feat: Add session memory system with pgvector
- Add session_memories table for persistent learnings - Add memory_add, memory_search, memory_list, memory_context tools - Supports semantic search via embeddings - Categories: pattern, fix, preference, gotcha, architecture Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
Christian Gick
@@ -546,4 +546,58 @@ export const toolDefinitions = [
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},
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},
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},
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// Memory Tools
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{
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name: 'memory_add',
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description: 'Store a learning/memory for future sessions. Use at session end to persist insights.',
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inputSchema: {
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type: 'object',
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properties: {
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category: { type: 'string', enum: ['pattern', 'fix', 'preference', 'gotcha', 'architecture'], description: 'Memory category' },
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title: { type: 'string', description: 'Short title for the memory' },
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content: { type: 'string', description: 'The learning/insight to remember' },
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context: { type: 'string', description: 'When/where this applies (optional)' },
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project: { type: 'string', description: 'Project this relates to (optional)' },
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},
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required: ['category', 'title', 'content'],
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},
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},
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{
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name: 'memory_search',
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description: 'Search memories semantically. Returns relevant learnings for current context.',
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inputSchema: {
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type: 'object',
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properties: {
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query: { type: 'string', description: 'Search query' },
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project: { type: 'string', description: 'Filter by project (optional)' },
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category: { type: 'string', enum: ['pattern', 'fix', 'preference', 'gotcha', 'architecture'], description: 'Filter by category (optional)' },
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limit: { type: 'number', description: 'Max results (default: 5)' },
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},
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required: ['query'],
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},
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},
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{
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name: 'memory_list',
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description: 'List stored memories (non-semantic)',
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inputSchema: {
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type: 'object',
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properties: {
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project: { type: 'string', description: 'Filter by project (optional)' },
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category: { type: 'string', enum: ['pattern', 'fix', 'preference', 'gotcha', 'architecture'], description: 'Filter by category (optional)' },
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limit: { type: 'number', description: 'Max results (default: 20)' },
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},
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},
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},
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{
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name: 'memory_context',
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description: 'Get memories relevant to current session context. Use at session start.',
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inputSchema: {
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type: 'object',
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properties: {
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project: { type: 'string', description: 'Current project' },
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task_description: { type: 'string', description: 'Description of planned work (for semantic matching)' },
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},
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},
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},
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];
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259
src/tools/memories.ts
Normal file
259
src/tools/memories.ts
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@@ -0,0 +1,259 @@
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// Session memory operations for persistent learnings
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import { query, queryOne, execute } from '../db.js';
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import { getEmbedding, formatEmbedding } from '../embeddings.js';
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type MemoryCategory = 'pattern' | 'fix' | 'preference' | 'gotcha' | 'architecture';
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interface Memory {
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id: number;
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category: MemoryCategory;
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title: string;
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content: string;
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context: string | null;
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project: string | null;
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source_session: string | null;
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times_surfaced: number;
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created_at: string;
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}
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interface MemoryAddArgs {
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category: MemoryCategory;
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title: string;
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content: string;
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context?: string;
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project?: string;
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source_session?: string;
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}
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interface MemorySearchArgs {
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query: string;
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project?: string;
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category?: MemoryCategory;
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limit?: number;
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}
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interface MemoryListArgs {
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project?: string;
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category?: MemoryCategory;
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limit?: number;
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}
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/**
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* Add a new memory/learning
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*/
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export async function memoryAdd(args: MemoryAddArgs): Promise<string> {
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const { category, title, content, context, project, source_session } = args;
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// Generate embedding for semantic search
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const embedText = `${title}. ${content}`;
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const embedding = await getEmbedding(embedText);
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const embeddingValue = embedding ? formatEmbedding(embedding) : null;
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if (embeddingValue) {
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await execute(
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`INSERT INTO session_memories (category, title, content, context, project, source_session, embedding)
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VALUES ($1, $2, $3, $4, $5, $6, $7)`,
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[category, title, content, context || null, project || null, source_session || null, embeddingValue]
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);
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} else {
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await execute(
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`INSERT INTO session_memories (category, title, content, context, project, source_session)
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VALUES ($1, $2, $3, $4, $5, $6)`,
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[category, title, content, context || null, project || null, source_session || null]
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);
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}
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return `Stored memory: [${category}] ${title}`;
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}
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/**
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* Search memories semantically
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*/
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export async function memorySearch(args: MemorySearchArgs): Promise<string> {
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const { query: searchQuery, project, category, limit = 5 } = args;
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// Generate embedding for search
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const embedding = await getEmbedding(searchQuery);
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if (!embedding) {
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return 'Error: Could not generate embedding for search';
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}
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const embeddingStr = formatEmbedding(embedding);
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let whereClause = 'WHERE embedding IS NOT NULL';
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const params: unknown[] = [embeddingStr, limit];
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let paramIndex = 3;
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if (project) {
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whereClause += ` AND (project = $${paramIndex++} OR project IS NULL)`;
