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 rendianmeng
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rendianmeng
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gujieye
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故璃
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gujieye
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Gong Shiqi
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故璃
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若麒
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若麒
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@@ -13,8 +13,9 @@
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---
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_Chat with Qwen, generate images & videos, understand images, call agents,_
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_manage memory, search the web — all from your terminal._
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_Chat with Qwen, generate and edit images and videos, understand images, synthesize_
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_and recognize speech, call apps, manage memory, retrieve knowledge, search the web —_
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_every AI capability, one command away._
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_Built for AI Agents. Every command works as a structured tool call._
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@@ -22,28 +23,16 @@ _Built for AI Agents. Every command works as a structured tool call._
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## Features
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||||
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||||
Equip your AI Agent out-of-the-box with these capabilities, composable across complex tasks:
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- **Model generation** — Full-modality generation across text, image, video, and speech, with editing and reference-based generation
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||||
- **Asset understanding** — Parse and ask questions about images, documents, audio, and long videos
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||||
- **App orchestration** — Call Managed Agents, agents, and workflows published on Aliyun Model Studio, wired to knowledge bases, memory, web search, and MCP tools
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- **Training & deployment** — Validate and upload datasets, fine-tune models, deploy dedicated models as endpoints
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- **Account operations** — Login, UI-based configuration, model marketplace, usage and quota, rate-limit increases, team seat management
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- **Plan onboarding** — Connect subscription plans such as Token Plan to the CLI and common coding agents in one step
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||||
|
||||
- **Text chat** — Qwen3.8-max: major gains in agentic coding, frontend coding, and vibe coding
|
||||
- **Multimodal (Omni)** — Full omni-modal support across text + image + audio + video
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- **Image generation & editing** — Qwen-Image 3.0: pro text rendering, photorealism, strong semantic adherence, multi-image composition
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- **Video generation & editing** — happyhorse-1.1 series: text-/image-/reference-to-video and natural-language video editing (up to 9-image reference)
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- **Speech synthesis & recognition** — CosyVoice streaming TTS, voice cloning from 5–20s samples; FunAudio-ASR covers 30 languages including 7 Chinese dialects and 20+ Mandarin accents
|
||||
- **Image & video understanding** — Qwen-VL: long-form video analysis, chart/document parsing, visual reasoning, multilingual OCR
|
||||
- **Coding agent setup** — Configure Claude Code, Qwen Code, OpenCode, OpenClaw, Hermes Agent, or Codex to use DashScope with `bl config agent`
|
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> **Note:** App orchestration, training & deployment, account operations, and plan onboarding are currently available only to China site (aliyun.com) account holders and are not yet supported for international / global site accounts.
|
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||||
> **Note:** The features below are currently available only to China site (aliyun.com) account holders and are not yet supported for international / global site accounts.
|
||||
|
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- **Knowledge base & memory** — Multimodal RAG retrieval and cross-session memory for personalized, coherent dialogue
|
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- **App calls** — Invoke agents and workflows already published on Aliyun Model Studio
|
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- **MCP integration** — Orchestrate Bailian MCP servers: list services, inspect tools, and invoke any tool directly from the terminal
|
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- **Web search** — Real-time internet retrieval for up-to-date, accurate answers
|
||||
- **Model recommendation** — Describe your scenario and get best-fit model suggestions; supports scoped search, model comparison, and alternative discovery
|
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- **Fine-tuning & deployment** — Upload datasets, create text/audio/image fine-tune jobs (`finetune text|audio|image create`; text covers SFT/LoRA/DPO/CPT), probe job status non-blockingly (`finetune watch`), query per-model training capability (`finetune capability`), and deploy trained models as endpoints (`deploy text|audio|image create`)
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- **Console capabilities** — Browse the model marketplace (`model list`) and Bailian apps (`app list`), review a unified usage view (`usage summary`), check free-tier quota (`usage free`), view model usage statistics (`usage stats`), manage workspaces (`workspace list`), and manage rate limits (`quota list/request/check/history`)
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- **Local file auto-upload** — Every URL parameter accepts a local path; uploaded to free temp storage with 48-hour validity
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## Showcase: One-Sentence Cinematic Video
|
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## Showcase 1: A Cinematic Short Film from One Sentence
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|
||||
<p align="center">
|
||||
<a href="https://cloud.video.taobao.com/vod/dS2F4huqbw5Nfe5L3wwb3grz2q2DNYD3retq8dU-iHo.mp4">
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@@ -56,129 +45,77 @@ Equip your AI Agent out-of-the-box with these capabilities, composable across co
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A complete **2-minute, 16:9 cinematic short film** — produced end-to-end from a single natural-language sentence, with **zero manual editing**. This showcase demonstrates how an AI Agent can compose a multi-step creative pipeline by orchestrating three primitives:
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|
||||
- **[Qwen Code](https://github.com/QwenLM/qwen-code)** — the agentic coding model that interprets the user's intent and drives the workflow
|
||||
- **[Aliyun Model Studio CLI](https://bailian.console.aliyun.com/cli?source_channel=cli_github&)** — invokes **HappyHorse 1.1**, Aliyun Model Studio's text-/image-/reference-to-video generation model
|
||||
- **[Aliyun Model Studio CLI](https://github.com/modelstudioai/cli/)** — invokes **HappyHorse 1.1**, Aliyun Model Studio's text-/image-/reference-to-video generation model
|
||||
- **[spark-video Skill](https://github.com/JohnKeating1997/spark-video)** — handles scene decomposition, storyboarding, shot continuity, and final stitching
|
||||
|
||||
### The single prompt
|
||||
|
||||
> _"Generate a roughly 2-minute video in Japanese cinematic style — a sweet, innocent first-love story about a high-school girl. The plot should be heart-fluttering enough to make viewers want to fall in love. Aspect ratio: 16:9."_
|
||||
>
|
||||
> _(Original: "帮我生成一段日系影视风格，高中女生的青涩初恋故事，剧情高甜，让人看了想谈恋爱，2分钟左右的视频，尺寸是16:9")_
|
||||
|
||||
### How it works
|
||||
## Showcase 2: A Short-Film Director Managed Agent from One Sentence
|
||||
|
||||
1. **Qwen Code** parses the request, plans the narrative beats, and decides which tools to call.
|
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2. The **spark-video Skill** breaks the story into shots, writes per-shot prompts, and enforces visual continuity (characters, lighting, palette, lens language).
|
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3. **`bl video generate`** dispatches each shot to **HappyHorse 1.1** in parallel.
|
||||
4. The skill stitches all clips back together into a single 16:9 / ~2-min deliverable.
|
||||
<p align="center">
|
||||
<a href="https://cloud.video.taobao.com/vod/2v0GYLbJSQb2saj4iopTJDW3iRIHsintYlK-wTKbhqE.mp4">
|
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<img src="https://img.alicdn.com/imgextra/i4/6000000001674/O1CN01xhzixhxltbH3LxWu_!!6000000001674-0-tbvideo.jpg" alt="Click to play the demo video" width="720" />
|
||||
</a>
|
||||
</p>
|
||||
|
||||
No timeline scrubbing. No frame-by-frame editing. Just one sentence → one video.
|
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<p align="center"><i>👆 Click the cover to play the full demo</i></p>
|
||||
|
||||
One sentence builds a reusable cloud-side short-film director for storyboarding, storyboard image generation, and video creation:
|
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|
||||
- **[Qwen Code](https://github.com/QwenLM/qwen-code)** — understands the requirement and generates the agent configuration
|
||||
- **[Aliyun Model Studio CLI](https://github.com/modelstudioai/cli/)** — validates the configuration, previews the changes, and completes the deployment
|
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- **[Managed Agent](https://bailian.console.aliyun.com/cn-beijing/?tab=managed-agents#/managed-agents/quick-start)** — runs the director role along with its skills and tools in the cloud
|
||||
|
||||
### The single prompt
|
||||
|
||||
> _"Build me a Managed Agent app that can produce short films — a director expert that generates videos and can also design the matching storyboards."_
|
||||
|
||||
## Installation
|
||||
|
||||
**Agent install (recommended)**
|
||||
|
||||
Send the following to your Agent — it will detect your environment, then install and verify the CLI for you:
|
||||
|
||||
```text
|
||||
Please read https://bailian.aliyun.com/cli/install.md and install the Aliyun Model Studio CLI for me
|
||||
```
|
||||
|
||||
**Manual install (npm)**
|
||||
|
||||
```bash
|
||||
# Recommended — no Node required
|
||||
curl -fsSL https://bailian.aliyun.com/cli/install.sh | bash
|
||||
|
||||
# Windows (PowerShell)
|
||||
irm https://bailian.aliyun.com/cli/install.ps1 | iex
|
||||
|
||||
# Node users / developers (Node.js >= 18.17)
|
||||
npm install -g bailian-cli
|
||||
|
||||
# Agent skills
|
||||
npx skills add modelstudioai/cli --all -g
|
||||
```
|
||||
|
||||
> Binary install does not require Node.js. `npm install -g` remains fully supported.
|
||||
> Requires Node.js >= 18.17.
|
||||
|
||||
## Quick Start
|
||||
|
||||
```bash
|
||||
# Authenticate, recommended
|
||||
bl auth login --console
|
||||
Once installed, just describe your task to your AI Agent — no need to assemble commands by hand.
|
||||
|
||||
# Or authenticate with an API key
|
||||
bl auth login --api-key sk-xxxxx
|
||||
|
||||
# Or use Token Plan (Base URL built in; the key is tested during login)
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||||
bl auth login --config token-plan --api-key sk-sp-xxxxx
|
||||
|
||||
# Configure a coding agent to use DashScope
|
||||
bl config agent --agent codex --base-url https://dashscope.aliyuncs.com/compatible-mode/v1 --api-key sk-xxxxx --model qwen3-coder-plus
|
||||
|
||||
# Chat with Qwen
|
||||
bl text chat --message "What is DashScope?"
|
||||
|
||||
# Multimodal chat (text + image + audio + video)
|
||||
bl omni --message "Describe this image" --image ./photo.jpg
|
||||
|
||||
# Generate an image
|
||||
bl image generate --prompt "A cat in a spacesuit" --out-dir ./images/
|
||||
|
||||
# Generate a video from local image
|
||||
bl video generate --image ./cat.png --prompt "Make the cat move" --download cat.mp4
|
||||
|
||||
# Model recommendation — find the best model for your use case
|
||||
bl advisor recommend --message "I need a visual-understanding chatbot"
|
||||
|
||||
# Compare specific models
|
||||
bl advisor recommend --message "qwen-max vs deepseek-v3 for code generation"
|
||||
|
||||
# Browser login (required for console capability commands)
|
||||
bl auth login --console
|
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|
||||
# Fine-tune & deploy — a one-shot train-to-serve workflow
|
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bl dataset upload --file ./train.jsonl # Upload a .jsonl dataset (validated first)
|
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bl finetune text create --model qwen3-8b --datasets ./train.jsonl --training-type sft-lora # Local paths auto-upload
|
||||
bl finetune watch --job-id ft-xxx --output json # Non-blocking probe (running/succeeded return 0; failed/canceled report an error)
|
||||
bl finetune capability --model qwen3-8b # Which training types a model supports
|
||||
bl deploy text create --model qwen3-8b --name my-svc --plan mu # Deploy the trained model as an endpoint
|
||||
|
||||
# Browse models / apps / free-tier quota / usage statistics / workspaces
|
||||
bl model list # Browse model families and pricing
|
||||
bl app list
|
||||
bl usage summary # Unified view: free-tier quota + recent usage overview
|
||||
bl usage free # Free-tier quota across models (add --model/--expiring/--sort)
|
||||
bl usage stats --workspace-id <id> # Model usage statistics (add --model for per-model)
|
||||
bl workspace list # List all workspaces
|
||||
|
||||
# Rate limit management (list / check / request / history)
|
||||
bl quota list # View RPM/TPM limits (add --model to filter)
|
||||
bl quota check # Current usage vs rate limits (add --model/--period)
|
||||
bl quota request --model qwen3.6-plus --tpm 6000000 # Request a temporary TPM increase
|
||||
bl quota history # View quota-change history
|
||||
|
||||
# Token Plan team management (requires AK/SK, see auth below)
|
||||
bl token-plan list-seats # View subscription seat details
|
||||
bl token-plan add-member --account-name dev --org-id org_xxx
|
||||
bl token-plan assign-seats --workspace-id ws_xxx --seat-type standard --account-id acc_xxx
|
||||
bl token-plan create-key --account-id acc_xxx --workspace-id ws_xxx
|
||||
```
|
||||
| Scenario | What to say to your Agent |
|
||||
| ------------------------ | --------------------------------------------------------------------------------- |
|
||||
| Managed Agent | "Create a Managed Agent that can generate short-film storyboards and videos." |
|
||||
| Image & video generation | "Generate an image of a cat in a spacesuit on Mars, then turn it into a video." |
|
||||
| Usage & quota | "Show my recent model usage, free-tier quota, and rate limits." |
|
||||
| Model selection | "Recommend a model for image understanding and customer support." |
|
||||
| About Bailian CLI | "Tell me what Bailian CLI can do for me, and suggest how to use it for my needs." |
|
||||
|
||||
> More examples and scenarios: [Aliyun Model Studio CLI Site](https://bailian.console.aliyun.com/cli?source_channel=cli_github&)
|
||||
|
||||
## Authentication
|
||||
|
||||
### DashScope API Key
|
||||
### API Key
|
||||
|
||||
Required for most commands. Get your key from the [DashScope Console](https://bailian.console.aliyun.com/cn-beijing/?source_channel=key_github&tab=app#/api-key).
|
||||
|
||||
```bash
|
||||
# Option 1: Environment variable
|
||||
export DASHSCOPE_API_KEY=sk-xxxxx
|
||||
|
||||
# Option 2: Login command (persisted to ~/.bailian/config.json)
|
||||
bl auth login --api-key sk-xxxxx
|
||||
|
||||
# Option 3: Per-command flag
|
||||
bl text chat --api-key sk-xxxxx --message "Hello"
|
||||
```
|
||||
|
||||
### Token Plan API Key
|
||||
|
||||
Get or copy the API key from the [Token Plan subscription overview](https://bailian.console.aliyun.com/cn-beijing?tab=plan#/efm/subscription/overview).
|
||||
The CLI has the default Token Plan Base URL built in. Login tests the key first, then saves and activates the `token-plan` config only when validation succeeds.
|
||||
Get or copy your Token Plan API key from the [Token Plan subscription overview](https://bailian.console.aliyun.com/cn-beijing?tab=plan#/efm/subscription/overview).
|
||||
|
||||
```bash
|
||||
bl auth login --config token-plan --api-key sk-sp-xxxxx
|
||||
@@ -186,26 +123,20 @@ bl auth login --config token-plan --api-key sk-sp-xxxxx
|
||||
|
||||
### Console Login (OAuth)
|
||||
|
||||
Required for console capability commands (`model list`, `app list`, `usage summary/free/stats`, `workspace list`, `quota list/request/check/history`). Opens the Bailian console in your browser to sign in.
|
||||
Required for console capability commands (model list, app list, MCP list, workspace, usage queries, rate-limit increases, direct console calls). Opens the Bailian console in your browser to sign in.
|
||||
|
||||
```bash
|
||||
bl auth login --console
|
||||
```
|
||||
|
||||
### Alibaba Cloud OpenAPI AK/SK (Token Plan only)
|
||||
### Alibaba Cloud OpenAPI AK/SK
|
||||
|
||||
Required for the `token-plan` command group. Get your AccessKey from [RAM Console](https://ram.console.aliyun.com/manage/ak).
|
||||
Token Plan seat and member management requires an Alibaba Cloud AccessKey. Get yours from the [RAM Console](https://ram.console.aliyun.com/manage/ak).
|
||||
|
||||
> Recommended: create a RAM sub-account with minimum privileges instead of using the root account's AK/SK.
|
||||
|
||||
```bash
|
||||
# Option 1: Login command (persisted to ~/.bailian/config.json)
|
||||
bl auth login --open-api --access-key-id LTAI5t... --access-key-secret ...
|
||||
|
||||
# Option 2: Environment variables
|
||||
export ALIBABA_CLOUD_ACCESS_KEY_ID=LTAI5t...
|
||||
export ALIBABA_CLOUD_ACCESS_KEY_SECRET=...
|
||||
export BAILIAN_WORKSPACE_ID=ws-...
|
||||
```
|
||||
|
||||
## Configuration
|
||||
@@ -214,18 +145,31 @@ export BAILIAN_WORKSPACE_ID=ws-...
|
||||
# View current config
|
||||
bl config show
|
||||
|
||||
# Set defaults
|
||||
bl config set --key base_url --value https://dashscope-us.aliyuncs.com
|
||||
bl config set --key default_text_model --value qwen-turbo
|
||||
bl config set --key timeout --value 600
|
||||
# List all config profiles
|
||||
bl config list
|
||||
|
||||
# Self-update to latest or a specific version
|
||||
bl update
|
||||
bl update --to 0.1.14
|
||||
# Switch config profile
|
||||
bl config use --name token-plan
|
||||
```
|
||||
|
||||
Config file location: `~/.bailian/config.json`
|
||||
|
||||
## Update
|
||||
|
||||
```bash
|
||||
bl update
|
||||
```
|
||||
|
||||
Upgrades the CLI to the latest version and refreshes the installed Agent Skills. Release notes for every version live in [CHANGELOG.md](https://github.com/modelstudioai/cli/blob/main/CHANGELOG.md).
|
||||
|
||||
## Contributing
|
||||
|
||||
Bug reports, feature requests, and PRs are welcome. See [CONTRIBUTING.md](https://github.com/modelstudioai/cli/blob/main/CONTRIBUTING.md) for developer setup, repo layout, and the workflow for adding or changing commands.
