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### Summary Closes #15795 Knowledge-graph queries rank entities by `pagerank * sim` in `KGSearch`, but the entity chunks written at index time stopped carrying the values that ranking depends on. `graph_node_to_chunk` only stored `entity_type`, `description`, and `source_id`, dropping the node `pagerank` and the n-hop neighbour paths, while `search.py` still read them back as `rank_flt` and `n_hop_with_weight`. The producer of these fields, `update_nodes_pagerank_nhop_neighbour`, was removed in #6513, but the read side in `KGSearch` was never updated. The result is that on every knowledge-graph query: - `pagerank` resolves to `0`, so the `pagerank * sim` sort key is `0` for every entity and selection falls back to arbitrary order. - Every displayed entity score is `0.00`. - The n-hop relation-enrichment block is dead code because `n_hop_ents` is always empty, leaving `merge_tuples` and `is_continuous_subsequence` orphaned. This PR restores the missing index-time fields so the documented `P(E|Q) = pagerank * sim` ranking and the n-hop enrichment work again. What changed: - `graph_node_to_chunk` now writes `rank_flt` from the node pagerank and `n_hop_with_weight` from the recomputed n-hop neighbour paths. - Reintroduced the n-hop path computation (`n_neighbor`) in `rag/graphrag/utils.py`, reusing the previously orphaned `merge_tuples` / `is_continuous_subsequence` helpers, with a direction-agnostic edge-weight lookup for undirected graphs. `set_graph` computes the paths per added or updated node and passes them through. - `KGSearch` now selects `n_hop_with_weight` in the entity keyword search so Infinity and OceanBase return it (Elasticsearch and OpenSearch already read it from `_source`), and the read is hardened against missing keys or empty strings before `json.loads`. - Added the `n_hop_with_weight` column to OceanBase, including the `EXTRA_COLUMNS` migration entry so existing tables get it. The other engines already map both fields via dynamic templates or the Infinity mapping. Scope note: pagerank and n-hop are re-indexed for the added or updated nodes in each pass, consistent with the existing incremental indexing design. ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue) ### Testing Added unit tests in `test/unit_test/rag/graphrag/test_graphrag_utils.py`: - `n_neighbor`: path and weight shape, one-hop vs two-hop, isolated nodes, missing weights, and direction-agnostic lookup. - `graph_node_to_chunk`: `rank_flt` populated from pagerank and defaulting to `0`, `n_hop_with_weight` serialized and defaulting to an empty list. ``` uv run pytest test/unit_test/rag/graphrag/ # 106 passed uv run ruff check rag/graphrag/ rag/utils/ob_conn.py ```