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feat(video): upgrade happyhorse model from 1.0 to 1.1, video-edit has not been updated and is still 1.0.

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- Update default models in bl-api pipeline from happyhorse-1.0 to 1.1
- Replace happyhorse-1.0-t2v/i2v/r2v references with 1.1 versions in commands
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clh02467605
2026-06-22 14:30:48 +08:00
parent 1ffcbdd80c
commit 4e025dda8d
19 changed files with 49 additions and 49 deletions
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README.md
+3 -3
View File
@@ -27,7 +27,7 @@ Equip your AI Agent out-of-the-box with these capabilities, composable across co
- **Text chat** — Qwen3.7-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 2.0: pro text rendering, photorealism, strong semantic adherence, multi-image composition
- **Video generation & editing** — HappyHorse-1.0 series: text-/image-/reference-to-video and natural-language video editing (up to 9-image reference)
- **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
@@ -54,7 +54,7 @@ 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 1.0**, Aliyun Model Studio's text-/image-/reference-to-video generation model
- **[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
- **[spark-video Skill](https://github.com/JohnKeating1997/spark-video)** — handles scene decomposition, storyboarding, shot continuity, and final stitching
### The single prompt
@@ -67,7 +67,7 @@ A complete **2-minute, 16:9 cinematic short film** — produced end-to-end from
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 1.0** in parallel.
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.
No timeline scrubbing. No frame-by-frame editing. Just one sentence → one video.
README.zh.md
+3 -3
View File
@@ -27,7 +27,7 @@ _专为 AI Agent 打造，每个命令均可作为结构化工具调用。_
- **文本对话** — Qwen3.7-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 2.0：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-1.0 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
- **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
@@ -54,7 +54,7 @@ _专为 AI Agent 打造，每个命令均可作为结构化工具调用。_
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 1.0**,百炼的文生/图生/参考生视频模型
- **[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
@@ -65,7 +65,7 @@ _专为 AI Agent 打造，每个命令均可作为结构化工具调用。_
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 1.0**。
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。
没有时间线拖拽,没有逐帧剪辑。一句话 → 一部短片。
packages/cli/README.md
+3 -3
View File
@@ -27,7 +27,7 @@ Equip your AI Agent out-of-the-box with these capabilities, composable across co
- **Text chat** — Qwen3.7-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 2.0: pro text rendering, photorealism, strong semantic adherence, multi-image composition
- **Video generation & editing** — HappyHorse-1.0 series: text-/image-/reference-to-video and natural-language video editing (up to 9-image reference)
- **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
@@ -54,7 +54,7 @@ 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 1.0**, Aliyun Model Studio's text-/image-/reference-to-video generation model
- **[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
- **[spark-video Skill](https://github.com/JohnKeating1997/spark-video)** — handles scene decomposition, storyboarding, shot continuity, and final stitching
### The single prompt
@@ -67,7 +67,7 @@ A complete **2-minute, 16:9 cinematic short film** — produced end-to-end from
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 1.0** in parallel.
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.
No timeline scrubbing. No frame-by-frame editing. Just one sentence → one video.
