Hmbown

    Hmbown/CodeWhale

    #73 this week

    Open-source, community-driven agent harness

    cli
    llm
    deepseek
    rust
    terminal
    tui
    Rust
    MIT
    39.9K stars
    3.4K forks
    39.9K GitHub watchers
    Updated 7/18/2026
    View on GitHub

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    Use Cases & Benefits

    • Provides a terminal-native coding agent for DeepSeek V4 models enabling file editing, shell commands, git management, and web search via a keyboard-driven TUI.
    • Offers a 1M-token context window with real-time chain-of-thought reasoning and multi-tool integration for efficient, interactive coding workflows.
    • Use for interactive code exploration and editing directly within a terminal environment using advanced AI reasoning.
    • Use for automating complex coding tasks with approval gates or fully auto-approved workflows in trusted workspaces.
    • Use for integrating AI-driven coding agents into headless or server workflows via HTTP/SSE runtime API and MCP protocol support.

    About CodeWhale

    DeepSeek TUI

    A terminal-native coding agent for DeepSeek V4 models — with 1M-token context, thinking-mode reasoning, and full tool-use.

    简体中文 README

    npm i -g deepseek-tui
    

    CI npm crates.io

    DeepSeek TUI screenshot


    What is it?

    DeepSeek TUI is a coding agent that runs entirely in your terminal. It gives DeepSeek's frontier models direct access to your workspace — reading and editing files, running shell commands, searching the web, managing git, and orchestrating sub-agents — all through a fast, keyboard-driven TUI.

    Built for DeepSeek V4 (deepseek-v4-pro / deepseek-v4-flash) with 1M-token context windows and native thinking-mode (chain-of-thought) streaming. See the model's reasoning unfold in real time as it works through your tasks.

    Key Features

    • Native RLM (rlm_query tool) — fans out 1–16 cheap deepseek-v4-flash children in parallel against the existing DeepSeek client for batched analysis, decomposition, or parallel reasoning
    • Thinking-mode streaming — shows DeepSeek's chain-of-thought as it reasons about your code
    • Full tool suite — file ops, shell execution, git, web search/browse, apply-patch, sub-agents, MCP servers
    • 1M-token context — automatic intelligent compaction when context fills up
    • Three interaction modes — Plan (read-only explore), Agent (interactive with approval), YOLO (auto-approved). Decomposition-first system prompts teach the model to checklist_write, update_plan, and spawn sub-agents before acting
    • Reasoning-effort tiers — cycle through off → high → max with Shift+Tab
    • Session save/resume — checkpoint and resume long sessions
    • Workspace rollback — side-git pre/post-turn snapshots with /restore and revert_turn, without touching your repo's .git
    • HTTP/SSE runtime APIdeepseek serve --http for headless agent workflows
    • MCP protocol — connect to Model Context Protocol servers for extended tooling; see docs/MCP.md
    • Live cost tracking — per-turn and session-level token usage and cost estimates
    • Dark theme — DeepSeek-blue palette

    Quickstart

    npm install -g deepseek-tui
    deepseek
    

    China / mirror-friendly install

    If GitHub or npm downloads are slow from mainland China, install the Rust crates through a Cargo registry mirror:

    # ~/.cargo/config.toml
    [source.crates-io]
    replace-with = "tuna"
    
    [source.tuna]
    registry = "sparse+https://mirrors.tuna.tsinghua.edu.cn/crates.io-index/"
    

    Then install the canonical deepseek dispatcher and (optionally) the companion TUI binary:

    cargo install deepseek-tui-cli --locked   # provides `deepseek`
    cargo install deepseek-tui     --locked   # provides `deepseek-tui` (optional)
    deepseek --version
    

    You can also download prebuilt binaries directly from the GitHub Releases page when GitHub release assets are reachable. TUNA, rsproxy, Tencent COS, or Aliyun OSS mirrors can also be used with DEEPSEEK_TUI_RELEASE_BASE_URL when a mirrored release-asset directory is available.

    On first launch you'll be prompted for your DeepSeek API key. You can also set it ahead of time:

    # via CLI
    deepseek login --api-key "YOUR_DEEPSEEK_API_KEY"
    
    # via env var
    export DEEPSEEK_API_KEY="YOUR_DEEPSEEK_API_KEY"
    deepseek
    

    Using NVIDIA NIM

    deepseek auth set --provider nvidia-nim --api-key "YOUR_NVIDIA_API_KEY"
    deepseek --provider nvidia-nim
    
    # or per-process:
    DEEPSEEK_PROVIDER=nvidia-nim NVIDIA_API_KEY="..." deepseek
    

    Other DeepSeek V4 providers

    deepseek auth set --provider fireworks --api-key "YOUR_FIREWORKS_API_KEY"
    deepseek --provider fireworks --model deepseek-v4-pro
    
    # SGLang is self-hosted; auth is optional for localhost deployments.
    SGLANG_BASE_URL="http://localhost:30000/v1" deepseek --provider sglang --model deepseek-v4-flash
    
    Install from source
    git clone https://github.com/Hmbown/DeepSeek-TUI.git
    cd DeepSeek-TUI
    cargo install --path crates/tui --locked   # requires Rust 1.85+
    

    What's new in v0.8.0

    ⚡ Shell stability and post-send responsiveness

    Completed background shell jobs now release their live process and pipe handles as soon as completion is observed, while keeping the job record inspectable. This prevents long-running sessions from hitting Too many open files (os error 24), which could make checkpoint saves fail and cause shell spawning, message send, close, and Esc/cancel paths to lag or fail.

