fix: memory retrieval bug

models/memory/database.js

@@ -114,6 +114,22 @@ function resetSimpleState (overrides = {}) {
   }
 }
 
+function sanitiseRawFtsInput (input) {
+  if (!input) {
+    return ''
+  }
+  const trimmed = String(input).trim()
+  if (!trimmed) {
+    return ''
+  }
+  const replaced = trimmed
+    .replace(/["'`]+/g, ' ')
+    .replace(/\u3000/g, ' ')
+    .replace(/[^\p{L}\p{N}\u4E00-\u9FFF\u3040-\u30FF\uAC00-\uD7AF\u1100-\u11FF\s]+/gu, ' ')
+  const collapsed = replaced.replace(/\s+/g, ' ').trim()
+  return collapsed || trimmed
+}
+
 function isSimpleLibraryFile (filename) {
   return /(^libsimple.*\.(so|dylib|dll)$)|(^simple\.(so|dylib|dll)$)/i.test(filename)
 }
@@ -644,6 +660,16 @@ export function getSimpleExtensionState () {
   return { ...simpleExtensionState }
 }
 
+export function sanitiseFtsQueryInput (query, ftsConfig) {
+  if (!query) {
+    return ''
+  }
+  if (ftsConfig?.matchQuery) {
+    return String(query).trim()
+  }
+  return sanitiseRawFtsInput(query)
+}
+
 export function getMemoryDatabase () {
   if (dbInstance) {
     return dbInstance

models/memory/extractor.js

@@ -1,4 +1,4 @@
-import { SendMessageOption } from 'chaite'
+import { SendMessageOption, Chaite } from 'chaite'
 import ChatGPTConfig from '../../config/config.js'
 import { getClientForModel } from '../chaite/vectorizer.js'
 
@@ -43,9 +43,40 @@ function formatEntry (entry) {
   return str.length > limit ? str.slice(0, limit) + '…' : str
 }
 
-function resolveGroupExtractionPrompts () {
+async function resolvePresetSendMessageOption (presetId, scope) {
+  if (!presetId) {
+    return null
+  }
+  try {
+    const chaite = Chaite.getInstance?.()
+    if (!chaite) {
+      logger.warn(`[Memory] ${scope} extraction preset ${presetId} configured but Chaite is not initialized`)
+      return null
+    }
+    const presetManager = chaite.getChatPresetManager?.()
+    if (!presetManager) {
+      logger.warn(`[Memory] ${scope} extraction preset ${presetId} configured but preset manager unavailable`)
+      return null
+    }
+    const preset = await presetManager.getInstance(presetId)
+    if (!preset) {
+      logger.warn(`[Memory] ${scope} extraction preset ${presetId} not found`)
+      return null
+    }
+    logger.debug(`[Memory] using ${scope} extraction preset ${presetId}`)
+    return {
+      preset,
+      sendMessageOption: JSON.parse(JSON.stringify(preset.sendMessageOption || {}))
+    }
+  } catch (err) {
+    logger.error(`[Memory] failed to load ${scope} extraction preset ${presetId}:`, err)
+    return null
+  }
+}
+
+function resolveGroupExtractionPrompts (presetSendMessageOption) {
   const config = ChatGPTConfig.memory?.group || {}
-  const system = config.extractionSystemPrompt || `You are a knowledge extraction assistant that specialises in summarising long-term facts from group chat transcripts.
+  const system = config.extractionSystemPrompt || presetSendMessageOption?.systemOverride || `You are a knowledge extraction assistant that specialises in summarising long-term facts from group chat transcripts.
 Read the provided conversation and identify statements that should be stored as long-term knowledge for the group.
 Return a JSON array. Each element must contain:
 {
@@ -79,9 +110,9 @@ function buildExistingMemorySection (existingMemories = []) {
   return `以下是关于用户的已知长期记忆，请在提取新记忆时参考，避免重复已有事实，并在信息变更时更新描述：\n${lines.join('\n')}`
 }
 