|
||||
|
||||
Scan the QR code to join the Aliyun Model Studio CLI DingTalk user group for usage help, troubleshooting, bug reports, and tips from other users.
|
||||
|
||||
<img src="https://img.alicdn.com/imgextra/i3/O1CN015uuhYGb6j0L12xJZ_!!6000000006304-2-tps-516-485.png" alt="Aliyun Model Studio CLI DingTalk user group" width="240" />
|
||||
|
||||
## Links
|
||||
|
||||
| Resource | URL |
|
||||
@@ -237,11 +181,3 @@ Config file location: `~/.bailian/config.json`
|
||||
| Get API Key | https://bailian.console.aliyun.com/cn-beijing/?source_channel=key_github&tab=app#/api-key |
|
||||
| Get Token Plan API Key | https://bailian.console.aliyun.com/cn-beijing?tab=plan#/efm/subscription/overview |
|
||||
| Get AccessKey | https://ram.console.aliyun.com/manage/ak |
|
||||
|
||||
## Changelog
|
||||
|
||||
Release notes for every version live in [CHANGELOG.md](https://github.com/modelstudioai/cli/blob/main/CHANGELOG.md).
|
||||
|
||||
## Contributing
|
||||
|
||||
Bug reports, feature requests, and PRs are welcome. See [CONTRIBUTING.md](https://github.com/modelstudioai/cli/blob/main/CONTRIBUTING.md) for developer setup, repo layout, and the workflow for adding or changing commands.
|
||||
|
||||
+73
-138
@@ -22,28 +22,16 @@ _专为 AI Agent 打造，每个命令均可作为结构化工具调用。_
|
||||
|
||||
## 功能特性
|
||||
|
||||
让您的 AI Agent 开箱即具备以下能力，并可在复杂任务中自动组合调用：
|
||||
- **模型生成** — 文本、图像、视频、语音全模态生成，支持编辑与参考生成
|
||||
- **素材理解** — 图像、文档、音频、长视频的解析与问答
|
||||
- **应用编排** — 调用百炼已发布的 Managed Agent、智能体和工作流，接入知识库、记忆库、联网搜索与 MCP 工具
|
||||
- **模型训推** — 数据集校验上传、模型精调、专属模型部署上线
|
||||
- **账号运维** — 授权登录、界面化配置、模型市场、用量与额度、限流提额、团队席位管理
|
||||
- **套餐接入** — 支持 Token Plan 等订阅计划一键接到 CLI 和常见 Coding Agent
|
||||
|
||||
- **文本对话** — Qwen3.8-max：Agentic coding、前端编程、Vibe coding 等能力显著增强
|
||||
- **全模态对话** — 文本 + 图像 + 音频 + 视频全模态支持
|
||||
- **图像生成与编辑** — Qwen-Image 3.0：专业文字渲染、真实质感、强语义遵循、多图合成
|
||||
- **视频生成与编辑** — happyhorse-1.1 系列，支持文生 / 图生 / 参考生（最多 9 张图参考）/ 自然语言视频编辑
|
||||
- **语音合成与识别** — CosyVoice 实时流式合成，5-20s 样本即可克隆；FunAudio-ASR 覆盖 30 种语种，含汉语七大方言与 20+ 口音官话
|
||||
- **图像与视频理解** — Qwen-VL：长视频解析、复杂图表与文档识别、视觉推理、多语种 OCR
|
||||
- **Coding Agent 配置** — 使用 `bl config agent` 将 Claude Code、Qwen Code、OpenCode、OpenClaw、Hermes Agent 或 Codex 配置为使用 DashScope
|
||||
> **注意：** 应用编排、模型训推、账号运维和套餐接入目前仅支持中国站（aliyun.com）账号，暂不支持国际站 / 全球站账号。
|
||||
|
||||
> **注意：** 以下功能目前仅对中国站（aliyun.com）账号开放，国际站 / 全球站账号暂不支持。
|
||||
|
||||
- **知识库与记忆库** — 多模态 RAG 检索 + 跨会话记忆，提供个性化连贯对话体验
|
||||
- **应用调用** — 调用已发布在阿里云百炼平台上的智能体与工作流应用
|
||||
- **MCP 集成** — 统一调度百炼 MCP 服务：列出服务、查看工具、直接在终端调用任意工具
|
||||
- **联网搜索** — 实时互联网信息检索，提升回答准确性及时效性
|
||||
- **模型推荐** — 描述你的场景，智能推荐最适合的模型；支持限定范围搜索、模型对比和替代发现
|
||||
- **微调与部署** — 上传数据集、创建文本/音频/图像调优任务（`finetune text|audio|image create`；文本涵盖 SFT/LoRA/DPO/CPT）、非阻塞探测任务状态（`finetune watch`）、按模型查训练能力（`finetune capability`），并把训练好的模型部署为推理服务（`deploy text|audio|image create`）
|
||||
- **控制台能力** — 浏览模型市场（`model list`）和百炼应用（`app list`），查看统一用量视图（`usage summary`），查询模型免费额度（`usage free`），查看模型用量统计（`usage stats`），管理业务空间（`workspace list`），管理限流与提额（`quota list/request/check/history`）
|
||||
- **本地文件自动上传** — 所有 URL 参数同时支持本地路径，免费临时存储 48 小时
|
||||
|
||||
## 示例:一句话生成一部电影短片
|
||||
## 示例 1：一句话生成一部电影短片
|
||||
|
||||
<p align="center">
|
||||
<a href="https://cloud.video.taobao.com/vod/dS2F4huqbw5Nfe5L3wwb3grz2q2DNYD3retq8dU-iHo.mp4">
|
||||
@@ -53,130 +41,80 @@ _专为 AI Agent 打造，每个命令均可作为结构化工具调用。_
|
||||
|
||||
<p align="center"><i>👆 点击封面播放完整 2 分钟演示</i></p>
|
||||
|
||||
一部完整的 **2 分钟、16:9 电影感短片** —— 由一句自然语言端到端生成,**全程零手动剪辑**。这个示例展示了 AI Agent 如何把三个基础能力编排成一条多步创作流水线:
|
||||
一部完整的 **2 分钟、16:9 电影感短片** —— 由一句自然语言端到端生成，**全程零手动剪辑**。这个示例展示了 AI Agent 如何把三个基础能力编排成一条多步创作流水线：
|
||||
|
||||
- **[Qwen Code](https://github.com/QwenLM/qwen-code)** —— Agentic coding 模型,解析用户意图、驱动整个工作流
|
||||
- **[阿里云百炼 CLI](https://github.com/modelstudioai/cli/)** —— 调用 **HappyHorse 1.1**,百炼的文生/图生/参考生视频模型
|
||||
- **[Qwen Code](https://github.com/QwenLM/qwen-code)** —— Agentic coding 模型，解析用户意图、驱动整个工作流
|
||||
- **[阿里云百炼 CLI](https://github.com/modelstudioai/cli/)** —— 调用 **HappyHorse 1.1**，百炼的文生/图生/参考生视频模型
|
||||
- **[spark-video Skill](https://github.com/JohnKeating1997/spark-video)** —— 负责场景拆分、分镜设计、镜头连贯性和最终拼接
|
||||
|
||||
### 唯一的提示词
|
||||
|
||||
> _"帮我生成一段日系影视风格,高中女生的青涩初恋故事,剧情高甜,让人看了想谈恋爱,2 分钟左右的视频,尺寸是 16:9"_
|
||||
> _“帮我生成一段日系影视风格，高中女生的青涩初恋故事，剧情高甜，让人看了想谈恋爱，2 分钟左右的视频，尺寸是 16:9。”_
|
||||
|
||||
### 工作流程
|
||||
## 示例 2：一句话构建短片导演 Managed Agent
|
||||
|
||||
1. **Qwen Code** 解析需求、规划叙事节奏,决定要调用哪些工具。
|
||||
2. **spark-video Skill** 把故事拆成镜头、为每个镜头写提示词,并保证视觉连贯性(角色、光线、色调、镜头语言)。
|
||||
3. **`bl video generate`** 把每个镜头并行下发给 **HappyHorse 1.1**。
|
||||
4. Skill 把所有片段拼成最终的 16:9 / 约 2 分钟成片。
|
||||
<p align="center">
|
||||
<a href="https://cloud.video.taobao.com/vod/2v0GYLbJSQb2saj4iopTJDW3iRIHsintYlK-wTKbhqE.mp4">
|
||||
<img src="https://img.alicdn.com/imgextra/i4/6000000001674/O1CN01xhzixhxltbH3LxWu_!!6000000001674-0-tbvideo.jpg" alt="点击播放演示视频" width="720" />
|
||||
</a>
|
||||
</p>
|
||||
|
||||
没有时间线拖拽,没有逐帧剪辑。一句话 → 一部短片。
|
||||
<p align="center"><i>👆 点击封面播放完整演示</i></p>
|
||||
|
||||
一句话构建一个可复用的云端短片导演，用于分镜设计、分镜图生成和视频创作：
|
||||
|
||||
- **[Qwen Code](https://github.com/QwenLM/qwen-code)** —— 理解需求并生成 Agent 配置
|
||||
- **[阿里云百炼 CLI](https://github.com/modelstudioai/cli/)** —— 校验配置、预览变更并完成部署
|
||||
- **[Managed Agent](https://bailian.console.aliyun.com/cn-beijing/?tab=managed-agents#/managed-agents/quick-start)** —— 在云端运行导演角色及其 Skill 和工具
|
||||
|
||||
### 唯一的提示词
|
||||
|
||||
> _“帮我构建一个 managedagent 应用，能够实现短片拍摄，导演专家生成视频，然后也能进行设计对应的分镜图。”_
|
||||
|
||||
## 安装
|
||||
|
||||
**Agent 安装（推荐）**
|
||||
|
||||
把下面这句话发给你的 Agent，它会自行判断环境并完成安装与校验：
|
||||
|
||||
```text
|
||||
请阅读：https://bailian.aliyun.com/cli/install.md 并按照说明为我安装阿里云百炼 CLI
|
||||
```
|
||||
|
||||
**手动安装（npm）**
|
||||
|
||||
```bash
|
||||
# 推荐 — 无需本机 Node.js
|
||||
curl -fsSL https://bailian.aliyun.com/cli/install.sh | bash
|
||||
|
||||
# Windows（PowerShell）
|
||||
irm https://bailian.aliyun.com/cli/install.ps1 | iex
|
||||
|
||||
# Node 用户 / 开发者（需要 Node.js >= 18.17）
|
||||
npm install -g bailian-cli
|
||||
|
||||
# Agent skills
|
||||
npx skills add modelstudioai/cli --all -g
|
||||
```
|
||||
|
||||
> 二进制安装不依赖 Node.js。`npm install -g` 长期保留。
|
||||
> 需要预先安装 Node.js >= 18.17。
|
||||
|
||||
## 快速开始
|
||||
|
||||
```bash
|
||||
# 认证（推荐浏览器登录）
|
||||
bl auth login --console
|
||||
安装完成后，直接在 AI Agent 中描述你的任务，无需手动拼接命令。
|
||||
|
||||
# 或使用 API key 认证
|
||||
bl auth login --api-key sk-xxxxx
|
||||
|
||||
# 或使用 Token Plan（已内置 Base URL，登录时自动测试 Key）
|
||||
bl auth login --config token-plan --api-key sk-sp-xxxxx
|
||||
|
||||
# 配置 Coding Agent 使用 DashScope
|
||||
bl config agent --agent codex --base-url https://dashscope.aliyuncs.com/compatible-mode/v1 --api-key sk-xxxxx --model qwen3-coder-plus
|
||||
|
||||
# 和通义千问对话
|
||||
bl text chat --message "你好，介绍一下阿里云百炼平台"
|
||||
|
||||
# 多模态对话（文本 + 图片 + 音频 + 视频）
|
||||
bl omni --message "描述这张图片" --image ./photo.jpg
|
||||
|
||||
# 生成图片
|
||||
bl image generate --prompt "一只穿太空服的猫在火星上" --out-dir ./images/
|
||||
|
||||
# 图生视频（本地文件自动上传）
|
||||
bl video generate --image ./cat.png --prompt "让画面中的猫动起来" --download cat.mp4
|
||||
|
||||
# 模型推荐 — 根据场景推荐最适合的模型
|
||||
bl advisor recommend --message "我要做一个能理解图片的客服机器人"
|
||||
|
||||
# 对比特定模型
|
||||
bl advisor recommend --message "qwen-max 和 deepseek-v3 哪个更适合做代码生成"
|
||||
|
||||
# 浏览器登录（控制台能力相关命令需要）
|
||||
bl auth login --console
|
||||
|
||||
# 微调与部署 — 从训练到服务的一站式流程
|
||||
bl dataset upload --file ./train.jsonl # 上传 .jsonl 数据集（先校验）
|
||||
bl finetune text create --model qwen3-8b --datasets ./train.jsonl --training-type sft-lora # 本地路径自动上传
|
||||
bl finetune watch --job-id ft-xxx --output json # 非阻塞探测（运行中/成功返回 0；失败/取消报错）
|
||||
bl finetune capability --model qwen3-8b # 查询模型支持哪些训练方式
|
||||
bl deploy text create --model qwen3-8b --name my-svc --plan mu # 把训练好的模型部署为推理服务
|
||||
|
||||
# 浏览模型 / 应用 / 免费额度 / 用量统计 / 业务空间
|
||||
bl model list # 浏览模型系列与价格信息
|
||||
bl app list
|
||||
bl usage summary # 统一视图：免费额度 + 近期用量概览
|
||||
bl usage free # 各模型免费额度（可加 --model/--expiring/--sort）
|
||||
bl usage stats --workspace-id <id> # 模型用量统计（加 --model 查单模型）
|
||||
bl workspace list # 列出所有业务空间
|
||||
|
||||
# 限流管理与提额（list / check / request / history）
|
||||
bl quota list # 查看 RPM/TPM 限额（加 --model 过滤）
|
||||
bl quota check # 当前用量 vs 限流阈值（加 --model/--period）
|
||||
bl quota request --model qwen3.6-plus --tpm 6000000 # 申请临时 TPM 提额
|
||||
bl quota history # 查看提额历史记录
|
||||
|
||||
# Token Plan 团队版管理（需 AK/SK，见下方认证说明）
|
||||
bl token-plan list-seats # 查看订阅席位明细
|
||||
bl token-plan add-member --account-name dev --org-id org_xxx
|
||||
bl token-plan assign-seats --workspace-id ws_xxx --seat-type standard --account-id acc_xxx
|
||||
bl token-plan create-key --account-id acc_xxx --workspace-id ws_xxx
|
||||
```
|
||||
| 场景 | 可以这样对 Agent 说 |
|
||||
| ---------------- | ----------------------------------------------------------------------- |
|
||||
| Managed Agent | “帮我创建一个能够生成短片分镜和视频的 Managed Agent。” |
|
||||
| 图片和视频生成 | “生成一张穿着太空服的猫站在火星上的图片，再把它制作成一段视频。” |
|
||||
| 用量与额度 | “查看最近的模型用量、免费额度和限流情况。” |
|
||||
| 模型选型 | “推荐一个适合图片理解和智能客服的模型。” |
|
||||
| 了解 Bailian CLI | “介绍一下 Bailian CLI 能帮我完成哪些任务，并根据我的需求推荐使用方式。” |
|
||||
|
||||
> 更多案例与使用场景：[阿里云百炼 CLI 官方主页](https://bailian.console.aliyun.com/cli?source_channel=cli_github&)
|
||||
|
||||
## 认证方式
|
||||
|
||||
### DashScope API Key
|
||||
### API Key
|
||||
|
||||
大部分命令均需要 API Key。前往 [DashScope 控制台](https://bailian.console.aliyun.com/cn-beijing/?source_channel=key_github&tab=app#/api-key) 获取。
|
||||
|
||||
```bash
|
||||
# 方式一：环境变量
|
||||
export DASHSCOPE_API_KEY=sk-xxxxx
|
||||
|
||||
# 方式二：登录命令（持久化到 ~/.bailian/config.json）
|
||||
bl auth login --api-key sk-xxxxx
|
||||
|
||||
# 方式三：命令行参数
|
||||
bl text chat --api-key sk-xxxxx --message "你好"
|
||||
```
|
||||
|
||||
### Token Plan API Key
|
||||
|
||||
前往 [Token Plan 订阅详情](https://bailian.console.aliyun.com/cn-beijing?tab=plan#/efm/subscription/overview) 获取或复制 API Key。
|
||||
CLI 已内置 Token Plan 的默认 Base URL；登录命令会先测试 Key，通过后才保存并激活 `token-plan` 配置。
|
||||
Token Plan 的 API Key 前往 [Token Plan 订阅详情](https://bailian.console.aliyun.com/cn-beijing?tab=plan#/efm/subscription/overview) 获取或复制。
|
||||
|
||||
```bash
|
||||
bl auth login --config token-plan --api-key sk-sp-xxxxx
|
||||
@@ -184,26 +122,20 @@ bl auth login --config token-plan --api-key sk-sp-xxxxx
|
||||
|
||||
### 控制台登录（OAuth）
|
||||
|
||||
控制台能力命令（`model list`、`app list`、`usage summary/free/stats`、`workspace list`、`quota list/request/check/history`）需要使用此登录方式。打开浏览器跳转百炼控制台完成登录。
|
||||
控制台能力命令（模型列表、应用列表、MCP 列表、工作空间、用量查询、限流提额、控制台直调）需要使用此登录方式。打开浏览器跳转百炼控制台完成登录。
|
||||
|
||||
```bash
|
||||
bl auth login --console
|
||||
```
|
||||
|
||||
### 阿里云 OpenAPI AK/SK（仅 Token Plan）
|
||||
### 阿里云 OpenAPI AK/SK
|
||||
|
||||
`token-plan` 命令组需要阿里云 AccessKey。前往 [RAM 控制台](https://ram.console.aliyun.com/manage/ak) 获取。
|
||||
Token Plan 的席位与成员管理需要阿里云 AccessKey。前往 [RAM 控制台](https://ram.console.aliyun.com/manage/ak) 获取。
|
||||
|
||||
> 建议：创建 RAM 子账号并授予最小权限，避免使用主账号 AK/SK。
|
||||
|
||||
```bash
|
||||
# 方式一：登录命令（持久化到 ~/.bailian/config.json）
|
||||
bl auth login --open-api --access-key-id LTAI5t... --access-key-secret ...
