donobu/dist/tools/Tool.d.ts

Create browser automations with an LLM agent and replay them as Playwright scripts.

import { JSONSchema7 } from 'json-schema';
import { ToolCallContext } from '../models/ToolCallContext';
import { ToolCallResult } from '../models/ToolCallResult';
/** Represents a tool call to be invoked by a DonobuFlow. */
export declare abstract class Tool<NonGptParameters, GptParameters> {
    /**
     * This is the name for the tool that will be shared with the LLM when making requests.
     */
    readonly name: string;
    /** This is the description that will be shared with the LLM when making requests. */
    readonly description: string;
    /** This is the JSON-schema for the tool when it is invoked by a non-LLM. */
    readonly inputSchema: JSONSchema7;
    /**
     * This is the JSON-schema that will be shared with the LLM when making
     * requests during autonomous flows.
     **/
    readonly inputSchemaForGpt: JSONSchema7;
    /**
     * This is the message that will be displayed in the front-end control panel when this tool is
     * invoked, assuming the control panel is enabled.
     */
    readonly controlPanelMessage: string;
    /** Returns true if this tool requires the usage of a GPT. */
    readonly requiresGpt: boolean;
    protected constructor(name: string, description: string, parametersTypeNameForNonGptSchema: string, parametersTypeNameForGptSchema: string, requiresGpt?: boolean);
    /**
     * Invoke the tool with the given context and parameters.
     */
    abstract call(_context: ToolCallContext, _parameters: NonGptParameters): Promise<ToolCallResult>;
    /**
     * Invoke the tool as made from a GPT with the given context and parameters.
     */
    abstract callFromGpt(_context: ToolCallContext, _parameters: GptParameters): Promise<ToolCallResult>;
}
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