@jackhua/mini-langchain/dist/llms/base.d.ts

A lightweight TypeScript implementation of LangChain with cost optimization features

import { Message, AIMessage, LLMResult, LLMCallOptions, BaseCallbackHandler, GenerationChunk } from '../core/types';
/**
 * Abstract base class for all LLM implementations
 */
export declare abstract class BaseLLM {
    protected callbacks: BaseCallbackHandler[];
    protected verbose: boolean;
    constructor(config?: {
        callbacks?: BaseCallbackHandler[];
        verbose?: boolean;
    });
    /**
     * Generate a response from the LLM
     */
    abstract generate(messages: Message[], options?: LLMCallOptions): Promise<LLMResult>;
    /**
     * Stream a response from the LLM
     */
    abstract stream(messages: Message[], options?: LLMCallOptions): AsyncGenerator<GenerationChunk>;
    /**
     * Call the LLM with a simple string prompt
     */
    call(prompt: string, options?: LLMCallOptions): Promise<string>;
    /**
     * Predict the next message in a conversation
     */
    predict(messages: Message[], options?: LLMCallOptions): Promise<AIMessage>;
    /**
     * Add a callback handler
     */
    addCallback(callback: BaseCallbackHandler): void;
    /**
     * Remove a callback handler
     */
    removeCallback(callback: BaseCallbackHandler): void;
    /**
     * Handle LLM start callbacks
     */
    protected handleLLMStart(prompts: string[]): Promise<void>;
    /**
     * Handle LLM end callbacks
     */
    protected handleLLMEnd(output: LLMResult): Promise<void>;
    /**
     * Handle LLM error callbacks
     */
    protected handleLLMError(error: Error): Promise<void>;
    /**
     * Get the identifying parameters of the LLM
     */
    abstract get identifyingParams(): Record<string, any>;
    /**
     * Get the type of LLM
     */
    abstract get llmType(): string;
}
/**
 * Base class for chat-based LLMs
 */
export declare abstract class BaseChatLLM extends BaseLLM {
    /**
     * Convert messages to the format expected by the LLM
     */
    protected abstract formatMessages(messages: Message[]): any;
    /**
     * Default temperature for the model
     */
    protected defaultTemperature: number;
    /**
     * Default max tokens for the model
     */
    protected defaultMaxTokens: number;
    /**
     * Get default options
     */
    protected getDefaultOptions(): LLMCallOptions;
    /**
     * Merge options with defaults
     */
    protected mergeOptions(options?: LLMCallOptions): LLMCallOptions;
}
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