packages/cli/README.zh.md
+3 -3
View File
@@ -27,7 +27,7 @@ _专为 AI Agent 打造，每个命令均可作为结构化工具调用。_
- **文本对话** — Qwen3.7-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 2.0：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-1.0 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
- **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
@@ -54,7 +54,7 @@ _专为 AI Agent 打造，每个命令均可作为结构化工具调用。_
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 1.0**,百炼的文生/图生/参考生视频模型
- **[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
@@ -65,7 +65,7 @@ _专为 AI Agent 打造，每个命令均可作为结构化工具调用。_
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 1.0**。
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。
没有时间线拖拽,没有逐帧剪辑。一句话 → 一部短片。
packages/cli/src/commands/video/generate.ts
+4 -4
View File
@@ -31,12 +31,12 @@ import {
export default defineCommand({
name: "video generate",
description:
"Generate a video from text or image (happyhorse-1.0-t2v / happyhorse-1.0-i2v / wan2.6-t2v)",
"Generate a video from text or image (happyhorse-1.1-t2v / happyhorse-1.1-i2v / wan2.6-t2v)",
usage: "bl video generate --prompt <text> [--image <url>] [flags]",
options: [
{
flag: "--model <model>",
description: "Model ID (default: happyhorse-1.0-t2v, or happyhorse-1.0-i2v with --image)",
description: "Model ID (default: happyhorse-1.1-t2v, or happyhorse-1.1-i2v with --image)",
},
{ flag: "--prompt <text>", description: "Video description", required: true },
{ flag: "--image <url>", description: "Input image URL for image-to-video generation" },
@@ -98,7 +98,7 @@ export default defineCommand({
const model =
(flags.model as string) ||
config.defaultVideoModel ||
((flags.image as string) ? "happyhorse-1.0-i2v" : "happyhorse-1.0-t2v");
((flags.image as string) ? "happyhorse-1.1-i2v" : "happyhorse-1.1-t2v");
const format = detectOutputFormat(config.output);
const imageUrl = flags.image as string | undefined;
@@ -118,7 +118,7 @@ export default defineCommand({
input: {
prompt: prompt!,
negative_prompt: (flags.negativePrompt as string) || undefined,
// i2v models (happyhorse-1.0-i2v) require input.media with type 'first_frame'
// i2v models (happyhorse-1.1-i2v) require input.media with type 'first_frame'
...(resolvedImageUrl
? { media: [{ type: "first_frame" as const, url: resolvedImageUrl }] }
: {}),
packages/cli/src/commands/video/ref.ts
+3 -3
View File
@@ -30,10 +30,10 @@ import {
export default defineCommand({
name: "video ref",
description:
"Reference-to-video generation (happyhorse-1.0-r2v / wan2.6-r2v): multi-subject, multi-shot with voice",
"Reference-to-video generation (happyhorse-1.1-r2v / wan2.6-r2v): multi-subject, multi-shot with voice",
usage: "bl video ref --prompt <text> --image <url>... [--ref-video <url>...] [flags]",
options: [
{ flag: "--model <model>", description: "Model ID (default: happyhorse-1.0-r2v)" },
{ flag: "--model <model>", description: "Model ID (default: happyhorse-1.1-r2v)" },
{
flag: "--prompt <text>",
description: "Video description with reference markers (image1, video1, etc.)",
@@ -126,7 +126,7 @@ export default defineCommand({
const imageVoices = (flags.imageVoice as string[] | undefined) || [];
const videoVoices = (flags.videoVoice as string[] | undefined) || [];
const model = (flags.model as string) || "happyhorse-1.0-r2v";
const model = (flags.model as string) || "happyhorse-1.1-r2v";
const format = detectOutputFormat(config.output);
// --- Resolve file URLs (auto-upload local files) ---
