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CONTRIBUTING.md

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# Contributing to Mohawk Inference Engine
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Thanks for helping improve Mohawk Inference Engine. This repository is intentionally small, but it has a few conventions that keep the prototype and release docs easy to follow.
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## Before You Start
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- Read [README.md](README.md), [docs/ARCHITECTURE.md](docs/ARCHITECTURE.md), and [docs/PQC_INTEGRATION.md](docs/PQC_INTEGRATION.md).
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- If you are touching secure transport or session logic, run the focused prototype tests before opening a PR.
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- Keep changes small and scoped. This repo favors incremental updates over broad rewrites.
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## Development Setup
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```bash
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python -m pip install -r prototype/requirements.txt
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```
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Optional secure-local setup:
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```bash
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export OQS_INSTALL_PATH=/usr/local
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```
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## Code Style
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- Prefer readable, explicit Python over clever abstractions.
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- Preserve the current module structure under `prototype/`.
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- Keep doc updates in sync with code changes.
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- Avoid adding extra dependencies unless they clearly reduce complexity or improve correctness.
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## Testing Expectations
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Run the relevant tests for the slice you changed:
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```bash
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python -m pytest -q prototype/test_oqs_hybrid.py prototype/test_secure_hybrid_integration.py prototype/test_concurrency_smoke.py prototype/test_secure_run.py -q -rA
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```
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If you modify the load harness or telemetry path, also run the broader prototype smoke flow with the secure worker.
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## Pull Requests
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- Use a short imperative commit message.
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- Include a note about any environment variables or native libraries required to reproduce the change.
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- Mention any tests you ran in the PR description.
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## Release Hygiene
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- Do not commit generated artifacts, virtual environments, or local caches.
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- If you update the secure flow or binding assumptions, document the runtime requirement in [docs/PQC_INTEGRATION.md](docs/PQC_INTEGRATION.md).

LICENSE

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README.md

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# Mohawk-Inference-Engine
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build a much faster, leaner, and more secure local inference and management engine than a standard LM Studio setup
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# Mohawk Inference Engine
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Mohawk Inference Engine is a local inference and management stack for splitting model execution across multiple devices while keeping transport and session handling secure. The project focuses on three capabilities that are hard to get in one place in lightweight desktop tools: multi-device layer splitting, PQC-secured edge offload, and high-concurrency session management.
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## What This Repo Contains
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- A toy layer-splitting runtime that partitions a model into slices and runs them across workers.
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- A secure controller/worker path with X25519 plus optional liboqs-backed hybrid KEM support.
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- A session manager and load harness for concurrent encrypted inference runs.
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- Telemetry and timing hooks for preload and execute paths.
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## Quick Start
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```bash
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python -m pip install -r prototype/requirements.txt
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python prototype/run_demo.py
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```
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For the secure prototype, start the secure worker in a separate terminal:
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```bash
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python prototype/worker_secure.py --port 8003
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```
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If you have a local liboqs install, set:
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```bash
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export OQS_INSTALL_PATH=/usr/local
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```
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## Recommended Reading
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- [Project scope](docs/SCOPE.md)
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- [Architecture spec](docs/ARCHITECTURE.md)
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- [PQC integration notes](docs/PQC_INTEGRATION.md)
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- [Getting started guide](docs/GETTING_STARTED.md)
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- [Contributor guide](CONTRIBUTING.md)
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## Testing
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Run the focused prototype checks with:
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```bash
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python -m pytest -q prototype/test_oqs_hybrid.py prototype/test_secure_hybrid_integration.py prototype/test_concurrency_smoke.py prototype/test_secure_run.py -q -rA
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```
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## Release Notes
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- Release `v0.1.0` includes the liboqs devcontainer, secure prototype path, telemetry, and the scaling harness.
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- The repository is licensed under Apache-2.0. See [LICENSE](LICENSE).

docs/GETTING_STARTED.md

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# Getting Started
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This guide covers the shortest path from a fresh clone to running the prototype locally.
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## Prerequisites
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- Python 3.12 or newer
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- `pip`
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- Optional: a native liboqs install if you want the hybrid PQC path to activate
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## Install Dependencies
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```bash
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python -m pip install -r prototype/requirements.txt
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```
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If you have a local liboqs install, export:
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```bash
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export OQS_INSTALL_PATH=/usr/local
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```
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## Run the Demo
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```bash
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python prototype/run_demo.py
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```
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That script compares a single-node baseline against the distributed toy model path.
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## Run the Secure Worker
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```bash
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python prototype/worker_secure.py --port 8003
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```
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The secure path uses the hybrid X25519 + OQS adapter when the binding is present.
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## Run Tests
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```bash
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python -m pytest -q prototype/test_oqs_hybrid.py prototype/test_secure_hybrid_integration.py prototype/test_concurrency_smoke.py prototype/test_secure_run.py -q -rA
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```
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## Useful Docs
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- [README](../README.md)
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- [Architecture](ARCHITECTURE.md)
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- [PQC integration](PQC_INTEGRATION.md)
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- [Contributing](../CONTRIBUTING.md)

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