openclaw
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Multi-channel AI gateway with extensible messaging integrations
95 lines (94 loc) • 4.08 kB
TypeScript
import type { AssistantMessage, ImageContent, Model } from "../../../llm-core/src/index.js";
import type { AgentMessage, AgentTool, QueueMode, ThinkingLevel } from "../types.js";
import type { AbortResult, AgentHarnessEvent, AgentHarnessEventResultMap, AgentHarnessOptions, AgentHarnessOwnEvent, AgentHarnessResources, AgentHarnessStreamOptions, ExecutionEnv, NavigateTreeResult, PromptTemplate, Skill } from "./types.js";
/** Stateful harness for running, steering, compacting, and navigating sessions. */
export declare class CoreAgentHarness<TSkill extends Skill = Skill, TPromptTemplate extends PromptTemplate = PromptTemplate, TTool extends AgentTool = AgentTool> {
readonly env: ExecutionEnv;
private session;
private phase;
private runAbortController?;
private runPromise?;
private pendingSessionWrites;
private model;
private thinkingLevel;
private systemPrompt;
private streamOptions;
private getApiKeyAndHeaders?;
private runtime?;
private resources;
private tools;
private activeToolNames;
private steerQueue;
private steeringQueueMode;
private followUpQueue;
private followUpQueueMode;
private nextTurnQueue;
private handlers;
constructor(options: AgentHarnessOptions<TSkill, TPromptTemplate, TTool>);
private getHandlers;
private emitOwn;
private emitAny;
private emitHook;
private emitBeforeProviderRequest;
private emitBeforeProviderPayload;
private emitQueueUpdate;
private startRunPromise;
private createTurnState;
private createContext;
private createStreamFn;
private drainQueuedMessages;
private createLoopConfig;
private validateToolNames;
private flushPendingSessionWrites;
private handleAgentEvent;
private emitRunFailure;
private executeTurn;
prompt(text: string, options?: {
images?: ImageContent[];
}): Promise<AssistantMessage>;
skill(name: string, additionalInstructions?: string): Promise<AssistantMessage>;
promptFromTemplate(name: string, args?: string[]): Promise<AssistantMessage>;
steer(text: string, options?: {
images?: ImageContent[];
}): Promise<void>;
followUp(text: string, options?: {
images?: ImageContent[];
}): Promise<void>;
nextTurn(text: string, options?: {
images?: ImageContent[];
}): Promise<void>;
appendMessage(message: AgentMessage): Promise<void>;
compact(customInstructions?: string): Promise<{
summary: string;
firstKeptEntryId: string;
tokensBefore: number;
details?: unknown;
}>;
navigateTree(targetId: string, options?: {
summarize?: boolean;
customInstructions?: string;
replaceInstructions?: boolean;
label?: string;
}): Promise<NavigateTreeResult>;
getModel(): Model;
getThinkingLevel(): ThinkingLevel;
setModel(model: Model): Promise<void>;
setThinkingLevel(level: ThinkingLevel): Promise<void>;
setActiveTools(toolNames: string[]): Promise<void>;
getSteeringMode(): QueueMode;
setSteeringMode(mode: QueueMode): Promise<void>;
getFollowUpMode(): QueueMode;
setFollowUpMode(mode: QueueMode): Promise<void>;
getResources(): AgentHarnessResources<TSkill, TPromptTemplate>;
setResources(resources: AgentHarnessResources<TSkill, TPromptTemplate>): Promise<void>;
getStreamOptions(): AgentHarnessStreamOptions;
setStreamOptions(streamOptions: AgentHarnessStreamOptions): Promise<void>;
setTools(tools: TTool[], activeToolNames?: string[]): Promise<void>;
abort(): Promise<AbortResult>;
waitForIdle(): Promise<void>;
subscribe(listener: (event: AgentHarnessEvent<TSkill, TPromptTemplate>, signal?: AbortSignal) => Promise<void> | void): () => void;
on<TType extends keyof AgentHarnessEventResultMap>(type: TType, handler: (event: Extract<AgentHarnessOwnEvent, {
type: TType;
}>) => Promise<AgentHarnessEventResultMap[TType]> | AgentHarnessEventResultMap[TType]): () => void;
}
export { CoreAgentHarness as AgentHarness };