Config reference: `graph_search`

Enterprise tuning surface

Defaults + constraints are rendered directly from Pydantic.
Env keys when available

Many fields have an env-style alias (from TriBridConfig.to_flat_dict()).
Tooltip-level guidance

If a matching glossary entry exists, you’ll see deeper tuning notes.

Total parameters: 9

Group index

`(root)`

JSON key	Env key(s)	Type	Default	Constraints	Summary
`graph_search.chunk_entity_expansion_enabled`	—	`bool`	`true`	—	When mode='chunk', expand from seed chunks via Entity graph (IN_CHUNK links) to find related chunks
`graph_search.chunk_entity_expansion_weight`	—	`float`	`0.8`	≥ 0.0, ≤ 1.0	Blend weight for entity-expansion scores relative to seed chunk scores (mode='chunk')
`graph_search.chunk_neighbor_window`	—	`int`	`1`	≥ 0, ≤ 10	When mode='chunk', include up to N adjacent chunks (NEXT_CHUNK) around each seed hit
`graph_search.chunk_seed_overfetch_multiplier`	—	`int`	`10`	≥ 1, ≤ 50	When mode='chunk' and Neo4j uses a shared database, overfetch seed hits before filtering by corpus_id
`graph_search.enabled`	—	`bool`	`true`	—	Enable graph search in tri-brid retrieval
`graph_search.include_communities`	—	`bool`	`true`	—	Include community-based expansion in graph search
`graph_search.max_hops`	—	`int`	`2`	≥ 1, ≤ 5	Maximum graph traversal hops
`graph_search.mode`	—	`Literal["chunk", "entity"]`	`"chunk"`	allowed="chunk", "entity"	Graph retrieval mode. 'chunk' uses lexical chunk nodes + Neo4j vector index; 'entity' uses the legacy code-entity graph.
`graph_search.top_k`	—	`int`	`30`	≥ 5, ≤ 100	Number of results to retrieve from graph search