Crate plugmem_host 

The crate README is included below as module documentation, which makes every Rust example in it a doctest: a README that drifts from the API stops compiling instead of quietly lying.

plugmem-host

⚠️ Experimental. plugmem is mostly an AI-built experiment — written with the help of a small local model (Qwen3.6-35B-A3B-UD-Q4_K_XL.gguf) and various Claude models, in roughly equal measure. Expect non-professional design choices, rough edges, broken behavior, or mistakes. Use it at your own risk.

plugmem-host is the std host layer for the plugmem temporal-memory engine. It supplies what the no_std engine does not own — files, locking, and network — so from this one crate a Rust program gets remember / recall / revise / forget plus graph link/unlink, backed by durable storage. It re-exports the engine, so this one crate is all a Rust program needs.

Which crate do I need?

Writing Rust and just want a working memory? This is the crate — it has everything. The others are for narrower needs.

You want	Use	Why
A memory in a Rust program — the common case	plugmem-host (this crate, std)	Everything included: files, locking, read-only mmap, HTTP embedders, integrity, cross-process concurrency. One dependency — it re-exports the engine.
A memory in Rust with no std or your own storage (browser, wasm host, custom file layer)	plugmem-core (no_std)	The engine only. You bring the Storage trait, the clock, file I/O and embedding — so you also manage when the file opens and how memory loads.
Just the flat byte-pool containers	plugmem-arena (no_std)	The storage substrate, engine-agnostic.
A memory from a terminal or shell script	plugmem-cli (plugmem)	One file, no server; plugmem repl keeps the engine open for host speed.
A memory for an LLM agent or a non-Rust program	plugmem-mcp	Long-lived stdio JSON-RPC; language-independent. In Rust, embed this crate instead.
A memory in JavaScript / TypeScript (Node)	plugmem-napi	The engine as a native Node addon (napi-rs), in-process; on npm as plugmem.

Configuration

The shared config.toml loader and platform-aware database paths are documented in the full settings reference. plugmem-cli, plugmem-mcp and plugmem-napi use the same settings catalogue and database-path precedence; only their explicit override syntax differs.

The config feature is enabled by default for this native host crate, so Settings::load and read_config are available without extra feature flags. Applications that construct Config programmatically and want the smallest host dependency surface can use default-features = false; this does not alter the plugmem-core or WASM build.

What recall does

Recall is not a vector lookup — it fuses four sources by reciprocal-rank fusion with a recency boost (tags filter; they are not a source):

Source	Algorithm	What it finds
Lexical	BM25 (Robertson idf) over a Unicode (UAX #29) tokenizer	exact terms / keyword overlap
Semantic	int8-quantized cosine — a flat two-phase scan below a threshold, an HNSW graph above	meaning / nearest neighbours
Graph	entity graph with typed edges, breadth-first from query anchors	relational knowledge
Temporal	range scans over a recorded_at-ordered index; bitemporal validity	“what was true then”, time windows

Two clocks

Every fact carries two timestamps, and the distinction is the reason the temporal source exists at all:

• valid_from / valid_to — when the statement was true.
• recorded_at — when the memory learned it. Stamped by the engine.

One timestamp cannot hold both, and the host passes now explicitly, so the whole sequence is expressible:

const JAN: u64 = 1_767_225_600_000;
const MAR_5: u64 = 1_772_668_800_000;
const MAR_10: u64 = 1_773_100_800_000;

// In January the memory learns where kim lives.
let first = db.remember(RememberInput {
    entity: Some("kim"),
    ..RememberInput::text(JAN, "lives in Moscow")
})?;

// On March 10th it learns the address changed. `revise` closes the old
// interval at this instant; it does not delete the record.
db.revise(
    first.id,
    RememberInput {
        entity: Some("kim"),
        ..RememberInput::text(MAR_10, "lives in Berlin")
    },
)?;

// Now: Berlin.
db.recall(RecallQuery {
    entities: &["kim"],
    ..RecallQuery::text(MAR_10, "kim")
})?;

// As of March 5th: Moscow. Still valid then, and already recorded.
db.recall(RecallQuery {
    entities: &["kim"],
    as_of: Some(MAR_5),
    ..RecallQuery::text(MAR_10, "kim")
})?;

as_of moves both clocks: a fact answers only if it was valid at that instant and had already been recorded by then. The second half is the one people trip over. An as_of earlier than a fact’s recorded_at does not see it, because the memory genuinely knew nothing then — answering with today’s knowledge would be the wrong answer to “what did I hold”.

valid_from is the other half of the model: a statement that became true before you heard of it. Recording on March 10th that the move happened on March 1st — valid_from: Some(MAR_1) on the revision — closes the old interval at March 1st instead of at March 10th. A query as of March 5th then finds neither: Moscow had stopped being true, and Berlin was not yet known. That is not a hole in the model, it is the honest answer for that instant, and it is exactly what one timestamp cannot express.

