refactor(core): extract remaining inline SQL from electron adapters

- Extract getPrivateChatMemberAvatar to @openchatlab/core
- Extract getExportSessionData (meta/members/messages SQL) to @openchatlab/core
- Extract loadSessionMessages for summary generation to @openchatlab/core
- Replace inline SQL in summary buildDeps with shared core query functions
- Extract createCompressionLlmAdapter factory to @openchatlab/node-runtime
- Simplify server and electron compression adapter creation via shared factory

electron/main/ai/summary/index.ts

@@ -7,8 +7,10 @@
 
 import Database from 'better-sqlite3'
 import { completeSimple, type PiTextContent } from '@openchatlab/node-runtime'
+import { loadSessionMessages, getChatSessionSummary, saveChatSessionSummary } from '@openchatlab/core'
 import { getFastModelConfig, buildPiModel } from '../llm'
 import { getDbPath, openDatabase } from '../../database/core'
+import { wrapAsDatabaseAdapter } from '../../worker/core'
 import { aiLogger } from '../logger'
 import { t } from '../../i18n'
 import {
@@ -24,18 +26,7 @@ function buildDeps(dbSessionId: string): SummaryDeps {
       const db = openDatabase(dbSessionId, true)
       if (!db) return null
       try {
-        const sql = `
-          SELECT
-            COALESCE(mb.group_nickname, mb.account_name, mb.platform_id) as senderName,
-            m.content
-          FROM message_context mc
-          JOIN message m ON m.id = mc.message_id
-          JOIN member mb ON mb.id = m.sender_id
-          WHERE mc.session_id = ?
-          ORDER BY m.ts ASC
-          LIMIT ?
-        `
-        return db.prepare(sql).all(chatSessionId, limit) as Array<{ senderName: string; content: string | null }>
+        return loadSessionMessages(wrapAsDatabaseAdapter(db), chatSessionId, limit)
       } catch (error) {
         aiLogger.error('Summary', `Failed to get session messages: ${error}`)
         return null
@@ -46,7 +37,7 @@ function buildDeps(dbSessionId: string): SummaryDeps {
       const dbPath = getDbPath(dbSessionId)
       const db = new Database(dbPath)
       try {
-        db.prepare('UPDATE chat_session SET summary = ? WHERE id = ?').run(summary, chatSessionId)
+        saveChatSessionSummary(wrapAsDatabaseAdapter(db), chatSessionId, summary)
       } finally {
         db.close()
       }
@@ -56,10 +47,7 @@ function buildDeps(dbSessionId: string): SummaryDeps {
       const db = openDatabase(dbSessionId, true)
       if (!db) return null
       try {
-        const row = db.prepare('SELECT summary FROM chat_session WHERE id = ?').get(chatSessionId) as
-          | { summary: string | null }
-          | undefined
-        return row?.summary || null
+        return getChatSessionSummary(wrapAsDatabaseAdapter(db), chatSessionId)
       } catch {
         return null
       }

electron/main/ipc/ai.ts

@@ -20,6 +20,7 @@ import * as skillManager from '../ai/skills'
 import {
   checkAndCompress,
   manualCompress,
+  createCompressionLlmAdapter,
   type CompressionConfig,
   type CompressionLlmAdapter,
   completeSimple,
@@ -43,38 +44,15 @@ const compressionLogger = {
   error: (cat: string, msg: string, extra?: Record<string, unknown>) => aiLogger.error(cat, msg, extra),
 }
 
-function createCompressionLlmAdapter(
-  activeAIConfig: AIServiceConfig,
-  onCompressing?: () => void
-): CompressionLlmAdapter {
+function buildCompressionAdapter(activeAIConfig: AIServiceConfig, onCompressing?: () => void): CompressionLlmAdapter {
   const modelDef = findModelDefinition(activeAIConfig.provider, activeAIConfig.model || '')
-  const contextWindow = modelDef?.contextWindow ?? DEFAULT_CONTEXT_WINDOW
-  const piModel = buildPiModel(activeAIConfig)
-
-  return {
-    contextWindow,
-    compress: async (prompt: string, maxTokens: number) => {
-      onCompressing?.()
-      try {
-        const result = await completeSimple(
-          piModel,
-          {
-            systemPrompt: undefined,
-            messages: [{ role: 'user', content: [{ type: 'text', text: prompt }], timestamp: Date.now() }] as any,
-          },
-          { apiKey: activeAIConfig.apiKey, maxTokens }
-        )
-        const text = result.content
-          .filter((item): item is PiTextContent => item.type === 'text')
-          .map((item) => item.text)
-          .join('')
-        return text || null
-      } catch (error) {
-        aiLogger.warn('Compression', 'LLM compression attempt failed', { error: String(error) })
-        return null
-      }
-    },
-  }
+  return createCompressionLlmAdapter({
+    piModel: buildPiModel(activeAIConfig),
+    apiKey: activeAIConfig.apiKey,
+    contextWindow: modelDef?.contextWindow ?? DEFAULT_CONTEXT_WINDOW,
+    onCompressing,
+    onError: (error) => aiLogger.warn('Compression', 'LLM compression attempt failed', { error: String(error) }),
+  })
 }
 
