feat: implement full pipeline (pgvector, embeddings, ingest, query, HTTP)

- Add database schema with pgvector extension (L0/L1/L2 memories)
- Implement pgvector-backed vector store with similarity search
- Add Ollama embeddings client for 768-dim nomic embeddings
- Implement ingest worker to process records into L0/L1 memory
- Implement query worker with semantic search across memory tiers
- Rewrite HTTP server with database connection pooling
- Wire all endpoints to actual backend (ingest, query, projects, skills)
- Update main.rs to use DATABASE_URL from environment
- All code compiles, ready for Docker build and deployment

crates/mem-store/src/lib.rs

@@ -3,9 +3,11 @@ pub mod pgvector;
 pub mod rebuild;
 pub mod pg_repo;
 pub mod obsidian;
+pub mod schema;
 
 pub use event_log::{EventRecord, LogWriter};
-pub use pgvector::{VectorRecord, VectorStore};
+pub use pgvector::{VectorRecord, VectorStore, ChunkL0, MemoryL1, MemoryL2};
 pub use rebuild::RebuildState;
 pub use pg_repo::{PgRepo, MemoryNode, VectorKind, Level, ScoredNode};
 pub use obsidian::ObsidianProjector;
+pub use schema::init_schema;