The old record stays on disk either way. forget is the destructive verb: use it when a fact was wrong, not when it changed.

Edges are temporal the same way, so an as_of traversal walks the graph as it stood then — through relationships that have since been unlinked.

What plugmem-host adds

The retrieval above lives in the engine; this crate adds the OS side:

• File-backed storage — atomic snapshots (tmp + fsync + rename), an append-only journal with a configurable fsync policy, crash recovery (a torn journal tail is detected and dropped on open);
• OS locking, one writer — an advisory lock per database file. A second read-write open is refused with a typed HostError::Locked rather than corrupting the file silently. Readers do not take that lock;
• A read-only mmap open, concurrent with the writer — Database::open_readonly pins the current published snapshot generation and maps it, borrowing the mapped pages so a large read-mostly database resides only in the pages a query touches. Generations are immutable — a checkpoint writes a new one and never rewrites an old one — so a writer and any number of readers run at the same time, across threads and across processes, sharing the OS page cache. This is the WAL/MVCC arrangement, not “N readers or one writer”: a reader sees state as of the checkpoint it pinned (snapshot isolation) and calls refresh() to adopt a newer one;
• A write path that does not clone the file — Database::open memory-maps the snapshot and the engine borrows it as an overlay: mutations land in a small owned overlay (an appended tail plus per-page copy-on-write), so opening a multi-gigabyte database to append one fact no longer copies the whole image into RAM. A snapshot materializes the base + overlay into a fresh file and re-maps it. Validation is lazy (the SQLite model): an open range-checks the record metadata and nothing else, so the large text, vector and per-fact-metadata pools stay non-resident until a query touches them — a measured open residents well under half of a text-heavy image. What that guarantees is precise and worth stating: no stored id can make a read unsafe. It does not mean the data agrees with itself. The default open never checksums the image either, so it stays sparse; corruption is caught when the bad record is read (never a panic), or on demand with verify() (content and graph consistency) and scrub() (byte-level container integrity) — see Integrity & recovery below;
• Maintenance policy — auto-snapshot and optional auto-maintain, run inline (no background threads);
• Embedding providers — one HTTP client for the /v1/embeddings shape shared by OpenAI, Ollama, LM Studio, vLLM and llama.cpp-server.

Without an embedder it is fully functional — lexical, tags, graph and time still answer; vectors are an addition, not a requirement.

Example

use plugmem_host::{Config, Database, OpenAiCompatEmbedder, RecallQuery, RememberInput};

let mut cfg = Config::default();
cfg.dim = 768;

let (db, _report) = Database::builder(cfg)
    // one client covers OpenAI, Ollama, LM Studio, vLLM, llama.cpp-server:
    .embedder(Box::new(OpenAiCompatEmbedder::new(
        "http://localhost:11434/v1", // Ollama's OpenAI-compatible endpoint
        "nomic-embed-text",
        768,
    )))
    .open("agent.plugmem")?;

// The text is embedded automatically (outside the database lock),
// quantized and indexed:
db.remember(RememberInput::text(1_784_000_000_000, "prefers tokio"))?;

// Bulk load: the whole batch is embedded in one round-trip and the
// journal is fsynced once (not per fact) — the write path for `import`:
db.remember_many(vec![
    RememberInput::text(1_784_000_050_000, "uses pinned versions"),
    RememberInput::text(1_784_000_060_000, "lives in Berlin"),
])?;

// The query text is embedded too; recall fuses lexical, vector, graph
// and temporal evidence into one ranked, token-budgeted block:
let out = db.recall(RecallQuery::text(1_784_000_100_000, "which runtime?"))?;
println!("{}", out.rendered);

