deepy-cli 0.2.21

Deepy - Vibe coding for DeepSeek models in your terminal

Deepy

A terminal-native coding agent for real project work.

Install Website · GitHub Pages · 中文文档

What Deepy Is

Deepy is a Python CLI coding agent for real project work. It stays in your terminal and combines OpenAI Agents SDK tool orchestration, project Rules, Agent Skills, MCP, subagents, sessions, and visible UI to read code, edit files, run commands, search the web, and resume long tasks. It is DeepSeek-first while also supporting OpenAI-compatible providers.

Why Use It

• DeepSeek-first agent loop: tuned for DeepSeek V4 thinking mode while still supporting OpenAI-compatible providers such as OpenRouter and Xiaomi MiMo.
• Transparent terminal execution: thinking, tool calls, diffs, shell output, usage, and context pressure stay visible in the transcript.
• Project memory and continuity: AGENTS.md rules, JSONL sessions, /resume, /compact, automatic compacting, and context-window status keep long project work recoverable.
• Extensible agent ecosystem: Agent Skills, MCP servers, subagents, and skill-market installation give Deepy reusable workflows beyond built-in tools.
• Practical coding controls: stale-write protection, direct !cmd local commands, managed background tasks, and /ps / /stop keep local execution reviewable.
• Cross-platform shell support: POSIX shell, PowerShell, cmd, Windows paths, UTF-8 output, CRLF editing, and non-interactive Windows local command mode.

Quick Start

1. Install uv:

# macOS / Linux
curl -LsSf https://astral.sh/uv/install.sh | sh

# Windows PowerShell
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

2. Install Deepy:

uv tool install deepy-cli

3. Start Deepy in a project:

cd your-project
deepy

If Deepy has not been configured yet, the first run guides you through provider, API key, model, and theme setup. You can later run deepy config setup to reconfigure manually.

Upgrade or uninstall:

uv tool upgrade deepy-cli
uv tool uninstall deepy-cli

First Session

Try requests like these inside deepy:

Summarize this project and point out the main entry points.
Read @src/app.py and explain how the request flow works.
Fix the failing test, run the focused test, and summarize the diff.
Search the web for the current API behavior, then update the integration notes.

Useful interactive inputs:

@src/app.py       Mention a file in the current project
!pytest -q        Run a local non-interactive command directly
/model            Select provider, model, and thinking mode
/status           Show usage, context pressure, and DeepSeek balance
/resume           Resume a previous project session
/new              Start a fresh session
/compact          Compact the active session context
/mcp              Show MCP server status and tools
/skills           Manage local and market Skills
/ps               Show managed background shell tasks
/stop             Choose background shell tasks to stop
Esc               Interrupt the current model turn
Ctrl+D            Press twice to quit

What It Looks Like

Terminal-Centered Agent Loop

Deepy keeps model reasoning, WebFetch, shell output, and status lines visible in one transcript.

Code Editing With Reviewable Diff

File edits are shown with path information and readable diff output.

Search, Fetch, And Local Commands

Use WebSearch / WebFetch for external context, @ for file mentions, and ! for direct local commands.

Stable UI And Experimental TUI

The default deepy command starts the stable Rich/prompt-toolkit terminal UI. The opt-in Textual interface is available with:

deepy tui

The TUI has a scrollable transcript, live thinking blocks, richer tool output blocks, slash-command and @file suggestions, status/help screens, and a Deepy-owned diff view. It remains experimental and may change between releases.

/status shows session/project usage, context-window pressure, and DeepSeek balance in one panel. Exiting the TUI prints the same compact session summary as the stable terminal UI.

See docs/deepy-ui-and-tui.md for the full feature comparison and current limitations.

Rules

Rules are project and personal instructions that shape how Deepy should work. Deepy automatically loads them from AGENTS.md files:

• ~/.deepy/AGENTS.md for Deepy-wide personal guidance
• AGENTS.md files from the git root down to the current working directory

Project AGENTS.md files are loaded from broad to specific. A file in a nested directory appears after the repository root file and takes precedence when rules conflict. Direct user instructions still take precedence over loaded AGENTS.md guidance.

Run /init in the interactive terminal to have Deepy inspect the repository and create or refresh the project root AGENTS.md.

Skills

Skills are reusable capability packs. Deepy discovers three kinds:

• Project skills: <project>/.agents/skills/<name>/SKILL.md. These are shared with the current repository and take priority over user or built-in skills with the same name.
• User skills: ~/.agents/skills/<name>/SKILL.md. These are personal skills available across projects and override built-in skills with the same name.
• Built-in skills: packaged with Deepy for common workflows. They are always available, but they are not editable or uninstallable through the skill UI.

