feat(CF-1351): Remove unused memory_* tools from session-mcp
Auto memory (MEMORY.md + topic files) is the sole memory system. The session-mcp memory_* tools (PostgreSQL + pgvector) had zero entries after months of use — removing dead code to simplify the server. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
35
src/index.ts
35
src/index.ts
@@ -38,7 +38,7 @@ import {
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import { testConnection, close } from './db.js';
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import { toolDefinitions } from './tools/index.js';
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// Kept tools (sessions, memory, archives, infrastructure, docs, delegations, commits)
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// Kept tools (sessions, archives, infrastructure, docs, delegations, commits)
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import { taskDelegations, taskDelegationQuery } from './tools/delegations.js';
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import { projectLock, projectUnlock, projectLockStatus, projectContext } from './tools/locks.js';
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import { taskCommitAdd, taskCommitRemove, taskCommitsList, taskLinkCommits, sessionTasks } from './tools/commits.js';
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@@ -53,7 +53,6 @@ import {
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impactLearn,
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componentGraph,
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} from './tools/impact.js';
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import { memoryAdd, memorySearch, memoryList, memoryContext } from './tools/memories.js';
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import { toolDocAdd, toolDocSearch, toolDocGet, toolDocList, toolDocExport } from './tools/tool-docs.js';
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import {
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sessionStart,
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@@ -230,38 +229,6 @@ server.setRequestHandler(CallToolRequestSchema, async (request) => {
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result = JSON.stringify(await componentGraph(a.component_id), null, 2);
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break;
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// Memories
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case 'memory_add':
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result = await memoryAdd({
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category: a.category,
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title: a.title,
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content: a.content,
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context: a.context,
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project: a.project,
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session_id: a.session_id,
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task_id: a.task_id,
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});
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break;
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case 'memory_search':
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result = await memorySearch({
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query: a.query,
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project: a.project,
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category: a.category,
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limit: a.limit,
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search_mode: a.search_mode,
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});
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break;
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case 'memory_list':
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result = await memoryList({
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project: a.project,
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category: a.category,
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limit: a.limit,
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});
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break;
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case 'memory_context':
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result = await memoryContext(a.project, a.task_description);
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break;
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// Tool Documentation
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case 'tool_doc_add':
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result = await toolDocAdd({
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@@ -298,63 +298,6 @@ export const toolDefinitions = [
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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.',
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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' },
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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 (optional)' },
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session_id: { type: 'string', description: 'Session ID (optional)' },
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task_id: { type: 'string', description: 'Jira issue key (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 using hybrid (vector + keyword), vector-only, or keyword-only search.',
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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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search_mode: { type: 'string', enum: ['hybrid', 'vector', 'keyword'], description: 'Search mode (default: hybrid)' },
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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.',
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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' },
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},
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},
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},
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// Tool Documentation Tools
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{
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name: 'tool_doc_add',
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@@ -1,340 +0,0 @@
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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, generateContentHash, rrfMerge } 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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session_id: string | null;
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task_id: string | null;
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access_count: 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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session_id?: string;
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task_id?: string;
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}
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type SearchMode = 'hybrid' | 'vector' | 'keyword';
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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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search_mode?: SearchMode;
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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 (enhanced with session_id and task_id)
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* CF-306: Validates session_id exists before inserting to prevent foreign key violations
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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, session_id, task_id } = args;
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// CF-306: Validate session_id exists if provided
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let validSessionId = session_id || null;
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if (session_id) {
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const sessionExists = await queryOne<{ exists: boolean }>(
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`SELECT EXISTS(SELECT 1 FROM sessions WHERE id = $1) as exists`,
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[session_id]
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);
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if (!sessionExists?.exists) {
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console.warn(`[CF-306] Session ${session_id} not found in database - using NULL instead`);
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validSessionId = null;
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}
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}
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// CF-1314: Hash content for dedup before embedding API call
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const embedText = `${title}. ${content}`;
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const contentHash = generateContentHash(embedText);
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// Scope dedup to project if provided, otherwise global
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const existing = project
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? await queryOne<{ id: number }>(
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'SELECT id FROM memories WHERE content_hash = $1 AND project = $2 LIMIT 1',
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[contentHash, project]
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)
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: await queryOne<{ id: number }>(
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'SELECT id FROM memories WHERE content_hash = $1 AND project IS NULL LIMIT 1',
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[contentHash]
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);
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if (existing) {
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return `Memory already exists (id: ${existing.id}): [${category}] ${title}`;
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}
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// Generate embedding for semantic search
