DeepCode Agent工作流

Option A — Install the CLI

Install uv first if it is not already available. On Windows PowerShell:

winget install --id astral-sh.uv --exact

Open a new terminal after the first uv installation, then run:

uv tool install --python 3.12 deepcode-hku
deepcode init

The explicit Python selection is intentional: DeepCode requires Python 3.12+ and must not fall back to an unsupported legacy package on an older interpreter. If an existing uv tool environment still contains DeepCode 1.x, migrate it with uv tool upgrade --python 3.12 deepcode-hku.

Create a model connection once. --api-key opens a non-echoing prompt:

deepcode provider set personal-openrouter --template openrouter --label "OpenRouter · Personal" --api-key
deepcode provider models personal-openrouter --refresh
deepcode provider test personal-openrouter --model <model-id>

Enter the repository you want DeepCode to work in and start the interactive Agent:

cd <your-project>
deepcode

deepcode init creates minimal user configuration under ~/.deepcode/. Credentials are stored separately in user-private storage and are never written to Session history. pipx install deepcode-hku and pip install deepcode-hku are also supported in an appropriate Python 3.12+ environment.

Option B — Install Desktop

Desktop release bundles are distributed separately from the Python package. Check GitHub Releases for a signed installer for your platform. If no installer is attached, use the source setup below.

macOS and Linux from source

Install the platform dependencies from the Tauri 2 prerequisite guide, plus Git, Python 3.12+, uv, Node.js 22+, and stable Rust. Then run:

git clone https://github.com/HKUDS/DeepCode.git
cd DeepCode
uv venv --python 3.12
uv pip install --python .venv/bin/python -e .
.venv/bin/deepcode init
cd desktop
npm ci
npm run setup:sidecar
npm run build:sidecar
cd ..
mkdir -p ~/.local/bin
ln -sf "$(pwd)/scripts/deepcode-desktop" ~/.local/bin/deepcode-desktop
export PATH="$HOME/.local/bin:$PATH"
deepcode-desktop

The final link is a one-time source launcher installation. Afterwards, deepcode-desktop starts this checkout from any directory, provided ~/.local/bin is on PATH. Add the export to your shell profile if it is not already configured. The command launches Desktop; add or select the repository you want to work on from the Project sidebar.

Windows from source

Windows requires Microsoft Edge WebView2 and the Visual Studio 2022 Build Tools workload Desktop development with C++. Accept the UAC prompt raised by Build Tools:

winget install --id Git.Git --exact
winget install --id astral-sh.uv --exact
winget install --id OpenJS.NodeJS.LTS --exact
winget install --id Rustlang.Rustup --exact
winget install --id Microsoft.VisualStudio.2022.BuildTools --exact `
  --override "--wait --passive --norestart --add Microsoft.VisualStudio.Workload.VCTools --includeRecommended"

Close PowerShell, open a new window, and verify the toolchains:

git --version
uv --version
node --version
rustup default stable-msvc
rustc --version
cargo --version

Clone, prepare, and start Desktop:

git clone https://github.com/HKUDS/DeepCode.git
Set-Location DeepCode
uv venv --python 3.12
uv pip install --python .venv\Scripts\python.exe -e .
.venv\Scripts\deepcode.exe init
Set-Location desktop
npm ci
$env:DEEPCODE_PYTHON = (Resolve-Path ..\.venv\Scripts\python.exe)
npm run setup:sidecar
npm run build:sidecar
npm run tauri -- dev

Keep that PowerShell window open while Desktop is running. See the Desktop source guide for subsequent launches and troubleshooting.

Configure the Desktop model

Open Settings → AI providers after Desktop starts.

_{Provider credentials, model discovery, and inference verification stay in one Desktop workflow.} </div>

1. Select Add provider, choose the service, and enter an API key or its environment-variable name. 2. Select Save and check to verify the credential and load the provider's model catalog without sending repository content. 3. Under Agent model, choose an exact model ID and select Save and verify model. This final check sends only a minimal inference request. 4. Add or open a Project, create a Session, choose the model, Thinking effort, and access level, then describe the task in natural language.

The interface changes how the work is presented, not the Agent, policy, configuration, or Session history behind it.

Quick start

DeepCode has two interfaces with separate installation paths. Choose one to get started; both use the same Agent runtime and canonical Session history.

uv tool install --python 3.12 deepcode-hku installs the CLI and shared Python runtime. It does not install the Tauri Desktop application.

Your models, your reasoning settings

DeepCode is not tied to one model provider. Connect OpenRouter, OpenAI, Anthropic, DeepSeek, Gemini, an OpenAI-compatible gateway, Ollama, vLLM, or another compatible endpoint with your own API Key.

Before use, a connection can check credentials, the model catalog, and a real inference request. Each Session can choose a model and Thinking Level. Changing models mid-Session affects future Turns only; it does not delete history or confuse where earlier work came from. When supported, DeepCode can also show a reasoning summary returned by the Provider.

🖥️ **Interface Showcase**

🖥️ DeepCode Desktop

Local Plugins

Plugins optionally package Skills behind a validated local manifest; standalone project and user Skills continue to install and run without a Plugin. New packages must use the Agent Plugins 1.0.0 manifest and fixed skills/ layout. Add a trusted folder from the Desktop Plugins workspace or with `deepcode plugin add <path>`; its Skills then appear in the ordinary Skill catalog and Composer. A standards-compliant mcp.json may also contribute MCP servers; registration remains inert and those processes start only inside an Agent Session. DeepCode does not execute Plugin hooks or Apps and does not download from a Marketplace. See the local Plugin contract.

Automations and headless workflows

The Desktop Automation workspace turns a trusted Project instruction into a manual or interval run while keeping the normal Agent, Session, Goal, permissions, recovery, and Run history. Use it for repeatable work such as repository health checks, regression review, or scheduled maintenance.

Shell scripts and CI systems can use the same runtime without opening an interface. The separate Headless and Automation guide contains the exec, loop, Automation, Provider, Skill, and Session administration commands. They are advanced integration surfaces—not a second way ordinary Desktop or CLI users must learn to talk to DeepCode.