OC-Sidememory combines a byte-level DFA with transactional semantic state. The DFA checks JSON structure. The semantic guide tracks completed values, contains counters, captures, and immutable membership sets.
For guide state $\sigma$, token $x$, DFA decision $D$, and semantic decision $S$:
A(\sigma,x)=D(\sigma,x)\land S(\sigma,x)
The semantic layer can remove structurally valid candidates, but it cannot add new candidates:
M_{OC}=M_{DFA}\land\neg M_{deny}
Features
| Capability | Behavior |
|---|---|
uniqueItems |
Rejects an exact duplicate in the current array instance |
contains |
Enforces minContains and maxContains over completed direct items |
| Captures | Compares a later property with an earlier property in declared order |
| Imported membership | Checks values against immutable, versioned sets |
| Exact equality | Handles numbers, decoded strings, arrays, and order-independent objects |
| Transactions | Makes probes pure and rejected advances atomic |
| Rollback | Restores bounded token checkpoints, including EOS |
Unsupported schema combinations fail during compilation. See the supported profile and limitations.
Installation
Python:
pip install oc-sidememory
Rust:
cargo add oc-sidememory
From a checkout:
uv sync
uv run maturin develop --release
Python example
Build the vocabulary from a normal Transformers tokenizer. Compile the schema once, then create one guide for each generation sequence.
import json
import oc_sidememory
from transformers import AutoTokenizer
tokenizer = AutoTokenizer.from_pretrained("openai-community/gpt2")
vocabulary = oc_sidememory.Vocabulary.from_transformers(tokenizer)
schema = {
"type": "array",
"items": {"type": "string", "enum": ["red", "green", "blue"]},
"minItems": 3,
"maxItems": 3,
"uniqueItems": True,
}
compiled = oc_sidememory.compile_schema(
json.dumps(schema), vocabulary, tokenizer.vocab_size
)
guide = oc_sidememory.SidememoryGuide(compiled, max_rollback=32)
valid = tokenizer.encode('["red","green","blue"]', add_special_tokens=False)
duplicate = tokenizer.encode('["red","red","blue"]', add_special_tokens=False)
assert guide.accepts_tokens(valid, finish=True)
assert not guide.accepts_tokens(duplicate, finish=True)
accepts_tokens, probe, advance, and mask construction use the same Rust transition routine.
Python does not contain a second semantic validator.
How uniqueness changes a mask
After completing "red" in a unique array:
| Layer | Next item candidates |
|---|---|
| Structural DFA | "red", "green", "blue" |
| Semantic guide | "green", "blue" |
The duplicate is removed before sampling. A direct attempt to advance it is rejected by the same semantic transition.
Exact guarantees
Let $C(v)$ be the canonical value of $v$, and let $H_a$ be the history of live array instance $a$. Uniqueness admits $v$ exactly when:
U(v)\iff C(v)\notin H_a
For predicate $P$, contains counts matching completed direct items:
c_a=\sum_{i=1}^{n}\mathbf{1}[P(v_i)],\qquad l\le c_a\le u
Equality and imported membership use canonical values, not raw JSON spelling or fingerprints:
E(v,r)\iff C(v)=C(r)
I(v,S)\iff C(v)\in S
A probe leaves logical state unchanged:
P_x(\sigma)=\sigma
Rolling back $k$ committed token transitions restores the earlier logical state:
R_k(T_{x_k}(\cdots T_{x_1}(\sigma)))=\sigma
Revision counters and retained allocation capacity are not part of logical state equality.
Command-line interface
oc-sidememory capabilities
oc-sidememory compile --schema schema.json --vocabulary vocabulary.json
oc-sidememory check --schema schema.json --vocabulary vocabulary.json \
--tokens tokens.json --finish
Commands emit versioned JSON. Vocabulary files store token bytes as base64, so token data does not need to be UTF-8. See the CLI reference.
Performance
Mask latency depends on candidate count, token bytes, emitted events, predicate work, equality work, and current semantic history. Recorded release-mode measurements and their environment are in docs/performance.md. They are engineering measurements, not universal throughput claims.
Documentation
| Guide | Subject |
|---|---|
| Architecture | Ownership, transitions, journals, and rollback |
| Python API | Compilation, guides, imports, masks, and exceptions |
| Rust API | Core construction, lifecycle, and error types |
| Extensions v1 | Ordered captures and relations |
| Imported memory | Identity, canonicalization, and lifetime |
| Supported profile | Implemented schema surface |
| Limitations | Explicit boundaries and non-goals |
The example ladder covers uniqueness, contains, capture equality, imported membership, and composed rollback using public APIs.
Development
cargo fmt --all --check
cargo clippy --workspace --all-targets --all-features -- -D warnings
cargo test --workspace --all-features
uv run pytest -q
Deterministic correctness tests require no model or network. See CONTRIBUTING.md and SECURITY.md.
Provenance and license
OC-Sidememory is independently developed from an Apache-2.0 outlines-core source import and is
not endorsed by its upstream authors. See PROVENANCE.md,
MODIFICATIONS.md, NOTICE, and LICENSE.
1 maintainer
Metadata
1 maintainer
Release files for oc-sidememory 0.1.0
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|---|---|
| Size | 1.3 MB |
| Tags | CPython 3.11 macOS 11.0+ ARM64 |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Yes |
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twine/7.0.0 CPython/3.13.14
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Transparency logRelease files / oc_sidememory-0.1.0-cp310-cp310-win_amd64.whl
| Download URL | oc_sidememory-0.1.0-cp310-cp310-win_amd64.whl |
|---|---|
| Size | 1.4 MB |
| Tags | CPython 3.10 Windows x86-64 |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
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Transparency logRelease files / oc_sidememory-0.1.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
| Download URL | oc_sidememory-0.1.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl |
|---|---|
| Size | 1.5 MB |
| Tags | CPython 3.10 Linux glibc 2.17+ x86-64 |
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SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
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Provenance
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