# Weavatrix Memory
`weavatrix-memory` is the event-sourced temporal evidence and context-retrieval
engine used by Weavatrix. It turns immutable code, task, decision, test,
failure, and handoff events into small evidence-carrying graphs for a specific
task and token budget.
The crate is a standalone MIT-licensed Rust library. `weavatrix-rust` composes
it into the wider repository-intelligence engine, while the `weavatrix`
product exposes that engine through MCP. This crate owns temporal memory,
projection, persistence contracts, retrieval, and context compilation; it does
not own MCP transport or a long-running server.
Its deterministic core does not require an LLM, vector database, external
graph database, async runtime, system clock, or Git executable. Durable storage
is available without requiring a database.
The minimum supported Rust version is 1.89.
## Why it exists
Generic agent memory usually answers “what looks similar?” Engineering work
also needs exact answers to:
- What was true on this branch at that time?
- What did the agent know when it made the decision?
- Was this approach already tried and why did it fail?
- Which commit, symbol, test, benchmark, or user correction supports the fact?
- What is the smallest reproducible evidence graph that fits this context
window?
Weavatrix Memory keeps the immutable history and derives a fresh graph for each
query instead of mutating one opaque “current truth”.
## Current guarantees
- Atomic per-stream append.
- Owned-batch append path that avoids cloning caller-owned payloads.
- Receipt-only append path that moves committed payloads directly into storage.
- Optimistic concurrency with `NoStream`, `Exact`, and `Any` expectations.
- Globally ordered cursors and independently versioned streams.
- Globally unique event identifiers.
- Strict replay validation for cursor gaps and stream-version gaps.
- Framed filesystem journal with table-driven CRC32C corruption detection.
- Standard-library exclusive writer locks and `SyncAll` durability by default.
- Strict open by default and explicit recovery for incomplete trailing batches.
- Immutable generation-named projection snapshots and validated resume.
- Explicit-ack catch-up subscriptions with redelivery before acknowledgement.
- Caller-provided timestamps and identifiers for reproducible tests.
- Separate valid-time and known-time queries.
- Evidence required for every memory relation and retraction.
- Explicit supersession without deleting historical facts.
- Validated bulk projection with compact dual-CSR incident indexes.
- Borrowed temporal views for zero-copy lexical and vector indexing.
- Deterministic projection into canonical `weavatrix-graph` snapshots.
- Provider-neutral literal, lexical, semantic, and hybrid retrieval with
deterministic reciprocal-rank fusion.
- Provider-neutral auto-extraction with strict, scope-aware entity linking and
idempotent event plans.
- Hard context budget with a replaceable token estimator and compilation
receipt.
- Repository and branch-scoped projections.
- Dependency-free, versioned compact binary projection snapshots.
- Optional size-bounded LZ4 envelopes that keep incompressible input raw.
- Optional XChaCha20-Poly1305 authenticated encryption with key identifiers,
purpose-bound AAD, and OS-generated nonces.
- Optional guarded mmap reads for immutable snapshot generations.
- Belief revision, reasoning-gap, drift, and consolidation analysis over the
canonical graph.
- Exact-evidence retrieval metrics and adapters for public memory benchmarks.
## Architecture
```text
source / AST / issue / agent observation
|
v
ExtractionProvider -> strict EntityLinker -> reviewed event plan
|
v
append-only events
|
v
in-memory or framed file event store
|
v
strict replay validator + optional snapshot resume
|
v
bitemporal memory projection
|
+<-- lexical / semantic RetrievalProvider
|
v
immutable weavatrix-graph snapshot
|
+--> belief / gap / drift / consolidation reports
|
v
budgeted context compiler + receipt
```
The in-memory and filesystem stores implement the same `EventStore` contract.
Database, Git, lexical, semantic, and MCP adapters belong behind separate
interfaces or higher-level Weavatrix modules.
The source tree follows enforced inward dependencies:
| Temporal model | IDs, timestamps, events, evidence, facts, views, shared errors | None |
| Projection | Replay cursors, bitemporal projection, graph projection | Temporal model |
| Storage | Codecs, event stores, snapshots, compact snapshot adapter | Temporal model, projection |
| Retrieval | Context compilation, rank fusion, analytics, evaluation | Temporal model, projection |
| Extraction | Provider port, entity linker, validated event plans | Temporal model, projection |
| Facade | Stable crate-root exports | All internal layers |
Internal modules import the owning module rather than routing dependencies
through the public facade. `.weavatrix/architecture.json` enforces zero runtime
cycles, no dependency exceptions or baseline debt, at most 300 physical lines
per Rust file, and at most 100 physical lines per function. Integration tests,
benchmarks, and the evaluation CLI are verification adapters outside the
runtime layer graph.