Benchmarks

cargo run -p plugmem-host --example edge_lifecycle
cargo run -p plugmem-host --example maintain_modes
cargo run --release -p plugmem-host --example bench_database -- 100000 --diagnose-recall | tee database-benchmark-100k.tsv
cargo run --release -p plugmem-host --example bench_database -- 1000000 --diagnose-recall | tee database-benchmark-1m.tsv
cat database-benchmark-100k.tsv database-benchmark-1m.tsv > database-benchmark-scale.tsv
cargo run -p plugmem-bench-charts -- database-benchmark-scale.tsv --force
cargo run --release -p plugmem-host --example bench_edges -- 100000 | tee edge-benchmark-100k.tsv
cargo run --release -p plugmem-host --example bench_edges -- 1000000 | tee edge-benchmark-1m.tsv
cat edge-benchmark-100k.tsv edge-benchmark-1m.tsv > edge-benchmark-scale.tsv
cargo run -p plugmem-bench-charts -- edge-benchmark-scale.tsv --force
cargo bench -p plugmem-host

The committed assets/database-*.svg charts are generated from the database runs; assets/edge-lifecycle-*.svg charts are generated from bench_edges.

For the same-workload comparison between 100k and 1M, see the measured scale table on GitHub. For the public Rust API, see the plugmem-host documentation on docs.rs. The database example uses deterministic synthetic facts and dim=0; it does not call an embedding service or use a network connection.

Native builds are 64-bit, so a host process reads every capacity class of the shared file format: databases sized for the 32-bit wasm budget (≤ 2 GiB, the default) and databases with larger limits alike. Opening, reading, scanning and checkpointing go through the mmap overlay, whose clean pages the OS can reclaim — so those work on a database larger than RAM. A rebuild (maintain and recover) is disk-first too: it streams the two big pools (vectors, text) through temp files and keeps only the metadata and the HNSW graph resident, so peak RAM tracks the record count, not the image size. The residual limit is the graph itself — a database whose graph exceeds RAM is a further tier. The per-structure byte costs and pool limits (what a fact, an edge or a vector weighs, and where each tops out) are tabulated in plugmem-core’s Capacity — what weighs what. The snapshot format is pointer-width independent — a file written here opens unchanged in a wasm32 or wasm64 build of the core, as long as its configured limits fit that host.

Files

One database at agent.plugmem is:

file	role
agent.plugmem	the snapshot — the engine’s memory image, verbatim
agent.plugmem.journal	append-only journal since the last snapshot
agent.plugmem.lock	advisory lock file

Snapshot writes are atomic (tmp + fsync + rename + directory fsync): a reader observes the old image or the new one, never a torn file. Journal appends are fsynced per operation by default (FsyncPolicy::EachOp); OnSnapshot trades the crash-window of the journal tail for speed. On open, the journal is replayed over the snapshot deterministically; a torn tail from a crash mid-append is detected, dropped and reported.

Workspaces (optional)

Default: one Database, one file. Workspace is for a process serving many independent memories — a directory of named databases, opened on demand and pooled, plus an optional registry of what each is for.

use plugmem_host::{DbName, IfMissing, Settings};

let ws = Settings::load(None)?.open_workspace("/srv/bot".as_ref())?;
let db = ws.get(&DbName::parse("chat-42")?, now_ms(), IfMissing::Create)?;

A name is [a-z0-9][a-z0-9_-]* and cannot represent a path, so it resolves to exactly one file inside the directory. The pool bounds how many stay open; close_idle releases the rest, which matters because an open writer holds the file’s exclusive lock — the timeout is a liveness setting, not a memory one.

The core is untouched by any of this: one Memory is still one database. See specs/10-workspace.md.

Concurrency model

The engine is single-writer by design. The host runs a WAL/MVCC-style versioned layout, so one writer and any number of readers run at the same time — across threads and processes — without a reader ever blocking the writer or seeing a torn image.

