/**
 * Observer module for the observational memory system.
 *
 * Handles extracting observations from raw conversation messages via a
 * background LLM call. The observer watches the conversation and produces
 * structured, timestamped observations that become the agent's sole
 * memory of past interactions.
 *
 * References:
 *   - observational-memory-architecture.md (Observer System section)
 *   - compaction-strategy.md
 */
import type { CompleteFn } from '../compaction.js';
import type { AgentMessage } from '../../context-manager.js';
import type { ObserverOutput } from './types.js';
/**
 * Converts an array of AgentMessages into a formatted string for the
 * observer LLM.
 *
 * Each message is formatted with role and positional timestamp. Messages
 * with content arrays (tool calls/results) receive structured formatting
 * so the observer can extract meaningful takeaways.
 *
 * Messages with timestamps are formatted with their actual date and time.
 * Messages without timestamps fall back to sequential labels.
 * Messages are grouped by date when timestamps are available.
 */
export declare function formatMessagesForObserver(messages: AgentMessage[]): string;
/**
 * Parse the raw LLM output from the observer.
 *
 * Extracts content from `<observations>`, `<current-task>`, and
 * `<suggested-response>` XML blocks. Uses simple string matching
 * (not a DOM parser) and is lenient with malformed output.
 *
 * If no `<observations>` tag is found, the entire output is used as
 * observations (graceful fallback).
 */
export declare function parseObserverOutput(raw: string): ObserverOutput;
/**
 * Build the full observer system prompt.
 *
 * Starts with `OBSERVER_SYSTEM_PROMPT` from constants and optionally
 * appends consumer-provided custom instructions.
 *
 * @param previousObservations - Previous observations for context (unused in system prompt, kept for signature consistency)
 * @param previousObserverTokens - Token budget for previous observations (unused in system prompt)
 * @param customInstruction - Optional consumer-provided instruction to append
 * @returns The complete system prompt string
 */
export declare function buildObserverPrompt(previousObservations: string | null, previousObserverTokens: number, customInstruction?: string): string;
/**
 * Build the message array to send to the observer LLM.
 *
 * Constructs a sequence of user messages:
 * 1. (Optional) Previous observations for deduplication context
 * 2. The formatted message history
 * 3. A task instruction to extract observations
 *
 * @param messages - The conversation messages to observe
 * @param previousObservations - Previous observations to prevent duplication
 * @param previousObserverTokens - Token budget for the previous observations context
 * @returns Array of message objects for the LLM call
 */
export declare function buildObserverMessages(messages: AgentMessage[], previousObservations: string | null, previousObserverTokens: number): unknown[];
/**
 * Check if the output contains degenerate repetition.
 *
 * Detects a line appearing 5+ times consecutively, which is a known
 * failure mode of LLMs under certain conditions (e.g., high temperature,
 * long context, repetitive input patterns).
 *
 * @param text - The text to check for repetition
 * @returns true if degenerate repetition is detected
 */
export declare function detectDegenerateRepetition(text: string): boolean;
/**
 * Run the observer LLM call to extract observations from messages.
 *
 * Orchestrates the full observer pipeline:
 * 1. Builds the system prompt (with optional custom instructions)
 * 2. Builds the message array (with previous observations context)
 * 3. Calls the LLM via `complete`
 * 4. Parses the structured output
 * 5. Detects and retries on degenerate repetition (once)
 *
 * @param complete - The LLM completion function
 * @param messages - The conversation messages to observe
 * @param previousObservations - Previous observations for deduplication
 * @param config - Observer configuration
 * @returns Parsed observer output with observations, current task, and suggested response
 */
export declare function runObserver(complete: CompleteFn, messages: AgentMessage[], previousObservations: string | null, config: {
    previousObserverTokens: number;
    observerInstruction?: string;
}): Promise<ObserverOutput>;
//# sourceMappingURL=observer.d.ts.map