mirror of
https://github.com/getcompanion-ai/co-mono.git
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Major changes: - Replace monolithic SessionEvent with reason discriminator with individual event types: session_start, session_before_switch, session_switch, session_before_new, session_new, session_before_branch, session_branch, session_before_compact, session_compact, session_shutdown - Each event has dedicated result type (SessionBeforeSwitchResult, etc.) - HookHandler type now allows bare return statements (void in return type) - HookAPI.on() has proper overloads for each event with correct typing Additional fixes: - AgentSession now always subscribes to agent in constructor (was only subscribing when external subscribe() called, breaking internal handlers) - Standardize on undefined over null throughout codebase - HookUIContext methods return undefined instead of null - SessionManager methods return undefined instead of null - Simplify hook exports to 'export type * from types.js' - Add detailed JSDoc for skipConversationRestore vs cancel - Fix createBranchedSession to rebuild index in persist mode - newSession() now returns the session file path Updated all example hooks, tests, and emission sites to use new event types.
604 lines
19 KiB
TypeScript
604 lines
19 KiB
TypeScript
/**
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* Context compaction for long sessions.
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*
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* Pure functions for compaction logic. The session manager handles I/O,
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* and after compaction the session is reloaded.
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*/
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import type { AgentMessage } from "@mariozechner/pi-agent-core";
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import type { AssistantMessage, Model, Usage } from "@mariozechner/pi-ai";
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import { complete } from "@mariozechner/pi-ai";
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import { convertToLlm, createBranchSummaryMessage, createHookMessage } from "./messages.js";
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import type { CompactionEntry, SessionEntry } from "./session-manager.js";
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/**
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* Extract AgentMessage from an entry if it produces one.
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* Returns undefined for entries that don't contribute to LLM context.
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*/
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function getMessageFromEntry(entry: SessionEntry): AgentMessage | undefined {
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if (entry.type === "message") {
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return entry.message;
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}
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if (entry.type === "custom_message") {
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return createHookMessage(entry.customType, entry.content, entry.display, entry.details, entry.timestamp);
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}
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if (entry.type === "branch_summary") {
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return createBranchSummaryMessage(entry.summary, entry.fromId, entry.timestamp);
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}
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return undefined;
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}
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/** Result from compact() - SessionManager adds uuid/parentUuid when saving */
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export interface CompactionResult<T = unknown> {
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summary: string;
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firstKeptEntryId: string;
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tokensBefore: number;
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/** Hook-specific data (e.g., ArtifactIndex, version markers for structured compaction) */
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details?: T;
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}
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// ============================================================================
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// Types
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// ============================================================================
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export interface CompactionSettings {
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enabled: boolean;
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reserveTokens: number;
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keepRecentTokens: number;
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}
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export const DEFAULT_COMPACTION_SETTINGS: CompactionSettings = {
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enabled: true,
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reserveTokens: 16384,
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keepRecentTokens: 20000,
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};
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// ============================================================================
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// Token calculation
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// ============================================================================
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/**
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* Calculate total context tokens from usage.
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* Uses the native totalTokens field when available, falls back to computing from components.
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*/
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export function calculateContextTokens(usage: Usage): number {
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return usage.totalTokens || usage.input + usage.output + usage.cacheRead + usage.cacheWrite;
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}
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/**
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* Get usage from an assistant message if available.
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* Skips aborted and error messages as they don't have valid usage data.
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*/
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function getAssistantUsage(msg: AgentMessage): Usage | undefined {
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if (msg.role === "assistant" && "usage" in msg) {
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const assistantMsg = msg as AssistantMessage;
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if (assistantMsg.stopReason !== "aborted" && assistantMsg.stopReason !== "error" && assistantMsg.usage) {
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return assistantMsg.usage;
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}
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}
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return undefined;
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}
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/**
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* Find the last non-aborted assistant message usage from session entries.
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*/
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export function getLastAssistantUsage(entries: SessionEntry[]): Usage | undefined {
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for (let i = entries.length - 1; i >= 0; i--) {
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const entry = entries[i];
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if (entry.type === "message") {
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const usage = getAssistantUsage(entry.message);
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if (usage) return usage;
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}
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}
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return undefined;
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}
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/**
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* Check if compaction should trigger based on context usage.