    🪟 Windows REPL runtime CI hardening

    Windows gets a longer Python bootstrap readiness timeout for the REPL runtime tests, matching GitHub runner startup contention without weakening bootstrap failures on other platforms.

    🌏 Cargo mirror install docs

    The README now includes a TUNA Cargo mirror setup and direct release asset guidance for users with slow GitHub/npm access.

    🧪 Test hardening

    New regression coverage proves completed background shell jobs drop their live process handles after exec_shell_wait.

    Full changelog: CHANGELOG.md.


    What's new in v0.7.8

    ⚡ Shell controls: foreground-to-background detach + exec_shell_cancel

    A running foreground command can now be moved to the background interactive session — press Ctrl+B while a command is executing to open shell controls, then either detach it (it continues running and can be polled with exec_shell_wait) or cancel the current turn.

    New tool: exec_shell_cancel — cancel a specific background shell task by task_id, or cancel all running background tasks with all: true.

    Cancel-aware exec_shell_wait — canceling a turn while exec_shell_wait is blocking now stops the wait but leaves the background task running.

    🐛 Unicode glob search fix

    Filenames containing multi-byte characters (e.g., dialogue_line__冰糖.mp3) no longer panic the matches_glob function — byte-index slicing was replaced with char_indices() boundary-safe iteration.

    🔄 Swarm UI reconciliation

    The fanout card no longer pre-seeds with zero-state workers, eliminating the "0 done · 0 running · 0 failed · N pending" vs sidebar "N running" contradiction. The sidebar now shows "dispatching N" before the first progress event arrives from a agent_swarm invocation.

    Full changelog: CHANGELOG.md.


    What's new in v0.7.6

    🌐 UI Localization

    DeepSeek TUI now speaks your language. The new locale setting in settings.toml controls UI chrome — composer, history search, /config, help overlay, and status hints — without changing model output language.

    SettingDisplay
    locale = \"auto\"Checks LC_ALLLC_MESSAGESLANG (default)
    locale = \"ja\"Japanese
    locale = \"zh-Hans\"Chinese Simplified
    locale = \"pt-BR\"Portuguese (Brazil)
    locale = \"en\"English fallback

    Unsure what to pick? Run locale in your terminal; the first matching tag is used automatically.

    📋 Smarter paste handling

    Paste-burst detection catches rapid-key pastes in terminals that don't send bracketed-paste events — CRLF is normalized, and multiline pastes stay buffered until you stop typing. Configurable via paste_burst_detection.

    Forgot that prompt you wrote an hour ago? Alt+R opens a live search across input history and recovered drafts. Type to filter, Enter to accept, Esc to restore what you were typing.

    👁️ Pending input preview

    During a running turn, queued messages, pending steers, and context chips appear above the composer so you can see what will be sent next. Alt+↑ pops the last queued message back for editing.

    ⚙️ Grouped /config editor

    /config now groups settings by section (Model, Permissions, Display, ...) with a live filter. ↑/↓ (or j/k when the filter is empty) navigate; Enter/e edit the selected row; Esc clears the filter or closes.

    ⌨️ Searchable help overlay

    ? (with empty input), F1, or Ctrl+/ opens a searchable help overlay. Type to filter commands and keybindings; multi-term searches act as AND.

    Full history: CHANGELOG.md.


    Models & Pricing

    DeepSeek TUI targets DeepSeek V4 models with 1M-token context windows by default.

    ModelContextInput (cache hit)Input (cache miss)Output
    deepseek-v4-pro1M$0.003625 / 1M*$0.435 / 1M*$0.87 / 1M*
    deepseek-v4-flash1M$0.0028 / 1M$0.14 / 1M$0.28 / 1M

    Legacy aliases deepseek-chat and deepseek-reasoner silently map to deepseek-v4-flash.

    NVIDIA NIM hosted variants (deepseek-ai/deepseek-v4-pro, deepseek-ai/deepseek-v4-flash) use your NVIDIA account terms — no DeepSeek platform billing.

    *DeepSeek lists the Pro rates above as a limited-time 75% discount valid until 2026-05-05 15:59 UTC; the TUI cost estimator falls back to base Pro rates after that timestamp.