-function resolveUserExtractionPrompts (existingMemories = []) {
+function resolveUserExtractionPrompts (existingMemories = [], presetSendMessageOption) {
   const config = ChatGPTConfig.memory?.user || {}
-  const systemTemplate = config.extractionSystemPrompt || `You are an assistant that extracts long-term personal preferences or persona details about a user.
+  const systemTemplate = config.extractionSystemPrompt || presetSendMessageOption?.systemOverride || `You are an assistant that extracts long-term personal preferences or persona details about a user.
 Given a conversation snippet between the user and the bot, identify durable information such as preferences, nicknames, roles, speaking style, habits, or other facts that remain valid over time.
 Return a JSON array of **strings**, and nothing else, without any other characters including \`\`\` or \`\`\`json. Each string must be a short sentence (in the same language as the conversation) describing one piece of long-term memory. Do not include keys, JSON objects, or additional metadata. Ignore temporary topics or uncertain information.`
   const userTemplate = config.extractionUserPrompt || `下面是用户与机器人的对话，请根据系统提示提取可长期记忆的个人信息。
@@ -103,8 +134,16 @@ function buildUserPrompt (messages, template) {
   return template.replace('${messages}', body)
 }
 
-async function callModel ({ prompt, systemPrompt, model, maxToken = 4096, temperature = 0.2 }) {
+async function callModel ({ prompt, systemPrompt, model, maxToken = 4096, temperature = 0.2, sendMessageOption }) {
-  const { client } = await getClientForModel(model)
+  const options = sendMessageOption
+    ? JSON.parse(JSON.stringify(sendMessageOption))
+    : {}
+  options.model = model || options.model
+  if (!options.model) {
+    throw new Error('No model available for memory extraction call')
+  }
+  const resolvedModel = options.model
+  const { client } = await getClientForModel(resolvedModel)
   const response = await client.sendMessage({
     role: 'user',
     content: [
@@ -114,10 +153,11 @@ async function callModel ({ prompt, systemPrompt, model, maxToken = 4096, temper
       }
     ]
   }, SendMessageOption.create({
-    model,
+    ...options,
-    // temperature,
+    model: options.model,
-    maxToken,
+    temperature: options.temperature ?? temperature,
-    systemOverride: systemPrompt,
+    maxToken: options.maxToken ?? maxToken,
+    systemOverride: systemPrompt ?? options.systemOverride,
     disableHistoryRead: true,
     disableHistorySave: true,
     stream: false
@@ -125,44 +165,54 @@ async function callModel ({ prompt, systemPrompt, model, maxToken = 4096, temper
   return collectTextFromResponse(response)
 }
 
-function resolveGroupExtractionModel () {
+function resolveGroupExtractionModel (presetSendMessageOption) {
   const config = ChatGPTConfig.memory?.group
   if (config?.extractionModel) {
     return config.extractionModel
   }
+  if (presetSendMessageOption?.model) {
+    return presetSendMessageOption.model
+  }
   if (ChatGPTConfig.llm?.defaultModel) {
     return ChatGPTConfig.llm.defaultModel
   }
-  return ChatGPTConfig.llm?.embeddingModel || ''
+  return ''
 }
 
-function resolveUserExtractionModel () {
+function resolveUserExtractionModel (presetSendMessageOption) {
   const config = ChatGPTConfig.memory?.user
   if (config?.extractionModel) {
     return config.extractionModel
   }
+  if (presetSendMessageOption?.model) {
+    return presetSendMessageOption.model
+  }
   if (ChatGPTConfig.llm?.defaultModel) {
     return ChatGPTConfig.llm.defaultModel
   }
-  return ChatGPTConfig.llm?.embeddingModel || ''
+  return ''
 }
 
