sqlite-graphrag 1.2.8

Persistent GraphRAG memory for Claude Code, Codex, Cursor, and 27 AI agents — one self-contained ~19 MiB Rust binary, zero daemon. Never re-explain your codebase again. Hybrid retrieval (FTS5 BM25 + cosine similarity + multi-hop graph traversal) surfaces the right memory in milliseconds. Embedding and entity enrichment run as parallel REST calls against your cloud LLM — no fragile headless subprocesses, no ONNX runtime, no model downloads. Soft-delete with full version history, transactional atomic writes, BLAKE3-tracked mutations. OAuth-only: raw API keys ABORT the spawn.
Documentation 
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//! Persistence layer for the `memories` table and its vector companion.
//!
//! Functions here encapsulate every SQL statement touching `memories`,
//! `memory_embeddings` and the FTS5 `fts_memories` shadow table. Callers receive
//! typed [`MemoryRow`] or [`NewMemory`] values and never build SQL strings.
//!
//! One submodule per storage surface: `rows` holds the typed shapes, `crud`
//! the single-row lookups and mutations, `listing` the paginated reads,
//! `vectors` the `memory_embeddings` companion and its KNN query, `fts` the
//! FTS5 shadow table, and [`soft_delete`] the tombstone lifecycle.

mod crud;
mod fts;
mod listing;
mod rows;
mod soft_delete;
mod vectors;

pub use crud::{find_by_hash, find_by_name, insert, read_by_name, read_full, update};
pub use fts::{fts_search, sync_fts_after_update};
pub use listing::{count, list};
pub use rows::{MemoryRow, NewMemory};
pub use soft_delete::{clear_deleted_at, find_by_name_any_state, list_deleted_before, soft_delete};
pub use vectors::{delete_vec, knn_search, upsert_vec};

#[cfg(test)]
mod tests;