|
||||
|
||||
# 方式二：环境变量
|
||||
export ALIBABA_CLOUD_ACCESS_KEY_ID=LTAI5t...
|
||||
export ALIBABA_CLOUD_ACCESS_KEY_SECRET=...
|
||||
export BAILIAN_WORKSPACE_ID=ws-...
|
||||
```
|
||||
|
||||
## 配置
|
||||
@@ -212,20 +144,31 @@ export BAILIAN_WORKSPACE_ID=ws-...
|
||||
# 查看当前配置
|
||||
bl config show
|
||||
|
||||
# 设置默认值
|
||||
bl config set --key base_url --value https://dashscope-us.aliyuncs.com
|
||||
bl config set --key default_text_model --value qwen-turbo
|
||||
bl config set --key timeout --value 600
|
||||
# 查看全部配置档
|
||||
bl config list
|
||||
|
||||
# 自更新到最新版本
|
||||
bl update
|
||||
|
||||
# 安装指定版本
|
||||
bl update --to 0.1.14
|
||||
# 切换配置档
|
||||
bl config use --name token-plan
|
||||
```
|
||||
|
||||
配置文件位置：`~/.bailian/config.json`
|
||||
|
||||
## 更新
|
||||
|
||||
```bash
|
||||
bl update
|
||||
```
|
||||
|
||||
升级 CLI 至最新版本，并同步更新已安装的 Agent Skills。每个版本的变更详情记录在 [CHANGELOG.zh.md](https://github.com/modelstudioai/cli/blob/main/CHANGELOG.zh.md)。
|
||||
|
||||
## 参与贡献
|
||||
|
||||
欢迎提 Issue、Feature Request 和 PR。开发环境搭建、仓库结构、新增/修改命令的工作流请见 [CONTRIBUTING.zh.md](https://github.com/modelstudioai/cli/blob/main/CONTRIBUTING.zh.md)。
|
||||
|
||||
欢迎扫码加入阿里云百炼 CLI 钉钉用户交流群，获取使用答疑、问题排查、Bug 反馈和使用经验交流支持。
|
||||
|
||||
<img src="https://img.alicdn.com/imgextra/i3/O1CN015uuhYGb6j0L12xJZ_!!6000000006304-2-tps-516-485.png" alt="阿里云百炼 CLI 钉钉用户交流群" width="240" />
|
||||
|
||||
## 相关链接
|
||||
|
||||
| 资源 | 地址 |
|
||||
@@ -237,11 +180,3 @@ bl update --to 0.1.14
|
||||
| 获取 API Key | https://bailian.console.aliyun.com/cn-beijing/?source_channel=key_github&tab=app#/api-key |
|
||||
| 获取 Token Plan API Key | https://bailian.console.aliyun.com/cn-beijing?tab=plan#/efm/subscription/overview |
|
||||
| 获取 AccessKey | https://ram.console.aliyun.com/manage/ak |
|
||||
|
||||
## 更新日志
|
||||
|
||||
每个版本的变更详情记录在 [CHANGELOG.zh.md](https://github.com/modelstudioai/cli/blob/main/CHANGELOG.zh.md)。
|
||||
|
||||
## 参与贡献
|
||||
|
||||
欢迎提 Issue、Feature Request 和 PR。开发环境搭建、仓库结构、新增/修改命令的工作流请见 [CONTRIBUTING.zh.md](https://github.com/modelstudioai/cli/blob/main/CONTRIBUTING.zh.md)。
|
||||
|
||||
@@ -25,7 +25,7 @@ defineCommand({ auth }) → runtime/authStage → ctx.client → command.run(ctx
|
||||
当前 command 鉴权域(`AuthRequirement`):
|
||||
|
||||
- `apiKey` — DashScope / OpenAI-compatible 模型域,用 API key 与 model base URL
|
||||
- `console` — Bailian Console Gateway,用 console access token + region/site/switchAgent/workspace
|
||||
- `console` — Bailian Console Gateway,用 console access token + region/site/switchAgent;`workspace_id` 是独立的 Settings 作用域,不属于 credential
|
||||
- `openapi` — 阿里云 OpenAPI 签名域,用 AccessKey ID/Secret 调用 Token Plan 等 OpenAPI
|
||||
- `none` — 本地命令、登录/配置类命令、无需 credential 的命令
|
||||
|
||||
@@ -35,7 +35,7 @@ defineCommand({ auth }) → runtime/authStage → ctx.client → command.run(ctx
|
||||
|
||||
- `bl auth login --api-key ...` 只更新 `api_key` / `base_url`
|
||||
- `bl auth login --console` 只更新 `access_token` 以及回调携带的 console 作用域字段
|
||||
- `bl auth login --open-api ...` 只更新 `access_key_id` / `access_key_secret`
|
||||
- `bl auth login --open-api ...` 更新 `access_key_id` / `access_key_secret`,同时会调用 OpenAPI 生成 CLI `access_token` 并一并写入;即一次 `--open-api` 登录同时产生 `openapi` 与 `console` 域凭证
|
||||
- `bl auth logout --console` 只清 `access_token`
|
||||
- `bl auth logout --open-api` 只清 `access_key_id` / `access_key_secret` / `security_token`
|
||||
- `bl auth logout` 清 `api_key` + `base_url` + `access_token` + `access_key_*`
|
||||
@@ -78,6 +78,9 @@ defineCommand({ auth }) → runtime/authStage → ctx.client → command.run(ctx
|
||||
- 如新增鉴权域,扩展 `AuthRequirement`
|
||||
- 更新 `credentialFlagDefs()` 暴露该域可见的 flag
|
||||
- 必要时新增 `*_AUTH_FLAGS`
|
||||
- `workspace_id` 是作用域字段而非 credential,不要把它放进 `ConsoleCredential`;读取方式按命令 `auth` 域区分:
|
||||
- `auth: "console"` 命令通过 `CONSOLE_AUTH_FLAGS` 自动获得 `--workspace-id`,由 `buildSettings()` 解析到 `settings.workspaceId`,命令统一从 `settings.workspaceId` 读取
|
||||
- `auth: "apiKey"`/`"openapi"`/`"none"` 命令如需 `--workspace-id`,必须自声明 flag;因它不会进入 credential/global flags,命令从 `ctx.flags.workspaceId` 读取(可回退到 `settings.workspaceId`)
|
||||
- [ ] `packages/core/src/auth/types.ts`:
|
||||
- 新增 credential 类型 / source / scope 字段
|
||||
- [ ] `packages/core/src/auth/resolver.ts`:
|
||||
@@ -131,6 +134,8 @@ defineCommand({ auth }) → runtime/authStage → ctx.client → command.run(ctx
|
||||
|
||||
## 完成后自查
|
||||
|
||||
本仓库同时存在 `bl`(packages/cli) 与 `kscli`(packages/kscli) 两个入口,二者共享 core/runtime 鉴权链路,但暴露的命令不同。如果改动会影响两个入口共用的命令或错误提示,再分别验证它们各自实际暴露的路径;不要假设 `kscli` 也有 `bl auth *` 命令。
|
||||
|
||||
```sh
|
||||
# 各种凭证组合
|
||||
unset DASHSCOPE_API_KEY ALIBABA_CLOUD_ACCESS_KEY_ID ALIBABA_CLOUD_ACCESS_KEY_SECRET
|
||||
@@ -150,9 +155,11 @@ Console 登录/网关相关改动:
|
||||
|
||||
```sh
|
||||
pnpm -F bailian-cli exec tsx src/main.ts auth login --console
|
||||
pnpm -F bailian-cli exec tsx src/main.ts usage stats --dry-run --output json
|
||||
pnpm -F bailian-cli exec tsx src/main.ts usage stats --dry-run --output json --workspace-id ws-xxx
|
||||
```
|
||||
|
||||
注意:`usage stats --dry-run` 仍会先校验 workspace,必须传入 `--workspace-id`(或 `BAILIAN_WORKSPACE_ID` / config `workspace_id`)。
|
||||
|
||||
## 常见漏点
|
||||
|
||||
- ✗ 加了新 token 来源但忘了改 resolver 优先级,实际不生效
|
||||
|
||||
+73
-137
@@ -13,8 +13,9 @@
|
||||
|
||||
---
|
||||
|
||||
_Chat with Qwen, generate images & videos, understand images, call agents,_
|
||||
_manage memory, search the web — all from your terminal._
|
||||
_Chat with Qwen, generate and edit images and videos, understand images, synthesize_
|
||||
_and recognize speech, call apps, manage memory, retrieve knowledge, search the web —_
|
||||
_every AI capability, one command away._
|
||||
|
||||
_Built for AI Agents. Every command works as a structured tool call._
|
||||
|
||||
@@ -22,28 +23,16 @@ _Built for AI Agents. Every command works as a structured tool call._
|
||||
|
||||
## Features
|
||||
|
||||
Equip your AI Agent out-of-the-box with these capabilities, composable across complex tasks:
|
||||
- **Model generation** — Full-modality generation across text, image, video, and speech, with editing and reference-based generation
|
||||
- **Asset understanding** — Parse and ask questions about images, documents, audio, and long videos
|
||||
- **App orchestration** — Call Managed Agents, agents, and workflows published on Aliyun Model Studio, wired to knowledge bases, memory, web search, and MCP tools
|
||||
- **Training & deployment** — Validate and upload datasets, fine-tune models, deploy dedicated models as endpoints
|
||||
- **Account operations** — Login, UI-based configuration, model marketplace, usage and quota, rate-limit increases, team seat management
|
||||
- **Plan onboarding** — Connect subscription plans such as Token Plan to the CLI and common coding agents in one step
|
||||
|
||||
- **Text chat** — Qwen3.8-max: major gains in agentic coding, frontend coding, and vibe coding
|
||||
- **Multimodal (Omni)** — Full omni-modal support across text + image + audio + video
|
||||
- **Image generation & editing** — Qwen-Image 3.0: pro text rendering, photorealism, strong semantic adherence, multi-image composition
|
||||
- **Video generation & editing** — happyhorse-1.1 series: text-/image-/reference-to-video and natural-language video editing (up to 9-image reference)
|
||||
- **Speech synthesis & recognition** — CosyVoice streaming TTS, voice cloning from 5–20s samples; FunAudio-ASR covers 30 languages including 7 Chinese dialects and 20+ Mandarin accents
|
||||
- **Image & video understanding** — Qwen-VL: long-form video analysis, chart/document parsing, visual reasoning, multilingual OCR
|
||||
- **Coding agent setup** — Configure Claude Code, Qwen Code, OpenCode, OpenClaw, Hermes Agent, or Codex to use DashScope with `bl config agent`
|
||||
> **Note:** App orchestration, training & deployment, account operations, and plan onboarding are currently available only to China site (aliyun.com) account holders and are not yet supported for international / global site accounts.
|
||||
|
||||
> **Note:** The features below are currently available only to China site (aliyun.com) account holders and are not yet supported for international / global site accounts.
|
||||
|
||||
- **Knowledge base & memory** — Multimodal RAG retrieval and cross-session memory for personalized, coherent dialogue
|
||||
- **App calls** — Invoke agents and workflows already published on Aliyun Model Studio
|
||||
- **MCP integration** — Orchestrate Bailian MCP servers: list services, inspect tools, and invoke any tool directly from the terminal
|
||||
- **Web search** — Real-time internet retrieval for up-to-date, accurate answers
|
||||
- **Model recommendation** — Describe your scenario and get best-fit model suggestions; supports scoped search, model comparison, and alternative discovery
|
||||
- **Fine-tuning & deployment** — Upload datasets, create text/audio/image fine-tune jobs (`finetune text|audio|image create`; text covers SFT/LoRA/DPO/CPT), probe job status non-blockingly (`finetune watch`), query per-model training capability (`finetune capability`), and deploy trained models as endpoints (`deploy text|audio|image create`)
|
||||
- **Console capabilities** — Browse the model marketplace (`model list`) and Bailian apps (`app list`), review a unified usage view (`usage summary`), check free-tier quota (`usage free`), view model usage statistics (`usage stats`), manage workspaces (`workspace list`), and manage rate limits (`quota list/request/check/history`)
|
||||
- **Local file auto-upload** — Every URL parameter accepts a local path; uploaded to free temp storage with 48-hour validity
|
||||
|
||||
## Showcase: One-Sentence Cinematic Video
|
||||
## Showcase 1: A Cinematic Short Film from One Sentence
|
||||
|
||||
<p align="center">
|
||||
<a href="https://cloud.video.taobao.com/vod/dS2F4huqbw5Nfe5L3wwb3grz2q2DNYD3retq8dU-iHo.mp4">
|
||||
@@ -56,129 +45,77 @@ Equip your AI Agent out-of-the-box with these capabilities, composable across co
|
||||
A complete **2-minute, 16:9 cinematic short film** — produced end-to-end from a single natural-language sentence, with **zero manual editing**. This showcase demonstrates how an AI Agent can compose a multi-step creative pipeline by orchestrating three primitives:
|
||||
|
||||
- **[Qwen Code](https://github.com/QwenLM/qwen-code)** — the agentic coding model that interprets the user's intent and drives the workflow
|
||||
- **[Aliyun Model Studio CLI](https://bailian.console.aliyun.com/cli?source_channel=cli_github&)** — invokes **HappyHorse 1.1**, Aliyun Model Studio's text-/image-/reference-to-video generation model
|
||||
- **[Aliyun Model Studio CLI](https://github.com/modelstudioai/cli/)** — invokes **HappyHorse 1.1**, Aliyun Model Studio's text-/image-/reference-to-video generation model
|
||||
- **[spark-video Skill](https://github.com/JohnKeating1997/spark-video)** — handles scene decomposition, storyboarding, shot continuity, and final stitching
|
||||
|
||||
### The single prompt
|
||||
|
||||
> _"Generate a roughly 2-minute video in Japanese cinematic style — a sweet, innocent first-love story about a high-school girl. The plot should be heart-fluttering enough to make viewers want to fall in love. Aspect ratio: 16:9."_
|
||||
>
|
||||
> _(Original: "帮我生成一段日系影视风格，高中女生的青涩初恋故事，剧情高甜，让人看了想谈恋爱，2分钟左右的视频，尺寸是16:9")_
|
||||
|
||||
### How it works
|
||||
## Showcase 2: A Short-Film Director Managed Agent from One Sentence
|
||||
|
||||
1. **Qwen Code** parses the request, plans the narrative beats, and decides which tools to call.
|
||||
2. The **spark-video Skill** breaks the story into shots, writes per-shot prompts, and enforces visual continuity (characters, lighting, palette, lens language).
|
||||
3. **`bl video generate`** dispatches each shot to **HappyHorse 1.1** in parallel.
|
||||
4. The skill stitches all clips back together into a single 16:9 / ~2-min deliverable.
|
||||
<p align="center">
|
||||
<a href="https://cloud.video.taobao.com/vod/2v0GYLbJSQb2saj4iopTJDW3iRIHsintYlK-wTKbhqE.mp4">
|
||||
<img src="https://img.alicdn.com/imgextra/i4/6000000001674/O1CN01xhzixhxltbH3LxWu_!!6000000001674-0-tbvideo.jpg" alt="Click to play the demo video" width="720" />
|
||||
</a>
|
||||
</p>
|
||||
|
||||
No timeline scrubbing. No frame-by-frame editing. Just one sentence → one video.
|
||||
<p align="center"><i>👆 Click the cover to play the full demo</i></p>
|
||||
|
||||
One sentence builds a reusable cloud-side short-film director for storyboarding, storyboard image generation, and video creation:
|
||||
|
||||
- **[Qwen Code](https://github.com/QwenLM/qwen-code)** — understands the requirement and generates the agent configuration
|
||||
- **[Aliyun Model Studio CLI](https://github.com/modelstudioai/cli/)** — validates the configuration, previews the changes, and completes the deployment
|
||||
- **[Managed Agent](https://bailian.console.aliyun.com/cn-beijing/?tab=managed-agents#/managed-agents/quick-start)** — runs the director role along with its skills and tools in the cloud
|
||||
|
||||
### The single prompt
|
||||
|
||||
> _"Build me a Managed Agent app that can produce short films — a director expert that generates videos and can also design the matching storyboards."_
|
||||
|
||||
## Installation
|
||||
|
||||
**Agent install (recommended)**
|
||||
|
||||
Send the following to your Agent — it will detect your environment, then install and verify the CLI for you:
|
||||
|
||||
```text
|
||||
Please read https://bailian.aliyun.com/cli/install.md and install the Aliyun Model Studio CLI for me
|
||||
```
|
||||
|
||||
**Manual install (npm)**
|
||||
|
||||
```bash
|
||||
# Recommended — no Node required
|
||||
curl -fsSL https://bailian.aliyun.com/cli/install.sh | bash
|
||||
|
||||
# Windows (PowerShell)
|
||||
irm https://bailian.aliyun.com/cli/install.ps1 | iex
|
||||
|
||||
# Node users / developers (Node.js >= 18.17)
|
||||
npm install -g bailian-cli
|
||||
|
||||
# Agent skills
|
||||
npx skills add modelstudioai/cli --all -g
|
||||
```
|
||||
|
||||
> Binary install does not require Node.js. `npm install -g` remains fully supported.
|
||||
> Requires Node.js >= 18.17.