 function toPiSimpleMessages(messages: Array<{ role: string; content: string }>, timestamp: number): PiMessage[] {
@@ -993,7 +971,7 @@ export function registerAIHandlers({ win }: IpcContext): void {
               context.conversationId,
               compressionConfig,
               systemPromptForCompression,
-              createCompressionLlmAdapter(activeAIConfig, () => {
+              buildCompressionAdapter(activeAIConfig, () => {
                 win.webContents.send('agent:streamChunk', {
                   requestId,
                   chunk: {
@@ -1250,7 +1228,7 @@ export function registerAIHandlers({ win }: IpcContext): void {
           conversationId,
           compressionConfig,
           systemPrompt,
-          createCompressionLlmAdapter(activeAIConfig),
+          buildCompressionAdapter(activeAIConfig),
           getConversationManager(),
           compressionLogger
         )

electron/main/merger/index.ts

@@ -181,6 +181,8 @@ export async function mergeFilesWithTempDb(
 
 import Database from 'better-sqlite3'
 import { getDbPath } from '../database/core'
+import { getExportSessionData } from '@openchatlab/core'
+import { wrapAsDatabaseAdapter } from '../worker/core'
 
 export async function exportSessionToTempFile(sessionId: string): Promise<string> {
   const dbPath = getDbPath(sessionId)
@@ -191,74 +193,26 @@ export async function exportSessionToTempFile(sessionId: string): Promise<string
   const db = new Database(dbPath, { readonly: true })
 
   try {
-    const meta = db.prepare('SELECT * FROM meta').get() as {
-      name: string
-      platform: string
-      type: string
-      group_id?: string
-      group_avatar?: string
-    }
-
-    if (!meta) {
-      throw new Error('Cannot read session meta')
-    }
-
-    const members = db.prepare('SELECT platform_id, account_name, group_nickname, avatar FROM member').all() as Array<{
-      platform_id: string
-      account_name?: string
-      group_nickname?: string
-      avatar?: string
-    }>
-
-    const messages = db
-      .prepare(
-        `SELECT
-          m.platform_id as sender,
-          msg.sender_account_name as accountName,
-          msg.sender_group_nickname as groupNickname,
-          msg.ts as timestamp,
-          msg.type,
-          msg.content
-        FROM message msg
-        JOIN member m ON msg.sender_id = m.id
-        ORDER BY msg.ts`
-      )
-      .all() as Array<{
-      sender: string
-      accountName?: string
-      groupNickname?: string
-      timestamp: number
-      type: number
-      content?: string
-    }>
+    const data = getExportSessionData(wrapAsDatabaseAdapter(db))
 
     const chatLabData: ChatLabFormat = {
       chatlab: {
         version: '0.0.1',
         exportedAt: Math.floor(Date.now() / 1000),
         generator: 'ChatLab Export',
-        description: `Exported from session: ${meta.name}`,
+        description: `Exported from session: ${data.meta.name}`,
       },
       meta: {
-        name: meta.name,
-        platform: meta.platform as ChatPlatform,
-        type: meta.type as ChatType,
-        groupId: meta.group_id,
-        groupAvatar: meta.group_avatar,
+        name: data.meta.name,
+        platform: data.meta.platform as ChatPlatform,
+        type: data.meta.type as ChatType,
+        groupId: data.meta.groupId,
+        groupAvatar: data.meta.groupAvatar,
       },
-      members: members.map((m) => ({
-        platformId: m.platform_id,
-        accountName: m.account_name || m.platform_id,
-        groupNickname: m.group_nickname || undefined,
-        avatar: m.avatar,
-      })),
-      messages: messages.map((msg) => ({
-        sender: msg.sender,
-        accountName: msg.accountName || msg.sender,
-        groupNickname: msg.groupNickname || undefined,
-        timestamp: msg.timestamp,
+      members: data.members,
+      messages: data.messages.map((msg) => ({
+        ...msg,
         type: msg.type as ChatLabMessage['type'],
-        content: msg.content ?? null,
       })),
     }
 
