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It still backs the setup\n// page's \"has this bot been used yet?\" check.\n\n/** Maximum UTF-8 size of the JSON persisted for one conversation. */\nexport const MAX_STORED_JSON_SIZE = 500 * 1024;\nconst MAX_TOOL_RESULT_SIZE = 500;\nconst TRUNCATED_SUFFIX = \"… [truncated]\";\n\n/**\n * Make a bounded copy for persistence. Stored conversations are only records;\n * live context is rebuilt from Slack on every turn.\n */\nexport function trimForStorage(messages: ModelMessage[]): ModelMessage[] {\n const trimmed = capImages(structuredClone(messages));\n let trimmedToolResults = 0;\n\n for (const message of trimmed) {\n if (message.role !== \"tool\" || !Array.isArray(message.content)) continue;\n\n for (const part of message.content as any[]) {\n if (!part || part.type !== \"tool-result\") continue;\n\n const key = \"output\" in part\n ? \"output\"\n : \"result\" in part\n ? \"result\"\n : undefined;\n if (!key) continue;\n\n const value = part[key];\n let serialized: string;\n try {\n serialized = typeof value === \"string\"\n ? value\n : JSON.stringify(value) ?? String(value);\n } catch {\n serialized = String(value);\n }\n\n if (serialized.length <= MAX_TOOL_RESULT_SIZE) continue;\n\n const shortened =\n serialized.slice(\n 0,\n MAX_TOOL_RESULT_SIZE - TRUNCATED_SUFFIX.length,\n ) + TRUNCATED_SUFFIX;\n\n // AI SDK 6 uses `output`; keep its ToolResultOutput shape valid. The\n // `result` fallback handles records produced by older tool adapters.\n if (key === \"output\") {\n part.output = { type: \"text\", value: shortened };\n } else {\n part.result = shortened;\n }\n trimmedToolResults++;\n }\n }\n\n let droppedMessages = 0;\n while (\n trimmed.length > 0 &&\n storedJsonSize(trimmed) > MAX_STORED_JSON_SIZE\n ) {\n trimmed.shift();\n droppedMessages++;\n }\n\n if (trimmedToolResults > 0 || droppedMessages > 0) {\n console.warn(\n `[ConvStore] Trimmed ${trimmedToolResults} tool result(s) and dropped ${droppedMessages} leading message(s) before saving`,\n );\n }\n\n return trimmed;\n}\n\nfunction storedJsonSize(value: unknown): number {\n return new TextEncoder().encode(JSON.stringify(value)).byteLength;\n}\n\nexport async function saveConversation(\n threadTs: string,\n channel: string,\n messages: ModelMessage[],\n): Promise {\n const storedMessages = trimForStorage(messages);\n const json = JSON.stringify(storedMessages);\n await sqlite.execute({\n sql: `INSERT INTO conversations (thread_ts, channel, messages, updated_at)\n VALUES (?, ?, ?, datetime('now'))\n ON CONFLICT(thread_ts) DO UPDATE SET\n messages = excluded.messages,\n updated_at = excluded.updated_at`,\n args: [threadTs, channel, json],\n });\n console.log(\n `[ConvStore] Saved ${storedMessages.length}/${messages.length} messages for thread ${threadTs} (${storedJsonSize(storedMessages)} bytes)`,\n );\n}\n\n// ── Cap images in stored conversations ───────────────────────────────────────\n// Images are persisted in the conversation as base64 blobs — a handful can\n// balloon a thread's SQLite row from KBs to MBs. We trim all but the most\n// recent images down to a short text note before saving, so cost stays\n// proportional to the *text*, not the attachments. The latest images are kept\n// because they're the ones most likely to still be on-topic next turn.\n\n/** Keep at most this many image parts across the whole stored conversation. */\nconst MAX_IMAGES = 2;\n\nexport function capImages(\n messages: T[],\n): T[] {\n const partsWithImage = messages.flatMap((m, i) =>\n Array.isArray(m.content)\n ? m.content.map((part, j) => ({ part, i, j }))\n : []\n );\n\n // Walk \"by image\" from the END so we keep the most recent ones.\n let seen = 0;\n for (let k = partsWithImage.length - 1; k >= 0; k--) {\n const { part, i, j } = partsWithImage[k];\n if (!isImagePart(part)) continue;\n seen++;\n if (seen <= MAX_IMAGES) continue;\n\n const arr = messages[i].content as any[];\n // Replace an older image with a short text stub rather than dropping the\n // part — this keeps Anthropic's alternation/limits happy and notes that\n // something was attached. (These arrays are plain JSON, safely mutable.)\n arr[j] = {\n type: \"text\",\n text: \"[attached image — trimmed to keep this conversation small]\",\n };\n }\n\n return messages;\n}\n\n/** True for an image part in either the local or Anthropic-API content shape. */\nfunction isImagePart(part: any): boolean {\n if (!part || typeof part !== \"object\") return false;\n if (part.type === \"image\") {\n // Both shapes carry `type: \"image\"` — local: {type,image,mediaType},\n // Anthropic: {type,source:{type:\"base64\",media_type,data}}.\n return !!(part.image ?? part.source);\n }\n return false;\n}\n\n// ── Split long text into Slack-safe chunks (< 3000 chars each) ───────────────\n\nconst SLACK_BLOCK_LIMIT = 2900; // leave some margin under 3001\n\nexport function splitForSlack(text: string): string[] {\n if (text.length <= SLACK_BLOCK_LIMIT) return [text];\n\n const chunks: string[] = [];\n let remaining = text;\n\n while (remaining.length > 0) {\n if (remaining.length <= SLACK_BLOCK_LIMIT) {\n chunks.push(remaining);\n break;\n }\n\n // Try to split at a paragraph break\n let splitAt = remaining.lastIndexOf(\"\\n\\n\", SLACK_BLOCK_LIMIT);\n // Fall back to single newline\n if (splitAt < SLACK_BLOCK_LIMIT * 0.3)\n splitAt = remaining.lastIndexOf(\"\\n\", SLACK_BLOCK_LIMIT);\n // Fall back to space\n if (splitAt < SLACK_BLOCK_LIMIT * 0.3)\n splitAt = remaining.lastIndexOf(\" \", SLACK_BLOCK_LIMIT);\n // Last resort: hard cut\n if (splitAt < SLACK_BLOCK_LIMIT * 0.3) splitAt = SLACK_BLOCK_LIMIT;\n\n chunks.push(remaining.slice(0, splitAt));\n remaining = remaining.slice(splitAt).trimStart();\n }\n\n console.log(\n `[ConvStore] Split ${text.length} chars into ${chunks.length} chunks`,\n );\n return chunks;\n}\n\n// ── Count stored conversations ──────────────────────────────────────────────\n// The setup page's \"Talk to your bot\" step is marked done once the bot has\n// actually been chatted with — i.e. at least one conversation row exists.\n\nexport async function conversationCount(): Promise {\n const result = await sqlite.execute(\n \"SELECT COUNT(*) AS count FROM conversations\",\n );\n return Number(result.rows[0]?.count ?? 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