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const embedding = await getEmbedding(embedText);
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const embeddingValue = embedding ? formatEmbedding(embedding) : null;
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await execute(
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`INSERT INTO memories (category, title, content, context, project, session_id, task_id, embedding, content_hash)
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VALUES ($1, $2, $3, $4, $5, $6, $7, $8, $9)`,
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[category, title, content, context || null, project || null, validSessionId, task_id || null, embeddingValue, contentHash]
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);
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return `Stored memory: [${category}] ${title}`;
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}
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/**
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* Search memories with hybrid (vector + keyword), vector-only, or keyword-only mode (CF-1315)
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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, search_mode = 'hybrid' } = args;
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// Build shared filter clause
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const buildFilter = (startIdx: number) => {
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let where = '';
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const params: unknown[] = [];
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let idx = startIdx;
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if (project) {
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where += ` AND (project = $${idx++} OR project IS NULL)`;
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params.push(project);
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}
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if (category) {
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where += ` AND category = $${idx++}`;
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params.push(category);
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}
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return { where, params, nextIdx: idx };
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};
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// Vector search
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let vectorIds: number[] = [];
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let vectorRows: Map<number, Memory & { similarity: number }> = new Map();
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let embeddingFailed = false;
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if (search_mode !== 'keyword') {
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const embedding = await getEmbedding(searchQuery);
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if (embedding) {
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const embeddingStr = formatEmbedding(embedding);
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const filter = buildFilter(3);
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const params: unknown[] = [embeddingStr, limit, ...filter.params];
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const rows = await query<Memory & { similarity: number }>(
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`SELECT id, category, title, content, context, project, access_count,
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to_char(created_at, 'YYYY-MM-DD') as created_at,
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1 - (embedding <=> $1) as similarity
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FROM memories
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WHERE embedding IS NOT NULL${filter.where}
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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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vectorIds = rows.map(r => r.id);
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for (const r of rows) vectorRows.set(r.id, r);
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} else {
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embeddingFailed = true;
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if (search_mode === 'vector') {
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return 'Error: Could not generate embedding for vector search';
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}
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}
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}
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// Keyword search
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let keywordIds: number[] = [];
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let keywordRows: Map<number, Memory & { rank: number }> = new Map();
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if (search_mode !== 'vector') {
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const filter = buildFilter(3);
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const params: unknown[] = [searchQuery, limit, ...filter.params];
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const rows = await query<Memory & { rank: number }>(
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`SELECT id, category, title, content, context, project, access_count,
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to_char(created_at, 'YYYY-MM-DD') as created_at,
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ts_rank(search_vector, plainto_tsquery('english', $1)) as rank
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FROM memories
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WHERE search_vector @@ plainto_tsquery('english', $1)${filter.where}
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ORDER BY rank DESC
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LIMIT $2`,
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params
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);
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keywordIds = rows.map(r => r.id);
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for (const r of rows) keywordRows.set(r.id, r);
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}
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// Merge results
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let finalIds: number[];
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let searchLabel: string;
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if (search_mode === 'hybrid' && vectorIds.length > 0 && keywordIds.length > 0) {
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const merged = rrfMerge(vectorIds, keywordIds);
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finalIds = merged.slice(0, limit).map(m => m.id as number);
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searchLabel = 'hybrid';
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} else if (vectorIds.length > 0) {
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finalIds = vectorIds;
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searchLabel = 'vector';
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} else if (keywordIds.length > 0) {
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finalIds = keywordIds;
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searchLabel = embeddingFailed ? 'keyword (embedding unavailable)' : 'keyword';
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} else {
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return 'No relevant memories found';
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}
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// Update access_count for returned memories
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await execute(
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`UPDATE memories SET access_count = access_count + 1, last_accessed_at = NOW() WHERE id = ANY($1)`,
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[finalIds]
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);
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// Format output
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const lines = [`Relevant memories (${searchLabel}):\n`];
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for (const id of finalIds) {
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const m = vectorRows.get(id) || keywordRows.get(id);
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if (!m) continue;
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const sim = vectorRows.has(id) ? ` (${Math.round((vectorRows.get(id)!).similarity * 100)}% match)` : '';
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const proj = m.project ? ` [${m.project}]` : '';
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lines.push(`**[${m.category}]${proj}** ${m.title}${sim}`);
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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, access_count,
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to_char(created_at, 'YYYY-MM-DD') as created_at
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FROM 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 accessed = m.access_count > 0 ? ` (accessed ${m.access_count}x)` : '';
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lines.push(`• [${m.category}] ${proj}${m.title}${accessed}`);
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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 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 memories
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WHERE project = $1
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ORDER BY access_count DESC, created_at DESC
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LIMIT 5`,
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[project]
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);
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if (projectMemories.length > 0) {
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lines.push(`**${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 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 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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