• One writer. Database::open takes an exclusive writer lock; a second writer gets HostError::Locked immediately (a typed refusal, not silent corruption). The lock dies with the process, even on a crash. Readers do not take this lock, so they never contend with the writer.
• Many readers, concurrent with the writer. A checkpoint never overwrites a live file: it writes a new immutable snapshot generation and repoints a tiny manifest. Database::open_readonly pins the current generation with a shared lock and maps it — so it coexists with a live writer and reads a consistent snapshot “as of the last checkpoint” (it does not see writes made after it opened; reopen to advance). Readers across threads or processes share one copy of a generation in the OS page cache. The writer reclaims a superseded generation only once no reader still pins it, so disk stays bounded by the longest-lived reader.
• One process, many threads or agents. A Database is a Clone + Send + Sync handle; clone it freely. The read verbs (recall/get/stats/export/verify) take a shared guard and run concurrently; the write verbs take an exclusive guard and serialize — against each other and against readers (an RwLock over the engine, the same reader/writer discipline as the file lock, one level down). At microsecond engine calls neither is a bottleneck. ReadOnlyDatabase is Send + Sync too, and its reads are lock-free — a fan-out of reader threads over one mapped snapshot. (Each reader thread keeps its own recall scratch, so concurrent recalls never contend.)
• Many files. Fully independent databases: separate locks, separate mutexes, natural parallelism. Two models each with their own memory file never contend; two models sharing one memory clone one handle.
• Network stays outside the lock. Embedding calls (the slow, external part) run before the mutex is taken, so an agent waiting on its embedding provider does not stall the others.

The typical shape is build occasionally, read a lot: one writer snapshots the memory (on a schedule or in a maintenance window), then many read-only consumers query it in parallel.

use plugmem_host::{Config, Database, RecallQuery};

// Many readers over one checkpointed file — zero-copy, shared page cache.
// (A read-only open requires an empty journal: snapshot/checkpoint first.)
let ro = Database::open_readonly("agent.plugmem", Config::default())?;
let out = ro.recall(RecallQuery::text(1_784_000_100_000, "which runtime?"))?;
println!("{}", out.rendered);

Memory-mapped opens and disk-first rebuilds

Both open and open_readonly memory-map the snapshot; the engine borrows an overlay over the mapping rather than reading it into a heap copy. Opening is an mmap plus a bounds-check regardless of file size; only dereferenced pages fault in, and the OS may evict clean ones. Resident memory tracks the working set, not the file size.

A read-write handle appends new records to a small owned tail; the mapped base is never rewritten in place (the append-only structures avoid copy-on-write). A checkpoint streams the fresh image to a temp file and renames it atomically, unmapping first (Windows will not rename a mapped file).

Read-only handles take a shared lock and map the same snapshot, so several share one copy in the OS page cache. Open read-write only to mutate.

maintain and recover run disk-first: the two large pools (vectors, text) stream through a temp Scratch file (a sibling of the database, mapped on freeze, deleted on drop), keeping only metadata and the HNSW graph resident. Peak RAM is proportional to record count, not content size. On no_std (no files) the engine uses the in-RAM rebuild instead.

Integrity & recovery

The default open trusts the file (like SQLite): it does not checksum the whole image, so a large database opens sparse. Integrity is on demand, in three layers of increasing cost, and corruption is never a panic — the accessors tolerate bad bytes, these turn latent damage into an explicit error or a repaired file.

call	checks	cost
verify()	everything an open defers — stored text is valid UTF-8, metadata blobs decode, the fact↔vector-slot bijection holds, and the graph agrees with itself (both edge mirrors, a current edge against its open version, every open version reachable as a current edge)	one linear pass over the text + vector pools, plus a lookup per edge
scrub()	byte-level container integrity — each section’s stored xxh3 and the whole-file hash (the ZFS-scrub model)	resumable; a read-handle op
recover()	salvage — drop the content-corrupt facts, rebuild, write a clean copy	rebuilds in RAM ≈ image size

scrub() — the bitrot detector. A resumable iterator over the mapped snapshot: each next() hashes up to a slice budget, so you pace it yourself (run to completion, or a slice at a time on a background thread, pausing/cancelling between slices). It holds a shared lock for its whole life, reads the map linearly (pages fault in, get hashed, stay reclaimable — it never residents the whole file), and reports the first mismatch, naming the damaged section.

use plugmem_host::{Config, Database};

let ro = Database::open_readonly("agent.plugmem", Config::default())?;
// Verify every container byte, a slice at a time.
for step in ro.scrub()? {
    let progress = step?; // Err(Corrupt) names the first damaged section
    // e.g. report progress.done_bytes / progress.total_bytes to a UI
    let _ = progress;
}

recover() — Tier 2 salvage. For content corruption (bad text bytes, a broken vector bijection): it opens the source, drops the facts that fail verify()’s per-fact checks, compacts the survivors and their indexes, and writes a fresh image to a new file — leaving the source untouched as evidence. It returns a RecoverReport { kept, dropped_text, dropped_vector }. It is disk-first (the source opens as an mmap overlay and the two big pools stream through temp files), so peak RAM tracks the record count — a database larger than RAM can be recovered, as long as its graph fits.

