devo
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Open-source, model-neutral agent desktop/runtime for private, enterprise, and OpenAI-compatible model environments. Supports DeepSeek, Qwen, Kimi, Anthropic-compatible APIs, MCP, and local code search.
An open-source, model-neutral agent desktop/runtime for private, enterprise, and OpenAI-compatible model environments. Connect DeepSeek, Qwen, Kimi, Anthropic-compatible APIs, local gateways, or your own model endpoint.
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Why Devo · Features · Tested Models · Tested Platforms · Install · Quick Start · Docs
Why Devo
Devo is for teams that need a coding agent outside a single hosted model
ecosystem. It keeps model choice, runtime behavior, and workspace execution
under your control.
- Bring your own model - Connect OpenAI-compatible Chat Completions,
OpenAI-compatible Responses, Anthropic Messages, DeepSeek, Qwen, Kimi, or
private model gateways through provider/model bindings. - Works in private and intranet environments - Run a single local Rust
binary, support offline installation paths, and point Devo at internal
endpoints without depending on a hosted agent service. - Desktop and CLI workflows - Use the Desktop app for onboarding and daily
coding, or the CLI/TUI when you need terminal-native automation. - Built for agent runtime extensibility - MCP servers, reusable skills,
local semantic code search, auditable sessions, permissions, and multi-agent
flows are runtime features rather than one-off prompts.
Features
- Built-in semantic code search - Runs a local CPU code-embedding model and
combines dense retrieval with BM25 keyword matching, reducing code-search
context compared with grep/find-only agent. - Bring your own model provider - Use provider/model bindings for
OpenAI-compatible, Anthropic-compatible, DeepSeek, Qwen, Kimi, GLM, MiniMax,
Xiaomi MiMo, OpenRouter, or local endpoints. - MCP support - Connect external tools and context through
Model Context Protocol servers. - Skill support - Package repeatable workflows, instructions, scripts, and
references as reusable Agent Skills. - Long-running task support - Let Devo manage context automatically across
multi-turn work instead of losing the thread as tasks grow. - Multi-agent support - Split work across specialized agents while keeping
coordination visible in the session. - Plan Mode - Break larger tasks into clear multi-step plans before
implementation starts. - Parallel tool calls - Run multiple independent tools at parallel so
models spend less time waiting and more time making progress. - Permissioned tool execution - Review sensitive tool calls before they
touch your workspace. - Auditable sessions - Keep model output, tool calls, approvals, token
usage, and session history inspectable and resumable. - Cost and context visibility - Show input/output tokens, cached tokens, and
context-window usage where providers expose them. - Lightweight Rust runtime - Built in Rust with low memory overhead and a
compact local runtime.
Tested Models
Devo's built-in model catalog includes tested model definitions for Qwen, Kimi,
MiniMax, GLM, and DeepSeek. Provider endpoints remain configurable through
provider/model bindings.
Tested Platforms
Devo has been tested on macOS, Linux, Windows, and Kylin OS.
For Chinese Enterprise Users
Kylin OS coverage is called out because domestic operating systems are often
part of real deployment requirements in Chinese enterprise environments.
HarmonyOS support is on the roadmap; contributors with HarmonyOS devices are
welcome to build, test, and publish releases for that platform.
Screenshots
Installation
Devo can be installed in two forms. You can install the Desktop app, the
terminal-native TUI/CLI, or both on the same machine.
Option 1: Desktop App
Start here if you want the graphical Devo experience. Download the latest Devo
Desktop package from GitHub Releases,
then choose the asset that matches your operating system and architecture:
- macOS - download the
devo-desktop-...-mac-....dmgor.zipasset. - Windows - download the
devo-desktop-...-windows-....exeasset. - Linux - download the
devo-desktop-...-linux-....AppImage,.deb, or.rpmasset.
If macOS reports that Devo.app is damaged and cannot be opened, this is
expected. Current macOS Desktop builds are unsigned, so after installing,
run the following command so macOS can launch the app:
sudo xattr -dr com.apple.quarantine /Applications/Devo.app
Option 2: TUI / CLI
Install the terminal-native devo command if you prefer the TUI, want shell
automation, or want to use Devo alongside the Desktop app.
Linux / macOS:
curl -fsSL https://raw.githubusercontent.com/7df-lab/devo/main/install.sh | sh
Windows:
irm 'https://raw.githubusercontent.com/7df-lab/devo/main/install.ps1' | iex
The online installer places devo under the Devo home directory, installs therg sidecar used for fast repository search, and supports optional setup for
the local model used by code_search.
code_search model
Use this only if you want the Hugging Face model downloaded during installation.
Linux / macOS:
curl -fsSL https://raw.githubusercontent.com/7df-lab/devo/main/install.sh | sh -s -- --install-code-search-model
Windows:
$env:DEVO_INSTALL_CODE_SEARCH_MODEL = "1"; irm 'https://raw.githubusercontent.com/7df-lab/devo/main/install.ps1' | iex
Upgrade an existing installation to the latest release:
devo upgrade
The upgrade command runs the same platform installer, and the installer prints
the version transition, for example Version: v0.1.12 -> v0.1.15.
For air-gapped or intranet installs, see
Offline Installation.
Quick Start
Configure a provider, open a repository, and start the TUI:
cd /path/to/your/repo
devo onboard
Useful commands:
devo # start the interactive TUI in the current repo
devo resume <session-id>
Configuration
devo onboard is the recommended setup path. For manual config.toml paths,
provider/model binding fields, and custom model catalog examples, see
Configuration.
Docs
FAQ
What is the project status?
Devo is pre-1.0 and actively developed. It is ready for local evaluation,
experiments, and contributor use; public APIs and configuration may still
change.
What models are supported?
Built-in model metadata currently covers Qwen, Kimi, MiniMax, GLM, and DeepSeek
families. Any model endpoint that supports OpenAI-compatible Chat Completions,
OpenAI-compatible Responses, or the Anthropic Messages API can be connected through
provider/model bindings.
Contributing
Contributions are welcome while the project is still early:
- Architecture feedback on the client/server runtime, provider layer, safety
model, and TUI. - Documentation and translations.
- Provider, model, and wire API coverage.
- Focused fixes with validation commands and regression tests.
Open an issue or pull request to discuss changes.
Star History
License
This project is licensed under the MIT License.
If you find Devo useful, please consider giving it a star.
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