|
||||
|
||||
## Quick Start
|
||||
|
||||
```bash
|
||||
# Authenticate, recommended
|
||||
bl auth login --console
|
||||
Once installed, just describe your task to your AI Agent — no need to assemble commands by hand.
|
||||
|
||||
# Or authenticate with an API key
|
||||
bl auth login --api-key sk-xxxxx
|
||||
|
||||
# Or use Token Plan (Base URL built in; the key is tested during login)
|
||||
bl auth login --config token-plan --api-key sk-sp-xxxxx
|
||||
|
||||
# Configure a coding agent to use DashScope
|
||||
bl config agent --agent codex --base-url https://dashscope.aliyuncs.com/compatible-mode/v1 --api-key sk-xxxxx --model qwen3-coder-plus
|
||||
|
||||
# Chat with Qwen
|
||||
bl text chat --message "What is DashScope?"
|
||||
|
||||
# Multimodal chat (text + image + audio + video)
|
||||
bl omni --message "Describe this image" --image ./photo.jpg
|
||||
|
||||
# Generate an image
|
||||
bl image generate --prompt "A cat in a spacesuit" --out-dir ./images/
|
||||
|
||||
# Generate a video from local image
|
||||
bl video generate --image ./cat.png --prompt "Make the cat move" --download cat.mp4
|
||||
|
||||
# Model recommendation — find the best model for your use case
|
||||
bl advisor recommend --message "I need a visual-understanding chatbot"
|
||||
|
||||
# Compare specific models
|
||||
bl advisor recommend --message "qwen-max vs deepseek-v3 for code generation"
|
||||
|
||||
# Browser login (required for console capability commands)
|
||||
bl auth login --console
|
||||
|
||||
# Fine-tune & deploy — a one-shot train-to-serve workflow
|
||||
bl dataset upload --file ./train.jsonl # Upload a .jsonl dataset (validated first)
|
||||
bl finetune text create --model qwen3-8b --datasets ./train.jsonl --training-type sft-lora # Local paths auto-upload
|
||||
bl finetune watch --job-id ft-xxx --output json # Non-blocking probe (running/succeeded return 0; failed/canceled report an error)
|
||||
bl finetune capability --model qwen3-8b # Which training types a model supports
|
||||
bl deploy text create --model qwen3-8b --name my-svc --plan mu # Deploy the trained model as an endpoint
|
||||
|
||||
# Browse models / apps / free-tier quota / usage statistics / workspaces
|
||||
bl model list # Browse model families and pricing
|
||||
bl app list
|
||||
bl usage summary # Unified view: free-tier quota + recent usage overview
|
||||
bl usage free # Free-tier quota across models (add --model/--expiring/--sort)
|
||||
bl usage stats --workspace-id <id> # Model usage statistics (add --model for per-model)
|
||||
bl workspace list # List all workspaces
|
||||
|
||||
# Rate limit management (list / check / request / history)
|
||||
bl quota list # View RPM/TPM limits (add --model to filter)
|
||||
bl quota check # Current usage vs rate limits (add --model/--period)
|
||||
bl quota request --model qwen3.6-plus --tpm 6000000 # Request a temporary TPM increase
|
||||
bl quota history # View quota-change history
|
||||
|
||||
# Token Plan team management (requires AK/SK, see auth below)
|
||||
bl token-plan list-seats # View subscription seat details
|
||||
bl token-plan add-member --account-name dev --org-id org_xxx
|
||||
bl token-plan assign-seats --workspace-id ws_xxx --seat-type standard --account-id acc_xxx
|
||||
bl token-plan create-key --account-id acc_xxx --workspace-id ws_xxx
|
||||
```
|
||||
| Scenario | What to say to your Agent |
|
||||
| ------------------------ | --------------------------------------------------------------------------------- |
|
||||
| Managed Agent | "Create a Managed Agent that can generate short-film storyboards and videos." |
|
||||
| Image & video generation | "Generate an image of a cat in a spacesuit on Mars, then turn it into a video." |
|
||||
| Usage & quota | "Show my recent model usage, free-tier quota, and rate limits." |
|
||||
| Model selection | "Recommend a model for image understanding and customer support." |
|
||||
| About Bailian CLI | "Tell me what Bailian CLI can do for me, and suggest how to use it for my needs." |
|
||||
|
||||
> More examples and scenarios: [Aliyun Model Studio CLI Site](https://bailian.console.aliyun.com/cli?source_channel=cli_github&)
|
||||
|
||||
## Authentication
|
||||
|
||||
### DashScope API Key
|
||||
### API Key
|
||||
|
||||
Required for most commands. Get your key from the [DashScope Console](https://bailian.console.aliyun.com/cn-beijing/?source_channel=key_github&tab=app#/api-key).
|
||||
|
||||
```bash
|
||||
# Option 1: Environment variable
|
||||
export DASHSCOPE_API_KEY=sk-xxxxx
|
||||
|
||||
# Option 2: Login command (persisted to ~/.bailian/config.json)
|
||||
bl auth login --api-key sk-xxxxx
|
||||
|
||||
# Option 3: Per-command flag
|
||||
bl text chat --api-key sk-xxxxx --message "Hello"
|
||||
```
|
||||
|
||||
### Token Plan API Key
|
||||
|
||||
Get or copy the API key from the [Token Plan subscription overview](https://bailian.console.aliyun.com/cn-beijing?tab=plan#/efm/subscription/overview).
|
||||
The CLI has the default Token Plan Base URL built in. Login tests the key first, then saves and activates the `token-plan` config only when validation succeeds.
|
||||
Get or copy your Token Plan API key from the [Token Plan subscription overview](https://bailian.console.aliyun.com/cn-beijing?tab=plan#/efm/subscription/overview).
|
||||
|
||||
```bash
|
||||
bl auth login --config token-plan --api-key sk-sp-xxxxx
|
||||
@@ -186,26 +123,20 @@ bl auth login --config token-plan --api-key sk-sp-xxxxx
|
||||
|
||||
### Console Login (OAuth)
|
||||
|
||||
Required for console capability commands (`model list`, `app list`, `usage summary/free/stats`, `workspace list`, `quota list/request/check/history`). Opens the Bailian console in your browser to sign in.
|
||||
Required for console capability commands (model list, app list, MCP list, workspace, usage queries, rate-limit increases, direct console calls). Opens the Bailian console in your browser to sign in.
|
||||
|
||||
```bash
|
||||
bl auth login --console
|
||||
```
|
||||
|
||||
### Alibaba Cloud OpenAPI AK/SK (Token Plan only)
|
||||
### Alibaba Cloud OpenAPI AK/SK
|
||||
|
||||
Required for the `token-plan` command group. Get your AccessKey from [RAM Console](https://ram.console.aliyun.com/manage/ak).
|
||||
Token Plan seat and member management requires an Alibaba Cloud AccessKey. Get yours from the [RAM Console](https://ram.console.aliyun.com/manage/ak).
|
||||
|
||||
> Recommended: create a RAM sub-account with minimum privileges instead of using the root account's AK/SK.
|
||||
|
||||
```bash
|
||||
# Option 1: Login command (persisted to ~/.bailian/config.json)
|
||||
bl auth login --open-api --access-key-id LTAI5t... --access-key-secret ...
|
||||
|
||||
# Option 2: Environment variables
|
||||
export ALIBABA_CLOUD_ACCESS_KEY_ID=LTAI5t...
|
||||
export ALIBABA_CLOUD_ACCESS_KEY_SECRET=...
|
||||
export BAILIAN_WORKSPACE_ID=ws-...
|
||||
```
|
||||
|
||||
## Configuration
|
||||
@@ -214,18 +145,31 @@ export BAILIAN_WORKSPACE_ID=ws-...
|
||||
# View current config
|
||||
bl config show
|
||||
|
||||
# Set defaults
|
||||
bl config set --key base_url --value https://dashscope-us.aliyuncs.com
|
||||
bl config set --key default_text_model --value qwen-turbo
|
||||
bl config set --key timeout --value 600
|
||||
# List all config profiles
|
||||
bl config list
|
||||
|
||||
# Self-update to latest or a specific version
|
||||
bl update
|
||||
bl update --to 0.1.14
|
||||
# Switch config profile
|
||||
bl config use --name token-plan
|
||||
```
|
||||
|
||||
Config file location: `~/.bailian/config.json`
|
||||
|
||||
## Update
|
||||
|
||||
```bash
|
||||
bl update
|
||||
```
|
||||
|
||||
Upgrades the CLI to the latest version and refreshes the installed Agent Skills. Release notes for every version live in [CHANGELOG.md](https://github.com/modelstudioai/cli/blob/main/CHANGELOG.md).
|
||||
|
||||
## Contributing
|
||||
|
||||
Bug reports, feature requests, and PRs are welcome. See [CONTRIBUTING.md](https://github.com/modelstudioai/cli/blob/main/CONTRIBUTING.md) for developer setup, repo layout, and the workflow for adding or changing commands.
|
||||
|
||||
Scan the QR code to join the Aliyun Model Studio CLI DingTalk user group for usage help, troubleshooting, bug reports, and tips from other users.
|
||||
|
||||
<img src="https://img.alicdn.com/imgextra/i3/O1CN015uuhYGb6j0L12xJZ_!!6000000006304-2-tps-516-485.png" alt="Aliyun Model Studio CLI DingTalk user group" width="240" />
|
||||
|
||||
## Links
|
||||
|
||||
| Resource | URL |
|
||||
@@ -237,11 +181,3 @@ Config file location: `~/.bailian/config.json`
|
||||
| Get API Key | https://bailian.console.aliyun.com/cn-beijing/?source_channel=key_github&tab=app#/api-key |
|
||||
| Get Token Plan API Key | https://bailian.console.aliyun.com/cn-beijing?tab=plan#/efm/subscription/overview |
|
||||
| Get AccessKey | https://ram.console.aliyun.com/manage/ak |
|
||||
|
||||
## Changelog
|
||||
|
||||
Release notes for every version live in [CHANGELOG.md](https://github.com/modelstudioai/cli/blob/main/CHANGELOG.md).
|
||||
|
||||
## Contributing
|
||||
|
||||
Bug reports, feature requests, and PRs are welcome. See [CONTRIBUTING.md](https://github.com/modelstudioai/cli/blob/main/CONTRIBUTING.md) for developer setup, repo layout, and the workflow for adding or changing commands.
|
||||
|
||||
+73
-138
@@ -22,28 +22,16 @@ _专为 AI Agent 打造，每个命令均可作为结构化工具调用。_
|
||||
|
||||
## 功能特性
|
||||
|
||||
让您的 AI Agent 开箱即具备以下能力，并可在复杂任务中自动组合调用：
|
||||
- **模型生成** — 文本、图像、视频、语音全模态生成，支持编辑与参考生成
|
||||
- **素材理解** — 图像、文档、音频、长视频的解析与问答
|
||||
- **应用编排** — 调用百炼已发布的 Managed Agent、智能体和工作流，接入知识库、记忆库、联网搜索与 MCP 工具
|
||||
- **模型训推** — 数据集校验上传、模型精调、专属模型部署上线
|
||||
- **账号运维** — 授权登录、界面化配置、模型市场、用量与额度、限流提额、团队席位管理
|
||||
- **套餐接入** — 支持 Token Plan 等订阅计划一键接到 CLI 和常见 Coding Agent
|
||||
|
||||
- **文本对话** — Qwen3.8-max：Agentic coding、前端编程、Vibe coding 等能力显著增强
|
||||
- **全模态对话** — 文本 + 图像 + 音频 + 视频全模态支持
|
||||
- **图像生成与编辑** — Qwen-Image 3.0：专业文字渲染、真实质感、强语义遵循、多图合成
|
||||
- **视频生成与编辑** — happyhorse-1.1 系列，支持文生 / 图生 / 参考生（最多 9 张图参考）/ 自然语言视频编辑
|
||||
- **语音合成与识别** — CosyVoice 实时流式合成，5-20s 样本即可克隆；FunAudio-ASR 覆盖 30 种语种，含汉语七大方言与 20+ 口音官话
|
||||
- **图像与视频理解** — Qwen-VL：长视频解析、复杂图表与文档识别、视觉推理、多语种 OCR
|
||||
- **Coding Agent 配置** — 使用 `bl config agent` 将 Claude Code、Qwen Code、OpenCode、OpenClaw、Hermes Agent 或 Codex 配置为使用 DashScope
|
||||
> **注意：** 应用编排、模型训推、账号运维和套餐接入目前仅支持中国站（aliyun.com）账号，暂不支持国际站 / 全球站账号。
|
||||
|
||||
> **注意：** 以下功能目前仅对中国站（aliyun.com）账号开放，国际站 / 全球站账号暂不支持。
|
||||
|
||||
- **知识库与记忆库** — 多模态 RAG 检索 + 跨会话记忆，提供个性化连贯对话体验
|
||||
- **应用调用** — 调用已发布在阿里云百炼平台上的智能体与工作流应用
|
||||
- **MCP 集成** — 统一调度百炼 MCP 服务：列出服务、查看工具、直接在终端调用任意工具
|
||||
- **联网搜索** — 实时互联网信息检索，提升回答准确性及时效性
|
||||
- **模型推荐** — 描述你的场景，智能推荐最适合的模型；支持限定范围搜索、模型对比和替代发现
|
||||
- **微调与部署** — 上传数据集、创建文本/音频/图像调优任务（`finetune text|audio|image create`；文本涵盖 SFT/LoRA/DPO/CPT）、非阻塞探测任务状态（`finetune watch`）、按模型查训练能力（`finetune capability`），并把训练好的模型部署为推理服务（`deploy text|audio|image create`）
|
||||
- **控制台能力** — 浏览模型市场（`model list`）和百炼应用（`app list`），查看统一用量视图（`usage summary`），查询模型免费额度（`usage free`），查看模型用量统计（`usage stats`），管理业务空间（`workspace list`），管理限流与提额（`quota list/request/check/history`）
|
||||
- **本地文件自动上传** — 所有 URL 参数同时支持本地路径，免费临时存储 48 小时
|
||||
|
||||
## 示例:一句话生成一部电影短片
|
||||
## 示例 1：一句话生成一部电影短片
|
||||
|
||||
<p align="center">
|
||||
<a href="https://cloud.video.taobao.com/vod/dS2F4huqbw5Nfe5L3wwb3grz2q2DNYD3retq8dU-iHo.mp4">
|
||||
@@ -53,130 +41,80 @@ _专为 AI Agent 打造，每个命令均可作为结构化工具调用。_
|
||||
|
||||
<p align="center"><i>👆 点击封面播放完整 2 分钟演示</i></p>
|
||||
|
||||
一部完整的 **2 分钟、16:9 电影感短片** —— 由一句自然语言端到端生成,**全程零手动剪辑**。这个示例展示了 AI Agent 如何把三个基础能力编排成一条多步创作流水线:
|
||||
一部完整的 **2 分钟、16:9 电影感短片** —— 由一句自然语言端到端生成，**全程零手动剪辑**。这个示例展示了 AI Agent 如何把三个基础能力编排成一条多步创作流水线：
|
||||
|
||||
- **[Qwen Code](https://github.com/QwenLM/qwen-code)** —— Agentic coding 模型,解析用户意图、驱动整个工作流
|
||||
- **[阿里云百炼 CLI](https://github.com/modelstudioai/cli/)** —— 调用 **HappyHorse 1.1**,百炼的文生/图生/参考生视频模型
|
||||
- **[Qwen Code](https://github.com/QwenLM/qwen-code)** —— Agentic coding 模型，解析用户意图、驱动整个工作流
|
||||
- **[阿里云百炼 CLI](https://github.com/modelstudioai/cli/)** —— 调用 **HappyHorse 1.1**，百炼的文生/图生/参考生视频模型
|
||||
- **[spark-video Skill](https://github.com/JohnKeating1997/spark-video)** —— 负责场景拆分、分镜设计、镜头连贯性和最终拼接
|
||||
|
||||
### 唯一的提示词
|
||||
|
||||
> _"帮我生成一段日系影视风格,高中女生的青涩初恋故事,剧情高甜,让人看了想谈恋爱,2 分钟左右的视频,尺寸是 16:9"_
|
||||
> _“帮我生成一段日系影视风格，高中女生的青涩初恋故事，剧情高甜，让人看了想谈恋爱，2 分钟左右的视频，尺寸是 16:9。”_
|
||||
|
||||
### 工作流程
|
||||
## 示例 2：一句话构建短片导演 Managed Agent
|
||||
|
||||
1. **Qwen Code** 解析需求、规划叙事节奏,决定要调用哪些工具。
|
||||
2. **spark-video Skill** 把故事拆成镜头、为每个镜头写提示词,并保证视觉连贯性(角色、光线、色调、镜头语言)。
|
||||
3. **`bl video generate`** 把每个镜头并行下发给 **HappyHorse 1.1**。
|
||||
4. Skill 把所有片段拼成最终的 16:9 / 约 2 分钟成片。
|
||||
<p align="center">
|
||||
<a href="https://cloud.video.taobao.com/vod/2v0GYLbJSQb2saj4iopTJDW3iRIHsintYlK-wTKbhqE.mp4">
