feat(#2): Implement PostgreSQL 17 + pgvector database schema

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>

apps/api/prisma/migrations/20260128213002_add_vector_index/migration.sql

@@ -0,0 +1,8 @@
+-- Add HNSW index for fast vector similarity search on memory_embeddings table
+-- Using cosine distance operator for semantic similarity
+-- Parameters: m=16 (max connections per layer), ef_construction=64 (build quality)
+
+CREATE INDEX IF NOT EXISTS memory_embeddings_embedding_idx
+ON memory_embeddings
+USING hnsw (embedding vector_cosine_ops)
+WITH (m = 16, ef_construction = 64);