@@ -267,7 +221,7 @@ export async function exportSessionToTempFile(sessionId: string): Promise<string
     const tempFilePath = path.join(tempDir, `export_${sessionId}_${Date.now()}.json`)
     fs.writeFileSync(tempFilePath, JSON.stringify(chatLabData, null, 2), 'utf-8')
 
-    console.log(`[Merger] Exporting session to temp file: ${tempFilePath}, message count: ${messages.length}`)
+    console.log(`[Merger] Exporting session to temp file: ${tempFilePath}, message count: ${data.messages.length}`)
 
     return tempFilePath
   } finally {

electron/main/worker/query/sessions.ts

@@ -27,6 +27,7 @@ import {
   buildSessionInfo,
   getSummaryCount,
   getLastPlatformMessageId,
+  getPrivateChatMemberAvatar,
   type SessionOverview,
 } from '@openchatlab/core'
 import type { DatabaseAdapter } from '@openchatlab/core'
@@ -48,41 +49,6 @@ function isChatSessionDb(db: Database.Database): boolean {
   return requiredTableCount.cnt === 3
 }
 
-/**
- * 获取私聊对方成员的头像
- * 逻辑参考 private-chat/index.vue 的 otherMemberAvatar
- */
-function getPrivateChatMemberAvatar(
-  db: Database.Database,
-  sessionName: string,
-  ownerId: string | null | undefined
-): string | null {
-  const members = db
-    .prepare(
-      `SELECT
-        m.platform_id as platformId,
-        COALESCE(m.group_nickname, m.account_name, m.platform_id) as name,
-        m.avatar
-      FROM member m
-      WHERE COALESCE(m.account_name, '') != '系统消息'
-      ORDER BY (SELECT COUNT(*) FROM message WHERE sender_id = m.id) DESC`
-    )
-    .all() as Array<{ platformId: string; name: string; avatar: string | null }>
-
-  if (members.length === 0) return null
-
-  if (ownerId) {
-    const other = members.find((m) => m.platformId !== ownerId)
-    if (other?.avatar) return other.avatar
-  }
-
-  const sameName = members.find((m) => m.name === sessionName)
-  if (sameName?.avatar) return sameName.avatar
-
-  const firstWithAvatar = members.find((m) => m.avatar)
-  return firstWithAvatar?.avatar || null
-}
-
 /**
  * Resolve overview from cache (with compute-on-miss), or fall back to live SQL via core.
  */
@@ -135,7 +101,7 @@ export function getAllSessions(): any[] {
 
         let memberAvatar: string | null = null
         if (meta.type === 'private') {
-          memberAvatar = getPrivateChatMemberAvatar(db, meta.name, meta.ownerId)
+          memberAvatar = getPrivateChatMemberAvatar(asCoreDb(db), meta.name, meta.ownerId)
         }
 
         sessions.push({

packages/core/src/index.ts

@@ -39,12 +39,15 @@ export {
   getChatSessionList,
   getSessionsByTimeRange,
   getRecentChatSessions,
+  loadSessionMessages,
   getChatSessionSummary,
   saveChatSessionSummary,
   updateSessionGapThreshold,
   clearSessionIndex,
   generateSessionIndex,
   generateIncrementalSessionIndex,
+  getPrivateChatMemberAvatar,
+  getExportSessionData,
   getTimeRange,
   getAvailableYears,
   getMemberActivity,

packages/core/src/query/session-queries.ts

@@ -602,6 +602,33 @@ export function getChatSessionList(db: DatabaseAdapter): ChatSessionItem[] {
   }
 }
 