 export async function extractGroupFacts (messages) {
   if (!messages || messages.length === 0) {
     return []
   }
-  const model = resolveGroupExtractionModel()
+  const groupConfig = ChatGPTConfig.memory?.group || {}
+  const presetInfo = await resolvePresetSendMessageOption(groupConfig.extractionPresetId, 'group')
+  const presetOptions = presetInfo?.sendMessageOption
+  const model = resolveGroupExtractionModel(presetOptions)
   if (!model) {
     logger.warn('No model configured for group memory extraction')
     return []
   }
   try {
-    const prompts = resolveGroupExtractionPrompts()
+    const prompts = resolveGroupExtractionPrompts(presetOptions)
-    logger.debug(`[Memory] start group fact extraction, messages=${messages.length}, model=${model}`)
+    logger.debug(`[Memory] start group fact extraction, messages=${messages.length}, model=${model}${presetInfo?.preset ? `, preset=${presetInfo.preset.id}` : ''}`)
     const text = await callModel({
       prompt: buildGroupUserPrompt(messages, prompts.userTemplate),
       systemPrompt: prompts.system,
-      model
+      model,
+      sendMessageOption: presetOptions
     })
     const parsed = parseJSON(text)
     if (Array.isArray(parsed)) {
@@ -184,18 +234,22 @@ export async function extractUserMemories (messages, existingMemories = []) {
   if (!messages || messages.length === 0) {
     return []
   }
-  const model = resolveUserExtractionModel()
+  const userConfig = ChatGPTConfig.memory?.user || {}
+  const presetInfo = await resolvePresetSendMessageOption(userConfig.extractionPresetId, 'user')
+  const presetOptions = presetInfo?.sendMessageOption
+  const model = resolveUserExtractionModel(presetOptions)
   if (!model) {
     logger.warn('No model configured for user memory extraction')
     return []
   }
   try {
-    const prompts = resolveUserExtractionPrompts(existingMemories)
+    const prompts = resolveUserExtractionPrompts(existingMemories, presetOptions)
-    logger.debug(`[Memory] start user memory extraction, snippets=${messages.length}, existing=${existingMemories.length}, model=${model}`)
+    logger.debug(`[Memory] start user memory extraction, snippets=${messages.length}, existing=${existingMemories.length}, model=${model}${presetInfo?.preset ? `, preset=${presetInfo.preset.id}` : ''}`)
     const text = await callModel({
       prompt: buildUserPrompt(messages, prompts.userTemplate),
       systemPrompt: prompts.system,
-      model
+      model,
+      sendMessageOption: presetOptions
     })
     const parsed = parseJSON(text)
     if (Array.isArray(parsed)) {

models/memory/groupMemoryStore.js

@@ -1,4 +1,4 @@
-import { getMemoryDatabase, getVectorDimension, getGroupMemoryFtsConfig, resetVectorTableDimension } from './database.js'
+import { getMemoryDatabase, getVectorDimension, getGroupMemoryFtsConfig, resetVectorTableDimension, sanitiseFtsQueryInput } from './database.js'
 import ChatGPTConfig from '../../config/config.js'
 import { embedTexts } from '../chaite/vectorizer.js'
 
@@ -342,37 +342,42 @@ export class GroupMemoryStore {
     if (!queryText || !queryText.trim()) {
       return []
     }
-    const trimmedQuery = queryText.trim()
+    const originalQuery = queryText.trim()
     const ftsConfig = getGroupMemoryFtsConfig()
-    const matchExpression = ftsConfig.matchQuery ? `${ftsConfig.matchQuery}(?)` : '?'
+    const matchQueryParam = sanitiseFtsQueryInput(originalQuery, ftsConfig)
     const results = []
     const seen = new Set()
-    try {
+    if (matchQueryParam) {
-      const rows = this.db.prepare(`
+      const matchExpression = ftsConfig.matchQuery ? `${ftsConfig.matchQuery}(?)` : '?'
-        SELECT gf.*, bm25(group_facts_fts) AS bm25_score
+      try {
-        FROM group_facts_fts
+        const rows = this.db.prepare(`
-        JOIN group_facts gf ON gf.id = group_facts_fts.rowid
+          SELECT gf.*, bm25(group_facts_fts) AS bm25_score
-        WHERE gf.group_id = ?
+          FROM group_facts_fts
-          AND group_facts_fts MATCH ${matchExpression}
+          JOIN group_facts gf ON gf.id = group_facts_fts.rowid
-        ORDER BY bm25_score ASC
+          WHERE gf.group_id = ?
-        LIMIT ?
+            AND group_facts_fts MATCH ${matchExpression}
-      `).all(groupId, trimmedQuery, limit)
+          ORDER BY bm25_score ASC
-      for (const row of rows) {
+          LIMIT ?
-        const bm25Threshold = this.bm25Threshold
+        `).all(groupId, matchQueryParam, limit)
-        if (bm25Threshold) {
+        for (const row of rows) {
-          const score = Number(row?.bm25_score)
+          const bm25Threshold = this.bm25Threshold
-          if (!Number.isFinite(score) || score > bm25Threshold) {
+          if (bm25Threshold) {
-            continue
+            const score = Number(row?.bm25_score)
+            if (!Number.isFinite(score) || score > bm25Threshold) {
+              continue
+            }
+            row.bm25_score = score
+          }
+          if (row && !seen.has(row.id)) {
+            results.push(row)
+            seen.add(row.id)
           }
-          row.bm25_score = score
-        }
-        if (row && !seen.has(row.id)) {
-          results.push(row)
-          seen.add(row.id)
         }
+      } catch (err) {
+        logger.warn('Text search failed for group memory:', err)
       }
-    } catch (err) {
+    } else {
-      logger.warn('Text search failed for group memory:', err)
+      logger.debug('[Memory] group memory text search skipped MATCH due to empty query after sanitisation')
     }
 
