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{ sqlite } from \"https://esm.town/v/stevekrouse/sqlite\";\nimport { tables } from \"../database/schema.ts\";\nimport type { Memory, UserProfile, Atom } from \"../../shared/types.ts\";\nimport { MiniAtomSpace } from \"./atomspace.ts\";\n\nexport class MemorySystem {\n private atomSpace: MiniAtomSpace;\n\n constructor(atomSpace: MiniAtomSpace) {\n this.atomSpace = atomSpace;\n }\n\n // Create a new memory and associated atoms\n async formMemory(\n userId: string,\n content: string,\n type: Memory['type'],\n importance: number,\n tags: string[] = []\n ): Promise {\n const memoryId = crypto.randomUUID();\n const now = new Date().toISOString();\n\n // Extract key concepts from content to create atoms\n const concepts = this.extractConcepts(content);\n const atomIds: string[] = [];\n\n // Create atoms for each concept\n for (const concept of concepts) {\n const existingAtoms = await this.atomSpace.searchByName(concept);\n \n if (existingAtoms.length > 0) {\n // Reinforce existing atom\n const atom = existingAtoms[0];\n const newSTI = Math.min(100, atom.sti + 20);\n const newLTI = Math.min(100, atom.lti + Math.floor(importance * 10));\n await this.atomSpace.updateSTI(atom.id, newSTI);\n await this.atomSpace.updateLTI(atom.id, newLTI);\n atomIds.push(atom.id);\n } else {\n // Create new atom\n const atom = await this.atomSpace.createAtom({\n type: 'concept',\n name: concept,\n sti: Math.floor(importance * 50) + 30,\n lti: Math.floor(importance * 20),\n confidence: 0.8,\n strength: importance,\n tags: [userId, ...tags]\n });\n atomIds.push(atom.id);\n }\n }\n\n // Create memory record\n const memory: Memory = {\n id: memoryId,\n userId,\n content,\n type,\n atoms: atomIds,\n importance,\n created: new Date(now),\n lastReinforced: new Date(now),\n tags\n };\n\n await sqlite.execute(\n `INSERT INTO ${tables.MEMORIES_TABLE} \n (id, user_id, content, type, atoms, importance, created, last_reinforced, tags)\n VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)`,\n [\n memory.id,\n memory.userId,\n memory.content,\n memory.type,\n JSON.stringify(memory.atoms),\n memory.importance,\n now,\n now,\n JSON.stringify(memory.tags)\n ]\n );\n\n // Create links between memory atoms\n await this.createMemoryLinks(atomIds, memoryId);\n\n return memory;\n }\n\n // Extract key concepts from text (simplified NLP)\n private extractConcepts(text: string): string[] {\n const words = text.toLowerCase()\n .replace(/[^\\w\\s]/g, ' ')\n .split(/\\s+/)\n .filter(word => word.length > 2);\n\n // Filter out common words and extract meaningful concepts\n const stopWords = new Set(['the', 'and', 'but', 'for', 'are', 'with', 'this', 'that', 'you', 'not', 'can', 'have', 'will', 'was', 'been', 'said', 'like', 'very', 'much', 'more', 'some', 'what', 'when', 'where', 'how', 'why', 'who']);\n \n const concepts = words.filter(word => !stopWords.has(word));\n \n // Look for compound concepts (simple bigrams)\n const bigrams: string[] = [];\n for (let i = 0; i < words.length - 1; i++) {\n if (!stopWords.has(words[i]) && !stopWords.has(words[i + 1])) {\n bigrams.push(`${words[i]} ${words[i + 1]}`);\n }\n }\n\n return [...new Set([...concepts, ...bigrams])].slice(0, 8); // Limit concepts\n }\n\n // Create links between atoms in a memory\n private async createMemoryLinks(atomIds: string[], memoryId: string): Promise {\n if (atomIds.length < 2) return;\n\n // Create similarity links between concepts in the same memory\n for (let i = 0; i < atomIds.length - 1; i++) {\n for (let j = i + 1; j < atomIds.length; j++) {\n await this.atomSpace.createLink({\n type: 'link',\n linkType: 'similarity',\n outgoing: [atomIds[i], atomIds[j]],\n sti: 30,\n lti: 20,\n confidence: 0.7,\n strength: 0.6,\n name: `memory_link_${memoryId}`,\n tags: ['memory_link']\n });\n }\n }\n }\n\n // Retrieve memories for a user\n async getUserMemories(userId: string, limit: number = 10): Promise {\n const result = await sqlite.execute(\n `SELECT * FROM ${tables.MEMORIES_TABLE} \n WHERE user_id = ? \n ORDER BY importance DESC, last_reinforced DESC \n LIMIT ?`,\n [userId, limit]\n );\n\n if (!result || !Array.isArray(result)) {\n return [];\n }\n\n return result.map(row => this.rowToMemory(row));\n }\n\n // Find memories related to concepts\n async findRelatedMemories(concepts: string[], userId?: string): Promise {\n // Simplified approach - just search by content for now\n if (concepts.length === 0) return [];\n \n let sql = `\n SELECT * FROM ${tables.MEMORIES_TABLE} \n WHERE (${concepts.map(() => 'content LIKE ?').join(' OR ')})\n `;\n \n const params = concepts.map(c => `%${c}%`);\n\n if (userId) {\n sql += ` AND user_id = ?