Use `append` when the pending events must remain available to the caller. Use
`append_owned` to transfer a batch into the store without cloning its input
payloads. Use `append_owned_receipt` when the caller only needs committed
positions; this avoids cloning committed payloads back out of the store.
## Durable storage
`FileEventStore` writes each append batch as one checksummed frame. Memory state
is updated only after the complete frame has been written and flushed or synced.
On reopen, the journal rebuilds and validates global positions, stream versions,
and event identifiers.
The default `RecoveryPolicy::Strict` rejects any truncated tail. Explicit
`TruncatePartialTail` recovery removes only an incomplete final batch. Invalid
headers, impossible sizes, malformed payloads, and checksum failures are never
silently repaired.
The file store is intentionally one-writer-per-journal. It acquires an
OS-backed exclusive lock through the Rust standard library and retains the
file-length guard against non-cooperating writers. A competing `FileEventStore`
fails before scanning or appending, and the OS releases the lock after process
termination. Applications needing coordinated concurrent writers should
provide a database-backed `EventStore`.
`Durability::SyncAll` is the default and syncs file data plus metadata.
`SyncData` and `Flush` remain explicit lower-cost choices for workloads with
weaker persistence requirements.
Serialization is injected through the `Codec<T>` trait. The crate has no
default codec, compression, encryption, or mmap dependency. Storage features
are opt-in:
| `json` | `JsonCodec`, powered by Tokio-free `blazingly-json` |
| `compression` | Size-bounded `Lz4Codec<C>` |
| `encryption` | `XChaCha20Codec<C, K>` and key-provider contracts |
| `mmap` | Guarded read-only snapshot mapping |
| `secure-storage` | `compression`, `encryption`, and `mmap` |
The `json` feature has no direct or runtime `serde_json` dependency.
`blazingly-json` implements the same Serde-based `JsonCodec` contract, so stored
JSON and the public codec API remain unchanged.
```toml
[dependencies]
weavatrix-memory = { version = "0.3.2", features = ["secure-storage"] }
```
`FileSnapshotStore` writes immutable, position-named snapshots through a
temporary file and atomic rename. `replay_tracked` produces the exact cursor;
`resume` rejects any gap between that cursor and the supplied event tail.
`CompactSnapshotCodec` stores the complete replay cursor, temporal revisions,
facts, supersessions, and retractions in a bounds-checked versioned binary
format. Lookup and CSR indexes are derived and validated during decode rather
than serialized redundantly.
Codec wrappers compose in encode order. Compress before encrypting:
```rust,ignore
let codec = XChaCha20Codec::new(
Lz4Codec::new(CompactSnapshotCodec, 512 * 1024 * 1024)?,
StaticKey::new("2026-q3", key_from_secret_manager)?,
b"projection-snapshot",
512 * 1024 * 1024,
)?;
let snapshots = FileSnapshotStore::open(
directory,
"context",
codec,
SnapshotOptions::default(),
)?
.with_memory_mapped_reads();
```
`Lz4Codec` records the original length and rejects it before allocation when it
exceeds the configured limit. It stores raw bytes when compression would grow
the payload. `XChaCha20Codec` authenticates the envelope header and caller
context as AAD; the key identifier remains visible so an `EncryptionKeys`
provider can retain old decryption keys during rotation. It is a raw-key API,
not a password KDF.
`StaticKey` zeroizes its owned 256-bit key on drop, and the encryption wrapper
zeroizes temporary plaintext buffers after encode and decode. Applications must
still source keys from a secret manager or KMS, protect any copies made before
construction, and never use a deterministic `NonceSource` outside tests.
Authentication failures, wrong contexts, unavailable keys, malformed envelopes,
and oversized plaintexts fail closed.
Memory mapping is opt-in because it is a workload tradeoff, not a universal
speedup. Snapshot generations created by this store are never overwritten.
The mmap adapter holds a shared advisory lock, but a non-cooperating external
process can still truncate a mapped file; all writers must honor the lock and
immutable-generation contract.
`CatchUpSubscription` does not advance its checkpoint during `poll`. Consumers
must explicitly acknowledge a delivered position, so a failed handler receives
the same events again.