packages/cli/src/pipeline/steps/bl-api.ts
+1 -1
View File
@@ -391,7 +391,7 @@ export async function videoGenerate(
});
}
const model = input.model || (input.image ? "happyhorse-1.0-i2v" : "happyhorse-1.0-t2v");
const model = input.model || (input.image ? "happyhorse-1.1-i2v" : "happyhorse-1.1-t2v");
let resolvedImageUrl: string | undefined;
if (input.image) {
packages/cli/tests/e2e/video-download.e2e.test.ts
+1 -1
View File
@@ -91,7 +91,7 @@ describe.skipIf(!isBailianE2EVideoEnabled() || !isDashScopeE2EReady())(
"video",
"generate",
"--model",
"happyhorse-1.0-t2v",
"happyhorse-1.1-t2v",
"--duration",
"3",
"--prompt",
packages/cli/tests/e2e/video-generate-i2v.e2e.test.ts
+4 -4
View File
@@ -37,7 +37,7 @@ describe.skipIf(!isBailianE2EVideoEnabled() || !isDashScopeE2EReady())(
"video",
"generate",
"--model",
"happyhorse-1.0-i2v",
"happyhorse-1.1-i2v",
"--image",
"https://example.com/placeholder.png",
"--non-interactive",
@@ -53,7 +53,7 @@ describe.skipIf(!isBailianE2EVideoEnabled() || !isDashScopeE2EReady())(
"generate",
"--dry-run",
"--model",
"happyhorse-1.0-t2v",
"happyhorse-1.1-t2v",
"--prompt",
"干跑无图",
"--non-interactive",
@@ -68,7 +68,7 @@ describe.skipIf(!isBailianE2EVideoEnabled() || !isDashScopeE2EReady())(
expect(data.request?.input?.media).toBeUndefined();
});
test("【happyhorse-1.0-i2v】图片生成视频", async () => {
test("【happyhorse-1.1-i2v】图片生成视频", async () => {
const outDir = makeE2eOutputDir(e2eLabelFromMetaUrl(import.meta.url));
const png = join(outDir, "e2e-gen.png");
const gen = await runCli([
@@ -95,7 +95,7 @@ describe.skipIf(!isBailianE2EVideoEnabled() || !isDashScopeE2EReady())(
"video",
"generate",
"--model",
"happyhorse-1.0-i2v",
"happyhorse-1.1-i2v",
"--image",
imagePath,
"--prompt",
packages/cli/tests/e2e/video-generate-t2v.e2e.test.ts
+5 -5
View File
@@ -37,7 +37,7 @@ describe.skipIf(!isBailianE2EVideoEnabled() || !isDashScopeE2EReady())(
"video",
"generate",
"--model",
"happyhorse-1.0-t2v",
"happyhorse-1.1-t2v",
"--non-interactive",
]);
expect(exitCode).toBe(0);
@@ -51,7 +51,7 @@ describe.skipIf(!isBailianE2EVideoEnabled() || !isDashScopeE2EReady())(
"generate",
"--dry-run",
"--model",
"happyhorse-1.0-t2v",
"happyhorse-1.1-t2v",
"--prompt",
"干跑校验",
"--non-interactive",
@@ -62,18 +62,18 @@ describe.skipIf(!isBailianE2EVideoEnabled() || !isDashScopeE2EReady())(
const data = parseStdoutJson<{ request?: { model?: string; input?: { prompt?: string } } }>(
stdout,
);
expect(data.request?.model).toBe("happyhorse-1.0-t2v");
expect(data.request?.model).toBe("happyhorse-1.1-t2v");
expect(data.request?.input?.prompt).toBe("干跑校验");
});
test("【happyhorse-1.0-t2v】文本生成视频", async () => {
test("【happyhorse-1.1-t2v】文本生成视频", async () => {
const outDir = makeE2eOutputDir(e2eLabelFromMetaUrl(import.meta.url));
const { stdout, stderr, exitCode } = await runCli([
...cliTimeoutPrefix(),
"video",
"generate",
"--model",
"happyhorse-1.0-t2v",
"happyhorse-1.1-t2v",
"--prompt",
"夕阳下海面波光，远景静态镜头",
"--download",
packages/cli/tests/e2e/video-ref-r2v.e2e.test.ts
+4 -4
View File
@@ -37,7 +37,7 @@ describe.skipIf(!isBailianE2EVideoEnabled() || !isDashScopeE2EReady())(
"video",
"ref",
"--model",
"happyhorse-1.0-r2v",
"happyhorse-1.1-r2v",
"--image",
"https://example.com/x.png",
"--non-interactive",
@@ -52,7 +52,7 @@ describe.skipIf(!isBailianE2EVideoEnabled() || !isDashScopeE2EReady())(
"video",
"ref",
"--model",
"happyhorse-1.0-r2v",
"happyhorse-1.1-r2v",
"--prompt",
"仅有描述无素材",