     if (results.length < limit) {
@@ -384,7 +389,7 @@ export class GroupMemoryStore {
             AND instr(fact, ?) > 0
           ORDER BY importance DESC, created_at DESC
           LIMIT ?
-        `).all(groupId, trimmedQuery, Math.max(limit * 2, limit))
+        `).all(groupId, originalQuery, Math.max(limit * 2, limit))
         for (const row of likeRows) {
           if (row && !seen.has(row.id)) {
             results.push(row)

models/memory/userMemoryStore.js

@@ -1,4 +1,4 @@
-import { getMemoryDatabase, getUserMemoryFtsConfig } from './database.js'
+import { getMemoryDatabase, getUserMemoryFtsConfig, sanitiseFtsQueryInput } from './database.js'
 import { md5 } from '../../utils/common.js'
 
 function normaliseId (value) {
@@ -213,42 +213,46 @@ export class UserMemoryStore {
     const normUserId = normaliseId(userId)
     const normGroupId = normaliseId(groupId)
     const filteredExclude = (excludeIds || []).filter(Boolean)
-    const trimmedQuery = queryText.trim()
+    const originalQuery = queryText.trim()
     const ftsConfig = getUserMemoryFtsConfig()
-    const matchExpression = ftsConfig.matchQuery ? `${ftsConfig.matchQuery}(?)` : '?'
+    const matchQueryParam = sanitiseFtsQueryInput(originalQuery, ftsConfig)
-    const params = [normUserId]
-    let query = `
-      SELECT um.*, bm25(user_memory_fts) AS bm25_score
-      FROM user_memory_fts
-      JOIN user_memory um ON um.id = user_memory_fts.rowid
-      WHERE um.user_id = ?
-        AND user_memory_fts MATCH ${matchExpression}
-    `
-    params.push(trimmedQuery)
-    if (normGroupId) {
-      query += ' AND (um.group_id = ? OR um.group_id IS NULL)'
-      params.push(normGroupId)
-    }
-    if (filteredExclude.length) {
-      query += ` AND um.id NOT IN (${filteredExclude.map(() => '?').join(',')})`
-      params.push(...filteredExclude)
-    }
-    query += `
-      ORDER BY bm25_score ASC, um.updated_at DESC
-      LIMIT ?
-    `
-    params.push(limit)
     const results = []
     const seen = new Set(filteredExclude)
-    try {
+    if (matchQueryParam) {
-      const ftsRows = this.db.prepare(query).all(...params)
+      const matchExpression = ftsConfig.matchQuery ? `${ftsConfig.matchQuery}(?)` : '?'
-      appendRows(results, ftsRows, seen)
+      const params = [normUserId, matchQueryParam]
-    } catch (err) {
+      let query = `
-      logger?.warn?.('User memory text search failed:', err)
+        SELECT um.*, bm25(user_memory_fts) AS bm25_score
+        FROM user_memory_fts
+        JOIN user_memory um ON um.id = user_memory_fts.rowid
+        WHERE um.user_id = ?
+          AND user_memory_fts MATCH ${matchExpression}
+      `
+      if (normGroupId) {
+        query += ' AND (um.group_id = ? OR um.group_id IS NULL)'
+        params.push(normGroupId)
+      }
+      if (filteredExclude.length) {
+        query += ` AND um.id NOT IN (${filteredExclude.map(() => '?').join(',')})`
+        params.push(...filteredExclude)
+      }
+      query += `
+        ORDER BY bm25_score ASC, um.updated_at DESC
+        LIMIT ?
+      `
+      params.push(limit)
+      try {
+        const ftsRows = this.db.prepare(query).all(...params)
+        appendRows(results, ftsRows, seen)
+      } catch (err) {
+        logger?.warn?.('User memory text search failed:', err)
+      }
+    } else {
+      logger?.debug?.('[Memory] user memory text search skipped MATCH due to empty query after sanitisation')
     }
 
     if (results.length < limit) {
-      const likeParams = [normUserId, trimmedQuery]
+      const likeParams = [normUserId, originalQuery]
       let likeQuery = `
         SELECT um.*
         FROM user_memory um