adk-typescript/dist/models/LiteLlm.d.ts

TypeScript port of Google's Agent Development Kit (ADK)

import { BaseLlm } from './BaseLlm';
import { LlmRequest } from './LlmRequest';
import { LlmResponse } from './LlmResponse';
export declare class TextChunk {
    text: string;
    constructor(text: string);
}
export declare class FunctionChunk {
    id?: string | null | undefined;
    name?: string | null | undefined;
    args?: string | null | undefined;
    constructor(id?: string | null | undefined, name?: string | null | undefined, args?: string | null | undefined);
}
/**
 * LiteLLM client for making completions
 * This implementation uses any types in places where strict typing is challenging
 * due to differences between the TypeScript and JavaScript implementations
 */
export declare class LiteLLMClient {
    /**
     * Asynchronously calls completion
     * @param model The model name
     * @param messages The messages to send
     * @param tools The tools to use
     * @param kwargs Additional arguments
     * @returns A promise resolving to the model response
     */
    acompletion(model: string, messages: any[], tools?: any[], ...kwargs: any[]): Promise<any>;
    /**
     * Synchronously calls completion
     * @param model The model name
     * @param messages The messages to send
     * @param tools The tools to use
     * @param stream Whether to stream the response
     * @param kwargs Additional arguments
     * @returns An iterable of model responses
     */
    completion(model: string, messages: any[], tools?: any[], stream?: boolean, ...kwargs: any[]): any;
}
/**
 * LiteLlm class - wrapper around LiteLLM
 */
export declare class LiteLlm extends BaseLlm {
    llmClient: LiteLLMClient;
    private _additionalArgs;
    /**
     * Constructor
     * @param model The model name
     * @param additionalArgs Additional arguments
     */
    constructor(model: string, additionalArgs?: Record<string, any>);
    /**
     * Generate content asynchronously
     * @param llmRequest The request
     * @param stream Whether to stream
     * @returns AsyncGenerator yielding responses
     */
    generateContentAsync(llmRequest: LlmRequest, stream?: boolean): AsyncGenerator<LlmResponse, void, unknown>;
    /**
     * List of supported models
     * @returns Empty array - LiteLlm supports all models
     */
    static supportedModels(): string[];
}