|
||||
<img src="https://img.alicdn.com/imgextra/i4/6000000001674/O1CN01xhzixhxltbH3LxWu_!!6000000001674-0-tbvideo.jpg" alt="点击播放演示视频" width="720" />
|
||||
</a>
|
||||
</p>
|
||||
|
||||
没有时间线拖拽,没有逐帧剪辑。一句话 → 一部短片。
|
||||
<p align="center"><i>👆 点击封面播放完整演示</i></p>
|
||||
|
||||
一句话构建一个可复用的云端短片导演，用于分镜设计、分镜图生成和视频创作：
|
||||
|
||||
- **[Qwen Code](https://github.com/QwenLM/qwen-code)** —— 理解需求并生成 Agent 配置
|
||||
- **[阿里云百炼 CLI](https://github.com/modelstudioai/cli/)** —— 校验配置、预览变更并完成部署
|
||||
- **[Managed Agent](https://bailian.console.aliyun.com/cn-beijing/?tab=managed-agents#/managed-agents/quick-start)** —— 在云端运行导演角色及其 Skill 和工具
|
||||
|
||||
### 唯一的提示词
|
||||
|
||||
> _“帮我构建一个 managedagent 应用，能够实现短片拍摄，导演专家生成视频，然后也能进行设计对应的分镜图。”_
|
||||
|
||||
## 安装
|
||||
|
||||
**Agent 安装（推荐）**
|
||||
|
||||
把下面这句话发给你的 Agent，它会自行判断环境并完成安装与校验：
|
||||
|
||||
```text
|
||||
请阅读：https://bailian.aliyun.com/cli/install.md 并按照说明为我安装阿里云百炼 CLI
|
||||
```
|
||||
|
||||
**手动安装（npm）**
|
||||
|
||||
```bash
|
||||
# 推荐 — 无需本机 Node.js
|
||||
curl -fsSL https://bailian.aliyun.com/cli/install.sh | bash
|
||||
|
||||
# Windows（PowerShell）
|
||||
irm https://bailian.aliyun.com/cli/install.ps1 | iex
|
||||
|
||||
# Node 用户 / 开发者（需要 Node.js >= 18.17）
|
||||
npm install -g bailian-cli
|
||||
|
||||
# Agent skills
|
||||
npx skills add modelstudioai/cli --all -g
|
||||
```
|
||||
|
||||
> 二进制安装不依赖 Node.js。`npm install -g` 长期保留。
|
||||
> 需要预先安装 Node.js >= 18.17。
|
||||
|
||||
## 快速开始
|
||||
|
||||
```bash
|
||||
# 认证（推荐浏览器登录）
|
||||
bl auth login --console
|
||||
安装完成后，直接在 AI Agent 中描述你的任务，无需手动拼接命令。
|
||||
|
||||
# 或使用 API key 认证
|
||||
bl auth login --api-key sk-xxxxx
|
||||
|
||||
# 或使用 Token Plan（已内置 Base URL，登录时自动测试 Key）
|
||||
bl auth login --config token-plan --api-key sk-sp-xxxxx
|
||||
|
||||
# 配置 Coding Agent 使用 DashScope
|
||||
bl config agent --agent codex --base-url https://dashscope.aliyuncs.com/compatible-mode/v1 --api-key sk-xxxxx --model qwen3-coder-plus
|
||||
|
||||
# 和通义千问对话
|
||||
bl text chat --message "你好，介绍一下阿里云百炼平台"
|
||||
|
||||
# 多模态对话（文本 + 图片 + 音频 + 视频）
|
||||
bl omni --message "描述这张图片" --image ./photo.jpg
|
||||
|
||||
# 生成图片
|
||||
bl image generate --prompt "一只穿太空服的猫在火星上" --out-dir ./images/
|
||||
|
||||
# 图生视频（本地文件自动上传）
|
||||
bl video generate --image ./cat.png --prompt "让画面中的猫动起来" --download cat.mp4
|
||||
|
||||
# 模型推荐 — 根据场景推荐最适合的模型
|
||||
bl advisor recommend --message "我要做一个能理解图片的客服机器人"
|
||||
|
||||
# 对比特定模型
|
||||
bl advisor recommend --message "qwen-max 和 deepseek-v3 哪个更适合做代码生成"
|
||||
|
||||
# 浏览器登录（控制台能力相关命令需要）
|
||||
bl auth login --console
|
||||
|
||||
# 微调与部署 — 从训练到服务的一站式流程
|
||||
bl dataset upload --file ./train.jsonl # 上传 .jsonl 数据集（先校验）
|
||||
bl finetune text create --model qwen3-8b --datasets ./train.jsonl --training-type sft-lora # 本地路径自动上传
|
||||
bl finetune watch --job-id ft-xxx --output json # 非阻塞探测（运行中/成功返回 0；失败/取消报错）
|
||||
bl finetune capability --model qwen3-8b # 查询模型支持哪些训练方式
|
||||
bl deploy text create --model qwen3-8b --name my-svc --plan mu # 把训练好的模型部署为推理服务
|
||||
|
||||
# 浏览模型 / 应用 / 免费额度 / 用量统计 / 业务空间
|
||||
bl model list # 浏览模型系列与价格信息
|
||||
bl app list
|
||||
bl usage summary # 统一视图：免费额度 + 近期用量概览
|
||||
bl usage free # 各模型免费额度（可加 --model/--expiring/--sort）
|
||||
bl usage stats --workspace-id <id> # 模型用量统计（加 --model 查单模型）
|
||||
bl workspace list # 列出所有业务空间
|
||||
|
||||
# 限流管理与提额（list / check / request / history）
|
||||
bl quota list # 查看 RPM/TPM 限额（加 --model 过滤）
|
||||
bl quota check # 当前用量 vs 限流阈值（加 --model/--period）
|
||||
bl quota request --model qwen3.6-plus --tpm 6000000 # 申请临时 TPM 提额
|
||||
bl quota history # 查看提额历史记录
|
||||
|
||||
# Token Plan 团队版管理（需 AK/SK，见下方认证说明）
|
||||
bl token-plan list-seats # 查看订阅席位明细
|
||||
bl token-plan add-member --account-name dev --org-id org_xxx
|
||||
bl token-plan assign-seats --workspace-id ws_xxx --seat-type standard --account-id acc_xxx
|
||||
bl token-plan create-key --account-id acc_xxx --workspace-id ws_xxx
|
||||
```
|
||||
| 场景 | 可以这样对 Agent 说 |
|
||||
| ---------------- | ----------------------------------------------------------------------- |
|
||||
| Managed Agent | “帮我创建一个能够生成短片分镜和视频的 Managed Agent。” |
|
||||
| 图片和视频生成 | “生成一张穿着太空服的猫站在火星上的图片，再把它制作成一段视频。” |
|
||||
| 用量与额度 | “查看最近的模型用量、免费额度和限流情况。” |
|
||||
| 模型选型 | “推荐一个适合图片理解和智能客服的模型。” |
|
||||
| 了解 Bailian CLI | “介绍一下 Bailian CLI 能帮我完成哪些任务，并根据我的需求推荐使用方式。” |
|
||||
|
||||
> 更多案例与使用场景：[阿里云百炼 CLI 官方主页](https://bailian.console.aliyun.com/cli?source_channel=cli_github&)
|
||||
|
||||
## 认证方式
|
||||
|
||||
### DashScope API Key
|
||||
### API Key
|
||||
|
||||
大部分命令均需要 API Key。前往 [DashScope 控制台](https://bailian.console.aliyun.com/cn-beijing/?source_channel=key_github&tab=app#/api-key) 获取。
|
||||
|
||||
```bash
|
||||
# 方式一：环境变量
|
||||
export DASHSCOPE_API_KEY=sk-xxxxx
|
||||
|
||||
# 方式二：登录命令（持久化到 ~/.bailian/config.json）
|
||||
bl auth login --api-key sk-xxxxx
|
||||
|
||||
# 方式三：命令行参数
|
||||
bl text chat --api-key sk-xxxxx --message "你好"
|
||||
```
|
||||
|
||||
### Token Plan API Key
|
||||
|
||||
前往 [Token Plan 订阅详情](https://bailian.console.aliyun.com/cn-beijing?tab=plan#/efm/subscription/overview) 获取或复制 API Key。
|
||||
CLI 已内置 Token Plan 的默认 Base URL；登录命令会先测试 Key，通过后才保存并激活 `token-plan` 配置。
|
||||
Token Plan 的 API Key 前往 [Token Plan 订阅详情](https://bailian.console.aliyun.com/cn-beijing?tab=plan#/efm/subscription/overview) 获取或复制。
|
||||
|
||||
```bash
|
||||
bl auth login --config token-plan --api-key sk-sp-xxxxx
|
||||
@@ -184,26 +122,20 @@ bl auth login --config token-plan --api-key sk-sp-xxxxx
|
||||
|
||||
### 控制台登录（OAuth）
|
||||
|
||||
控制台能力命令（`model list`、`app list`、`usage summary/free/stats`、`workspace list`、`quota list/request/check/history`）需要使用此登录方式。打开浏览器跳转百炼控制台完成登录。
|
||||
控制台能力命令（模型列表、应用列表、MCP 列表、工作空间、用量查询、限流提额、控制台直调）需要使用此登录方式。打开浏览器跳转百炼控制台完成登录。
|
||||
|
||||
```bash
|
||||
bl auth login --console
|
||||
```
|
||||
|
||||
### 阿里云 OpenAPI AK/SK（仅 Token Plan）
|
||||
### 阿里云 OpenAPI AK/SK
|
||||
|
||||
`token-plan` 命令组需要阿里云 AccessKey。前往 [RAM 控制台](https://ram.console.aliyun.com/manage/ak) 获取。
|
||||
Token Plan 的席位与成员管理需要阿里云 AccessKey。前往 [RAM 控制台](https://ram.console.aliyun.com/manage/ak) 获取。
|
||||
|
||||
> 建议：创建 RAM 子账号并授予最小权限，避免使用主账号 AK/SK。
|
||||
|
||||
```bash
|
||||
# 方式一：登录命令（持久化到 ~/.bailian/config.json）
|
||||
bl auth login --open-api --access-key-id LTAI5t... --access-key-secret ...
|
||||
|
||||
# 方式二：环境变量
|
||||
export ALIBABA_CLOUD_ACCESS_KEY_ID=LTAI5t...
|
||||
export ALIBABA_CLOUD_ACCESS_KEY_SECRET=...
|
||||
export BAILIAN_WORKSPACE_ID=ws-...
|
||||
```
|
||||
|
||||
## 配置
|
||||
@@ -212,20 +144,31 @@ export BAILIAN_WORKSPACE_ID=ws-...
|
||||
# 查看当前配置
|
||||
bl config show
|
||||
|
||||
# 设置默认值
|
||||
bl config set --key base_url --value https://dashscope-us.aliyuncs.com
|
||||
bl config set --key default_text_model --value qwen-turbo
|
||||
bl config set --key timeout --value 600
|
||||
# 查看全部配置档
|
||||
bl config list
|
||||
|
||||
# 自更新到最新版本
|
||||
bl update
|
||||
|
||||
# 安装指定版本
|
||||
bl update --to 0.1.14
|
||||
# 切换配置档
|
||||
bl config use --name token-plan
|
||||
```
|
||||
|
||||
配置文件位置：`~/.bailian/config.json`
|
||||
|
||||
## 更新
|
||||
|
||||
```bash
|
||||
bl update
|
||||
```
|
||||
|
||||
升级 CLI 至最新版本，并同步更新已安装的 Agent Skills。每个版本的变更详情记录在 [CHANGELOG.zh.md](https://github.com/modelstudioai/cli/blob/main/CHANGELOG.zh.md)。
|
||||
|
||||
## 参与贡献
|
||||
|
||||
欢迎提 Issue、Feature Request 和 PR。开发环境搭建、仓库结构、新增/修改命令的工作流请见 [CONTRIBUTING.zh.md](https://github.com/modelstudioai/cli/blob/main/CONTRIBUTING.zh.md)。
|
||||
|
||||
欢迎扫码加入阿里云百炼 CLI 钉钉用户交流群，获取使用答疑、问题排查、Bug 反馈和使用经验交流支持。
|
||||
|
||||
<img src="https://img.alicdn.com/imgextra/i3/O1CN015uuhYGb6j0L12xJZ_!!6000000006304-2-tps-516-485.png" alt="阿里云百炼 CLI 钉钉用户交流群" width="240" />
|
||||
|
||||
## 相关链接
|
||||
|
||||
| 资源 | 地址 |
|
||||
@@ -237,11 +180,3 @@ bl update --to 0.1.14
|
||||
| 获取 API Key | https://bailian.console.aliyun.com/cn-beijing/?source_channel=key_github&tab=app#/api-key |
|
||||
| 获取 Token Plan API Key | https://bailian.console.aliyun.com/cn-beijing?tab=plan#/efm/subscription/overview |
|
||||
| 获取 AccessKey | https://ram.console.aliyun.com/manage/ak |
|
||||
|
||||
## 更新日志
|
||||
|
||||
每个版本的变更详情记录在 [CHANGELOG.zh.md](https://github.com/modelstudioai/cli/blob/main/CHANGELOG.zh.md)。
|
||||
|
||||
## 参与贡献
|
||||
|
||||
欢迎提 Issue、Feature Request 和 PR。开发环境搭建、仓库结构、新增/修改命令的工作流请见 [CONTRIBUTING.zh.md](https://github.com/modelstudioai/cli/blob/main/CONTRIBUTING.zh.md)。
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "bailian-cli",
|
||||
"version": "1.14.1",
|
||||
"version": "1.14.2",
|
||||
"description": "CLI for Aliyun Model Studio (DashScope) AI Platform.",
|
||||
"keywords": [
|
||||
"agent",
|
||||
|
||||
@@ -93,6 +93,7 @@ import {
|
||||
skillUpdate,
|
||||
skillRemove,
|
||||
skillList,
|
||||
skillInit,
|
||||
managedAgentInit,
|
||||
managedAgentValidate,
|
||||
managedAgentPlan,
|
||||
@@ -211,6 +212,7 @@ export const commands: Record<string, AnyCommand> = {
|
||||
"skill update": skillUpdate,
|
||||
"skill remove": skillRemove,
|
||||
"skill list": skillList,
|
||||
"skill init": skillInit,
|
||||
"managed-agent init": managedAgentInit,
|
||||
"managed-agent validate": managedAgentValidate,
|
||||
"managed-agent plan": managedAgentPlan,
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "bailian-cli-commands",
|
||||
"version": "1.14.1",
|
||||
"version": "1.14.2",
|
||||
"description": "Command library for bailian-cli products (knowledge, memory, media, …). See https://www.npmjs.com/package/bailian-cli for usage.",
|
||||
"homepage": "https://bailian.console.aliyun.com/cli",
|
||||
"bugs": {
|
||||
|
||||
@@ -2,7 +2,6 @@ import {
|
||||
BailianError,
|
||||
ExitCode,
|
||||
defineCommand,
|
||||
detectOutputFormat,
|
||||
detectInstalledAgents,
|
||||
fetchSkillsIndex,
|
||||
getSkillRegistryBaseUrl,
|
||||
@@ -28,22 +27,31 @@ const INSTALL_CONCURRENCY = 3;
|
||||
export default defineCommand({
|
||||
description: "Install skills from the Bailian skill registry into local agents",
|
||||
auth: "none",
|
||||
usageArgs: "--name <all|name,...>",
|
||||
usageArgs: "--all | --name <name,...>",
|
||||
flags: {
|
||||
all: {
|
||||
type: "switch",
|
||||
description: "Install all skills from the registry",
|
||||
},
|
||||
name: {
|
||||
type: "string",
|
||||
valueHint: "<all|name,...>",
|
||||
description: "Skills to install: all or comma-separated skill names",
|
||||
required: true,
|
||||
valueHint: "<name,...>",
|
||||
description: "Comma-separated skill names to install",
|
||||
},
|
||||
},
|
||||
exampleArgs: ["--name all", "--name spark-video,bailian-model-recommend"],
|
||||
validate(flags) {
|
||||
if (flags.all && flags.name) return "Use either --all or --name, not both";
|
||||
if (!flags.all && !flags.name)
|
||||
return "Specify --all to install everything or --name <name,...> for specific skills";
|
||||
return undefined;
|
||||
},
|
||||
exampleArgs: ["--all", "--name spark-video,bailian-model-recommend"],
|
||||
async run(ctx) {
|
||||
const format = detectOutputFormat(ctx.settings.output);
|
||||
const requested = parseSkillNames(ctx.flags.name, false);
|
||||
const format = ctx.settings.outputExplicit ? ctx.settings.output : "json";
|
||||
const index = await fetchSkillsIndex();
|
||||
const remoteNames = Object.keys(index.skills);
|
||||
const names = requested === "all" ? remoteNames : requested;
|
||||
const parsed = ctx.flags.all ? "all" : parseSkillNames(ctx.flags.name, false);
|
||||
const names = parsed === "all" ? remoteNames : parsed;
|
||||
|
||||
const lock = readSkillLock();
|
||||
const agents = detectInstalledAgents();
|
||||
|
||||
@@ -0,0 +1,107 @@
|
||||
import {
|
||||
BailianError,
|
||||
ExitCode,
|
||||
defineCommand,
|
||||
detectInstalledAgents,
|
||||
fetchSkillsIndex,
|
||||
getSkillRegistryBaseUrl,
|
||||
installSkillWithFanout,
|
||||
readSkillLock,
|
||||
runWithConcurrency,
|
||||
writeSkillLock,
|
||||
} from "bailian-cli-core";
|
||||
import { emitBare, emitResult, formatTable } from "bailian-cli-runtime";
|
||||
|
||||
interface InitOutcome {
|
||||
name: string;
|
||||
status: "installed" | "failed";
|
||||
publishedAt?: string;
|
||||
agents?: string[];
|
||||
reason?: string;
|
||||
}
|
||||
|
||||
/** Prefix used to identify first-party Bailian skills in the registry. */
|
||||
const BAILIAN_PREFIX = "bailian-";
|
||||
|
||||
/** Max number of skills downloading/installing at the same time. */
|
||||
const INIT_CONCURRENCY = 3;
|
||||
|
||||
export default defineCommand({
|
||||
description: "Install all bailian-* skills (one-shot bootstrap for new environments)",
|
||||
auth: "none",
|
||||
usageArgs: "",
|
||||
exampleArgs: [""],
|
||||
notes: [
|
||||
"Fetches the registry index and installs every skill whose name starts with bailian-",
|
||||
