
The state of the agent.
embed
▸ embed(input): Promise<number[]>
Send a message to the OpenAI API for embedding.
Parameters
| Name | Type | Description |
|---|---|---|
input | string | The input to be embedded. |
Returns
Promise<number[]>
The embedding of the input.
ensureParticipantExists
▸ ensureParticipantExists(user_id, room_id): Promise<void>
Ensure the existence of a participant in the room. If the participant does not exist, they are added to the room.
Parameters
| Name | Type | Description |
|---|---|---|
user_id | `${string}-${string}-${string}-${string}-${string}` | The user ID to ensure the existence of. |
room_id | `${string}-${string}-${string}-${string}-${string}` | - |
Returns
Promise<void>
Throws
An error if the participant cannot be added.
ensureRoomExists
▸ ensureRoomExists(user_id, room_id?): Promise<`${string}-${string}-${string}-${string}-${string}`>
Ensure the existence of a room between the agent and a user. If no room exists, a new room is created and the user and agent are added as participants. The room ID is returned.
Parameters
| Name | Type | Description |
|---|---|---|
user_id | `${string}-${string}-${string}-${string}-${string}` | The user ID to create a room with. |
room_id? | `${string}-${string}-${string}-${string}-${string}` | - |
Returns
Promise<`${string}-${string}-${string}-${string}-${string}`>
The room ID of the room between the agent and the user.
Throws
An error if the room cannot be created.
evaluate
▸ evaluate(message, state?): Promise<string[]>
Evaluate the message and state using the registered evaluators.
Parameters
| Name | Type | Description |
|---|---|---|
message | Message | The message to evaluate. |
state? | State | The state of the agent. |
Returns
Promise<string[]>
The results of the evaluation.
getConversationLength
▸ getConversationLength(): number
Get the number of messages that are kept in the conversation buffer.
Returns
number
The number of recent messages to be kept in memory.
processActions
▸ processActions(message, content, state?): Promise<unknown>
Process the actions of a message.
Parameters
| Name | Type | Description |
|---|---|---|
message | Message | The message to process. |
content | Content | The content of the message to process actions from. |
state? | State | - |
Returns
Promise<unknown>
registerAction
▸ registerAction(action): void
Register an action for the agent to perform.
Parameters
| Name | Type | Description |
|---|---|---|
action | Action | The action to register. |
Returns
void
registerContextProvider
▸ registerContextProvider(provider): void
Register a context provider to provide context for message generation.
Parameters
| Name | Type | Description |
|---|---|---|
provider | Provider | The context provider to register. |
Returns
void
registerEvaluator
▸ registerEvaluator(evaluator): void
Register an evaluator to assess and guide the agent's responses.
Parameters
| Name | Type | Description |
|---|---|---|
evaluator | Evaluator | The evaluator to register. |
Returns
void
retrieveCachedEmbedding
▸ retrieveCachedEmbedding(input): Promise<null | number[]>
Parameters
| Name | Type |
|---|---|
input | string |
Returns
Promise<null | number[]>