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*/
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export function shouldCompact(contextTokens: number, contextWindow: number, settings: CompactionSettings): boolean {
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if (!settings.enabled) return false;
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return contextTokens > contextWindow - settings.reserveTokens;
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}
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// ============================================================================
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// Cut point detection
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// ============================================================================
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/**
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* Estimate token count for a message using chars/4 heuristic.
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* This is conservative (overestimates tokens).
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*/
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export function estimateTokens(message: AgentMessage): number {
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let chars = 0;
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switch (message.role) {
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case "user": {
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const content = (message as { content: string | Array<{ type: string; text?: string }> }).content;
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if (typeof content === "string") {
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chars = content.length;
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} else if (Array.isArray(content)) {
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for (const block of content) {
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if (block.type === "text" && block.text) {
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chars += block.text.length;
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}
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}
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}
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return Math.ceil(chars / 4);
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}
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case "assistant": {
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const assistant = message as AssistantMessage;
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for (const block of assistant.content) {
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if (block.type === "text") {
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chars += block.text.length;
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} else if (block.type === "thinking") {
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chars += block.thinking.length;
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} else if (block.type === "toolCall") {
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chars += block.name.length + JSON.stringify(block.arguments).length;
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}
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}
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return Math.ceil(chars / 4);
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}
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case "hookMessage":
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case "toolResult": {
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if (typeof message.content === "string") {
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chars = message.content.length;
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} else {
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for (const block of message.content) {
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if (block.type === "text" && block.text) {
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chars += block.text.length;
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}
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if (block.type === "image") {
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chars += 4800; // Estimate images as 4000 chars, or 1200 tokens
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}
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}
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}
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return Math.ceil(chars / 4);
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}
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case "bashExecution": {
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chars = message.command.length + message.output.length;
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return Math.ceil(chars / 4);
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}
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case "branchSummary":
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case "compactionSummary": {
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chars = message.summary.length;
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return Math.ceil(chars / 4);
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}
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}
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return 0;
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}
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/**
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* Find valid cut points: indices of user, assistant, custom, or bashExecution messages.
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* Never cut at tool results (they must follow their tool call).
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* When we cut at an assistant message with tool calls, its tool results follow it
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* and will be kept.
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* BashExecutionMessage is treated like a user message (user-initiated context).
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*/
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function findValidCutPoints(entries: SessionEntry[], startIndex: number, endIndex: number): number[] {
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const cutPoints: number[] = [];
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for (let i = startIndex; i < endIndex; i++) {
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const entry = entries[i];
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switch (entry.type) {
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case "message": {
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const role = entry.message.role;
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switch (role) {
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case "bashExecution":
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case "hookMessage":
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case "branchSummary":
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case "compactionSummary":
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case "user":
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case "assistant":
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cutPoints.push(i);
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break;
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case "toolResult":
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break;
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}
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break;
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}
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case "thinking_level_change":
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case "model_change":
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case "compaction":
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case "branch_summary":
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case "custom":
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case "custom_message":
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case "label":
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}
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// branch_summary and custom_message are user-role messages, valid cut points
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if (entry.type === "branch_summary" || entry.type === "custom_message") {
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cutPoints.push(i);
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}
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}
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return cutPoints;
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}
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/**
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* Find the user message (or bashExecution) that starts the turn containing the given entry index.
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* Returns -1 if no turn start found before the index.
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* BashExecutionMessage is treated like a user message for turn boundaries.
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*/
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export function findTurnStartIndex(entries: SessionEntry[], entryIndex: number, startIndex: number): number {
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for (let i = entryIndex; i >= startIndex; i--) {
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const entry = entries[i];
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// branch_summary and custom_message are user-role messages, can start a turn
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if (entry.type === "branch_summary" || entry.type === "custom_message") {
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return i;
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}
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if (entry.type === "message") {
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const role = entry.message.role;
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if (role === "user" || role === "bashExecution") {
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return i;
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}
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}
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}
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return -1;
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}
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export interface CutPointResult {
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/** Index of first entry to keep */
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firstKeptEntryIndex: number;
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/** Index of user message that starts the turn being split, or -1 if not splitting */
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turnStartIndex: number;
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/** Whether this cut splits a turn (cut point is not a user message) */
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isSplitTurn: boolean;
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}
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/**
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* Find the cut point in session entries that keeps approximately `keepRecentTokens`.
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*
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* Algorithm: Walk backwards from newest, accumulating estimated message sizes.
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* Stop when we've accumulated >= keepRecentTokens. Cut at that point.
