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-llm/Cargo.toml

@@ -14,3 +14,5 @@ thiserror = { workspace = true }
 reqwest = { workspace = true }
 tracing = { workspace = true }
 chrono = { workspace = true }
+pgvector = { workspace = true }
+uuid = { workspace = true }