Skip to main content

Local CLI-first AI code review for git diffs with analyzer-backed context.

Project description

Apex Ray logo animation

Apex Ray

CI Docs PyPI Python 3.14+ License: Apache-2.0

Local CLI-first AI code review for git diffs with analyzer-backed context.

Full documentation: dobrotacreator.github.io/apex-ray

Apex Ray reads a git diff, builds compact context packs around changed code, runs optional LLM review through a local CLI provider, verifies findings, and writes Markdown, JSON, and HTML reports. It is designed for teams that want review intelligence locally, without depending on a hosted PR-review product.

Apex Ray is pre-1.0. Report schemas and configuration can change while the project is prepared for production use.

Install

One-off run without a persistent install:

uvx apex-ray --help
uvx apex-ray doctor

User-level CLI install:

uv tool install apex-ray
apex-ray --version
apex-ray doctor

pipx install apex-ray is also supported if you use pipx for isolated Python CLI tools.

Quick Start

In a project you want to review:

apex-ray init
apex-ray doctor
git status --short

Inspect and commit the setup files before using the first worktree review for application changes.

If Apex Ray later warns that generated agent instructions are outdated, refresh only those managed artifacts with:

apex-ray init --refresh-agent-artifacts --dry-run
apex-ray init --refresh-agent-artifacts

Run a deterministic no-LLM review:

apex-ray review --worktree --no-llm --output .apex-ray/reports/review.md --json .apex-ray/reports/review.json

Run the configured LLM review:

apex-ray review --worktree --llm --output .apex-ray/reports/review.md --json .apex-ray/reports/review.json --html .apex-ray/reports/review.html

Review a branch against the configured base:

apex-ray review --base main --llm

Continue only unreviewed packs from a partial report:

apex-ray review --continue-from .apex-ray/reports/review.json --residual-priority p0 --llm
apex-ray review --continue-from .apex-ray/reports/review.json --only-pack '<pack-id>' --llm

Run the same gate that apex-ray init wires into pre-push:

apex-ray gate pre-push

The gate reviews review.base...HEAD, writes .apex-ray/reports/pre-push.md and .apex-ray/reports/pre-push.json, prints an agent-friendly blocking summary, and exits non-zero when the configured policy fails.

See the full Quick Start and Review Workflow docs for installation requirements, provider setup, report interpretation, continuation commands, cache behavior, and troubleshooting.

What It Does

  • Builds context packs from changed files, symbols, callers, callees, contracts, metadata, and related tests.
  • Runs a language-neutral diff -> context pack -> optional LLM review workflow.
  • Uses enhanced analyzers for TypeScript/JavaScript, Python, and Go today, with Rust planned next.
  • Supports project-specific rules and repo-committed review memory.
  • Runs without LLM calls, or with Codex CLI / Claude Code CLI when configured.
  • Routes cheap and strong models through profiles.
  • Tracks LLM coverage, skipped packs, partial severity, provider failures, cache usage, and continuation commands.
  • Replays historical GitHub PR review comments for local evals.
  • Writes local telemetry so teams can tune cost, latency, and coverage over time.

Analyzer Coverage

Apex Ray's review pipeline is language-neutral. It is strongest where an analyzer backend can build repository-aware context instead of relying only on diff hunks.

Status Language family Strongest current surfaces
Enhanced analyzer available TypeScript, JavaScript NestJS controllers/providers/modules/guards, DTO/schema validators, route and DI metadata, workspace imports/exports, enum/const fanout, cache and permission surfaces, related tests.
Enhanced analyzer available Python FastAPI routes/dependencies, Pydantic models/settings/validators, SQLAlchemy sessions/transactions, Alembic migrations, async worker/event flows, external HTTP/cloud/Redis adapters, dataclass/TypedDict/Protocol contracts, pytest/unittest tests and fixtures.
Enhanced analyzer available Go Type-aware package loading, repository-relative symbols, changed and deleted symbol ranges, callers/callees, interface contracts, context metadata, syntax-only fallback, and related tests.
Enhanced analyzer planned Rust Repository-aware symbols, callers/callees, contracts, service boundaries, persistence/I/O surfaces, and related tests.
Generic fallback Other reviewable diffs Diff-hunk context, risk signals, project rules, memory, reports, and optional LLM review without a repository-aware symbol graph.

What It Does Not Do

Apex Ray does not replace CI, tests, linters, typecheck, dependency scanners, SAST, or human review. It focuses on diff-aware behavioral review and makes partial coverage explicit.

Documentation

Development

For local development from source:

git clone git@github.com:dobrotacreator/apex-ray.git
cd apex-ray
uv sync --all-groups
npm --prefix analyzer-runtimes/typescript ci
npm --prefix analyzer-runtimes/typescript run build

Useful checks:

uv run coverage run -m pytest -q
uv run coverage report -m
npm --prefix analyzer-runtimes/typescript run typecheck
npm --prefix analyzer-runtimes/typescript test
npm --prefix analyzer-runtimes/typescript run coverage
git diff --check

See docs/development.md and CONTRIBUTING.md.

Maintainers: release automation is documented in docs/development.md.

License

Apache-2.0. See LICENSE.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

apex_ray-0.1.10.tar.gz (5.0 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

apex_ray-0.1.10-py3-none-any.whl (4.9 MB view details)

Uploaded Python 3

File details

Details for the file apex_ray-0.1.10.tar.gz.

File metadata

  • Download URL: apex_ray-0.1.10.tar.gz
  • Upload date:
  • Size: 5.0 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for apex_ray-0.1.10.tar.gz
Algorithm Hash digest
SHA256 c786d7d686e7effaa28ca6630ecefd201361fc7c1fe0fdd2657244c87b49f6e9
MD5 3bd7e60fc6b867c7626e2aa25acde01c
BLAKE2b-256 a43f0a4d450fcacc4d0bb381f5cd64a6f741998f07bb55d8a566d7266a374b54

See more details on using hashes here.

Provenance

The following attestation bundles were made for apex_ray-0.1.10.tar.gz:

Publisher: publish-pypi.yml on dobrotacreator/apex-ray

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file apex_ray-0.1.10-py3-none-any.whl.

File metadata

  • Download URL: apex_ray-0.1.10-py3-none-any.whl
  • Upload date:
  • Size: 4.9 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for apex_ray-0.1.10-py3-none-any.whl
Algorithm Hash digest
SHA256 d145ff3b7a53ba8917947909e2f7e0ac2387ca38cf1c1caff900e00ef3fee205
MD5 d22b1205604e5e2491b70e9c031ff8b3
BLAKE2b-256 b8ec44ac4a53713a2c8dd69bc31a4e31b040b5690b7a4be6c91a47d9a4f929af

See more details on using hashes here.

Provenance

The following attestation bundles were made for apex_ray-0.1.10-py3-none-any.whl:

Publisher: publish-pypi.yml on dobrotacreator/apex-ray

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page