mirror of
https://github.com/getcompanion-ai/co-mono.git
synced 2026-04-15 19:05:11 +00:00
The old messagesToText only extracted text content, losing all tool calls. Now uses convertToLlm like compaction does, preserving the full conversation including tool calls, which is essential for generating useful summaries.
373 lines
11 KiB
TypeScript
373 lines
11 KiB
TypeScript
/**
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* Branch summarization for tree navigation.
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*
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* When navigating to a different point in the session tree, this generates
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* a summary of the branch being left so context isn't lost.
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*/
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import type { AgentMessage } from "@mariozechner/pi-agent-core";
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import type { Model } from "@mariozechner/pi-ai";
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import { complete } from "@mariozechner/pi-ai";
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import {
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convertToLlm,
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createBranchSummaryMessage,
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createCompactionSummaryMessage,
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createHookMessage,
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} from "../messages.js";
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import type { ReadonlySessionManager, SessionEntry } from "../session-manager.js";
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import { estimateTokens } from "./compaction.js";
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// ============================================================================
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// Types
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// ============================================================================
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export interface BranchSummaryResult {
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summary?: string;
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readFiles?: string[];
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modifiedFiles?: string[];
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aborted?: boolean;
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error?: string;
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}
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/** Details stored in BranchSummaryEntry.details for file tracking */
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export interface BranchSummaryDetails {
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readFiles: string[];
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modifiedFiles: string[];
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}
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export interface FileOperations {
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read: Set<string>;
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written: Set<string>;
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edited: Set<string>;
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}
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export interface BranchPreparation {
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/** Messages extracted for summarization, in chronological order */
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messages: AgentMessage[];
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/** File operations extracted from tool calls */
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fileOps: FileOperations;
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/** Total estimated tokens in messages */
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totalTokens: number;
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}
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export interface CollectEntriesResult {
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/** Entries to summarize, in chronological order */
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entries: SessionEntry[];
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/** Common ancestor between old and new position, if any */
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commonAncestorId: string | null;
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}
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export interface GenerateBranchSummaryOptions {
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/** Model to use for summarization */
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model: Model<any>;
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/** API key for the model */
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apiKey: string;
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/** Abort signal for cancellation */
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signal: AbortSignal;
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/** Optional custom instructions for summarization */
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customInstructions?: string;
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/** Tokens reserved for prompt + LLM response (default 16384) */
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reserveTokens?: number;
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}
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// ============================================================================
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// Entry Collection
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// ============================================================================
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/**
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* Collect entries that should be summarized when navigating from one position to another.
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*
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* Walks from oldLeafId back to the common ancestor with targetId, collecting entries
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* along the way. Does NOT stop at compaction boundaries - those are included and their
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* summaries become context.
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*
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* @param session - Session manager (read-only access)
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* @param oldLeafId - Current position (where we're navigating from)
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* @param targetId - Target position (where we're navigating to)
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* @returns Entries to summarize and the common ancestor
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*/
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export function collectEntriesForBranchSummary(
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session: ReadonlySessionManager,
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oldLeafId: string | null,
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targetId: string,
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): CollectEntriesResult {
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// If no old position, nothing to summarize
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if (!oldLeafId) {
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return { entries: [], commonAncestorId: null };
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}
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// Find common ancestor (deepest node that's on both paths)
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const oldPath = new Set(session.getPath(oldLeafId).map((e) => e.id));
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const targetPath = session.getPath(targetId);
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// targetPath is root-first, so iterate backwards to find deepest common ancestor
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let commonAncestorId: string | null = null;
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for (let i = targetPath.length - 1; i >= 0; i--) {
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if (oldPath.has(targetPath[i].id)) {
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commonAncestorId = targetPath[i].id;
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break;
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}
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}
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// Collect entries from old leaf back to common ancestor
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const entries: SessionEntry[] = [];
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let current: string | null = oldLeafId;
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while (current && current !== commonAncestorId) {
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const entry = session.getEntry(current);
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if (!entry) break;
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entries.push(entry);
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current = entry.parentId;
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}
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// Reverse to get chronological order
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entries.reverse();
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return { entries, commonAncestorId };
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}
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// ============================================================================
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// Entry to Message Conversion
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// ============================================================================
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/**
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* Extract AgentMessage from a session entry.
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* Similar to getMessageFromEntry in compaction.ts but also handles compaction entries.
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*/
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function getMessageFromEntry(entry: SessionEntry): AgentMessage | undefined {
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switch (entry.type) {
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case "message":
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// Skip tool results - context is in assistant's tool call
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if (entry.message.role === "toolResult") return undefined;
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return entry.message;
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case "custom_message":
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return createHookMessage(entry.customType, entry.content, entry.display, entry.details, entry.timestamp);
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case "branch_summary":
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return createBranchSummaryMessage(entry.summary, entry.fromId, entry.timestamp);
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case "compaction":
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return createCompactionSummaryMessage(entry.summary, entry.tokensBefore, entry.timestamp);
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// These don't contribute to conversation content
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case "thinking_level_change":
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case "model_change":
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case "custom":
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case "label":
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return undefined;
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}
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}
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/**
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* Extract file operations from tool calls in an assistant message.
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*/
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function extractFileOpsFromMessage(message: AgentMessage, fileOps: FileOperations): void {
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if (message.role !== "assistant") return;
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if (!("content" in message) || !Array.isArray(message.content)) return;
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for (const block of message.content) {
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if (typeof block !== "object" || block === null) continue;
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if (!("type" in block) || block.type !== "toolCall") continue;
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if (!("arguments" in block) || !("name" in block)) continue;
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const args = block.arguments as Record<string, unknown> | undefined;
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if (!args) continue;
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const path = typeof args.path === "string" ? args.path : undefined;
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if (!path) continue;
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switch (block.name) {
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case "read":
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fileOps.read.add(path);
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break;
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case "write":
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fileOps.written.add(path);
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break;
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case "edit":
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fileOps.edited.add(path);
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break;
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}
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}
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}
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/**
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* Prepare entries for summarization with token budget.