`;\n params.push(userId);\n }\n\n sql += ` ORDER BY importance DESC, last_reinforced DESC LIMIT 5`;\n\n try {\n const result = await sqlite.execute(sql, params);\n \n if (!result || !Array.isArray(result)) {\n return [];\n }\n \n return result.map(row => this.rowToMemory(row));\n } catch (error) {\n console.error(\"Error finding related memories:\", error);\n return [];\n }\n }\n\n // Reinforce a memory (increase importance and update LTI of related atoms)\n async reinforceMemory(memoryId: string, reinforcementStrength: number = 0.1): Promise {\n const memory = await this.getMemory(memoryId);\n if (!memory) return;\n\n const newImportance = Math.min(1.0, memory.importance + reinforcementStrength);\n const now = new Date().toISOString();\n\n await sqlite.execute(\n `UPDATE ${tables.MEMORIES_TABLE} \n SET importance = ?, last_reinforced = ? \n WHERE id = ?`,\n [newImportance, now, memoryId]\n );\n\n // Boost LTI of related atoms\n for (const atomId of memory.atoms) {\n const atom = await this.atomSpace.getAtom(atomId);\n if (atom) {\n const ltiBoost = Math.floor(reinforcementStrength * 20);\n await this.atomSpace.updateLTI(atomId, Math.min(100, atom.lti + ltiBoost));\n }\n }\n }\n\n // Get or create user profile\n async getUserProfile(userId: string): Promise {\n const result = await sqlite.execute(\n `SELECT * FROM ${tables.USERS_TABLE} WHERE id = ?`,\n [userId]\n );\n\n if (result && Array.isArray(result) && result.length > 0) {\n const row = result[0];\n const memories = await this.getUserMemories(userId, 5);\n \n return {\n id: row.id,\n name: row.name,\n interests: JSON.parse(row.interests || '[]'),\n memories,\n interactionCount: row.interaction_count,\n lastSeen: new Date(row.last_seen),\n relationship: row.relationship\n };\n } else {\n // Create new user profile\n const now = new Date().toISOString();\n await sqlite.execute(\n `INSERT INTO ${tables.USERS_TABLE} \n (id, interaction_count, last_seen, relationship, created)\n VALUES (?, ?, ?, ?, ?)`,\n [userId, 0, now, 'new', now]\n );\n\n return {\n id: userId,\n interests: [],\n memories: [],\n interactionCount: 0,\n lastSeen: new Date(),\n relationship: 'new'\n };\n }\n }\n\n // Update user profile after interaction\n async updateUserProfile(userId: string, newInterests: string[] = []): Promise {\n const profile = await this.getUserProfile(userId);\n const updatedInterests = [...new Set([...profile.interests, ...newInterests])];\n \n // Determine relationship level based on interaction count\n let relationship: UserProfile['relationship'] = 'new';\n if (profile.interactionCount > 20) relationship = 'close_friend';\n else if (profile.interactionCount > 10) relationship = 'friend';\n else if (profile.interactionCount > 3) relationship = 'acquaintance';\n\n const now = new Date().toISOString();\n await sqlite.execute(\n `UPDATE ${tables.USERS_TABLE} \n SET interests = ?, interaction_count = interaction_count + 1, \n last_seen = ?, relationship = ?\n WHERE id = ?`,\n [JSON.stringify(updatedInterests), now, relationship, userId]\n );\n }\n\n private async getMemory(id: string): Promise {\n const result = await sqlite.execute(\n `SELECT * FROM ${tables.MEMORIES_TABLE} WHERE id = ?`,\n [id]\n );\n\n if (!result || !Array.isArray(result) || result.length === 0) {\n return null;\n }\n\n return this.rowToMemory(result[0]);\n }\n\n private rowToMemory(row: any): Memory {\n return {\n id: row.id,\n userId: row.user_id,\n content: row.content,\n type: row.type,\n atoms: JSON.parse(row.atoms || '[]'),\n importance: row.importance,\n created: new Date(row.created),\n lastReinforced: new Date(row.last_reinforced),\n tags: JSON.parse(row.tags || '[]')\n };\n }\n\n // Generate memory tags based on content analysis\n generateMemoryTags(content: string, userProfile: UserProfile): string[] {\n const tags: string[] = [];\n const lowerContent = content.toLowerCase();\n\n // Interest-based tags\n for (const interest of userProfile.interests) {\n if (lowerContent.includes(interest.toLowerCase())) {\n tags.push(`interest:${interest}`);\n }\n }\n\n // Emotion tags\n if (lowerContent.match(/\\b(love|like|enjoy|excited|happy|amazing)\\b/)) tags.push('positive');\n if (lowerContent.match(/\\b(hate|dislike|sad|angry|frustrated|terrible)\\b/)) tags.push('negative');\n if (lowerContent.match(/\\b(question|wonder|curious|how|why|what)\\b/)) tags.push('inquiry');\n\n // Activity tags\n if (lowerContent.match(/\\b(play|game|gaming|video game)\\b/)) tags.push('gaming');\n if (lowerContent.match(/\\b(read|book|story|novel)\\b/)) tags.push('reading');\n if (lowerContent.match(/\\b(music|song|listen|band)\\b/)) tags.push('music');\n if (lowerContent.match(/\\b(work|job|career|office)\\b/)) tags.push('work');\n\n return tags;\n }\n}","deleted","label",[170,171,152],"backend","cognitive","permalink","https://www.val.town/x/zone/NanoCog1/code/backend/cognitive/memory.ts","extension","actionData","errors"]