use plugmem_host::{Config, Database};

// now = a millisecond timestamp; dst must differ from src.
let report = Database::recover("agent.plugmem", "agent.recovered.plugmem",
                               Config::default(), 1_784_000_000_000)?;
println!("kept {}, dropped {} text + {} vector",
         report.kept, report.dropped_text, report.dropped_vector);

What recover does not do. Structural damage — a snapshot that will not even parse — is not salvageable here: the source fails to open and recover returns the typed error; restore from a backup instead (Tier 0).

Recovery layers (first release). Most recovery is not salvage at all:

• Tier 0 — restore. A snapshot is one atomic file (tmp + fsync + rename); back it up and copy it back. scrub() tells you when to. This covers the overwhelming majority of cases.
• Tier 1 — regenerate. Re-ingest from your upstream source (logs, documents) into a fresh database.
• Tier 2 — recover(). Content-corruption salvage, as above.

Maintenance policy

Configured through the builder, executed inside the same critical section as the operation that triggered it — there are no background threads, matching the engine’s own philosophy:

knob	default	effect
snapshot_every_ops	1024	full snapshot + journal reset after N mutations
snapshot_journal_bytes	4 MiB	…or when the journal outgrows this
maintain_every_forgets	off	optional auto-maintain (physical purge)
—	always on	re-shard when the layout no longer fits the data

maintain is policy-driven. The default Auto path first checks whether anything is pending; with no tombstones, stale text index or vector tail to optimize, it returns a no-op report without rewriting the snapshot. When work is pending, host maintenance stays disk-first: text and vector pools stream through scratch files, ordinary BM25 compaction filters existing postings, and HNSW work is bounded unless a full rebuild is explicitly requested.

maintain_with_options selects the policy explicitly. No mode ever drops a fact revision or an edge version — what the heavier modes buy is bytes and index freshness, never less history.

mode	what it does	cost
Auto	only pending work; no-op when there is none	bounded
Compact	purge tombstones, compact storage and indexes	O(live records)
ReindexText	rebuild BM25 by re-tokenizing stored text	O(text)
OptimizeVectors	build or advance the vector graph	O(vectors)
Full	rebuild everything, fully optimize vectors, repack the edge arenas	O(database)

Full is the only mode that repacks the edge arenas. Relinking many relations fragments them — the incoming mirror is keyed by the far endpoint, so interleaved runs keep splitting pages in half — and rewriting them in key order packs the pages again. Measured over 200 relations relinked 1000 times (200k retained versions): 31.9 MB → 23.4 MB, 59 ms, every version kept.

The same selection is exposed by plugmem maintain --mode <mode>, the mode argument of the MCP plugmem_maintain tool, and maintain(mode?) in the Node bindings.

Embedders

The Embedder trait is two methods (dim, batched embed). OpenAiCompatEmbedder speaks the /v1/embeddings shape that OpenAI, Ollama, LM Studio, vLLM and llama.cpp-server share — there is no provider-specific client because there is no provider-specific protocol. The dimension is configured explicitly (no startup probe); a server answering with a different one is a typed error. Tests run against a local mock — no network in CI.

embed takes &self, and the trait requires Send + Sync, because an embedder is a client of a remote service rather than a piece of mutable state. That is what lets every caller share one instance with no lock in front of it: SharedEmbedder is a plain refcount, a Database holds its embedder unlocked, and concurrent verbs sit in the provider at the same time instead of queueing behind one HTTP request. An implementation that does need mutable state (a cache, a rate-limit budget) brings its own interior mutability, which is the only place that knows what may overlap.

Feature flags

• serde — Serialize/Deserialize on the public data types (FactSnapshot, ExportedFact, RecoverReport, FsyncPolicy), forwarding to plugmem-core/serde. Off by default. HostError is deliberately not covered — it wraps std::io::Error, which is not serializable.
• counters — deterministic work counters for the perf gates, forwarded to plugmem-core/counters. Do not enable it in normal use — it is a single-threaded measurement build only. The arena’s counter Cells are not Sync, so with counters on the engine lock falls back from an RwLock to a Mutex: the read verbs then serialize instead of running concurrently. The public API is identical either way — only the internal lock (and thus read concurrency) changes. Leave it off to keep concurrent readers; reach for it only when measuring operation counts in a specific scenario.