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*
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* Can cut at user OR assistant messages (never tool results). When cutting at an
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* assistant message with tool calls, its tool results come after and will be kept.
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*
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* Returns CutPointResult with:
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* - firstKeptEntryIndex: the entry index to start keeping from
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* - turnStartIndex: if cutting mid-turn, the user message that started that turn
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* - isSplitTurn: whether we're cutting in the middle of a turn
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*
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* Only considers entries between `startIndex` and `endIndex` (exclusive).
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*/
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export function findCutPoint(
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entries: SessionEntry[],
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startIndex: number,
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endIndex: number,
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keepRecentTokens: number,
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): CutPointResult {
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const cutPoints = findValidCutPoints(entries, startIndex, endIndex);
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if (cutPoints.length === 0) {
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return { firstKeptEntryIndex: startIndex, turnStartIndex: -1, isSplitTurn: false };
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}
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// Walk backwards from newest, accumulating estimated message sizes
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let accumulatedTokens = 0;
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let cutIndex = cutPoints[0]; // Default: keep from first message (not header)
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for (let i = endIndex - 1; i >= startIndex; i--) {
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const entry = entries[i];
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if (entry.type !== "message") continue;
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// Estimate this message's size
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const messageTokens = estimateTokens(entry.message);
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accumulatedTokens += messageTokens;
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// Check if we've exceeded the budget
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if (accumulatedTokens >= keepRecentTokens) {
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// Find the closest valid cut point at or after this entry
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for (let c = 0; c < cutPoints.length; c++) {
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if (cutPoints[c] >= i) {
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cutIndex = cutPoints[c];
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break;
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}
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}
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break;
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}
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}
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// Scan backwards from cutIndex to include any non-message entries (bash, settings, etc.)
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while (cutIndex > startIndex) {
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const prevEntry = entries[cutIndex - 1];
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// Stop at session header or compaction boundaries
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if (prevEntry.type === "compaction") {
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break;
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}
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if (prevEntry.type === "message") {
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// Stop if we hit any message
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break;
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}
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// Include this non-message entry (bash, settings change, etc.)
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cutIndex--;
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}
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// Determine if this is a split turn
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const cutEntry = entries[cutIndex];
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const isUserMessage = cutEntry.type === "message" && cutEntry.message.role === "user";
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const turnStartIndex = isUserMessage ? -1 : findTurnStartIndex(entries, cutIndex, startIndex);
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return {
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firstKeptEntryIndex: cutIndex,
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turnStartIndex,
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isSplitTurn: !isUserMessage && turnStartIndex !== -1,
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};
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}
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// ============================================================================
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// Summarization
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// ============================================================================
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const SUMMARIZATION_PROMPT = `You are performing a CONTEXT CHECKPOINT COMPACTION. Create a handoff summary for another LLM that will resume the task.
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Include:
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- Current progress and key decisions made
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- Important context, constraints, or user preferences
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- Absolute file paths of any relevant files that were read or modified
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- What remains to be done (clear next steps)
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- Any critical data, examples, or references needed to continue
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Be concise, structured, and focused on helping the next LLM seamlessly continue the work.`;
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/**
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* Generate a summary of the conversation using the LLM.