## Example
```rust
use weavatrix_memory::{
AgentId, ContextCompiler, ContextRequest, EntityId, EventId, EventStore,
Evidence, ExpectedVersion, FactId, InMemoryStore, MemoryEvent, MemoryFact,
MemoryNode, MemoryProjection, NewEvent, SessionId, StreamId, Timestamp,
replay,
};
fn at(value: i64) -> Timestamp {
Timestamp::from_unix_micros(value)
}
let agent = AgentId::new("agent:codex")?;
let session = SessionId::new("session:714")?;
let task = EntityId::new("task:714")?;
let file = EntityId::new("file:query-builder")?;
let recorded_at = at(20);
let nodes = [
MemoryNode::new(task.clone(), "task", "Fix one-day query accuracy")?,
MemoryNode::new(file.clone(), "file", "query-builder.rs")?,
];
let fact = MemoryFact::new(
FactId::new("fact:714:affected")?,
task.clone(),
"affects",
file,
at(10),
recorded_at,
agent.clone(),
session.clone(),
Evidence::new("test", "query-accuracy-suite")?,
)?;
let payloads = vec![
MemoryEvent::NodeUpserted { node: nodes[0].clone() },
MemoryEvent::NodeUpserted { node: nodes[1].clone() },
MemoryEvent::FactRecorded { fact },
];
let pending = payloads
.into_iter()
.enumerate()
.map(|(index, payload)| {
let event_type = payload.event_type();
NewEvent::new(
EventId::new(format!("event:{index}"))?,
event_type,
recorded_at,
recorded_at,
agent.clone(),
session.clone(),
payload,
)
})
.collect::<Result<Vec<_>, weavatrix_memory::MemoryError>>()?;
let stream = StreamId::new("task:714")?;
let mut store = InMemoryStore::default();
store.append(&stream, ExpectedVersion::NoStream, &pending)?;
let projection: MemoryProjection = replay(&store.load_all(None, usize::MAX))?;
let request = ContextRequest::new(vec![task], at(30), at(30), 2_000)?;
let bundle = ContextCompiler::default().compile(&projection, &request)?;
assert_eq!(bundle.graph.edge_count(), 1);
assert!(bundle.receipt.estimated_tokens <= 2_000);
# Ok::<(), weavatrix_memory::MemoryError>(())
```
## Bitemporal semantics
`valid_at` asks when a fact was true in the modeled world. `known_at` asks what
the system had recorded by a given moment. A correction recorded today can
replace a fact from last month without rewriting what an agent knew yesterday.
Facts retain:
- valid interval;
- observation and recording times;
- agent and session identities;
- confidence in basis points;
- one or more evidence records;
- the fact they supersede, when applicable.
## Auto-extraction and entity linking
`ExtractionProvider` isolates parsing or model inference from the deterministic
memory core. Providers return typed local mentions, relation candidates,
confidence, optional byte spans, stable IDs, external IDs, and candidate hints.
`AutoExtractionEngine` then:
- validates UTF-8 spans, temporal intervals, identifiers, and provider identity;
- links by stable ID, external ID, scoped normalized label, alias, or provider
hint;
- applies an explicit minimum score and winner margin;
- reports ambiguous and unresolved endpoints instead of guessing;
- creates deterministic node and fact IDs for unmatched entities;
- preserves source, locator, digest, provider, span, agent, session, and
confidence provenance;
- returns a non-mutating event plan suitable for review and atomic append.
`EntityLinker` can be built once from a temporal `MemoryView` and reused for a
batch. This keeps AST, issue-tracker, model, and future semantic adapters outside
the core while giving all of them the same validation and linking contract.
## Context compilation
`ContextCompiler` can start from exact entity identifiers or from one or more
`RetrievalProvider` implementations. A provider returns exact entity IDs from
literal, lexical, semantic, or hybrid search. Integer reciprocal-rank fusion
combines their ranks without pretending BM25 and vector scores share a scale;
the result retains provider, channel, rank, and raw-score provenance.
`MemoryProjection::view_ref` exposes the same bitemporal selection as `view`
while borrowing node, fact, and evidence payloads. A future
`weavatrix-search-vector` adapter can index this view and implement
`RetrievalProvider`; the memory crate therefore does not depend on an embedding
model or vector engine. Provider-local scores are used only to establish each
provider's rank, while reciprocal-rank fusion remains scale-independent.
After seed resolution, the compiler traverses selected relations in both
directions, ranks nearby evidence deterministically, and stops before exceeding
the configured budget. The receipt records:
- projection time and source event position;
- estimator identity and estimated usage;
- examined and selected fact counts;
- omissions caused by budget;
- facts excluded by repository or branch scope.
The built-in byte estimator is deterministic and dependency-free. Applications
that need model-exact counts implement the small `TokenEstimator` trait.
