"use strict";Object.defineProperty(exports, "__esModule", { value: true });exports.SUMMARIZATION_SYSTEM_PROMPT = void 0;exports.computeFileLists = computeFileLists;exports.createFileOps = createFileOps;exports.extractFileOpsFromMessage = extractFileOpsFromMessage;exports.formatFileOperations = formatFileOperations;exports.serializeConversation = serializeConversation; /**
 * Shared utilities for compaction and branch summarization.
 */
function createFileOps() {
  return {
    read: new Set(),
    written: new Set(),
    edited: new Set()
  };
}
/**
 * Extract file operations from tool calls in an assistant message.
 */
function extractFileOpsFromMessage(message, fileOps) {
  if (message.role !== "assistant")
  return;
  if (!("content" in message) || !Array.isArray(message.content))
  return;
  for (const block of message.content) {
    if (typeof block !== "object" || block === null)
    continue;
    if (!("type" in block) || block.type !== "toolCall")
    continue;
    if (!("arguments" in block) || !("name" in block))
    continue;
    const args = block.arguments;
    if (!args)
    continue;
    const path = typeof args.path === "string" ? args.path : undefined;
    if (!path)
    continue;
    switch (block.name) {
      case "read":
        fileOps.read.add(path);
        break;
      case "write":
        fileOps.written.add(path);
        break;
      case "edit":
        fileOps.edited.add(path);
        break;
    }
  }
}
/**
 * Compute final file lists from file operations.
 * Returns readFiles (files only read, not modified) and modifiedFiles.
 */
function computeFileLists(fileOps) {
  const modified = new Set([...fileOps.edited, ...fileOps.written]);
  const readOnly = [...fileOps.read].filter((f) => !modified.has(f)).sort();
  const modifiedFiles = [...modified].sort();
  return { readFiles: readOnly, modifiedFiles };
}
/**
 * Format file operations as XML tags for summary.
 */
function formatFileOperations(readFiles, modifiedFiles) {
  const sections = [];
  if (readFiles.length > 0) {
    sections.push(`<read-files>\n${readFiles.join("\n")}\n</read-files>`);
  }
  if (modifiedFiles.length > 0) {
    sections.push(`<modified-files>\n${modifiedFiles.join("\n")}\n</modified-files>`);
  }
  if (sections.length === 0)
  return "";
  return `\n\n${sections.join("\n\n")}`;
}
// ============================================================================
// Message Serialization
// ============================================================================
/** Maximum characters for a tool result in serialized summaries. */
const TOOL_RESULT_MAX_CHARS = 2000;
/**
 * Truncate text to a maximum character length for summarization.
 * Keeps the beginning and appends a truncation marker.
 */
function truncateForSummary(text, maxChars) {
  if (text.length <= maxChars)
  return text;
  const truncatedChars = text.length - maxChars;
  return `${text.slice(0, maxChars)}\n\n[... ${truncatedChars} more characters truncated]`;
}
/**
 * Serialize LLM messages to text for summarization.
 * This prevents the model from treating it as a conversation to continue.
 * Call convertToLlm() first to handle custom message types.
 *
 * Tool results are truncated to keep the summarization request within
 * reasonable token budgets. Full content is not needed for summarization.
 */
function serializeConversation(messages) {
  const parts = [];
  for (const msg of messages) {
    if (msg.role === "user") {
      const content = typeof msg.content === "string" ?
      msg.content :
      msg.content.
      filter((c) => c.type === "text").
      map((c) => c.text).
      join("");
      if (content)
      parts.push(`[User]: ${content}`);
    } else
    if (msg.role === "assistant") {
      const textParts = [];
      const thinkingParts = [];
      const toolCalls = [];
      for (const block of msg.content) {
        if (block.type === "text") {
          textParts.push(block.text);
        } else
        if (block.type === "thinking") {
          thinkingParts.push(block.thinking);
        } else
        if (block.type === "toolCall") {
          const args = block.arguments;
          const argsStr = Object.entries(args).
          map(([k, v]) => `${k}=${JSON.stringify(v)}`).
          join(", ");
          toolCalls.push(`${block.name}(${argsStr})`);
        }
      }
      if (thinkingParts.length > 0) {
        parts.push(`[Assistant thinking]: ${thinkingParts.join("\n")}`);
      }
      if (textParts.length > 0) {
        parts.push(`[Assistant]: ${textParts.join("\n")}`);
      }
      if (toolCalls.length > 0) {
        parts.push(`[Assistant tool calls]: ${toolCalls.join("; ")}`);
      }
    } else
    if (msg.role === "toolResult") {
      const content = msg.content.
      filter((c) => c.type === "text").
      map((c) => c.text).
      join("");
      if (content) {
        parts.push(`[Tool result]: ${truncateForSummary(content, TOOL_RESULT_MAX_CHARS)}`);
      }
    }
  }
  return parts.join("\n\n");
}
// ============================================================================
// Summarization System Prompt
// ============================================================================
const SUMMARIZATION_SYSTEM_PROMPT = exports.SUMMARIZATION_SYSTEM_PROMPT = `You are a context summarization assistant. Your task is to read a conversation between a user and an AI coding assistant, then produce a structured summary following the exact format specified.

Do NOT continue the conversation. Do NOT respond to any questions in the conversation. ONLY output the structured summary.`; /* v9-fc874a30f36fe2fd */