"Equivalent to: bl skill add --all (filtered to bailian-* skills)",
|
||||
],
|
||||
async run(ctx) {
|
||||
const format = ctx.settings.outputExplicit ? ctx.settings.output : "json";
|
||||
const index = await fetchSkillsIndex();
|
||||
|
||||
// Discover all bailian-* skills from the live registry index
|
||||
const names = Object.keys(index.skills).filter((name) => name.startsWith(BAILIAN_PREFIX));
|
||||
|
||||
const lock = readSkillLock();
|
||||
const agents = detectInstalledAgents();
|
||||
|
||||
const tasks = names.map((name) => async (): Promise<InitOutcome> => {
|
||||
const entry = index.skills[name];
|
||||
try {
|
||||
const record = await installSkillWithFanout(
|
||||
name,
|
||||
entry,
|
||||
agents,
|
||||
lock.skills[name]?.links ?? [],
|
||||
);
|
||||
lock.skills[name] = record.lockEntry;
|
||||
return {
|
||||
name,
|
||||
status: "installed",
|
||||
publishedAt: entry.publishedAt,
|
||||
agents: record.linkedAgents,
|
||||
};
|
||||
} catch (err) {
|
||||
return {
|
||||
name,
|
||||
status: "failed",
|
||||
reason: err instanceof Error ? err.message : String(err),
|
||||
};
|
||||
}
|
||||
});
|
||||
const results = await runWithConcurrency(tasks, INIT_CONCURRENCY);
|
||||
writeSkillLock(lock);
|
||||
|
||||
if (format === "json") {
|
||||
emitResult(
|
||||
{
|
||||
registry: getSkillRegistryBaseUrl(),
|
||||
agents: agents.map((agent) => agent.id),
|
||||
skills: results,
|
||||
},
|
||||
format,
|
||||
);
|
||||
} else if (results.length === 0) {
|
||||
emitBare("No bailian-* skills found in the registry.");
|
||||
} else {
|
||||
const rows = results.map((result) => [
|
||||
result.name,
|
||||
result.status,
|
||||
result.publishedAt ? result.publishedAt.slice(0, 10) : "-",
|
||||
result.status === "installed" ? result.agents?.join(", ") || "-" : (result.reason ?? "-"),
|
||||
]);
|
||||
for (const line of formatTable(["NAME", "STATUS", "PUBLISHED", "AGENTS / REASON"], rows)) {
|
||||
emitBare(line);
|
||||
}
|
||||
}
|
||||
|
||||
const failed = results.filter((result) => result.status === "failed");
|
||||
if (failed.length > 0) {
|
||||
throw new BailianError(
|
||||
`${failed.length}/${results.length} skill(s) failed to install`,
|
||||
ExitCode.GENERAL,
|
||||
"Check the reason for failed skills in the output; network failures can be retried with bl skill init",
|
||||
);
|
||||
}
|
||||
},
|
||||
});
|
||||
@@ -1,6 +1,5 @@
|
||||
import {
|
||||
defineCommand,
|
||||
detectOutputFormat,
|
||||
computeSkillStatuses,
|
||||
fetchSkillsIndex,
|
||||
getSkillRegistryBaseUrl,
|
||||
@@ -24,7 +23,7 @@ export default defineCommand({
|
||||
"STATUS: installed | outdated | not-installed | missing (lock has it, dir deleted) | untracked (dir exists, not managed)",
|
||||
],
|
||||
async run(ctx) {
|
||||
const format = detectOutputFormat(ctx.settings.output);
|
||||
const format = ctx.settings.outputExplicit ? ctx.settings.output : "json";
|
||||
// Three-way reconciliation: live remote index × skill-lock.json (installation facts) × disk
|
||||
const index = await fetchSkillsIndex();
|
||||
const lock = readSkillLock();
|
||||
|
||||
@@ -2,7 +2,6 @@ import {
|
||||
BailianError,
|
||||
ExitCode,
|
||||
defineCommand,
|
||||
detectOutputFormat,
|
||||
listSkillDirsOnDisk,
|
||||
parseSkillNames,
|
||||
readSkillLock,
|
||||
@@ -34,7 +33,7 @@ export default defineCommand({
|
||||
exampleArgs: ["--name spark-video", "--name all"],
|
||||
async run(ctx) {
|
||||
// Purely local operation: no remote access, works offline
|
||||
const format = detectOutputFormat(ctx.settings.output);
|
||||
const format = ctx.settings.outputExplicit ? ctx.settings.output : "json";
|
||||
const requested = parseSkillNames(ctx.flags.name, false);
|
||||
const lock = readSkillLock();
|
||||
const names = requested === "all" ? Object.keys(lock.skills) : requested;
|
||||
|
||||
@@ -2,7 +2,6 @@ import {
|
||||
BailianError,
|
||||
ExitCode,
|
||||
defineCommand,
|
||||
detectOutputFormat,
|
||||
detectInstalledAgents,
|
||||
fanOutSkillToAgents,
|
||||
fetchSkillsIndex,
|
||||
@@ -29,19 +28,27 @@ const UPDATE_CONCURRENCY = 3;
|
||||
export default defineCommand({
|
||||
description: "Update installed skills to the latest registry versions",
|
||||
auth: "none",
|
||||
usageArgs: "[--name <all|name,...>]",
|
||||
usageArgs: "[--all] [--name <name,...>]",
|
||||
flags: {
|
||||
all: {
|
||||
type: "switch",
|
||||
description: "Update all installed skills (default when neither --all nor --name is given)",
|
||||
},
|
||||
name: {
|
||||
type: "string",
|
||||
valueHint: "<all|name,...>",
|
||||
description:
|
||||
"Skills to update: all (default, only changed ones) or comma-separated names (force update installed skills)",
|
||||
valueHint: "<name,...>",
|
||||
description: "Comma-separated skill names to update (must be already installed)",
|
||||
},
|
||||
},
|
||||
exampleArgs: ["", "--name spark-video"],
|
||||
validate(flags) {
|
||||
if (flags.all && flags.name) return "Use either --all or --name, not both";
|
||||
return undefined;
|
||||
},
|
||||
exampleArgs: ["", "--all", "--name spark-video"],
|
||||
async run(ctx) {
|
||||
const format = detectOutputFormat(ctx.settings.output);
|
||||
const requested = parseSkillNames(ctx.flags.name, true);
|
||||
const format = ctx.settings.outputExplicit ? ctx.settings.output : "json";
|
||||
const updateAll = ctx.flags.all || !ctx.flags.name;
|
||||
const requested = updateAll ? "all" : parseSkillNames(ctx.flags.name, false);
|
||||
const index = await fetchSkillsIndex();
|
||||
const lock = readSkillLock();
|
||||
const disk = new Set(listSkillDirsOnDisk());
|
||||
|
||||
@@ -117,3 +117,4 @@ export { default as skillAdd } from "./commands/skill/add.ts";
|
||||
export { default as skillUpdate } from "./commands/skill/update.ts";
|
||||
export { default as skillRemove } from "./commands/skill/remove.ts";
|
||||
export { default as skillList } from "./commands/skill/list.ts";
|
||||
export { default as skillInit } from "./commands/skill/init.ts";
|
||||
|
||||
@@ -17,12 +17,14 @@ describe("e2e: skill", () => {
|
||||
test("skill add --help exits successfully", async () => {
|
||||
const { stderr, exitCode } = await runCommandE2e(SKILL_ROUTES, ["skill", "add", "--help"]);
|
||||
expect(exitCode, stderr).toBe(0);
|
||||
expect(stderr).toMatch(/--all/);
|
||||
expect(stderr).toMatch(/--name/);
|
||||
});
|
||||
|
||||
test("skill update --help exits successfully", async () => {
|
||||
const { stderr, exitCode } = await runCommandE2e(SKILL_ROUTES, ["skill", "update", "--help"]);
|
||||
expect(exitCode, stderr).toBe(0);
|
||||
expect(stderr).toMatch(/--all/);
|
||||
expect(stderr).toMatch(/--name/);
|
||||
});
|
||||
|
||||
@@ -37,18 +39,37 @@ describe("e2e: skill", () => {
|
||||
expect(exitCode, stderr).toBe(0);
|
||||
expect(stderr).toMatch(/list|registry/i);
|
||||
});
|
||||
|
||||
test("skill init --help exits successfully", async () => {
|
||||
const { stderr, exitCode } = await runCommandE2e(SKILL_ROUTES, ["skill", "init", "--help"]);
|
||||
expect(exitCode, stderr).toBe(0);
|
||||
expect(stderr).toMatch(/bailian/i);
|
||||
});
|
||||
});
|
||||
|
||||
// Local-only cases: auth "none" + validation happens before any network access, no gating needed
|
||||
describe("e2e: skill (local, no credentials)", () => {
|
||||
test("skill add without --name errors as usage error (2)", async () => {
|
||||
test("skill add without --all or --name errors as usage error (2)", async () => {
|
||||
const { stdout, stderr, exitCode } = await runCommandE2e(SKILL_ROUTES, [
|
||||
"skill",
|
||||
"add",
|
||||
"--quiet",
|
||||
]);
|
||||
expect(exitCode).toBe(2);
|
||||
expect(`${stdout}\n${stderr}`).toMatch(/--name|Usage:/i);
|
||||
expect(`${stdout}\n${stderr}`).toMatch(/--all|--name|Usage:/i);
|
||||
});
|
||||
|
||||
test("skill add with both --all and --name errors as usage error (2)", async () => {
|
||||
const { stdout, stderr, exitCode } = await runCommandE2e(SKILL_ROUTES, [
|
||||
"skill",
|
||||
"add",
|
||||
"--all",
|
||||
"--name",
|
||||
"spark-video",
|
||||
"--quiet",
|
||||
]);
|
||||
expect(exitCode).toBe(2);
|
||||
expect(`${stdout}\n${stderr}`).toMatch(/--all|--name|either/i);
|
||||
});
|
||||
|
||||
test("skill remove without --name errors as usage error (2)", async () => {
|
||||
@@ -61,19 +82,6 @@ describe("e2e: skill (local, no credentials)", () => {
|
||||
expect(`${stdout}\n${stderr}`).toMatch(/--name|Usage:/i);
|
||||
});
|
||||
|
||||
test("skill add rejects mixing all with specific names (2)", async () => {
|
||||
// parseSkillNames throws UsageError before fetchSkillsIndex — offline-safe
|
||||
const { stdout, stderr, exitCode } = await runCommandE2e(SKILL_ROUTES, [
|
||||
"skill",
|
||||
"add",
|
||||
"--name",
|
||||
"all,spark-video",
|
||||
"--quiet",
|
||||
]);
|
||||
expect(exitCode).toBe(2);
|
||||
expect(`${stdout}\n${stderr}`).toMatch(/all/i);
|
||||
});
|
||||
|
||||
test("skill remove of a not-installed skill fails with reason (1)", async () => {
|
||||
const configDir = makeTempConfigDir();
|
||||
const { stdout, exitCode } = await runCommandE2e(
|
||||
|
||||
@@ -165,6 +165,7 @@ export const SKILL_ROUTES: E2eRouteExports = {
|
||||
"skill update": "skillUpdate",
|
||||
"skill remove": "skillRemove",
|
||||
"skill list": "skillList",
|
||||
"skill init": "skillInit",
|
||||
};
|
||||
|
||||
export const MANAGED_AGENT_ROUTES: E2eRouteExports = {
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "bailian-cli-core",
|
||||
"version": "1.14.1",
|
||||
"version": "1.14.2",
|
||||
"description": "Core SDK for bailian-cli. See https://www.npmjs.com/package/bailian-cli for usage.",
|
||||
"homepage": "https://bailian.console.aliyun.com/cli",
|
||||
"bugs": {
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "knowledge-studio-cli",
|
||||
"version": "1.14.1",
|
||||
"version": "1.14.2",
|
||||
"description": "Lightweight RAG CLI for Aliyun Model Studio — focused on knowledge-base retrieval.",
|
||||
"keywords": [
|
||||
"alibaba-cloud",
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "bailian-cli-runtime",
|
||||
"version": "1.14.1",
|
||||
"version": "1.14.2",
|
||||
"description": "Runtime framework for bailian-cli (createCli, registry, args, output, pipeline). See https://www.npmjs.com/package/bailian-cli for usage.",
|
||||
"homepage": "https://bailian.console.aliyun.com/cli",
|
||||
"bugs": {
|
||||
@@ -40,10 +40,12 @@
|
||||
"check": "vp check"
|
||||
},
|
||||
"dependencies": {
|
||||
"@modelcontextprotocol/server": "catalog:",
|
||||
"bailian-cli-core": "workspace:*",
|
||||
"boxen": "catalog:",
|
||||
"chalk": "catalog:",
|
||||
"undici": "catalog:"
|
||||
"undici": "catalog:",
|
||||
"zod": "catalog:"
|
||||
},
|
||||
"devDependencies": {
|
||||
"@clack/prompts": "^0.7.0",
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
import { parseFlags } from "./args.ts";
|
||||
import { parseFlags, parsePath } from "./args.ts";
|
||||
import { CommandRegistry } from "./registry.ts";
|
||||
import { resolve } from "./resolve.ts";
|
||||
import {
|
||||
@@ -32,6 +32,8 @@ import { printWelcomeBanner, printQuickStart } from "./output/banner.ts";
|
||||
import { loadCommandPacks } from "./command-packs/load.ts";
|
||||
import { createCommandPackManager } from "./command-packs/manager.ts";
|
||||
import type { CommandPackPolicy } from "./command-packs/types.ts";
|
||||
import { printMcpServeHelp } from "./mcp-server/help.ts";
|
||||
import { serveMcpStdio } from "./mcp-server/serve.ts";
|
||||
|
||||
/** Per-product identity injected by each CLI entrypoint (bl / rag / …). */
|
||||
export interface CliOptions {
|
||||
@@ -112,6 +114,11 @@ export function createCli(commands: Record<string, AnyCommand>, opts: CliOptions
|
||||
/** Render help for `path`; root ([]) doubles as the onboarding / login guide. */
|
||||
function renderHelp(registry: CommandRegistry, path: string[], argv: string[]): void {
|
||||
registry.printHelp(path, process.stderr);
|
||||
if (path.length === 1 && path[0] === "mcp") {
|
||||
process.stderr.write(
|
||||
`\nAlso available (runtime built-in):\n mcp serve Start a local STDIO MCP server exposing all CLI commands as tools\n`,
|
||||
);
|
||||
}
|
||||
if (path.length > 0) return;
|
||||
|
||||
let hasKey = false;
|
||||
@@ -138,6 +145,28 @@ export function createCli(commands: Record<string, AnyCommand>, opts: CliOptions
|
||||
}
|
||||
|
||||
async function dispatch(registry: CommandRegistry, argv: string[]): Promise<void> {
|
||||
const parsed = parsePath(argv);
|
||||
// Handle --version before path-specific dispatch (including mcp serve).
|
||||
if (parsed.hasVersionFlag) {
|
||||
process.stdout.write(`${binName} ${version}\n`);
|
||||
return;
|
||||
}
|
||||
|
||||
// Runtime built-in: local STDIO MCP host. Not a defineCommand leaf — needs the
|
||||
// full registry to mount tools, so it lives here instead of packages/commands.