## Memory analytics
`MemoryAnalytics` operates on bitemporal projections and canonical
`weavatrix-graph` topology:
- belief revision finds explicit corrections and competing targets, then
traces their downstream confidence cascade;
- reasoning-gap analysis reports unsupported decisions, single-source
inferences, weak foundations, stale evidence, and unstable revision chains;
- drift reconstructs immutable belief timelines and correction rates;
- consolidation returns a deterministic plan for duplicate supersession,
orphan review, and revision checkpoints without deleting history.
## Accuracy evaluation
The provider-neutral evaluator reports Hit@K, Recall@K, nDCG@K, and MRR from
exact evidence identifiers. The repository includes adapters for the public
[LoCoMo](https://github.com/snap-research/locomo) and
[LongMemEval](https://github.com/xiaowu0162/LongMemEval) formats plus a
coding-agent regression suite. See [benchmark instructions](benchmarks/README.md).
The full official files were parsed successfully in the local verification
run: 1,978 evidence-bearing `LoCoMo` questions and 470 non-abstention
LongMemEval-S questions. The dependency-free literal smoke baseline produced:
| `LoCoMo` | 0.2230 | 0.3918 | 0.3559 | 0.2980 |
| LongMemEval-S cleaned | 0.6787 | 0.8894 | 0.7883 | 0.7679 |
| Coding-agent v1 (7 cases) | 0.8571 | 1.0000 | 1.0000 | 0.9286 |
These are adapter smoke results, not claims about the future
`weavatrix-search` or semantic/vector provider.
## Benchmarks
The repository contains executable, median-based benchmarks rather than copied
one-off timings. On an Intel Core Ultra 7 255U, Windows 11, Rust 1.97.1,
`--release`, a 100,000-event run produced:
| In-memory evidence append + load | 97.313 ms | 1,027,608 events/s |
| Owned append, committed envelopes returned | 61.156 ms | 1,635,170 events/s |
| Receipt-only owned append | 39.990 ms | 2,500,643 events/s |
| `cqrs-es` 0.5.0 evidence append + load | 144.972 ms | 689,787 events/s |
| CRC32C JSON append + `sync_data` | 336.196 ms | 297,445 events/s |
| Durable reopen + index validation | 337.736 ms | 296,088 events/s |
| Bitemporal projection replay | 91.603 ms | 1,091,667 events/s |
The competitor workload carries the same event identifier, event type,
occurred/recorded timestamps, and agent/session identities. Weavatrix
additionally checks identifier uniqueness and optimistic concurrency and
assigns a global cursor. Each side performs append followed by a cloned stream
load. Fixtures are created outside the timed region; nine samples are measured
after two warmups and the median is reported. Under this evidence-equivalent
contract, Weavatrix used 32.9% less time than `cqrs-es` in this run. The owned
and receipt-only rows expose progressively narrower return contracts and avoid
unneeded output clones. These are
local measurements, not universal hardware claims.
An exploratory Redis 8.8 Streams cross-check used a 512-byte payload, one
client, Docker-local `redis-benchmark`, and AOF enabled. With
`appendfsync always`, `XADD` reached 7,680 events/s at pipeline 100; changing to
the default-like `everysec` policy reached 200,000 events/s but can lose about
one second of writes. This is not an output-equivalent competitor benchmark:
it excludes client-side JSON serialization, projection replay, identifier
validation, and optimistic concurrency. It confirms the useful Redis pattern
is batched writes plus an explicit durability tradeoff. `FileEventStore`
already writes one checksummed frame and performs one selected sync per append
batch, while Redis remains the appropriate separate layer when coordinated
multiwriter access or replication is required.
The graph-memory harness also compares against `agentic-memory` 0.4.2. At
100,000 nodes and 300,000 edges:
| Depth-2 context, identical 13-node/33-edge output | 0.193 ms | 5.042 ms | Weavatrix 26.1x faster |
| Validated `try_from_parts` + dual CSR | 71.076 ms | 42.191 ms | `agentic-memory` 1.68x faster |
| Strict replay of 400,000 envelopes | 494.020 ms | n/a | Different contract |
The context row is output-equivalent. The bulk-construction row compares each
crate's parts constructor, but the contracts are still not identical:
Weavatrix validates node and fact domains, evidence, uniqueness, endpoints, and
supersession before building both CSR directions. The harness records that
`agentic-memory::MemoryGraph::from_parts` accepts a dangling edge. The new bulk
path reduced the measured construction gap from 18.2x to 1.68x without dropping
those checks; strict event replay remains a separately reported operation.
The current-view path was also profiled at 100,000 nodes and 300,000 facts.