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params.splice(params.length - 1, 0, project);
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}
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if (category) {
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whereClause += ` AND category = $${paramIndex++}`;
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params.splice(params.length - 1, 0, category);
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}
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const memories = await query<Memory & { similarity: number }>(
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`SELECT id, category, title, content, context, project, times_surfaced,
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to_char(created_at, 'YYYY-MM-DD') as created_at,
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1 - (embedding <=> $1) as similarity
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FROM session_memories
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${whereClause}
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ORDER BY embedding <=> $1
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LIMIT $2`,
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params
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);
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if (memories.length === 0) {
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return 'No relevant memories found';
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}
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// Update times_surfaced for returned memories
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const ids = memories.map(m => m.id);
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await execute(
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`UPDATE session_memories SET times_surfaced = times_surfaced + 1, last_surfaced = NOW() WHERE id = ANY($1)`,
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[ids]
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);
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const lines = ['Relevant memories:\n'];
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for (const m of memories) {
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const sim = Math.round(m.similarity * 100);
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const proj = m.project ? ` [${m.project}]` : '';
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lines.push(`**[${m.category}]${proj}** ${m.title} (${sim}% match)`);
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lines.push(` ${m.content}`);
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if (m.context) {
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lines.push(` _Context: ${m.context}_`);
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}
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lines.push('');
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}
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return lines.join('\n');
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}
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/**
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* List memories (non-semantic)
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*/
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export async function memoryList(args: MemoryListArgs): Promise<string> {
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const { project, category, limit = 20 } = args;
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let whereClause = 'WHERE 1=1';
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const params: unknown[] = [];
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let paramIndex = 1;
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if (project) {
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whereClause += ` AND (project = $${paramIndex++} OR project IS NULL)`;
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params.push(project);
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}
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if (category) {
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whereClause += ` AND category = $${paramIndex++}`;
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params.push(category);
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}
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params.push(limit);
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const memories = await query<Memory>(
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`SELECT id, category, title, content, context, project, times_surfaced,
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to_char(created_at, 'YYYY-MM-DD') as created_at
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FROM session_memories
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${whereClause}
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ORDER BY created_at DESC
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LIMIT $${paramIndex}`,
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params
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);
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if (memories.length === 0) {
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return `No memories found${project ? ` for project ${project}` : ''}`;
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}
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const lines = [`Memories${project ? ` (${project})` : ''}:\n`];
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for (const m of memories) {
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const proj = m.project ? `[${m.project}] ` : '';
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const surfaced = m.times_surfaced > 0 ? ` (shown ${m.times_surfaced}x)` : '';
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lines.push(`• [${m.category}] ${proj}${m.title}${surfaced}`);
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lines.push(` ${m.content.slice(0, 100)}${m.content.length > 100 ? '...' : ''}`);
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}
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return lines.join('\n');
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}
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/**
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* Delete a memory by ID
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*/
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export async function memoryDelete(id: number): Promise<string> {
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const result = await execute('DELETE FROM session_memories WHERE id = $1', [id]);
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if (result === 0) {
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return `Memory not found: ${id}`;
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}
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return `Deleted memory: ${id}`;
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}
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/**
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* Get memories relevant to current context (for session start)
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*/
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export async function memoryContext(project: string | null, taskDescription?: string): Promise<string> {
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const lines: string[] = [];
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// Get project-specific memories
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if (project) {
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const projectMemories = await query<Memory>(
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`SELECT category, title, content FROM session_memories
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WHERE project = $1
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ORDER BY times_surfaced DESC, created_at DESC
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LIMIT 5`,
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[project]
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);
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if (projectMemories.length > 0) {
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lines.push(`**${project} Memories:**`);
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for (const m of projectMemories) {
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lines.push(`• [${m.category}] ${m.title}: ${m.content}`);
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}
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lines.push('');
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}
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}
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// If task description provided, do semantic search
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if (taskDescription) {
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const embedding = await getEmbedding(taskDescription);
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if (embedding) {
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const relevant = await query<Memory>(
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`SELECT category, title, content, project
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FROM session_memories
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WHERE embedding IS NOT NULL
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ORDER BY embedding <=> $1
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LIMIT 3`,
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[formatEmbedding(embedding)]
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);
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if (relevant.length > 0) {
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lines.push('**Relevant memories for this task:**');
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for (const m of relevant) {
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const proj = m.project ? `[${m.project}] ` : '';
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lines.push(`• ${proj}${m.title}: ${m.content}`);
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}
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}
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}
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}
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// Get recent gotchas (always useful)
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const gotchas = await query<Memory>(
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`SELECT title, content FROM session_memories
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WHERE category = 'gotcha'
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ORDER BY created_at DESC
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LIMIT 3`,
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[]
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);
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if (gotchas.length > 0) {
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lines.push('\n**Recent gotchas:**');
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for (const g of gotchas) {
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lines.push(`⚠️ ${g.title}: ${g.content}`);
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}
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}
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return lines.length > 0 ? lines.join('\n') : 'No memories to surface';
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}
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