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*/
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export async function generateSummary(
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currentMessages: AgentMessage[],
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model: Model<any>,
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reserveTokens: number,
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apiKey: string,
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signal?: AbortSignal,
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customInstructions?: string,
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): Promise<string> {
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const maxTokens = Math.floor(0.8 * reserveTokens);
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const prompt = customInstructions
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? `${SUMMARIZATION_PROMPT}\n\nAdditional focus: ${customInstructions}`
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: SUMMARIZATION_PROMPT;
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// Transform custom messages (like bashExecution) to LLM-compatible messages
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const transformedMessages = convertToLlm(currentMessages);
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const summarizationMessages = [
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...transformedMessages,
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{
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role: "user" as const,
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content: [{ type: "text" as const, text: prompt }],
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timestamp: Date.now(),
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},
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];
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const response = await complete(model, { messages: summarizationMessages }, { maxTokens, signal, apiKey });
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if (response.stopReason === "error") {
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throw new Error(`Summarization failed: ${response.errorMessage || "Unknown error"}`);
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}
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const textContent = response.content
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.filter((c): c is { type: "text"; text: string } => c.type === "text")
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.map((c) => c.text)
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.join("\n");
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return textContent;
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}
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// ============================================================================
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// Compaction Preparation (for hooks)
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// ============================================================================
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export interface CompactionPreparation {
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cutPoint: CutPointResult;
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/** UUID of first entry to keep */
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firstKeptEntryId: string;
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/** Messages that will be summarized and discarded */
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messagesToSummarize: AgentMessage[];
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/** Messages that will be kept after the summary (recent turns) */
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messagesToKeep: AgentMessage[];
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tokensBefore: number;
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boundaryStart: number;
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}
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export function prepareCompaction(
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entries: SessionEntry[],
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settings: CompactionSettings,
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): CompactionPreparation | undefined {
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if (entries.length > 0 && entries[entries.length - 1].type === "compaction") {
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return undefined;
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}
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let prevCompactionIndex = -1;
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for (let i = entries.length - 1; i >= 0; i--) {
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if (entries[i].type === "compaction") {
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prevCompactionIndex = i;
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break;
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}
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}
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const boundaryStart = prevCompactionIndex + 1;
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const boundaryEnd = entries.length;
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const lastUsage = getLastAssistantUsage(entries);
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const tokensBefore = lastUsage ? calculateContextTokens(lastUsage) : 0;
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const cutPoint = findCutPoint(entries, boundaryStart, boundaryEnd, settings.keepRecentTokens);
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// Get UUID of first kept entry
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const firstKeptEntry = entries[cutPoint.firstKeptEntryIndex];
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if (!firstKeptEntry?.id) {
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return undefined; // Session needs migration
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}
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const firstKeptEntryId = firstKeptEntry.id;
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const historyEnd = cutPoint.isSplitTurn ? cutPoint.turnStartIndex : cutPoint.firstKeptEntryIndex;
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// Messages to summarize (will be discarded after summary)
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const messagesToSummarize: AgentMessage[] = [];
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for (let i = boundaryStart; i < historyEnd; i++) {
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const msg = getMessageFromEntry(entries[i]);
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if (msg) messagesToSummarize.push(msg);
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}
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// Messages to keep (recent turns, kept after summary)
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const messagesToKeep: AgentMessage[] = [];
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for (let i = cutPoint.firstKeptEntryIndex; i < boundaryEnd; i++) {
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const msg = getMessageFromEntry(entries[i]);
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if (msg) messagesToKeep.push(msg);
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}
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return { cutPoint, firstKeptEntryId, messagesToSummarize, messagesToKeep, tokensBefore, boundaryStart };
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}
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// ============================================================================
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// Main compaction function
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// ============================================================================
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const TURN_PREFIX_SUMMARIZATION_PROMPT = `You are performing a CONTEXT CHECKPOINT COMPACTION for a split turn.
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This is the PREFIX of a turn that was too large to keep in full. The SUFFIX (recent work) is being kept.
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Create a handoff summary that captures:
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- What the user originally asked for in this turn
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- Key decisions and progress made early in this turn
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- Important context needed to understand the kept suffix
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Be concise. Focus on information needed to understand the retained recent work.`;
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/**
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* Calculate compaction and generate summary.
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* Returns CompactionResult - SessionManager adds uuid/parentUuid when saving.