"--non-interactive",
@@ -61,7 +61,7 @@ describe.skipIf(!isBailianE2EVideoEnabled() || !isDashScopeE2EReady())(
expect(stderr).toMatch(/--image|ref-video|At least one|required/i);
});
test("【happyhorse-1.0-r2v】视频参考生成", async () => {
test("【happyhorse-1.1-r2v】视频参考生成", async () => {
const outDir = makeE2eOutputDir(e2eLabelFromMetaUrl(import.meta.url));
const gen = await runCli([
"image",
@@ -88,7 +88,7 @@ describe.skipIf(!isBailianE2EVideoEnabled() || !isDashScopeE2EReady())(
"video",
"ref",
"--model",
"happyhorse-1.0-r2v",
"happyhorse-1.1-r2v",
"--prompt",
"图1在画面中心轻微晃动",
"--image",
packages/cli/tests/stress/lib/fixtures.mjs
+1 -1
View File
@@ -180,7 +180,7 @@ export async function ensurePrerequisites(ctx) {
"video",
"generate",
"--model",
"happyhorse-1.0-t2v",
"happyhorse-1.1-t2v",
"--prompt",
"压测前置短视频：海浪与静态远景，无明显人物。",
"--duration",
packages/cli/tests/stress/lib/suite-fixtures.mjs
+1 -1
View File
@@ -132,7 +132,7 @@ export async function generateCombinedFixtures({ suiteRoot, cliPackage }) {
"video",
"generate",
"--model",
"happyhorse-1.0-t2v",
"happyhorse-1.1-t2v",
"--prompt",
"压测前置短视频：海浪与静态远景，无明显人物。",
"--duration",
packages/cli/tests/stress/targets/video-i2v.mjs
+1 -1
View File
@@ -16,7 +16,7 @@ const motions = [
export const runStress = defineStressTarget({
canonical: "video-i2v",
defaultModel: "happyhorse-1.0-i2v",
defaultModel: "happyhorse-1.1-i2v",
batchDirPrefix: "video-i2v-batch",
helpText: "pnpm run test:stress -- video-i2v [--reuse-fixtures] -- --count 5 -c 2",
packages/cli/tests/stress/targets/video-ref.mjs
+1 -1
View File
@@ -16,7 +16,7 @@ const prompts = [
export const runStress = defineStressTarget({
canonical: "video-ref",
defaultModel: "happyhorse-1.0-r2v",
defaultModel: "happyhorse-1.1-r2v",
batchDirPrefix: "video-ref-batch",
helpText: "pnpm run test:stress -- video-ref [--reuse-fixtures] -- --count 5 -c 2",
packages/cli/tests/stress/targets/video-t2v.mjs
+1 -1
View File
@@ -45,7 +45,7 @@ const pick = (arr) => arr[Math.floor(Math.random() * arr.length)];
export const runStress = defineStressTarget({
canonical: "video-t2v",
defaultModel: "happyhorse-1.0-t2v",
defaultModel: "happyhorse-1.1-t2v",
batchDirPrefix: "video-t2v-batch",
helpText: `用法：pnpm run test:stress -- video-t2v -- --concurrency 1 --count 3
详见 docs/agents/stress-batch-tests.md`,
skills/bailian-cli/SKILL.md
+2 -2
View File
@@ -45,9 +45,9 @@ Do not guess flags — use the reference files or `--help`.
| Video/audio understanding (with audio reply) | `bl omni --video` / `--audio` | Prefer over generic VL for A/V Q&A |
| Image from text | `bl image generate` | `qwen-image-2.0` |
| Image edit / multi-image merge | `bl image edit` (repeat `--image`) | `qwen-image-2.0` |
| Video from text or image | `bl video generate` | `happyhorse-1.0-t2v` / `-i2v` with `--image` |
| Video from text or image | `bl video generate` | `happyhorse-1.1-t2v` / `-i2v` with `--image` |
| Video edit / style transfer | `bl video edit` | `happyhorse-1.0-video-edit` |
| Reference-to-video + voice | `bl video ref` | `happyhorse-1.0-r2v` |
| Reference-to-video + voice | `bl video ref` | `happyhorse-1.1-r2v` |
| Image / video describe (text only) | `bl vision describe` | `qwen-vl-max` |
| TTS | `bl speech synthesize` | `cosyvoice-v3-flash` |
| ASR | `bl speech recognize` | `fun-asr` |
skills/bailian-cli/reference/index.md
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@@ -51,8 +51,8 @@ Use this index for the full quick index and global flags.
