@langchain/core/dist/messages/ai.d.ts

Core LangChain.js abstractions and schemas

import { BaseMessage, BaseMessageChunk, type MessageType, BaseMessageFields } from "./base.js";
import { InvalidToolCall, ToolCall, ToolCallChunk } from "./tool.js";
export type AIMessageFields = BaseMessageFields & {
    tool_calls?: ToolCall[];
    invalid_tool_calls?: InvalidToolCall[];
    usage_metadata?: UsageMetadata;
};
/**
 * Breakdown of input token counts.
 *
 * Does not *need* to sum to full input token count. Does *not* need to have all keys.
 */
export type InputTokenDetails = {
    /**
     * Audio input tokens.
     */
    audio?: number;
    /**
     * Input tokens that were cached and there was a cache hit.
     *
     * Since there was a cache hit, the tokens were read from the cache.
     * More precisely, the model state given these tokens was read from the cache.
     */
    cache_read?: number;
    /**
     * Input tokens that were cached and there was a cache miss.
     *
     * Since there was a cache miss, the cache was created from these tokens.
     */
    cache_creation?: number;
};
/**
 * Breakdown of output token counts.
 *
 * Does *not* need to sum to full output token count. Does *not* need to have all keys.
 */
export type OutputTokenDetails = {
    /**
     * Audio output tokens
     */
    audio?: number;
    /**
     * Reasoning output tokens.
     *
     * Tokens generated by the model in a chain of thought process (i.e. by
     * OpenAI's o1 models) that are not returned as part of model output.
     */
    reasoning?: number;
};
/**
 * Usage metadata for a message, such as token counts.
 */
export type UsageMetadata = {
    /**
     * Count of input (or prompt) tokens. Sum of all input token types.
     */
    input_tokens: number;
    /**
     * Count of output (or completion) tokens. Sum of all output token types.
     */
    output_tokens: number;
    /**
     * Total token count. Sum of input_tokens + output_tokens.
     */
    total_tokens: number;
    /**
     * Breakdown of input token counts.
     *
     * Does *not* need to sum to full input token count. Does *not* need to have all keys.
     */
    input_token_details?: InputTokenDetails;
    /**
     * Breakdown of output token counts.
     *
     * Does *not* need to sum to full output token count. Does *not* need to have all keys.
     */
    output_token_details?: OutputTokenDetails;
};
/**
 * Represents an AI message in a conversation.
 */
export declare class AIMessage extends BaseMessage {
    tool_calls?: ToolCall[];
    invalid_tool_calls?: InvalidToolCall[];
    /**
     * If provided, token usage information associated with the message.
     */
    usage_metadata?: UsageMetadata;
    get lc_aliases(): Record<string, string>;
    constructor(fields: string | AIMessageFields, 
    /** @deprecated */
    kwargs?: Record<string, unknown>);
    static lc_name(): string;
    _getType(): MessageType;
    get _printableFields(): Record<string, unknown>;
}
export declare function isAIMessage(x: BaseMessage): x is AIMessage;
export declare function isAIMessageChunk(x: BaseMessageChunk): x is AIMessageChunk;
export type AIMessageChunkFields = AIMessageFields & {
    tool_call_chunks?: ToolCallChunk[];
};
/**
 * Represents a chunk of an AI message, which can be concatenated with
 * other AI message chunks.
 */
export declare class AIMessageChunk extends BaseMessageChunk {
    tool_calls?: ToolCall[];
    invalid_tool_calls?: InvalidToolCall[];
    tool_call_chunks?: ToolCallChunk[];
    /**
     * If provided, token usage information associated with the message.
     */
    usage_metadata?: UsageMetadata;
    constructor(fields: string | AIMessageChunkFields);
    get lc_aliases(): Record<string, string>;
    static lc_name(): string;
    _getType(): MessageType;
    get _printableFields(): Record<string, unknown>;
    concat(chunk: AIMessageChunk): AIMessageChunk;
}