@juspay/neurolink/dist/context/summarizationEngine.d.ts

The pipe layer of an AI nervous system: one interface connecting provider neurons to your application, across three inference types — generate, stream and decide. `decide` returns typed, calibrated judgements from a non-generative model (~400ms, ~$0.00002

/**
 * Shared Summarization Engine
 *
 * Extracted from ConversationMemoryManager and RedisConversationMemoryManager
 * to eliminate code duplication. Both managers delegate to this engine.
 */
import type { ChatMessage, ConversationMemoryConfig, SessionMemory } from "../types/index.js";
/**
 * Centralized summarization engine for conversation memory.
 * Handles token counting, threshold checking, and summary generation.
 */
export declare class SummarizationEngine {
    /**
     * Check if a session needs summarization and perform it if so.
     * @param session - Session memory to check and potentially summarize
     * @param threshold - Token threshold that triggers summarization
     * @param config - Conversation memory configuration (partial allowed)
     * @param logPrefix - Prefix for log messages
     * @returns True if summarization was performed
     */
    checkAndSummarize(session: SessionMemory, threshold: number, config: Partial<ConversationMemoryConfig>, logPrefix?: string, requestId?: string): Promise<boolean>;
    /**
     * Perform token-based summarization on a session.
     * Uses pointer-based, non-destructive approach.
     * @param session - Session memory to summarize
     * @param threshold - Token threshold for calculating split point
     * @param config - Conversation memory configuration (partial allowed)
     * @param logPrefix - Prefix for log messages
     */
    summarizeSession(session: SessionMemory, threshold: number, config: Partial<ConversationMemoryConfig>, logPrefix?: string, requestId?: string): Promise<void>;
    /**
     * Estimate total tokens for a message array.
     * @param messages - Array of chat messages
     * @returns Estimated token count
     */
    estimateTokens(messages: ChatMessage[]): number;
    /**
     * Find split index to keep recent messages within target token count.
     * Works backwards from the most recent message to find the split point.
     * @param messages - Array of messages to analyze
     * @param targetRecentTokens - Target token count for recent messages
     * @returns Index at which to split (messages before this index will be summarized)
     */
    findSplitIndexByTokens(messages: ChatMessage[], targetRecentTokens: number): number;
}