| `bl usage stats` | Query model usage statistics | [usage.md](usage.md) |
| `bl video download` | Download a completed video by task ID | [video.md](video.md) |
| `bl video edit` | Edit a video with happyhorse-1.0-video-edit (style transfer, object replacement, etc.) | [video.md](video.md) |
| `bl video generate` | Generate a video from text or image (happyhorse-1.0-t2v / happyhorse-1.0-i2v / wan2.6-t2v) | [video.md](video.md) |
| `bl video ref` | Reference-to-video generation (happyhorse-1.0-r2v / wan2.6-r2v): multi-subject, multi-shot with voice | [video.md](video.md) |
| `bl video generate` | Generate a video from text or image (happyhorse-1.1-t2v / happyhorse-1.1-i2v / wan2.6-t2v) | [video.md](video.md) |
| `bl video ref` | Reference-to-video generation (happyhorse-1.1-r2v / wan2.6-r2v): multi-subject, multi-shot with voice | [video.md](video.md) |
| `bl video task get` | Query async task status | [video.md](video.md) |
| `bl vision describe` | Describe an image or video using Qwen-VL | [vision.md](vision.md) |
| `bl workspace list` | List all workspaces | [workspace.md](workspace.md) |
skills/bailian-cli/reference/video.md
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@@ -11,8 +11,8 @@ Index: [index.md](index.md)
| ------------------- | ----------------------------------------------------------------------------------------------------- |
| `bl video download` | Download a completed video by task ID |
| `bl video edit` | Edit a video with happyhorse-1.0-video-edit (style transfer, object replacement, etc.) |
| `bl video generate` | Generate a video from text or image (happyhorse-1.0-t2v / happyhorse-1.0-i2v / wan2.6-t2v) |
| `bl video ref` | Reference-to-video generation (happyhorse-1.0-r2v / wan2.6-r2v): multi-subject, multi-shot with voice |
| `bl video generate` | Generate a video from text or image (happyhorse-1.1-t2v / happyhorse-1.1-i2v / wan2.6-t2v) |
| `bl video ref` | Reference-to-video generation (happyhorse-1.1-r2v / wan2.6-r2v): multi-subject, multi-shot with voice |
| `bl video task get` | Query async task status |
## Command details
@@ -94,14 +94,14 @@ bl video edit --video https://example.com/input.mp4 --prompt "Put clothes on the
| Field | Value |
| --------------- | ------------------------------------------------------------------------------------------ |
| **Name** | `video generate` |
| **Description** | Generate a video from text or image (happyhorse-1.0-t2v / happyhorse-1.0-i2v / wan2.6-t2v) |
| **Description** | Generate a video from text or image (happyhorse-1.1-t2v / happyhorse-1.1-i2v / wan2.6-t2v) |
| **Usage** | `bl video generate --prompt <text> [--image <url>] [flags]` |
#### Options
| Flag | Type | Required | Description |
| --------------------------- | ------- | -------- | --------------------------------------------------------------------------------------- |
| `--model <model>` | string | no | Model ID (default: happyhorse-1.0-t2v, or happyhorse-1.0-i2v with --image) |
| `--model <model>` | string | no | Model ID (default: happyhorse-1.1-t2v, or happyhorse-1.1-i2v with --image) |
| `--prompt <text>` | string | yes | Video description |
| `--image <url>` | string | no | Input image URL for image-to-video generation |
| `--negative-prompt <text>` | string | no | Negative prompt to exclude unwanted content |
@@ -143,14 +143,14 @@ bl video generate --prompt "A cat playing with a ball" --watermark false
| Field | Value |
| --------------- | ----------------------------------------------------------------------------------------------------- |
| **Name** | `video ref` |
| **Description** | Reference-to-video generation (happyhorse-1.0-r2v / wan2.6-r2v): multi-subject, multi-shot with voice |
| **Description** | Reference-to-video generation (happyhorse-1.1-r2v / wan2.6-r2v): multi-subject, multi-shot with voice |
| **Usage** | `bl video ref --prompt <text> --image <url>... [--ref-video <url>...] [flags]` |
#### Options
| Flag | Type | Required | Description |
| --------------------------- | ------- | -------- | --------------------------------------------------------------------------------------- |
| `--model <model>` | string | no | Model ID (default: happyhorse-1.0-r2v) |
| `--model <model>` | string | no | Model ID (default: happyhorse-1.1-r2v) |
| `--prompt <text>` | string | yes | Video description with reference markers (image1, video1, etc.) |
| `--image <url>` | array | no | Reference image URL or local file (repeatable for multiple subjects) |
| `--ref-video <url>` | array | no | Reference video URL or local file (repeatable) |