|
||||
if (parsed.path[0] === "mcp" && parsed.path[1] === "serve") {
|
||||
if (parsed.hasHelpFlag) {
|
||||
printMcpServeHelp(binName);
|
||||
return;
|
||||
}
|
||||
await serveMcpStdio({
|
||||
identity,
|
||||
leaves: registry.getLeafEntries(),
|
||||
commandPacks: commandPackManager,
|
||||
});
|
||||
return;
|
||||
}
|
||||
|
||||
const res = resolve(argv, registry);
|
||||
|
||||
switch (res.kind) {
|
||||
|
||||
@@ -95,3 +95,15 @@ export { initPipelineSteps } from "./pipeline/init.ts";
|
||||
export { executePipeline, streamPipelineEvents } from "./pipeline/executor.ts";
|
||||
export { collectPipelineIssues, collectPipelineHints } from "./pipeline/validation.ts";
|
||||
export type { PipelineDefinition, PipelineLifecycleEvent } from "./pipeline/types.ts";
|
||||
|
||||
// Local STDIO MCP server (bl mcp serve)
|
||||
export { serveMcpStdio } from "./mcp-server/serve.ts";
|
||||
export type { ServeMcpStdioOptions } from "./mcp-server/serve.ts";
|
||||
export {
|
||||
buildToolDescriptors,
|
||||
flagsToInputSchema,
|
||||
flagsToZodObject,
|
||||
pathToToolName,
|
||||
} from "./mcp-server/schema.ts";
|
||||
export type { JsonSchemaObject, McpToolDescriptor } from "./mcp-server/schema.ts";
|
||||
export { withCapturedOutput } from "./mcp-server/output-capture.ts";
|
||||
|
||||
@@ -0,0 +1,19 @@
|
||||
/** Help text for the runtime built-in `mcp serve` path. */
|
||||
export function printMcpServeHelp(binName: string): void {
|
||||
process.stderr.write(
|
||||
[
|
||||
"Start a local STDIO MCP server exposing all CLI commands as tools (for connectors such as QwenWork)",
|
||||
`Usage: ${binName} mcp serve`,
|
||||
"",
|
||||
"Notes:",
|
||||
" Speaks MCP over stdin/stdout. Do not treat this process as a normal CLI that prints results to stdout.",
|
||||
` Authenticate first with \`${binName} auth login\` (or env credentials); tools reuse the same local credential resolution as the CLI.`,
|
||||
` Distinct from \`${binName} mcp list|tools|call\`, which call Bailian marketplace MCP servers.`,
|
||||
" This path is a runtime built-in (not a commands-library leaf), so it can mount the full product command map.",
|
||||
"",
|
||||
"Examples:",
|
||||
` ${binName} mcp serve`,
|
||||
"",
|
||||
].join("\n"),
|
||||
);
|
||||
}
|
||||
@@ -0,0 +1,119 @@
|
||||
import type {
|
||||
AnyCommand,
|
||||
CommandPackManager,
|
||||
FlagDef,
|
||||
FlagsDef,
|
||||
Identity,
|
||||
ParsedFlags,
|
||||
} from "bailian-cli-core";
|
||||
import {
|
||||
BailianError,
|
||||
Client,
|
||||
ExitCode,
|
||||
UsageError,
|
||||
buildSettings,
|
||||
buildSources,
|
||||
makeAuthStore,
|
||||
makeConfigStore,
|
||||
resolveModelBaseUrl,
|
||||
} from "bailian-cli-core";
|
||||
import { camelToKebab } from "../args.ts";
|
||||
import { compose, authStage, runCommandStage, type RunContext } from "../middleware.ts";
|
||||
import { withCapturedOutput } from "./output-capture.ts";
|
||||
|
||||
export interface InvokeCommandOptions {
|
||||
identity: Identity;
|
||||
path: string[];
|
||||
command: AnyCommand;
|
||||
/** Tool arguments keyed by camelCase flag names. */
|
||||
args: Record<string, unknown>;
|
||||
commandPacks: CommandPackManager;
|
||||
}
|
||||
|
||||
function coerceOwnFlags(command: AnyCommand, args: Record<string, unknown>): ParsedFlags<FlagsDef> {
|
||||
const defs: FlagsDef = command.flags ?? {};
|
||||
const ownFlags: Record<string, unknown> = {};
|
||||
|
||||
for (const key of Object.keys(defs)) {
|
||||
const def: FlagDef = defs[key]!;
|
||||
if (key in args) {
|
||||
ownFlags[key] = args[key];
|
||||
continue;
|
||||
}
|
||||
if (def.type === "switch") {
|
||||
ownFlags[key] = false;
|
||||
}
|
||||
}
|
||||
|
||||
for (const key of Object.keys(defs)) {
|
||||
const def: FlagDef = defs[key]!;
|
||||
if (def.type !== "switch" && "required" in def && def.required && !(key in ownFlags)) {
|
||||
throw new UsageError(`Missing required flag: --${camelToKebab(key)}`);
|
||||
}
|
||||
}
|
||||
|
||||
const invalid = command.validate?.(ownFlags as ParsedFlags<FlagsDef>);
|
||||
if (invalid) throw new UsageError(invalid);
|
||||
|
||||
return ownFlags as ParsedFlags<FlagsDef>;
|
||||
}
|
||||
|
||||
function formatInvokeError(error: unknown): string {
|
||||
if (error instanceof BailianError) {
|
||||
const parts = [error.message];
|
||||
if (error.hint) parts.push(error.hint);
|
||||
return parts.join("\n");
|
||||
}
|
||||
if (error instanceof Error) return error.message;
|
||||
return String(error);
|
||||
}
|
||||
|
||||
/**
|
||||
* Run one leaf command under MCP: force JSON + quiet, capture emitResult/emitBare,
|
||||
* reuse auth stage. Does not write to process.stdout.
|
||||
*/
|
||||
export async function invokeCommandForMcp(
|
||||
options: InvokeCommandOptions,
|
||||
): Promise<{ ok: true; text: string } | { ok: false; text: string }> {
|
||||
try {
|
||||
const ownFlags = coerceOwnFlags(options.command, options.args);
|
||||
const sources = buildSources({});
|
||||
const settings = {
|
||||
...buildSettings(sources),
|
||||
quiet: true,
|
||||
output: "json" as const,
|
||||
verbose: false,
|
||||
};
|
||||
|
||||
const ctx: RunContext = {
|
||||
identity: options.identity,
|
||||
path: options.path,
|
||||
command: options.command,
|
||||
flags: ownFlags,
|
||||
settings,
|
||||
sources,
|
||||
configStore: makeConfigStore(sources.configName),
|
||||
authStore: makeAuthStore(sources),
|
||||
commandPacks: options.commandPacks,
|
||||
client: new Client({
|
||||
identity: options.identity,
|
||||
settings,
|
||||
baseUrl: resolveModelBaseUrl(sources),
|
||||
}),
|
||||
};
|
||||
|
||||
const run = compose([authStage, runCommandStage]);
|
||||
const { stdout } = await withCapturedOutput(() => run(ctx));
|
||||
const text = stdout.trimEnd() || JSON.stringify({ ok: true });
|
||||
return { ok: true, text };
|
||||
} catch (error) {
|
||||
const text = formatInvokeError(error);
|
||||
if (error instanceof BailianError && error.exitCode === ExitCode.AUTH) {
|
||||
return {
|
||||
ok: false,
|
||||
text: `${text}\n\nAuthenticate in a terminal first: ${options.identity.binName} auth login`,
|
||||
};
|
||||
}
|
||||
return { ok: false, text };
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,30 @@
|
||||
import { AsyncLocalStorage } from "node:async_hooks";
|
||||
|
||||
interface CaptureState {
|
||||
chunks: string[];
|
||||
}
|
||||
|
||||
const captureStore = new AsyncLocalStorage<CaptureState>();
|
||||
|
||||
/** True when {@link emitResult} / {@link emitBare} should buffer instead of writing stdout. */
|
||||
export function isCapturingOutput(): boolean {
|
||||
return captureStore.getStore() !== undefined;
|
||||
}
|
||||
|
||||
/** Append a line to the active capture buffer. No-op outside {@link withCapturedOutput}. */
|
||||
export function appendCapturedOutput(chunk: string): void {
|
||||
const state = captureStore.getStore();
|
||||
if (state) state.chunks.push(chunk);
|
||||
}
|
||||
|
||||
/**
|
||||
* Run `fn` while diverting {@link emitResult} / {@link emitBare} into a buffer
|
||||
* so MCP STDIO can keep exclusive ownership of process.stdout.
|
||||
*/
|
||||
export async function withCapturedOutput<T>(
|
||||
fn: () => Promise<T>,
|
||||
): Promise<{ value: T; stdout: string }> {
|
||||
const state: CaptureState = { chunks: [] };
|
||||
const value = await captureStore.run(state, fn);
|
||||
return { value, stdout: state.chunks.join("") };
|
||||
}
|
||||
@@ -0,0 +1,129 @@
|
||||
import type { AnyCommand, FlagDef, FlagsDef } from "bailian-cli-core";
|
||||
import { z } from "zod";
|
||||
|
||||
/** JSON Schema object shape (used in unit tests / descriptor snapshots). */
|
||||
export interface JsonSchemaObject {
|
||||
type: "object";
|
||||
properties: Record<string, Record<string, unknown>>;
|
||||
required?: string[];
|
||||
additionalProperties?: boolean;
|
||||
}
|
||||
|
||||
/** Zod object schema for `McpServer.registerTool({ inputSchema })`. */
|
||||
export function flagsToZodObject(flags: FlagsDef | undefined) {
|
||||
const shape: Record<string, z.ZodTypeAny> = {};
|
||||
|
||||
for (const key of Object.keys(flags ?? {})) {
|
||||
const def: FlagDef = flags![key]!;
|
||||
let schema: z.ZodTypeAny;
|
||||
|
||||
if (def.type === "switch" || def.type === "boolean") {
|
||||
schema = z.boolean();
|
||||
} else if (def.type === "number") {
|
||||
schema = z.number();
|
||||
} else if (def.type === "array") {
|
||||
const item =
|
||||
def.choices && def.choices.length > 0
|
||||
? z.enum(def.choices as [string, ...string[]])
|
||||
: z.string();
|
||||
schema = z.array(item);
|
||||
} else if (def.choices && def.choices.length > 0) {
|
||||
schema = z.enum(def.choices as [string, ...string[]]);
|
||||
} else {
|
||||
schema = z.string();
|
||||
}
|
||||
|
||||
schema = schema.describe(def.description);
|
||||
const required = def.type !== "switch" && "required" in def && !!def.required;
|
||||
shape[key] = required ? schema : schema.optional();
|
||||
}
|
||||
|
||||
return z.object(shape);
|
||||
}
|
||||
|
||||
/** Stable MCP tool name from a space-separated command path, e.g. `text chat` → `bailian_text_chat`. */
|
||||
export function pathToToolName(path: string, prefix = "bailian"): string {
|
||||
const slug = path
|
||||
.trim()
|
||||
.split(/\s+/)
|
||||
.join("_")
|
||||
.replace(/[^a-zA-Z0-9_-]/g, "_");
|
||||
return `${prefix}_${slug}`;
|
||||
}
|
||||
|
||||
function flagToProperty(def: FlagDef): Record<string, unknown> {
|
||||
if (def.type === "switch") {
|
||||
return { type: "boolean", description: def.description };
|
||||
}
|
||||
if (def.type === "number") {
|
||||
const property: Record<string, unknown> = { type: "number", description: def.description };
|
||||
if (def.choices?.length) property.enum = def.choices.map((choice) => Number(choice));
|
||||
return property;
|
||||
}
|
||||
if (def.type === "boolean") {
|
||||
return { type: "boolean", description: def.description };
|
||||
}
|
||||
if (def.type === "array") {
|
||||
const items: Record<string, unknown> = { type: "string" };
|
||||
if (def.choices?.length) items.enum = [...def.choices];
|
||||
return { type: "array", items, description: def.description };
|
||||
}
|
||||
const property: Record<string, unknown> = { type: "string", description: def.description };
|
||||
if (def.choices?.length) property.enum = [...def.choices];
|
||||
return property;
|
||||
}
|
||||
|
||||
/** Build MCP `inputSchema` from a command's own flags (no global / credential flags). */
|
||||
export function flagsToInputSchema(flags: FlagsDef | undefined): JsonSchemaObject {
|
||||
const properties: Record<string, Record<string, unknown>> = {};
|
||||
const required: string[] = [];
|
||||
|
||||
for (const [key, def] of Object.entries(flags ?? {})) {
|
||||
properties[key] = flagToProperty(def);
|
||||
if (def.type !== "switch" && "required" in def && def.required) {
|
||||
required.push(key);
|
||||
}
|
||||
}
|
||||
|
||||
const schema: JsonSchemaObject = {
|
||||
type: "object",
|
||||
properties,
|
||||
additionalProperties: false,
|
||||
};
|
||||
if (required.length > 0) schema.required = required;
|
||||
return schema;
|
||||
}
|
||||
|
||||
export interface McpToolDescriptor {
|
||||
name: string;
|
||||
description: string;
|
||||
inputSchema: JsonSchemaObject;
|
||||
/** Original CLI path, e.g. `text chat`. */
|
||||
path: string;
|
||||
command: AnyCommand;
|
||||
}
|
||||
|
||||
/** Map leaf commands to MCP tool descriptors. */
|
||||
export function buildToolDescriptors(
|
||||
leaves: Array<{ path: string; command: AnyCommand }>,
|
||||
options?: { toolNamePrefix?: string; skipPaths?: ReadonlySet<string> },
|
||||
): McpToolDescriptor[] {
|
||||
const prefix = options?.toolNamePrefix ?? "bailian";
|
||||
const skipPaths = options?.skipPaths ?? new Set<string>();
|
||||
const tools: McpToolDescriptor[] = [];
|
||||
|
||||
for (const leaf of leaves) {
|
||||
if (skipPaths.has(leaf.path)) continue;
|
||||
const name = pathToToolName(leaf.path, prefix);
|
||||
const usage = leaf.command.usageArgs ? ` Usage: ${leaf.command.usageArgs}` : "";
|
||||
tools.push({
|
||||
name,
|
||||
description: `${leaf.command.description} (bl ${leaf.path}).${usage}`,
|
||||
inputSchema: flagsToInputSchema(leaf.command.flags),
|
||||
path: leaf.path,
|
||||
command: leaf.command,
|
||||
});
|
||||
}
|
||||
|
||||
return tools;
|
||||
}
|
||||
@@ -0,0 +1,55 @@
|
||||
import { McpServer } from "@modelcontextprotocol/server";
|
||||
import { StdioServerTransport } from "@modelcontextprotocol/server/stdio";
|
||||
import type { AnyCommand, CommandPackManager, Identity } from "bailian-cli-core";
|
||||
import { buildToolDescriptors, flagsToZodObject } from "./schema.ts";
|
||||
import { invokeCommandForMcp } from "./invoke.ts";
|
||||
|
||||
export interface ServeMcpStdioOptions {
|
||||
identity: Identity;
|
||||
/** Leaf command entries from the product command map / registry. */
|
||||
leaves: Array<{ path: string; command: AnyCommand }>;
|
||||
commandPacks: CommandPackManager;
|
||||
}
|
||||
|
||||
/**
|
||||
* Start an MCP server on stdin/stdout that exposes every leaf CLI command as a tool.
|
||||
* Resolves when the transport closes (client disconnect / EOF).
|
||||
*/
|
||||
export async function serveMcpStdio(options: ServeMcpStdioOptions): Promise<void> {
|
||||
const tools = buildToolDescriptors(options.leaves);
|
||||
|
||||
const mcpServer = new McpServer({
|
||||
name: `${options.identity.clientName}-mcp`,
|
||||
version: options.identity.version,
|
||||
});
|
||||
|
||||
for (const tool of tools) {
|
||||
mcpServer.registerTool(
|
||||
tool.name,
|
||||
{
|
||||
description: tool.description,
|
||||
inputSchema: flagsToZodObject(tool.command.flags),
|
||||
},
|
||||
async (args) => {
|
||||
const result = await invokeCommandForMcp({
|
||||
identity: options.identity,
|
||||
path: tool.path.split(" "),
|
||||
command: tool.command,
|
||||
args: (args ?? {}) as Record<string, unknown>,
|
||||
commandPacks: options.commandPacks,
|
||||
});
|
||||
|
||||
return {
|
||||
isError: !result.ok,
|
||||
content: [{ type: "text" as const, text: result.text }],
|
||||
};
|
||||
},
|
||||
);
|
||||
}
|
||||
|
||||
const transport = new StdioServerTransport();
|
||||
await mcpServer.connect(transport);
|
||||
process.stderr.write(
|
||||
`${options.identity.binName} mcp serve: STDIO MCP ready (${tools.length} tools)\n`,
|
||||
);
|
||||
}
|
||||
@@ -1,12 +1,21 @@
|
||||
import { formatOutput, type OutputFormat } from "bailian-cli-core";
|
||||
import { appendCapturedOutput, isCapturingOutput } from "../mcp-server/output-capture.ts";
|
||||
|
||||
/**
|
||||
* Emit the primary result of a command.
|
||||
* stdout → result (text by default; JSON with --output json)
|
||||
* stderr → human info (progress, logs, tips) — handled elsewhere
|
||||
*
|
||||
* When MCP STDIO capture is active, writes go to an in-memory buffer instead
|
||||
* of process.stdout so the JSON-RPC stream stays intact.
|
||||
*/
|
||||
export function emitResult(data: unknown, format: OutputFormat): void {
|
||||
process.stdout.write(formatOutput(data, format) + "\n");
|
||||
const line = formatOutput(data, format) + "\n";
|
||||
if (isCapturingOutput()) {
|
||||
appendCapturedOutput(line);
|
||||
return;
|
||||
}
|
||||
process.stdout.write(line);
|
||||
}
|
||||
|
||||
/**
|
||||
@@ -14,7 +23,12 @@ export function emitResult(data: unknown, format: OutputFormat): void {
|
||||
* Used in --quiet mode or when the result is a single scalar.