    Usage

    deepseek                                      # interactive TUI
    deepseek "explain this function"              # one-shot prompt
    deepseek --model deepseek-v4-flash "summarize" # model override
    deepseek --yolo                               # YOLO mode (auto-approve tools)
    deepseek login --api-key "..."                # save API key
    deepseek doctor                               # check setup & connectivity
    deepseek doctor --json                        # machine-readable diagnostics
    deepseek setup --status                       # read-only setup status
    deepseek setup --tools --plugins              # scaffold local tool/plugin dirs
    deepseek models                               # list live API models
    deepseek sessions                             # list saved sessions
    deepseek resume --last                        # resume latest session
    deepseek serve --http                         # HTTP/SSE API server
    deepseek mcp list                             # list configured MCP servers
    deepseek mcp validate                         # validate MCP config/connectivity
    deepseek mcp-server                           # run dispatcher MCP stdio server
    

    Keyboard shortcuts

    KeyAction
    TabComplete / or @ entries; while a turn is running, queue the draft as a follow-up; otherwise cycle mode
    Shift+TabCycle reasoning-effort: off → high → max
    F1Help
    EscBack / dismiss
    Ctrl+KCommand palette
    Ctrl+RResume an earlier session
    Alt+RSearch prompt history and recover cleared drafts
    @pathAttach file/directory context in composer
    (at composer start)Select attachment row for removal
    Alt+↑Edit last queued message
    /attach <path>Attach image/video media references; select the row with at composer start and remove with Backspace/Delete

    Modes

    ModeBehavior
    Plan 🔍Read-only investigation — model explores and proposes a decomposition plan (update_plan + checklist_write) before making changes
    Agent 🤖Default interactive mode — multi-step tool use with approval gates; model outlines work via checklist_write before requesting writes
    YOLOAuto-approve all tools in a trusted workspace; model still creates checklist_write/update_plan to keep work visible and trackable

    Configuration

    ~/.deepseek/config.toml — see config.example.toml for every option.

    Key environment overrides:

    VariablePurpose
    DEEPSEEK_API_KEYAPI key
    DEEPSEEK_BASE_URLAPI base URL
    DEEPSEEK_MODELDefault model
    DEEPSEEK_PROVIDERProvider: deepseek (default), nvidia-nim, fireworks, or sglang
    DEEPSEEK_PROFILEConfig profile name
    NVIDIA_API_KEYNVIDIA NIM API key
    FIREWORKS_API_KEYFireworks AI API key
    SGLANG_BASE_URLSelf-hosted SGLang endpoint
    SGLANG_API_KEYOptional SGLang bearer token

    Quick diagnostics: deepseek setup --status checks API key, MCP, sandbox, and .env state without network calls; deepseek doctor --json is suitable for CI; deepseek setup --tools --plugins scaffolds local tool and plugin directories.

    DeepSeek context caching is automatic — when the API returns cache hit/miss token fields, the TUI includes them in usage and cost tracking.

    Full reference: docs/CONFIGURATION.md and docs/MCP.md.

    UI locale is separate from model language — set locale in settings.toml or via the LC_ALL/LANG environment variables. See docs/CONFIGURATION.md.


    Publishing your own skill

    DeepSeek-TUI discovers skills from the active skills directory. Workspace-local .agents/skills wins when present, then ./skills, then the configured global directory (~/.deepseek/skills by default). Each skill is a directory with a SKILL.md file:

    ~/.deepseek/skills/my-skill/
    └── SKILL.md
    

    SKILL.md must start with YAML frontmatter:

    ---
    name: my-skill
    description: Use this when DeepSeek should follow my custom workflow.
    ---
    
    # My Skill
    
    Instructions for the agent go here.
    

    Run /skills to list discovered skills, /skill <name> to activate one for the next message, or /skill new to use the bundled skill-creator helper. Installed skills are also listed in the model-visible session context so the agent can choose relevant skills when the user names them or when the task matches their descriptions.

    DeepSeek-TUI can also install community skills directly from a GitHub repo, with no backend service in the loop:

    1. Create a public GitHub repo with a SKILL.md at the root containing the usual --- frontmatter (name, description).
    2. Multi-skill bundles use skills/<name>/SKILL.md instead — the installer picks the first match and names the install after the frontmatter name.
    3. Push to main (or master); the installer fetches archive/refs/heads/main.tar.gz and falls back to master.tar.gz.
    4. Users install via /skill install github:<owner>/<repo> — installs are gated by the [network] policy, validated for path traversal and size, and placed under ~/.deepseek/skills/<name>/.
    5. Submit a PR to the curated index.json (default registry) to make the skill installable by name (/skill install <name>) instead of the GitHub spec.
    6. Use /skill update <name>, /skill uninstall <name>, or /skill trust <name> for installed community skills. Trust is only needed when you want scripts bundled with a skill to be eligible for execution.

    Documentation

    DocTopic
    ARCHITECTURE.mdCodebase internals
    CONFIGURATION.mdFull config reference
    MODES.mdPlan / Agent / YOLO modes
    MCP.mdModel Context Protocol integration
    RUNTIME_API.mdHTTP/SSE API server
    RELEASE_RUNBOOK.mdRelease process
    OPERATIONS_RUNBOOK.mdOps & recovery

    Contributing

    See CONTRIBUTING.md. Pull requests welcome!

    Not affiliated with DeepSeek Inc.

    License

    MIT

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