feat(arch): replace single-level Louvain with multi-level Leiden community detection

The previous community detection ran a single local-moving pass with no
aggregation or refinement, so it fragmented graphs into hundreds of tiny,
sometimes internally-disconnected clusters (e.g. 275 on a mid-size repo).

Implement the Leiden algorithm (Traag, Waltman & van Eck 2019,
arXiv:1810.08473): local moving (fast, queue-based) -> refinement -> graph
aggregation, repeated until the partition can no longer be coarsened. The
refinement phase re-derives each community bottom-up from singletons, merging
only along edges, which guarantees every reported community is internally
connected. Aggregation seeds each level from the prior move-phase partition so
coarse structure carries over. A resolution parameter controls granularity.

Internals use a CSR graph (cbm_lg_t); self-loops are folded into the weighted
degree rather than materialised, so the modularity gain uses degree for the
null model and the adjacency for connectivity. cbm_louvain is preserved as a
thin wrapper over cbm_leiden(resolution=1.0) for API compatibility.

Tests: multi-level collapse (32-node clique chain -> few connected
communities), resolution control (path graph granularity), and a connectivity
checker proving the refinement guarantee; existing Louvain tests still pass.

Closes #57