|
||||
*/
|
||||
export function emitBare(value: string): void {
|
||||
process.stdout.write(value + "\n");
|
||||
const line = value + "\n";
|
||||
if (isCapturingOutput()) {
|
||||
appendCapturedOutput(line);
|
||||
return;
|
||||
}
|
||||
process.stdout.write(line);
|
||||
}
|
||||
|
||||
/**
|
||||
|
||||
@@ -83,6 +83,24 @@ export class CommandRegistry {
|
||||
return commands;
|
||||
}
|
||||
|
||||
/** All executable leaf paths with their commands (space-separated path keys). */
|
||||
getLeafEntries(): Array<{ path: string; command: AnyCommand }> {
|
||||
const entries: Array<{ path: string; command: AnyCommand }> = [];
|
||||
const collect = (node: CommandNode, prefix: string) => {
|
||||
for (const [name, child] of node.children) {
|
||||
const fullPath = prefix ? `${prefix} ${name}` : name;
|
||||
if (child.command) {
|
||||
entries.push({ path: fullPath, command: child.command });
|
||||
}
|
||||
if (child.children.size > 0) {
|
||||
collect(child, fullPath);
|
||||
}
|
||||
}
|
||||
};
|
||||
collect(this.root, "");
|
||||
return entries;
|
||||
}
|
||||
|
||||
/** First registered command path, for the "Getting Help" example (e.g. "knowledge retrieve"). */
|
||||
private helpExample(): string {
|
||||
const walk = (node: CommandNode, path: string[]): string | null => {
|
||||
|
||||
@@ -0,0 +1,72 @@
|
||||
import { describe, expect, test } from "vite-plus/test";
|
||||
import { defineCommand, type Identity } from "bailian-cli-core";
|
||||
import { emitResult } from "../src/output/output.ts";
|
||||
import { invokeCommandForMcp } from "../src/mcp-server/invoke.ts";
|
||||
import { createCommandPackManager } from "../src/command-packs/manager.ts";
|
||||
|
||||
const identity: Identity = {
|
||||
binName: "bl",
|
||||
version: "0.0.0-test",
|
||||
clientName: "bailian-cli",
|
||||
npmPackage: "bailian-cli",
|
||||
};
|
||||
|
||||
const commandPacks = createCommandPackManager(identity, { supported: {} });
|
||||
|
||||
describe("mcp-server invoke", () => {
|
||||
test("captures emitResult JSON without writing business output as protocol noise", async () => {
|
||||
const command = defineCommand({
|
||||
description: "Echo",
|
||||
auth: "none",
|
||||
flags: {
|
||||
prompt: {
|
||||
type: "string",
|
||||
valueHint: "<text>",
|
||||
description: "Prompt",
|
||||
required: true,
|
||||
},
|
||||
},
|
||||
async run(ctx) {
|
||||
emitResult({ echoed: ctx.flags.prompt }, "json");
|
||||
},
|
||||
});
|
||||
|
||||
const result = await invokeCommandForMcp({
|
||||
identity,
|
||||
path: ["text", "chat"],
|
||||
command,
|
||||
args: { prompt: "hello" },
|
||||
commandPacks,
|
||||
});
|
||||
|
||||
expect(result.ok).toBe(true);
|
||||
expect(JSON.parse(result.text)).toEqual({ echoed: "hello" });
|
||||
});
|
||||
|
||||
test("returns usage error when required flag missing", async () => {
|
||||
const command = defineCommand({
|
||||
description: "Echo",
|
||||
auth: "none",
|
||||
flags: {
|
||||
prompt: {
|
||||
type: "string",
|
||||
valueHint: "<text>",
|
||||
description: "Prompt",
|
||||
required: true,
|
||||
},
|
||||
},
|
||||
async run() {},
|
||||
});
|
||||
|
||||
const result = await invokeCommandForMcp({
|
||||
identity,
|
||||
path: ["text", "chat"],
|
||||
command,
|
||||
args: {},
|
||||
commandPacks,
|
||||
});
|
||||
|
||||
expect(result.ok).toBe(false);
|
||||
expect(result.text).toMatch(/Missing required flag/);
|
||||
});
|
||||
});
|
||||
@@ -0,0 +1,77 @@
|
||||
import { describe, expect, test } from "vite-plus/test";
|
||||
import { defineCommand } from "bailian-cli-core";
|
||||
import {
|
||||
buildToolDescriptors,
|
||||
flagsToInputSchema,
|
||||
flagsToZodObject,
|
||||
pathToToolName,
|
||||
} from "../src/mcp-server/schema.ts";
|
||||
|
||||
describe("mcp-server schema", () => {
|
||||
test("pathToToolName maps space path to bailian_*", () => {
|
||||
expect(pathToToolName("text chat")).toBe("bailian_text_chat");
|
||||
expect(pathToToolName("memory profile get")).toBe("bailian_memory_profile_get");
|
||||
});
|
||||
|
||||
test("flagsToInputSchema marks required strings and switch booleans", () => {
|
||||
const schema = flagsToInputSchema({
|
||||
prompt: {
|
||||
type: "string",
|
||||
valueHint: "<text>",
|
||||
description: "User prompt",
|
||||
required: true,
|
||||
},
|
||||
quiet: { type: "switch", description: "Quiet" },
|
||||
n: { type: "number", valueHint: "<n>", description: "Count" },
|
||||
tags: { type: "array", valueHint: "<tag>", description: "Tags" },
|
||||
});
|
||||
|
||||
expect(schema.type).toBe("object");
|
||||
expect(schema.required).toEqual(["prompt"]);
|
||||
expect(schema.properties.prompt).toMatchObject({ type: "string" });
|
||||
expect(schema.properties.quiet).toMatchObject({ type: "boolean" });
|
||||
expect(schema.properties.n).toMatchObject({ type: "number" });
|
||||
expect(schema.properties.tags).toMatchObject({
|
||||
type: "array",
|
||||
items: { type: "string" },
|
||||
});
|
||||
});
|
||||
|
||||
test("flagsToZodObject marks required fields", () => {
|
||||
const schema = flagsToZodObject({
|
||||
prompt: {
|
||||
type: "string",
|
||||
valueHint: "<text>",
|
||||
description: "User prompt",
|
||||
required: true,
|
||||
},
|
||||
n: { type: "number", valueHint: "<n>", description: "Count" },
|
||||
});
|
||||
|
||||
expect(schema.parse({ prompt: "hi" })).toEqual({ prompt: "hi" });
|
||||
expect(() => schema.parse({})).toThrow();
|
||||
});
|
||||
|
||||
test("buildToolDescriptors maps leaf paths", () => {
|
||||
const sample = defineCommand({
|
||||
description: "Sample",
|
||||
auth: "none",
|
||||
flags: {
|
||||
prompt: {
|
||||
type: "string",
|
||||
valueHint: "<text>",
|
||||
description: "Prompt",
|
||||
required: true,
|
||||
},
|
||||
},
|
||||
async run() {},
|
||||
});
|
||||
|
||||
const tools = buildToolDescriptors([{ path: "text chat", command: sample }]);
|
||||
|
||||
expect(tools).toHaveLength(1);
|
||||
expect(tools[0]?.name).toBe("bailian_text_chat");
|
||||
expect(tools[0]?.path).toBe("text chat");
|
||||
expect(tools[0]?.inputSchema.required).toEqual(["prompt"]);
|
||||
});
|
||||
});
|
||||
Generated
+32
-3
@@ -6,6 +6,9 @@ settings:
|
||||
|
||||
catalogs:
|
||||
default:
|
||||
'@modelcontextprotocol/server':
|
||||
specifier: ^2.0.0
|
||||
version: 2.0.0
|
||||
'@types/node':
|
||||
specifier: ^24
|
||||
version: 24.12.2
|
||||
@@ -24,12 +27,12 @@ catalogs:
|
||||
chalk:
|
||||
specifier: ^5.6.2
|
||||
version: 5.6.2
|
||||
tar-stream:
|
||||
specifier: ^3.2.0
|
||||
version: 3.2.0
|
||||
smol-toml:
|
||||
specifier: ^1.4.2
|
||||
version: 1.7.0
|
||||
tar-stream:
|
||||
specifier: ^3.2.0
|
||||
version: 3.2.0
|
||||
tsx:
|
||||
specifier: ^4.23.0
|
||||
version: 4.23.0
|
||||
@@ -45,6 +48,9 @@ catalogs:
|
||||
yauzl:
|
||||
specifier: ^3.4.0
|
||||
version: 3.4.0
|
||||
zod:
|
||||
specifier: ^4.4.3
|
||||
version: 4.4.3
|
||||
|
||||
overrides:
|
||||
vite: npm:@voidzero-dev/vite-plus-core@latest
|
||||
@@ -245,6 +251,9 @@ importers:
|
||||
|
||||
packages/runtime:
|
||||
dependencies:
|
||||
'@modelcontextprotocol/server':
|
||||
specifier: 'catalog:'
|
||||
version: 2.0.0
|
||||
bailian-cli-core:
|
||||
specifier: workspace:*
|
||||
version: link:../core
|
||||
@@ -257,6 +266,9 @@ importers:
|
||||
undici:
|
||||
specifier: 'catalog:'
|
||||
version: 6.27.0
|
||||
zod:
|
||||
specifier: 'catalog:'
|
||||
version: 4.4.3
|
||||
devDependencies:
|
||||
'@clack/prompts':
|
||||
specifier: ^0.7.0
|
||||
@@ -458,6 +470,14 @@ packages:
|
||||
cpu: [x64]
|
||||
os: [win32]
|
||||
|
||||
'@modelcontextprotocol/core@2.0.0':
|
||||
resolution: {integrity: sha512-pJCEwGG7Lfr/+PQp9ZTwKXNeO5wzbfKL7H3MYpCorM4oFBoQrdjnBgEoqG+RjhsvS1FKrDbKux+M1HhlnGWqcA==}
|
||||
engines: {node: '>=20'}
|
||||
|
||||
'@modelcontextprotocol/server@2.0.0':
|
||||
resolution: {integrity: sha512-YhHWdHfpFMQfd0prsEnxKeS3Qz3ytIGmsS0sth4KDjnacIT7hxk6hXHkJ9KysxlkvTM+WZAtQbbcUhdoP4Hvtw==}
|
||||
engines: {node: '>=20'}
|
||||
|
||||
'@napi-rs/wasm-runtime@1.1.4':
|
||||
resolution: {integrity: sha512-3NQNNgA1YSlJb/kMH1ildASP9HW7/7kYnRI2szWJaofaS1hWmbGI4H+d3+22aGzXXN9IJ+n+GiFVcGipJP18ow==}
|
||||
peerDependencies:
|
||||
@@ -1667,6 +1687,15 @@ snapshots:
|
||||
'@esbuild/win32-x64@0.28.1':
|
||||
optional: true
|
||||
|
||||
'@modelcontextprotocol/core@2.0.0':
|
||||
dependencies:
|
||||
zod: 4.4.3
|
||||
|
||||
'@modelcontextprotocol/server@2.0.0':
|
||||
dependencies:
|
||||
'@modelcontextprotocol/core': 2.0.0
|
||||
zod: 4.4.3
|
||||
|
||||
'@napi-rs/wasm-runtime@1.1.4(@emnapi/core@1.10.0)(@emnapi/runtime@1.10.0)':
|
||||
dependencies:
|
||||
'@emnapi/core': 1.10.0
|
||||
|
||||
+3
-1
@@ -3,14 +3,15 @@ packages:
|
||||
- tools/*
|
||||
|
||||
catalog:
|
||||
"@modelcontextprotocol/server": ^2.0.0
|
||||
"@types/node": ^24
|
||||
"@types/tar-stream": ^3.1.4
|
||||
"@types/yauzl": ^3.4.0
|
||||
ajv: ^8.20.0
|
||||
boxen: ^8.0.1
|
||||
chalk: ^5.6.2
|
||||
tar-stream: ^3.2.0
|
||||
smol-toml: ^1.4.2
|
||||
tar-stream: ^3.2.0
|
||||
tsx: ^4.23.0
|
||||
typescript: ^5
|
||||
undici: ^6.27.0
|
||||
@@ -19,6 +20,7 @@ catalog:
|
||||
vitest: npm:@voidzero-dev/vite-plus-test@latest
|
||||
yaml: ^2.8.3
|
||||
yauzl: ^3.4.0
|
||||
zod: ^4.4.3
|
||||
|
||||
catalogMode: prefer
|
||||
overrides:
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
---
|
||||
name: bailian-cli
|
||||
metadata:
|
||||
version: "1.14.1"
|
||||
version: "1.14.2"
|
||||
requires:
|
||||
bins: ["bl"]
|
||||
description: >-
|
||||
|
||||
@@ -52,6 +52,7 @@ Use this index for the skill-scoped quick index and global flags.
|
||||
| `bl quota request` | Request a temporary quota increase | [quota.md](quota.md) |
|
||||
| `bl search web` | Search the web using DashScope MCP WebSearch service | [search.md](search.md) |
|
||||
| `bl skill add` | Install skills from the Bailian skill registry into local agents | [skill.md](skill.md) |
|
||||
| `bl skill init` | Install all bailian-\* skills (one-shot bootstrap for new environments) | [skill.md](skill.md) |
|
||||
| `bl skill list` | List registry skills and diff against local installs | [skill.md](skill.md) |
|
||||
| `bl skill remove` | Remove locally installed skills (registry is untouched) | [skill.md](skill.md) |
|
||||
| `bl skill update` | Update installed skills to the latest registry versions | [skill.md](skill.md) |
|
||||
@@ -86,7 +87,7 @@ Use this index for the skill-scoped quick index and global flags.
|
||||
| `plugin` | `install`, `link`, `list`, `remove` | [plugin.md](plugin.md) |
|
||||
| `quota` | `check`, `history`, `list`, `request` | [quota.md](quota.md) |
|
||||
| `search` | `web` | [search.md](search.md) |
|
||||
| `skill` | `add`, `list`, `remove`, `update` | [skill.md](skill.md) |
|
||||
| `skill` | `add`, `init`, `list`, `remove`, `update` | [skill.md](skill.md) |
|
||||
| `text` | `chat` | [text.md](text.md) |
|
||||
| `token-plan` | `add-member`, `assign-seats`, `create-key`, `list-seats` | [token-plan.md](token-plan.md) |
|
||||
| `update` | `(root)` | [update.md](update.md) |
|
||||
|
||||
@@ -7,12 +7,13 @@ Index: [index.md](index.md)
|
||||
|
||||
## Commands in this group
|
||||
|
||||
| Command | Description |
|
||||
| ----------------- | ---------------------------------------------------------------- |
|
||||
| `bl skill add` | Install skills from the Bailian skill registry into local agents |
|
||||
| `bl skill list` | List registry skills and diff against local installs |
|
||||
| `bl skill remove` | Remove locally installed skills (registry is untouched) |
|
||||
| `bl skill update` | Update installed skills to the latest registry versions |
|
||||
| Command | Description |
|
||||
| ----------------- | ----------------------------------------------------------------------- |
|
||||
| `bl skill add` | Install skills from the Bailian skill registry into local agents |
|
||||
| `bl skill init` | Install all bailian-\* skills (one-shot bootstrap for new environments) |
|
||||
| `bl skill list` | List registry skills and diff against local installs |
|
||||
| `bl skill remove` | Remove locally installed skills (registry is untouched) |
|
||||
| `bl skill update` | Update installed skills to the latest registry versions |
|
||||
|
||||
## Command details
|
||||
|
||||
@@ -22,24 +23,48 @@ Index: [index.md](index.md)
|
||||
| --------------- | ---------------------------------------------------------------- |
|
||||
| **Name** | `skill add` |
|
||||
| **Description** | Install skills from the Bailian skill registry into local agents |
|
||||
| **Usage** | `bl skill add --name <all\|name,...>` |
|
||||
| **Usage** | `bl skill add --all \| --name <name,...>` |
|
||||
|
||||
#### Flags
|
||||
|
||||
| Flag | Type | Required | Description |
|
||||
| ------------------------ | ------ | -------- | ----------------------------------------------------- |
|
||||
| `--name <all\|name,...>` | string | yes | Skills to install: all or comma-separated skill names |
|
||||
| Flag | Type | Required | Description |
|
||||
| ------------------- | ------ | -------- | -------------------------------------- |
|
||||
| `--all` | switch | no | Install all skills from the registry |
|
||||
| `--name <name,...>` | string | no | Comma-separated skill names to install |
|
||||
|
||||
#### Examples
|
||||
|
||||
```bash
|
||||
bl skill add --name all
|
||||
bl skill add --all
|
||||
```
|
||||
|
||||
```bash
|
||||
bl skill add --name spark-video,bailian-model-recommend
|
||||
```
|
||||
|
||||
### `bl skill init`
|
||||
|
||||
| Field | Value |
|
||||
| --------------- | ----------------------------------------------------------------------- |
|
||||
| **Name** | `skill init` |
|
||||
| **Description** | Install all bailian-\* skills (one-shot bootstrap for new environments) |
|
||||
| **Usage** | `bl skill init` |
|
||||
|
||||
#### Flags
|
||||
|
||||
_No command-specific flags._
|
||||
|
||||
#### Notes
|
||||
|
||||
- Fetches the registry index and installs every skill whose name starts with bailian-
|
||||
- Equivalent to: bl skill add --all (filtered to bailian-\* skills)
|
||||
|
||||
#### Examples
|
||||
|
||||
```bash
|
||||
bl skill init
|
||||
```
|
||||
|
||||
### `bl skill list`
|
||||
|
||||
| Field | Value |
|
||||
@@ -96,13 +121,14 @@ bl skill remove --name all
|
||||
| --------------- | ------------------------------------------------------- |
|
||||
| **Name** | `skill update` |
|
||||
| **Description** | Update installed skills to the latest registry versions |
|
||||
| **Usage** | `bl skill update [--name <all\|name,...>]` |
|
||||
| **Usage** | `bl skill update [--all] [--name <name,...>]` |
|
||||
|
||||
#### Flags
|
||||
|
||||
| Flag | Type | Required | Description |
|
||||
| ------------------------ | ------ | -------- | ----------------------------------------------------------------------------------------------------------- |
|
||||
| `--name <all\|name,...>` | string | no | Skills to update: all (default, only changed ones) or comma-separated names (force update installed skills) |
|
||||
| Flag | Type | Required | Description |
|
||||
| ------------------- | ------ | -------- | ---------------------------------------------------------------------------- |
|
||||
| `--all` | switch | no | Update all installed skills (default when neither --all nor --name is given) |
|
||||
| `--name <name,...>` | string | no | Comma-separated skill names to update (must be already installed) |
|
||||
|
||||
#### Examples
|
||||
|
||||
@@ -110,6 +136,10 @@ bl skill remove --name all
|
||||
bl skill update
|
||||
```
|
||||
|
||||
```bash
|
||||
bl skill update --all
|
||||
```
|
||||
|
||||
```bash
|
||||
bl skill update --name spark-video
|
||||
```
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
---
|
||||
name: bailian-finetune
|
||||
metadata:
|
||||
version: "1.14.1"
|
||||
version: "1.14.2"
|
||||
requires:
|
||||
bins: ["bl"]
|
||||
description: >-
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
---
|
||||
name: bailian-gen
|
||||
metadata:
|
||||
version: "1.14.1"
|
||||
version: "1.14.2"
|
||||
requires:
|
||||
bins: ["bl"]
|
||||
description: >-
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
---
|
||||
name: bailian-managed-agent
|
||||
metadata:
|
||||
version: "1.14.1"
|
||||
version: "1.14.2"
|
||||
requires:
|
||||
bins: ["bl"]
|
||||
description: >-
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
---
|
||||
name: bailian-protocol
|
||||
metadata:
|
||||
version: "1.14.1"
|
||||
version: "1.14.2"
|
||||
requires:
|
||||
bins: ["bl"]
|
||||
description: >-
|
||||
|
||||
Reference in New Issue
Block a user