License

MIT. Native host layer for the plugmem engine: file-backed storage with exclusive locking, a thread-safe database handle with a maintenance policy, and embedding providers.

This crate is the “point it at a file and go” Rust experience:

use plugmem_host::{Config, Database, RecallQuery, RememberInput};

let (db, _report) = Database::open("agent.plugmem", Config::default())?;
db.remember(RememberInput::text(1_784_000_000_000, "prefers tokio"))?;
let out = db.recall(RecallQuery::text(1_784_000_100_000, "runtime?"))?;
println!("{}", out.rendered);

Concurrency model: one file has one owning process — a second open is refused with HostError::Locked; within the process, clone the Database handle across threads and agents; different files are fully independent. Embedding calls run outside the database lock.

With the default config feature, the host also accepts the shared config.toml format through Settings::load and read_config. The SETTINGS.md file is the reference documentation for that format, not an input file. Disable the feature with default-features = false when a caller wants only programmatic Config construction.

Modules

fact_flags

Bit flags of FactRecord::flags.

Structs

Config

Full engine configuration with the defaults.

Database

A clonable, thread-safe handle to one database file. See the module docs for the concurrency model.

DatabaseBuilder

Tuning knobs of a Database. Construct through Database::builder.

DbEntry

One database as the registry knows it.

DbName

A validated database name — the only thing a workspace resolves.

Description

What a caller says about a database.

EdgeId

Identifier of an edge version in the temporal entity graph.

EntityId

Identifier of an entity — a graph node created lazily on first mention.

ExportPage

One bounded page of currently-open facts.

ExportedFact

One exported fact — the human-readable, id-free shape Database::export dumps and an importer re-remembers. Internal ids and recorded_at are the engine’s bookkeeping and are not preserved across a round-trip; the knowledge itself (text, subject name, tags, validity start) is.

FactId

Identifier of a fact — the unit of memory.

FactRecord

The unit of memory: one fact (48-byte slot, Uniform arena).

FactSnapshot

An owned view of one fact — Memory::get returns borrows that cannot cross the lock, so the database hands out copies.

FileScratch

A host Scratch over a temp file (milestone H): sequential appends go through a buffered writer; freeze flushes and memory-maps the file, so the staged pool is read (randomly and sequentially) straight from the map instead of RAM. Dropping it unmaps and deletes the temp file.

FileStorage

File-backed Storage holding an advisory lock on its database.

LinkInput

Input of link.

MaintainReport

Report of a maintain pass.

MaintenanceOptions

Options for a maintenance pass.

MemScratch

In-memory Scratch: a growable buffer that “freezes” to a borrow of itself. The reference implementation — it backs tests, and because it drives the streaming path with no files it is the vehicle for the disk_first == in_memory property test. It stages in RAM, so it does not save RAM; a host Scratch over a temp file is what bounds RAM in practice.

NullEmbedder

The no-op embedder: dimension 0, never called by the database (a structural-only memory).

OpenAiCompatEmbedder

An /v1/embeddings client for any OpenAI-compatible server.

OpenReport

Report of an open: what the journal replay found.

ReadOnlyDatabase

A read-only database handle backed by a memory-mapped snapshot See the module docs. Send + Sync — share it across threads behind a reference or an Arc.

RecallQuery

A recall request. Default-like construction via RecallQuery::text plus field overrides.

RecallResult

A recall response. Reusable: pass to Memory::recall_into repeatedly and the buffers are recycled.

RecallScratch

Reusable recall scratch — caller-owned, so Memory::recall and Memory::recall_into take &self: many readers can recall the same engine at once, each threading its own scratch (the host wraps one per thread). Carries every buffer a recall mutates — the query-side term/score vectors, the fusion map, and its own tokenizer and name-normalization buffer — so a recall never touches the engine’s write-side scratches. Reused across calls it upholds the zero-alloc invariant.

RecalledEdge

One edge the graph source walked (: agents want the relations, not only the facts).

RecalledFact

One recalled fact.

RecoverReport

The outcome of a Database::recover salvage.

ReindexReport

What a Workspace::reindex pass did.

RememberInput

Input of remember and revise.

RememberOutcome

Result of remember/revise.

Scrub

A resumable, byte-level container scrub over a memory-mapped snapshot (— the ZFS-scrub model). Obtained from ReadOnlyDatabase::scrub.

