Defines GraphOperationsInterface, a Pydantic BaseModel that declares the full set of graph mutation and read operations (save/get/delete for all node/edge types, search, community ops). This interface acts as a contract that each database driver can implement, allowing backend-agnostic operation orchestration. The fallback mechanism (try interface, catch NotImplementedError, fallback to provider-branched queries) makes it extensible without breaking existing code. This pattern is reusable for any multi-database data access layer.

Provides predefined SearchConfig objects (e.g., COMBINED_HYBRID_SEARCH_RRF, NODE_HYBRID_SEARCH_CROSS_ENCODER) that compose search methods (fulltext, similarity, BFS) with rerankers (RRF, MMR, cross-encoder, node-distance, episode-mentions). These configs are declarative and can be used as is or customized via SearchConfig's builder methods. This pattern is reusable for any application needing configurable multi-stage retrieval pipelines.

Implements a multistage entity deduplication pipeline: first attempts exact-name and identity-property matching, then uses MinHash signatures with LSH bands for approximate similarity, entropy-gated fuzzy normalization, and finally escalates to LLM-based resolution. All stages are parameterizable and return structured DedupResolutionState. This module is self-contained and could be extracted as a standalone deduplication library for any entity resolution task.

Implements content-aware chunking: only chunks large, entity-dense content (measured by token density heuristics) and uses structure-preserving overlap for JSON/text/message formats. The covering-design algorithm (greedy Handshake with random fallback) generates chunk pairs for LLM edge extraction, ensuring all entity pairs are covered. This logic is self-contained and parameterizable via environment variables, making it reusable for any LLM extraction pipeline that needs to balance context window limits with entity coverage.