1.0 orangu 1.0.0 is out

AI coding that runs
on your machine.

orangu is an open-source AI coding environment for the terminal that reads your project, edits your files, reviews your branch, and runs your whole Git workflow — with its own pure-Rust inference server underneath. No API keys, no telemetry, no data leaves your machine.

Get started

$ curl -fsSL https://mnemosyne-systems.github.io/orangu/install.sh | sh

Why orangu

The private,
Git-centric companion.

orangu is the lean, private, Git-centric coding companion for the terminal — built for developers who run their own models and want a tightly integrated review workflow without sending a single line of code to the cloud. Since 1.0 it ships the whole stack, inference server included, so there is no proprietary backend anywhere in the chain.

100% local and private

Zero telemetry. After the model is downloaded, no internet is needed — it runs happily in air-gapped environments.

Built-in code review

An interactive two-pane reviewer (/review) and a category-by-category LLM auto-reviewer (/auto_review). orangu's standout feature.

The whole Git loop in the prompt

Branch, commit, rebase, squash, cherry-pick, stash, push, and GitHub/GitLab PRs, comments, and issues — all from the terminal.

Pure Rust, top to bottom

Quick startup, no runtime to install, no GC pauses — and since 1.0, the inference engine is Rust as well.

## issue-85-prune...origin/issue-85-prune

> /auto_review

Working @ 38.2 t/s (4s)

The prune_sessions_output function looks solid.

One suggestion: the OlderThan match arm uses

saturating_sub correctly — consider

returning the removed session count

alongside the UUID list for better UX.

> /commit "[#85] tool: /prune"

committed on issue-85-prune

> /push

pushed to origin/issue-85-prune

The stack

Three cooperating programs,
one Pure-Rust project.

orangu 1.0 is a complete, self-contained AI coding stack — not just a client. Every layer is open source under GPL v3, and there is no proprietary backend to call home to.

Diagram of the orangu stack: you talk to orangu, the coding environment; orangu talks over OpenAI-compatible HTTP to the optional orangu-coordinator, which starts and stops orangu-server and swaps the model per role; orangu-server runs the GGUF engine on CPU, Vulkan, CUDA, ROCm, or OpenCL. — One native stack — fully local, fully private, entirely your own.

orangu

The coding environment: terminal UI, workspace-aware local tools, the full Git and GitHub/GitLab loop, code review, knowledge graph, and semantic search.
orangu-coordinator Optional

An on-demand model manager. It starts and stops the server for you and swaps to whichever model each role needs — chat, review, and the rest — so a single-GPU machine never has to run several servers at once.
orangu-server

A native pure-Rust GGUF inference engine: model loading, tokenization, the transformer forward pass, sampling, and request scheduling — with no llama.cpp, no ggml, and no Python. It serves OpenAI-compatible endpoints and a built-in web console.

CPUVulkanCUDAROCmOpenCL

Code review & auto review

Your terminal is now a
code-review workstation.

This is orangu's standout feature. Review the changes on your branch — committed and uncommitted, measured against the merge base with your default branch — two ways: an interactive reviewer you drive, and a fully automated one the model runs end to end. Both require an up-to-date rebase, so you never review against stale code.

/review

Interactive review

Full-screen two-pane view — file checklist beside the selected file's diff
Mark each file approved or rejected; comment on any line under seven categories
Ask the model about a file on demand — the exchange joins your chat session
Open any file in $EDITOR without leaving the view
Exit writes a category-grouped report with an approve/reject conclusion, copied to your clipboard. No gh/glab needed

/auto_review

LLM-driven review

The model reviews the whole change and each file on its own, sorting findings into seven categories
Renders a final orangu approves / rejects this patch verdict
Smart about effort — lock files and binaries auto-approve, docs get doc checks, source gets the full set
Every finding pinned to its file:line; requests are length-capped and tool-free to stay fast on local models
Browse the report, override any verdict, then /export review or post with /comment

Features

Everything, in the terminal.

Private

Fully local

Runs on orangu-server or any other OpenAI-compatible server. Once models are downloaded, nothing leaves your machine.

Review

Code review built in

Interactive /review and automated /auto_review — the standout in-terminal review workflow.

Tools

Workspace-aware

Read, edit, list, /grep, fetch, and run shell commands — all scoped to your workspace.

Workspaces

Projects as tabs

Open several projects at once, each a tab with its own session, scrollback, queue, and history.

Skills

Agent Skills

Drop a SKILL.md into your repo; orangu discloses it progressively and loads it on demand.

Terminal

Built for the prompt

Ghost-text hints, Tab completion, live tokens/sec, queued commands, and Markdown with syntax highlighting.

30+ Slash commands

0 Cloud dependencies

1.0 Current version

What's new

The latest release.

orangu 1.0.0 Latest July 27, 2026

A complete stack — Three cooperating programs, written end to end in Rust, all under GPL v3.
orangu-server — A native pure-Rust GGUF inference engine. No llama.cpp, no ggml, no Python.
orangu-coordinator — Starts and stops the server on demand and swaps the model each request needs.
Five backends — Vulkan, CUDA, ROCm, and OpenCL, plus CPU with automated cross-verification.
OpenAI-compatible APIs — Chat, completions, and embeddings endpoints with prefix caching and slot preservation.
Built-in web console — Browser chat with Markdown, syntax highlighting, and LaTeX, embedded in the binary.

See all releases →

> /status

## feature/new-api...origin/feature/new-api

M src/config.rs

M src/bin/orangu/init.rs

> /diff

+ pub line_endings: String,

> /squash

squashed 3 commits into 1

> /pull_request

PR #96 created

Git integration

Your entire Git workflow,
from one prompt.

Commit, push, rebase, squash, review, and open pull requests, all without leaving the terminal. orangu understands your branch, your history, and your forge.

GitHub and GitLab

Create PRs, close issues, add review comments via gh or glab.

Full-screen review mode

Two-pane diff view with AI feedback, line annotations, and keyboard navigation.

Auto-sync on startup

Fast-forwards your default branch against origin silently every session.

orangu vs. a cloud coding assistant

A deliberate trade.

orangu makes a deliberate trade: a focused, offline-first, Git-centric terminal experience instead of a broad cloud platform. If you run your own models and care about privacy, that trade is the whole point.

	orangu	Typical cloud coding assistant
Where your code goes	Stays on your machine — zero telemetry	Sent to a third-party provider
Offline use	First-class; only the initial model download needs a network	Generally requires connectivity
Models	GGUF models you own, served by the bundled `orangu-server` — or any other OpenAI-compatible server	Vendor-hosted models, usually behind API keys
Cost	Free to run against models you host	Per-token / subscription billing
Footprint	Native Rust binaries, fast start, no runtime, no Python	Editor/cloud service + account
Code review	Built-in interactive and LLM auto review in the terminal	Usually delegated to the hosting platform
Git workflow	Full Git + GitHub/GitLab loop from the prompt	Varies; often browser-based
Privacy posture	Suited to regulated / air-gapped environments	Depends on the provider's data policy