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Establishes multi-tenant database layer with vector similarity search for AI-powered memory features. Includes Docker infrastructure, Prisma ORM integration, NestJS services, and shared types across the monorepo. Key changes: - Docker: PostgreSQL 17 + pgvector v0.7.4, Valkey cache - Schema: 8 models (User, Workspace, Task, Event, Project, ActivityLog, MemoryEmbedding) with RLS preparation - NestJS: PrismaModule, DatabaseModule, EmbeddingsService - Shared: Type-safe enums, constants, and database types Fixes #2 Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
3.3 KiB
3.3 KiB
Issue #2: PostgreSQL 17 + pgvector Schema
Objective
Design and implement the PostgreSQL 17 database schema with pgvector extension for Mosaic Stack.
Approach
- Docker Infrastructure - Build PostgreSQL 17 container with pgvector extension
- Prisma ORM - Define schema with 8 core models (User, Workspace, Task, Event, Project, etc.)
- Multi-tenant Design - All tables indexed by workspace_id for RLS preparation
- Vector Embeddings - pgvector integration for semantic memory with HNSW index
- NestJS Integration - PrismaService + EmbeddingsService for database operations
Progress
- Plan approved
- Phase 1: Docker Setup (5 tasks) - COMPLETED
- Phase 2: Prisma Schema (5 tasks) - COMPLETED
- Phase 3: NestJS Integration (5 tasks) - COMPLETED
- Phase 4: Shared Types & Seed (5 tasks) - COMPLETED
- Phase 5: Build & Verification (2 tasks) - COMPLETED
Completion Summary
Issue #2 successfully completed on 2026-01-28
What Was Delivered
-
Docker Infrastructure
- PostgreSQL 17 with pgvector v0.7.4 (HNSW index enabled)
- Valkey for caching
- Custom Dockerfile building pgvector from source
- Init scripts for extension setup
-
Database Schema (Prisma)
- 8 models: User, Workspace, WorkspaceMember, Task, Event, Project, ActivityLog, MemoryEmbedding
- 6 enums for type safety
- UUID primary keys throughout
- HNSW index on memory_embeddings for vector similarity search
- Full multi-tenant support with workspace_id indexing
- 2 migrations: init + vector index
-
NestJS Integration
- PrismaModule (global)
- PrismaService with lifecycle hooks and health checks
- EmbeddingsService for pgvector operations (raw SQL)
- Health endpoint updated with database status
-
Shared Types
- Enums mirroring Prisma schema
- Entity interfaces for type safety across monorepo
- Exported from @mosaic/shared
-
Development Tools
- Seed script with sample data (user, workspace, project, tasks, event)
- Prisma scripts in package.json
- Turbo integration for prisma:generate
- All builds passing with strict TypeScript
Database Statistics
- Tables: 8
- Extensions: uuid-ossp, vector (pgvector 0.7.4)
- Indexes: 14 total (including 1 HNSW vector index)
- Seed data: 1 user, 1 workspace, 1 project, 5 tasks, 1 event
Testing
- Unit tests for PrismaService (connection lifecycle, health check)
- Unit tests for EmbeddingsService (store, search, delete operations)
- Integration test with actual PostgreSQL database
- Seed data validation via Prisma Studio
Notes
Design Decisions
- UUID primary keys for multi-tenant scalability
- Native Prisma enums mapped to PostgreSQL enums for type safety
Unsupported("vector(1536)")type for pgvector (raw SQL operations)- Composite PK for WorkspaceMember (workspaceId + userId)
- Self-referencing Task model for subtasks support
Key Relations
- User → ownedWorkspaces (1:N), workspaceMemberships (N:M via WorkspaceMember)
- Workspace → tasks, events, projects, activityLogs, memoryEmbeddings (1:N each)
- Task → subtasks (self-referencing), project (optional N:1)
RLS Preparation (M2 Milestone)
- All tenant tables have workspace_id with index
- Future: PostgreSQL session variables (app.current_workspace_id, app.current_user_id)
- Future: RLS policies for workspace isolation