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*
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* Walks entries from NEWEST to OLDEST, adding messages until we hit the token budget.
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* This ensures we keep the most recent context when the branch is too long.
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*
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* Also collects file operations from:
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* - Tool calls in assistant messages
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* - Existing branch_summary entries' details (for cumulative tracking)
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*
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* @param entries - Entries in chronological order
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* @param tokenBudget - Maximum tokens to include (0 = no limit)
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*/
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export function prepareBranchEntries(entries: SessionEntry[], tokenBudget: number = 0): BranchPreparation {
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const messages: AgentMessage[] = [];
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const fileOps: FileOperations = {
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read: new Set(),
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written: new Set(),
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edited: new Set(),
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};
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let totalTokens = 0;
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// First pass: collect file ops from ALL entries (even if they don't fit in token budget)
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// This ensures we capture cumulative file tracking from nested branch summaries
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for (const entry of entries) {
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if (entry.type === "branch_summary" && entry.details) {
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const details = entry.details as BranchSummaryDetails;
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if (Array.isArray(details.readFiles)) {
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for (const f of details.readFiles) fileOps.read.add(f);
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}
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if (Array.isArray(details.modifiedFiles)) {
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// Modified files go into both edited and written for proper deduplication
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for (const f of details.modifiedFiles) {
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fileOps.edited.add(f);
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}
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}
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}
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}
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// Second pass: walk from newest to oldest, adding messages until token budget
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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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const message = getMessageFromEntry(entry);
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if (!message) continue;
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// Extract file ops from assistant messages (tool calls)
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extractFileOpsFromMessage(message, fileOps);
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const tokens = estimateTokens(message);
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// Check budget before adding
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if (tokenBudget > 0 && totalTokens + tokens > tokenBudget) {
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// If this is a summary entry, try to fit it anyway as it's important context
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if (entry.type === "compaction" || entry.type === "branch_summary") {
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if (totalTokens < tokenBudget * 0.9) {
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messages.unshift(message);
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totalTokens += tokens;
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}
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}
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// Stop - we've hit the budget
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break;
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}
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messages.unshift(message);
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totalTokens += tokens;
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}
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return { messages, fileOps, totalTokens };
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}
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// ============================================================================
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// Summary Generation
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// ============================================================================
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const BRANCH_SUMMARY_PROMPT = `Create a structured summary of this conversation branch for context when returning later.
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Use this EXACT format:
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## Goal
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[What was the user trying to accomplish in this branch?]
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## Constraints & Preferences
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- [Any constraints, preferences, or requirements mentioned]
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- [Or "(none)" if none were mentioned]
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## Progress
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### Done
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- [x] [Completed tasks/changes]
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### In Progress
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- [ ] [Work that was started but not finished]
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### Blocked
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- [Issues preventing progress, if any]
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## Key Decisions
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- **[Decision]**: [Brief rationale]
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## Next Steps
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1. [What should happen next to continue this work]
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Keep each section concise. Preserve exact file paths, function names, and error messages.`;
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/**
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* Generate a summary of abandoned branch entries.
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*
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* @param entries - Session entries to summarize (chronological order)
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* @param options - Generation options
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*/
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export async function generateBranchSummary(
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entries: SessionEntry[],
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options: GenerateBranchSummaryOptions,
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): Promise<BranchSummaryResult> {
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const { model, apiKey, signal, customInstructions, reserveTokens = 16384 } = options;
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// Token budget = context window minus reserved space for prompt + response
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const contextWindow = model.contextWindow || 128000;
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const tokenBudget = contextWindow - reserveTokens;
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const { messages, fileOps } = prepareBranchEntries(entries, tokenBudget);
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if (messages.length === 0) {
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return { summary: "No content to summarize" };
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}
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// Transform to LLM-compatible messages (preserves tool calls, etc.)
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const transformedMessages = convertToLlm(messages);
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// Build prompt
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const instructions = customInstructions || BRANCH_SUMMARY_PROMPT;
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// Append summarization prompt as final user message
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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: instructions }],
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timestamp: Date.now(),
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},
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];
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// Call LLM for summarization
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const response = await complete(model, { messages: summarizationMessages }, { apiKey, signal, maxTokens: 2048 });
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// Check if aborted or errored
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if (response.stopReason === "aborted") {
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return { aborted: true };
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}
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if (response.stopReason === "error") {
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return { error: response.errorMessage || "Summarization failed" };
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}
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let summary = 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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// Compute file lists
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const modified = new Set([...fileOps.edited, ...fileOps.written]);
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const readOnly = [...fileOps.read].filter((f) => !modified.has(f)).sort();
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const modifiedFiles = [...modified].sort();
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// Append file lists to summary text (for LLM context and TUI display)
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const fileSections: string[] = [];
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if (readOnly.length > 0) {
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fileSections.push(`<read-files>\n${readOnly.join("\n")}\n</read-files>`);
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}
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if (modifiedFiles.length > 0) {
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fileSections.push(`<modified-files>\n${modifiedFiles.join("\n")}\n</modified-files>`);
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}
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if (fileSections.length > 0) {
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summary += `\n\n${fileSections.join("\n\n")}`;
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}
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return {
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summary: summary || "No summary generated",
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readFiles: readOnly,
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modifiedFiles,
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};
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}
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