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Mastering Volcengine veCLI: Ultimate Guide to AI-Powered CLI for Code Generation & Cloud Deployment

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Turn Your Terminal into an AI Teammate: The No-Hype Guide to Volcengine veCLI

A complete, plain-English walkthrough of installing, logging in, switching models, writing code, deploying a blog and theming—without ever leaving the command line.
3 000+ words, fully based on Volcengine’s official docs, updated September 2025.

1. Six Quick Answers Before We Start

Question One-sentence reply
What is veCLI? An open-source CLI front-end that talks to Volcengine’s Ark models and cloud tools; you type plain English, it writes code, runs commands, or queries cloud data.
Does it cost money? The package is free; you only pay for the Volcengine tokens you consume.
Do I need a GPU? No. Inference runs in Volcengine’s cloud; local laptop only needs Node.js.
How is it different from GitHub Copilot? Works outside any IDE; runs on macOS, Linux, Windows; supports multiple models (Doubao, DeepSeek, Kimi, custom); can chain cloud APIs through MCP servers.
Will my code leak? File content is not logged by default; enterprise builds can disable telemetry completely (see §9).
Fastest install path? npm i -g @volcengine/vecli → set two env-vars → type vecli and chat.

2. Installation: Two Commands, Three Minutes

2.1 Prerequisites

  • Node.js 18 or newer (node -v)
  • npm reachable (official registry or your company mirror)

2.2 Global install (recommended)

npm install -g @volcengine/vecli@latest

One-off run without install:

npx @volcengine/vecli@latest

2.3 Smoke-test

vecli --version
# → veCLI 0.9.x (build xxxxx)

3. First Login: AK/SK Illustrated Flow

Works for personal laptops, CI containers, or shared jump boxes.

Step Where & What
① Get keys Volcengine console → Access Control → Access Keys → Create. Copy both strings immediately; the secret will disappear after the dialog closes.
② Export Append to ~/.bashrc, ~/.zshrc or CI secret:
export VOLCENGINE_ACCESS_KEY="AKxxxxxxxx"
export VOLCENGINE_SECRET_KEY="SKxxxxxxxx"
③ Verify vecli auth status
→ Logged in via AK/SK ✔

4. Run Your First Task in 30 Seconds

Non-interactive (one-liner):

echo "write a Python fibonacci function" | vecli

Interactive:

vecli
> write fibonacci and save it as fib.py

veCLI prints the code, then shows a write_file confirmation.
Type y → file created; job done.

5. Everyday Tweaks: Model, Theme, Extra Folders

Goal Command or setting
Temporary model vecli --model deepseek-v3-1
Permanent model ~/.ve/settings.json:
{"model": {"name": "deepseek-v3-1"}}
Change colours Inside veCLI type /theme → pick Dracula Dark (or build your own, §8).
Add more workspace folders vecli --include-directories ./api,./web

6. Let the AI Do: Files, Shell, Git

Built-in tools trigger on plain English:

You say veCLI calls
“rename fib.py to fibonacci.py” move_file
“git status” run_shell_command(git status)
“append ## License to README.md” replace_file

Safety: every write or shell action asks for confirmation.
CI mode: --yolo auto-approves (use consciously).

7. Mini-Project: Generate & Run a Blog Engine

One prompt:

vecli -p "create an Express+EJS blog, home page lists posts, click title for detail, save all files under ~/my-blog"

veCLI outputs:

  • app.js + routes
  • views/ templates
  • package.json

Then run:

cd ~/my-blog
npm install
node app.js

Visit http://localhost:3000—your blog is live.

8. Power-User Corner: Custom Themes & Commands

8.1 Roll Your Own Colour Theme

~/.ve/settings.json

"ui": {
  "customThemes": {
    "CorpGreen": {
      "name": "CorpGreen",
      "type": "custom",
      "Background": "#002b36",
      "Foreground": "#eee8d5",
      "AccentGreen": "#859900",
      "Comment": "#586e75",
      "Gray": "#839496"
    }
  }
}

Reload → /theme → select CorpGreen.

8.2 Turn Frequent Prompts into Slash-Commands

Scenario: generate unit tests every day.

  1. Create folder & file
mkdir -p ~/.ve/commands/test
nano ~/.ve/commands/test/unit.toml
  1. TOML content
description = "Generate Jest unit tests for the current file"
prompt = """
Please read @{file} and write comprehensive Jest tests for every exported function.
Requirements:
- Use TypeScript
- At least 2 assertions per function
- Save test as @{file}.test.ts
"""
  1. Use inside veCLI
> @src/utils.ts
> /test:unit

AI reads the source, writes the test file, and drops it next to the original.

9. Enterprise Lock-Down: Five Admin Controls

Drop these keys into /etc/vecli/settings.json (root-owned, 644).

Control JSON snippet Effect
Force sandbox "tools": {"sandbox": "docker"} All shell & file ops run inside container; host untouched.
Tool white-list "tools": {"core": ["ReadFileTool","ShellTool(ls)"]} Anything not listed is unreachable for every user.
Disable telemetry "privacy": {"usageStatisticsEnabled": false} No usage leaves the machine.
Enforce AK/SK "security": {"auth": {"enforcedType": "aksk"}} Blocks OAuth flows.
MCP catalog lock "mcp": {"allowed": ["corp-tools"]}, "mcpServers": {"corp-tools": {...}} Users cannot add their own MCP servers.

Merge order (highest wins):
system override > project .ve/settings.json > user ~/.ve/settings.json > system default.
Arrays (e.g. includeDirectories) are concatenated; colliding single values use the highest-priority file.

10. FAQ (Collected from Forums & Tickets)

Q1. My company blocks npm.
A. Mirror @volcengine/vecli to your private registry, then npm i -g @volcengine/vecli --registry=https://your-mirror.

Q2. I need two Volcengine accounts (prod / dev).
A. Keep two project folders, each with its own .ve/.env containing different AK/SK. Launch veCLI with --project-dir.

Q3. Garbled text or hang on Windows.
A. Set UTF-8: chcp 65001; if behind proxy, add https_proxy env-var. Use --debug to trace.

Q4. How to auto-approve in CI?
A. Start veCLI with --approval-mode yolo or list allowed tools: "tools": {"allowed": ["write_file","run_shell_command(npm test)"]}.

Q5. Can I work completely offline?
A. Inference requires Volcengine cloud; on-prem model serving is not exposed yet.

11. Post-Install Checklist (Print & Stick)

  1. vecli auth status → ✔
  2. vecli test-connection → latency < 500 ms
  3. Pick your cheapest model (--model)
  4. Add a project-level VE.md with coding rules
  5. Convert frequent prompts into .toml commands
  6. Alias vecli='vecli --sandbox' on shared PCs
  7. Append .ve/ to .gitignore to avoid leaking keys

12. What to Explore Next

  • Wire in the GitHub MCP server—let AI create issues and comment on PRs.
  • Build a custom sandbox.Dockerfile pre-loaded with your tool-chain.
  • Use /memory refresh to hot-reload hierarchical instructions (global + project + sub-folder).
  • Pipe telemetry to your own OTLP collector and monitor token spend in real time.

The terminal is no longer a black box; it’s a colleague that never sleeps.
Install veCLI once, offload the boring stuff, and free your brain for real problems.

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