Replacing ordered membership checks with a validated all-nodes-visible fast
path and adding a borrowed view produced:
| Owned bitemporal `MemoryView` | 492.755 ms | 207.412 ms | 2.38x |
| Borrowed `MemoryViewRef` | 492.755 ms | 10.957 ms | 45.0x |
The owned row returns the same owned node/fact payload contract before and
after. The borrowed row deliberately returns references and is intended for
search/vector indexing and other read-only consumers. Timings are local medians
from the executable competitor harness, not universal hardware claims.
At 10,000 nodes and 30,000 facts, the versioned compact snapshot codec measured:
| Encode | 11.647 ms | 36.878 ms | Compact 3.17x faster |
| Decode and validate indexes | 121.508 ms | 186.702 ms | Compact 1.54x faster |
| Snapshot size | 3,824,378 bytes | 9,543,533 bytes | Compact 59.9% smaller |
Both decoders restore the same projection and rebuild validated lookup and CSR
indexes. The benchmark reports nine samples after two warmups.
The `blazingly-json` migration was also measured against a temporary
`serde_json` oracle in the same process, with operations interleaved on the
same 9,543,533-byte snapshot. Two complete runs produced stable relative
results despite unrelated system load:
| Encode | 1.16x-1.23x |
| Decode and validate indexes | 1.13x |
The oracle dependency was removed after the differential measurement;
`serde_json` remains in `Cargo.lock` only through the isolated
`agentic-memory` and `cqrs-es` development benchmarks.
The secure-storage harness first serializes a 100,000-node, 300,000-fact
projection into 38,828,001 compact bytes, then measures only the byte transform.
The copy row is the `Vec` allocation/copy baseline:
| Copy only | 9.649 ms | 9.594 ms | 38,828,001 |
| LZ4 | 32.216 ms | 27.322 ms | 5,249,623 |
| XChaCha20-Poly1305 | 70.923 ms | 71.745 ms | 38,828,059 |
| LZ4 then XChaCha20-Poly1305 | 51.154 ms | 37.384 ms | 5,249,681 |
For this repetitive evidence fixture, LZ4 reduced the snapshot by 86.5%.
Authenticated encryption added 58 bytes. The combined path encrypts only the
compressed payload; it remained 86.5% smaller than compact binary alone.
Snapshot loads include directory selection, frame bounds and CRC32C checks,
complete projection decode, and index validation. Buffered and mmap order is
alternated on every sample:
| 10,000 nodes / 30,000 facts | 3,734,384 | 67.870 ms | 65.313 ms | mmap 3.8% faster |
| 100,000 nodes / 300,000 facts | 38,828,001 | 709.873 ms | 730.248 ms | mmap 2.9% slower |
The mmap path removes the encoded-payload heap allocation and copy, but its
mapping, locking, and page-fault overhead kept both cached local loads in the
same performance range and changed which path won. Buffered reads therefore
remain the default; mmap is for reducing peak heap and enabling large
immutable-file access, not a claimed speedup. Both tables report nine samples
after two warmups, with transform and read order alternated between samples.
The extraction harness indexes a 100,000-entity catalog containing label, alias,
and external-ID keys, then resolves 10,000 mentions:
| Catalog build, 100,000 entities | 449.895 ms | 222,274 entities/s |
| Reused indexed linker, 10,000 mentions | 36.683 ms | 272,604 links/s |
| Validated extraction event plan, 10,000 mentions | 69.444 ms | 144,001 mentions/s |
Provider output and fixtures are created outside the indexed-link timing. Each
row reports the median of nine samples after two warmups.
## Development
```console
cargo fmt --all --check
cargo clippy --all-targets --all-features -- -D warnings
cargo test --all-features --lib --tests
cargo audit
cargo bench --bench replay
cargo bench --features json --bench durable
cargo bench --bench event_store_competitors
cargo bench --bench memory_competitors
cargo bench --features json --bench snapshot_codecs
cargo bench --features secure-storage --bench secure_storage
cargo bench --bench extraction
cargo run --release --all-features --bin weavatrix-memory-eval
```
Set `WEAVATRIX_BENCH_EVENTS` to change any workload. The in-memory replay
benchmark runs two warmups and reports nine measured iterations. The durable
benchmark reports five isolated append, reopen/index, and projection samples.
The competitor benchmarks report nine samples after two warmups. Set
`WEAVATRIX_BENCH_NODES` and `WEAVATRIX_BENCH_EDGES_PER_NODE` for the graph
workload.
## Status
The public API is experimental before `1.0`. The filesystem journal and
snapshots are local embedded stores, not a distributed database. Exclusive
writer exclusion is built in; concurrent multiwriter scheduling, ACL policies,
Git history, MCP tools, compaction, and database adapters remain separate
layers.
## License
MIT