ScrubProgress

Progress of an in-flight ScrubCursor scan.

SettingDoc

Documentation for one supported config.toml key.

Settings

Resolved runtime settings: the engine config, an optional embedder, and the maintenance policy. The wrapper-specific knobs (import batch size, server workers) are read separately from the same read_config table.

SettingsHelp

Runtime access to the complete config.toml help catalogue.

ShardLayout

Shard counts for every arena group.

SharedEmbedder

One embedder handed to several databases.

Similar

One similar-fact hint.

Stats

Engine size counters. Every field is an O(1) read; the struct is #[non_exhaustive] so later stages (database identity markers, HNSW state) can extend it without a breaking change.

UnlinkInput

Input of unlink.

Workspace

Many databases in one directory, opened on demand and kept open for a while.

WorkspaceLayout

Where a workspace keeps its files.

WorkspaceLimits

How many databases a workspace keeps open, and for how long.

WorkspaceSettings

The [workspace] section: where a directory of named databases lives, and how many of them to keep open.

Enums

Error

Every way an engine call can fail.

FsyncPolicy

When journal appends reach the disk.

HostError

Every way the host layer can fail. Engine failures pass through as HostError::Engine; everything filesystem- or network-shaped is typed here.

IfMissing

Whether resolving a name that has no file yet creates one.

MaintenanceMode

The maintenance work requested by a caller.

NameProblem

Why a string is not a usable database name.

SettingScope

Which runtime surface owns a setting.

SettingsError

A configuration error: malformed TOML, a bad [engine] value, or an [embedder] section missing a required field. Distinct from HostError (which covers opening the database once settings are resolved).

SimilarReason

Why a fact was flagged as similar.

WorkspaceError

Every way a workspace operation can fail.

WorkspaceIssue

Something Workspace::verify found. Reported, never repaired — a workspace is a directory a person can edit, and guessing at their intent is how a consistency check becomes a data-loss bug.

Constants

ARCHIVED_TAG

Tag marking a database as archived: still present, still openable, no longer somewhere new work should go.

DEFAULT_IDLE_TIMEOUT_MS

Default idle window before a pooled handle is closed.

DEFAULT_MAX_OPEN

Handles kept open by default. Small on purpose: reopening a database the size of a chat is milliseconds, so caching is a latency win, not a requirement, and every extra handle is a lock somebody else cannot take.

DEFAULT_SCRUB_BUDGET

Default number of bytes a ScrubCursor hashes per next() slice The scrub slice-size bench sweeps 64 KiB…64 MiB and finds throughput essentially flat (the scan is xxh3/memory-bandwidth-bound, not per-slice-overhead-bound), so the budget is a pacing quantum, not a throughput knob: 1 MiB is ~sub-millisecond per slice — fine-grained enough to pause, cancel or report progress smoothly, with negligible overhead.

ENTRY_TAG

Tag every registry record carries, so the registry’s own facts are distinguishable from anything else written into that file.

MAX_DB_NAME

Longest database name a workspace accepts, in bytes.

MAX_OPEN_CEILING

Most databases a pool will hold open, whatever it is configured with.

SELF_ENTITY

The entity a database’s self-description hangs off.

VALID_TO_OPEN

valid_to value of an open fact (“true now”).

Traits

Embedder

Turns texts into embedding vectors. Batched by design — providers price and perform far better on batches.

Scratch

An append-only staging area: build it sequentially with write, then freeze it into a readable byte view for random and sequential reads. Dropping it discards the storage.

Functions

default_config_dir

The platform’s conventional per-user config directory.

default_config_path

The default config file path, when a platform user directory is available.

default_data_dir

The platform’s conventional per-user data directory.

default_database_path

The default persistent per-user database path.

read_config

Reads and parses config.toml, or Ok(None) if none applies. An explicit flag path must exist (a read error is a usage error); otherwise $PLUGMEM_CONFIG, then the platform path from crate::default_config_path, are read only if present. Wrappers call this once, then pass the table to Settings::from_table and also read their own keys (batch size, workers) from it.

settings_help

Returns the shared settings catalogue used by host, CLI, MCP and NAPI.

Type Aliases

Opener

Opens one database at a path. Supplied by the caller so this module stays out of the business of configuration — crate::Settings builds one that applies the engine config, the maintenance policy and a shared embedder.