Skills use the standard Agent Skills progressive-disclosure flow: Deepy shows Skill metadata first, and the model reads the full SKILL.md only when the task matches that skill.

The skill market is a curated source for installable Skills. Market-installed Skills can be installed into user or project scope, updated, and uninstalled through Deepy's Skills UI. Deepy records market-installed Skill metadata under ~/.deepy/skill-market/.

Use /skills to manage local and market Skills, or invoke a Skill directly:

/skills
/<name> [request]

MCP

Deepy can load MCP servers through the OpenAI Agents SDK. MCP is how you connect external tools such as search providers, databases, local services, or organization-specific context providers.

Most users only need ~/.deepy/mcp.json. Project-level MCP configuration is ignored by default because stdio MCP servers can start local commands. Enable it only for repositories you trust.

See docs/mcp.md for setup, fields, search preference, subagent MCP inheritance, and troubleshooting.

Trust Boundaries

• File edits are rendered with path information and readable diffs.
• Existing file replacement uses stale-write protection.
• !cmd is direct local command mode; model-started shell commands are shown in the transcript.
• MCP stdio servers start local commands. Project MCP config is ignored by default and should only be enabled for repositories you trust.
• Built-in subagents do not receive source mutation tools by default.
• The tester subagent uses constrained test_shell, not raw unrestricted shell.

Learning Resources

Topic	English	Chinese
Tutorial videos	docs/tutorial-videos.md	docs/tutorial-videos.zh-CN.md
MCP setup and troubleshooting	docs/mcp.md	docs/mcp.zh-CN.md
Subagents and custom subagents	docs/subagents.md	docs/subagents.zh-CN.md
Stable UI versus experimental TUI	docs/deepy-ui-and-tui.md	docs/deepy-ui-and-tui.zh-CN.md

Command Reference

deepy --version
deepy config setup
deepy config reset
deepy config theme
deepy doctor
deepy doctor --live --json
deepy status
deepy tui
deepy skills list
deepy skills show <name>
deepy sessions list
deepy sessions show <session-id>
deepy run "summarize this project"

Inside the interactive terminal:

/help                   Show interactive help
/model                  Select provider, model, and thinking mode
/status                 Show usage, context pressure, and DeepSeek balance
/resume                 Resume a previous project session
/new                    Start a fresh session
/compact                Compact the active session context
/mcp                    Show MCP server status and tools
/skills                 Manage local and market Skills
/<name> [request]       Invoke a Skill directly
/init                   Create or update project AGENTS.md
/theme                  Show or change terminal UI theme
/ps                     Show managed background shell tasks
/stop                   Choose background shell tasks to stop

Configuration

Deepy stores configuration in ~/.deepy/config.toml. The interactive first-run setup creates this file for most users.

Minimal resolved shape:

[model]
api_key = "sk-..."
provider = "deepseek"
name = "deepseek-v4-pro"
base_url = "https://api.deepseek.com"
thinking = true
reasoning_effort = "max"

[context]
window_tokens = 1048576
compact_trigger_ratio = 0.8
reserved_context_tokens = 50000
compact_preserve_recent_messages = 2

[ui]
theme = "dark" # dark or light

Manual configuration commands:

deepy config setup
deepy config init --api-key sk-... --provider deepseek --model deepseek-v4-pro
deepy config init --api-key sk-or-... --provider openrouter --model xiaomi/mimo-v2.5-pro
deepy config init --api-key sk-or-... --provider openrouter --model anthropic/claude-sonnet-4.5 --thinking minimal
deepy config init --api-key sk-... --provider xiaomi --model mimo-v2.5-pro
deepy config theme light

Supported provider/model pairs:

• deepseek: deepseek-v4-pro, deepseek-v4-flash; thinking modes none, high, max.
• openrouter: UI model selection offers xiaomi/mimo-v2.5-pro, xiaomi/mimo-v2.5; setup/init may also use a model id copied from OpenRouter. Thinking modes are enabled, disabled, xhigh, high, medium, low, minimal, none.
• xiaomi: mimo-v2.5-pro, mimo-v2.5; thinking modes enabled, disabled.

WebSearch uses Deepy's hosted SearXNG endpoint by default. You can override it:

[tools.web_search]
searxng_url = "https://your-searxng.example/"

Development

uv sync --group dev
uv run pytest
uv run ruff check
uv run ty check src
uv build

The Python package is built from src/deepy. GitHub Pages files and screenshot assets live outside the package directory and are not included in the wheel.