refactor: Partitioner & Generator

[ChenZiHong-Gavin]

This PR refactors the partitioner and generator system by decoupling graph partitioning from QA generation and creating a more modular architecture. The changes introduce new base classes and implementations for both partitioners and generators, moving away from the previous community detection approach to a more flexible partitioning system.

Introduces new partitioner classes (BFS, DFS, ECE, Leiden) with unified interfaces
Creates generator classes for different QA generation modes (Atomic, Aggregated, CoT, MultiHop)
Refactors the main generation workflow to use separate partition and generate steps

Key renames / removals in the ECE partitioner (originally traverse strategy for traverse_graph.py):

• Removed max_depth.
• Removed expand_method – expansion is always BFS (or DFS, depending on the concrete class).
• Removed loss_strategy – nodes and edges are treated as generic “units”; the single switch unit_sampling (“random”, “min_loss”, “max_loss”) decides the order in which they are visited.
• Removed bidirectional – graphs are always traversed in both directions.
• max_extra_edges → max_units_per_community (total nodes + edges allowed in one community).
• max_tokens → max_tokens_per_community (community-level token budget).

When unit_sampling="random" the ECE partitioner degenerates to a plain BFS partitioner, guaranteeing backward compatibility for experiments that only need uniform random expansion.

[ChenZiHong-Gavin]

/gemini-review

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