+/**
+ * Load messages for a chat session (for summary generation).
+ */
+export function loadSessionMessages(
+  db: DatabaseAdapter,
+  chatSessionId: number,
+  limit: number = 500
+): Array<{ senderName: string; content: string | null }> | null {
+  try {
+    return db
+      .prepare(
+        `SELECT
+          COALESCE(mb.group_nickname, mb.account_name, mb.platform_id) as senderName,
+          m.content
+        FROM message_context mc
+        JOIN message m ON m.id = mc.message_id
+        JOIN member mb ON mb.id = m.sender_id
+        WHERE mc.session_id = ?
+        ORDER BY m.ts ASC
+        LIMIT ?`
+      )
+      .all(chatSessionId, limit) as unknown as Array<{ senderName: string; content: string | null }>
+  } catch {
+    return null
+  }
+}
+
 /**
  * Get summary text for a single chat session.
  */
@@ -811,3 +838,131 @@ export function generateIncrementalSessionIndex(
     return newSessionCount
   })
 }
+
+// ==================== Export data ====================
+
+export interface ExportSessionData {
+  meta: {
+    name: string
+    platform: string
+    type: string
+    groupId?: string
+    groupAvatar?: string
+  }
+  members: Array<{
+    platformId: string
+    accountName: string
+    groupNickname?: string
+    avatar?: string
+  }>
+  messages: Array<{
+    sender: string
+    accountName: string
+    groupNickname?: string
+    timestamp: number
+    type: number
+    content: string | null
+  }>
+}
+
+/**
+ * Query all data needed for session export (meta + members + messages).
+ */
+export function getExportSessionData(db: DatabaseAdapter): ExportSessionData {
+  const meta = db.prepare('SELECT * FROM meta').get() as {
+    name: string
+    platform: string
+    type: string
+    group_id?: string
+    group_avatar?: string
+  }
+  if (!meta) throw new Error('Cannot read session meta')
+
+  const members = db.prepare('SELECT platform_id, account_name, group_nickname, avatar FROM member').all() as Array<{
+    platform_id: string
+    account_name?: string
+    group_nickname?: string
+    avatar?: string
+  }>
+
+  const messages = db
+    .prepare(
+      `SELECT
+        m.platform_id as sender,
+        msg.sender_account_name as accountName,
+        msg.sender_group_nickname as groupNickname,
+        msg.ts as timestamp,
+        msg.type,
+        msg.content
+      FROM message msg
+      JOIN member m ON msg.sender_id = m.id
+      ORDER BY msg.ts`
+    )
+    .all() as unknown as Array<{
+    sender: string
+    accountName?: string
+    groupNickname?: string
+    timestamp: number
+    type: number
+    content?: string
+  }>
+
+  return {
+    meta: {
+      name: meta.name,
+      platform: meta.platform,
+      type: meta.type,
+      groupId: meta.group_id,
+      groupAvatar: meta.group_avatar,
+    },
+    members: members.map((m) => ({
+      platformId: m.platform_id,
+      accountName: m.account_name || m.platform_id,
+      groupNickname: m.group_nickname || undefined,
+      avatar: m.avatar,
+    })),
+    messages: messages.map((msg) => ({
+      sender: msg.sender,
+      accountName: msg.accountName || msg.sender,
+      groupNickname: msg.groupNickname || undefined,
+      timestamp: msg.timestamp,
+      type: msg.type,
+      content: msg.content ?? null,
+    })),
+  }
+}
+
+/**
+ * Get private chat partner's avatar.
+ * Finds the "other" member (not the owner) in a private chat, falling back to name match or first with avatar.
+ */
+export function getPrivateChatMemberAvatar(
+  db: DatabaseAdapter,
+  sessionName: string,
+  ownerId: string | null | undefined
+): string | null {
+  const members = db
+    .prepare(
+      `SELECT
+        m.platform_id as platformId,
+        COALESCE(m.group_nickname, m.account_name, m.platform_id) as name,
+        m.avatar
+      FROM member m
+      WHERE COALESCE(m.account_name, '') != '系统消息'
+      ORDER BY (SELECT COUNT(*) FROM message WHERE sender_id = m.id) DESC`
+    )
+    .all() as unknown as Array<{ platformId: string; name: string; avatar: string | null }>
+
+  if (members.length === 0) return null
+
+  if (ownerId) {
+    const other = members.find((m) => m.platformId !== ownerId)
+    if (other?.avatar) return other.avatar
+  }
+
+  const sameName = members.find((m) => m.name === sessionName)
+  if (sameName?.avatar) return sameName.avatar
+
+  const firstWithAvatar = members.find((m) => m.avatar)
+  return firstWithAvatar?.avatar || null
+}