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*
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* @param entries - All session entries (must have uuid fields for v2)
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* @param model - Model to use for summarization
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* @param settings - Compaction settings
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* @param apiKey - API key for LLM
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* @param signal - Optional abort signal
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* @param customInstructions - Optional custom focus for the summary
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*/
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export async function compact(
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entries: SessionEntry[],
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model: Model<any>,
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settings: CompactionSettings,
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apiKey: string,
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signal?: AbortSignal,
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customInstructions?: string,
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): Promise<CompactionResult> {
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// Don't compact if the last entry is already a compaction
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if (entries.length > 0 && entries[entries.length - 1].type === "compaction") {
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throw new Error("Already compacted");
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}
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// Find previous compaction boundary
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let prevCompactionIndex = -1;
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for (let i = entries.length - 1; i >= 0; i--) {
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if (entries[i].type === "compaction") {
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prevCompactionIndex = i;
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break;
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}
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}
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const boundaryStart = prevCompactionIndex + 1;
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const boundaryEnd = entries.length;
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// Get token count before compaction
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const lastUsage = getLastAssistantUsage(entries);
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const tokensBefore = lastUsage ? calculateContextTokens(lastUsage) : 0;
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// Find cut point (entry index) within the valid range
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const cutResult = findCutPoint(entries, boundaryStart, boundaryEnd, settings.keepRecentTokens);
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// Extract messages for history summary (before the turn that contains the cut point)
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const historyEnd = cutResult.isSplitTurn ? cutResult.turnStartIndex : cutResult.firstKeptEntryIndex;
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const historyMessages: AgentMessage[] = [];
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for (let i = boundaryStart; i < historyEnd; i++) {
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const msg = getMessageFromEntry(entries[i]);
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if (msg) historyMessages.push(msg);
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}
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// Include previous summary if there was a compaction
|
|
if (prevCompactionIndex >= 0) {
|
|
const prevCompaction = entries[prevCompactionIndex] as CompactionEntry;
|
|
historyMessages.unshift({
|
|
role: "user",
|
|
content: `Previous session summary:\n${prevCompaction.summary}`,
|
|
timestamp: Date.now(),
|
|
});
|
|
}
|
|
|
|
// Extract messages for turn prefix summary (if splitting a turn)
|
|
const turnPrefixMessages: AgentMessage[] = [];
|
|
if (cutResult.isSplitTurn) {
|
|
for (let i = cutResult.turnStartIndex; i < cutResult.firstKeptEntryIndex; i++) {
|
|
const msg = getMessageFromEntry(entries[i]);
|
|
if (msg) turnPrefixMessages.push(msg);
|
|
}
|
|
}
|
|
|
|
// Generate summaries (can be parallel if both needed) and merge into one
|
|
let summary: string;
|
|
|
|
if (cutResult.isSplitTurn && turnPrefixMessages.length > 0) {
|
|
// Generate both summaries in parallel
|
|
const [historyResult, turnPrefixResult] = await Promise.all([
|
|
historyMessages.length > 0
|
|
? generateSummary(historyMessages, model, settings.reserveTokens, apiKey, signal, customInstructions)
|
|
: Promise.resolve("No prior history."),
|
|
generateTurnPrefixSummary(turnPrefixMessages, model, settings.reserveTokens, apiKey, signal),
|
|
]);
|
|
// Merge into single summary
|
|
summary = `${historyResult}\n\n---\n\n**Turn Context (split turn):**\n\n${turnPrefixResult}`;
|
|
} else {
|
|
// Just generate history summary
|
|
summary = await generateSummary(
|
|
historyMessages,
|
|
model,
|
|
settings.reserveTokens,
|
|
apiKey,
|
|
signal,
|
|
customInstructions,
|
|
);
|
|
}
|
|
|
|
// Get UUID of first kept entry
|
|
const firstKeptEntry = entries[cutResult.firstKeptEntryIndex];
|
|
const firstKeptEntryId = firstKeptEntry.id;
|
|
if (!firstKeptEntryId) {
|
|
throw new Error("First kept entry has no UUID - session may need migration");
|
|
}
|
|
|
|
return {
|
|
summary,
|
|
firstKeptEntryId,
|
|
tokensBefore,
|
|
};
|
|
}
|
|
|
|
/**
|
|
* Generate a summary for a turn prefix (when splitting a turn).
|
|
*/
|
|
async function generateTurnPrefixSummary(
|
|
messages: AgentMessage[],
|
|
model: Model<any>,
|
|
reserveTokens: number,
|
|
apiKey: string,
|
|
signal?: AbortSignal,
|
|
): Promise<string> {
|
|
const maxTokens = Math.floor(0.5 * reserveTokens); // Smaller budget for turn prefix
|
|
|
|
const transformedMessages = convertToLlm(messages);
|
|
const summarizationMessages = [
|
|
...transformedMessages,
|
|
{
|
|
role: "user" as const,
|
|
content: [{ type: "text" as const, text: TURN_PREFIX_SUMMARIZATION_PROMPT }],
|
|
timestamp: Date.now(),
|
|
},
|
|
];
|
|
|
|
const response = await complete(model, { messages: summarizationMessages }, { maxTokens, signal, apiKey });
|
|
|
|
if (response.stopReason === "error") {
|
|
throw new Error(`Turn prefix summarization failed: ${response.errorMessage || "Unknown error"}`);
|
|
}
|
|
|
|
return response.content
|
|
.filter((c): c is { type: "text"; text: string } => c.type === "text")
|
|
.map((c) => c.text)
|
|
.join("\n");
|
|
}
|