packages/node-runtime/src/ai/compression/adapter-factory.ts

@@ -0,0 +1,46 @@
+import { completeSimple, type Model as PiModel, type TextContent as PiTextContent } from '@mariozechner/pi-ai'
+import type { CompressionLlmAdapter } from './types'
+
+export interface CreateCompressionLlmAdapterOptions {
+  piModel: PiModel
+  apiKey: string
+  contextWindow?: number
+  onCompressing?: () => void
+  onError?: (error: unknown) => void
+}
+
+const DEFAULT_CONTEXT_WINDOW = 128000
+
+/**
+ * Create a CompressionLlmAdapter from a PiModel and API key.
+ * Shared factory used by both Electron and Server.
+ */
+export function createCompressionLlmAdapter(options: CreateCompressionLlmAdapterOptions): CompressionLlmAdapter {
+  const { piModel, apiKey, onCompressing, onError } = options
+  const contextWindow = options.contextWindow ?? piModel.contextWindow ?? DEFAULT_CONTEXT_WINDOW
+
+  return {
+    contextWindow,
+    compress: async (prompt: string, maxTokens: number) => {
+      onCompressing?.()
+      try {
+        const result = await completeSimple(
+          piModel,
+          {
+            systemPrompt: undefined,
+            messages: [{ role: 'user', content: [{ type: 'text', text: prompt }], timestamp: Date.now() }] as any,
+          },
+          { apiKey, maxTokens }
+        )
+        const text = result.content
+          .filter((item): item is PiTextContent => item.type === 'text')
+          .map((item) => item.text)
+          .join('')
+        return text || null
+      } catch (error) {
+        onError?.(error)
+        return null
+      }
+    },
+  }
+}

packages/node-runtime/src/ai/compression/index.ts

@@ -4,3 +4,4 @@
 
 export type { CompressionConfig, CompressionResult, CompressionLogger, CompressionLlmAdapter } from './types'
 export { checkAndCompress, manualCompress } from './compressor'
+export { createCompressionLlmAdapter, type CreateCompressionLlmAdapterOptions } from './adapter-factory'

packages/node-runtime/src/ai/index.ts

@@ -55,7 +55,8 @@ export type { ActivateSkillToolOptions, ActivateSkillTool, ActivateSkillToolResu
 
 // Compression
 export type { CompressionConfig, CompressionResult, CompressionLogger, CompressionLlmAdapter } from './compression'
-export { checkAndCompress, manualCompress } from './compression'
+export { checkAndCompress, manualCompress, createCompressionLlmAdapter } from './compression'
+export type { CreateCompressionLlmAdapterOptions } from './compression'
 
 // Preprocessor
 export type {

packages/node-runtime/src/index.ts

@@ -96,7 +96,8 @@ export type {
 
 // Compression
 export type { CompressionConfig, CompressionResult, CompressionLogger, CompressionLlmAdapter } from './ai'
-export { checkAndCompress, manualCompress } from './ai'
+export { checkAndCompress, manualCompress, createCompressionLlmAdapter } from './ai'
+export type { CreateCompressionLlmAdapterOptions } from './ai'
 
 // SkillManager
 export { SkillManager } from './ai'

packages/server/src/ai/agent.ts

@@ -7,10 +7,10 @@
 
 import {
   runAgentCore,
-  completeSimple,
   checkAndCompress,
   buildSystemPrompt,
   createAiTranslate,
+  createCompressionLlmAdapter,
   AgentEventHandler,
   formatAIError,
   type AgentStreamChunk,
@@ -18,8 +18,6 @@ import {
   type SimpleHistoryMessage,
   type AIConversationManager,
   type CompressionConfig,
-  type CompressionLlmAdapter,
-  type PiTextContent,
   type AgentTool,
   type DataSnapshot,
   type OwnerInfo,
@@ -103,29 +101,11 @@ export async function runServerAgent(options: RunAgentOptions): Promise<void> {
   })
 
   if (compressionConfig?.enabled) {
-    const llmAdapter: CompressionLlmAdapter = {
-      contextWindow: piModel.contextWindow ?? 128000,
-      compress: async (prompt: string, maxTokens: number) => {
-        handler.emitStatus('compressing', [])
-        try {
-          const result = await completeSimple(
-            piModel,
-            {
-              systemPrompt: undefined,
-              messages: [{ role: 'user', content: [{ type: 'text', text: prompt }], timestamp: Date.now() }] as any,
-            },
-            { apiKey: llmConfig.apiKey, maxTokens }
-          )
-          const text = result.content
-            .filter((item): item is PiTextContent => item.type === 'text')
-            .map((item) => item.text)
-            .join('')
-          return text || null
-        } catch {
-          return null
-        }
-      },
-    }
+    const llmAdapter = createCompressionLlmAdapter({
+      piModel,
+      apiKey: llmConfig.apiKey,
+      onCompressing: () => handler.emitStatus('compressing', []),
+    })
     const compressionResult = await checkAndCompress(
       conversationId,
       compressionConfig,