Happy Horse 1.0 Text to Video is Alibaba's text-to-video model on Versely. This page is its structured prompting reference: the 4 parameters its schema actually exposes, the t2v technique that applies to it, copy-ready templates.
Everything here is grounded in the same sources Versely's agent reads — the model's input schema. Where a line is general craft advice rather than a documented fact about Happy Horse 1.0 Text to Video, the page says so.
What Happy Horse 1.0 Text to Video wants
The exact input surface, from the same schema the Versely agent fetches with get_model_input_schema before every generation.
| Parameter | What it does | Values |
|---|---|---|
promptreq | Text prompt (max 2500 chars) | string (max 2500) |
duration | Seconds (integer enum 3-15) | 3 · 4 · 5 · 6 · 7 · 8 · 9 · 10 · 11 · 12 · 13 · 14 · 15default: 5 |
aspect_ratio | Aspect ratio | 16:9 · 9:16 · 1:1 · 4:3 · 3:4default: 16:9 |
resolution | Resolution | 720p · 1080pdefault: 1080p |
- — Verified against fal OpenAPI — no negative_prompt field; resolution is 720p/1080p only
Technique that applies here
Text-to-video: scene narrative, camera movement, temporal flow; negative prompts where supported
- VEO, Kling, and Sora all carry a MODEL_TIPS rule the prompt enhancer applies automatically, and all three converge on naming the camera: VEO's tip says to 'include camera angles, movement types (dolly, crane, steadicam), lighting setup, and temporal flow' and to 'be specific about scene transitions'; Kling's tip asks for 'camera movement (pan, zoom, tracking shot), subject action, and environment details... motion direction and pacing'; Sora's tip wants 'clear scene narratives, camera movements, and temporal progression.' None of these schemas expose a camera-movement parameter — the enhancer is rewriting your prose toward this language, so writing the move by name yourself ('slow dolly-in,' 'tracking shot following the subject') works with the family instead of getting rewritten.
- Seedance and MiniMax want a different register from the camera-forward families. Seedance's tip is 'motion-focused descriptions... movement patterns, choreography, and dynamic visual elements'; MiniMax's is 'narrative prompts... scene progression, character actions, and visual atmosphere in natural language.' Neither asks for named camera hardware — lead with what's moving and how the scene unfolds, not with lens or shot vocabulary.
- Wan's tip is the shortest in the whole family list — 'straightforward scene descriptions and style keywords' — and the schema backs that up: Wan 2.7 Text to Video's own params are prompt, negative_prompt, an optional audio_url, resolution, duration and a prompt_extend toggle, with no camera or style-detail field to write toward. Don't over-engineer a Wan prompt with the dense camera-movement language that rewards Kling; a plain sentence plus a style word (e.g. 'cinematic') is the shape the tip is asking for.
Copy-ready templates
Replace the bracketed slots; each template says when it's the right shape.
[SUBJECT] [ACTION] in [SETTING]. Camera: [CAMERA MOVEMENT — e.g. slow dolly-in / handheld tracking shot / static locked-off]. Lighting: [LIGHT DESCRIPTION]. Transition: [HOW THE SHOT RESOLVES].
Use when: VEO, Kling, or Sora-family t2v models — their applied MODEL_TIPS reward named camera movement and explicit transitions.
[SUBJECT] moves through [ONE CONTINUOUS ACTION / CHOREOGRAPHY] while [SECONDARY VISUAL DETAIL] happens around them. Atmosphere: [MOOD / VISUAL ATMOSPHERE].
Use when: Seedance or MiniMax t2v models, whose tips ask for motion/choreography and narrative scene-progression language rather than named camera direction.
How the Versely agent does this automatically
You can use this page by hand, or let the agent apply the same knowledge. Four real mechanisms — no more, no less:
get_model_input_schema— before generating, the agent looks up Happy Horse 1.0 Text to Video's exact input fields, required fields, allowed values, defaults, and min/max bounds. The parameter table above is that same surface.- The prompt enhancer's family rules — 12 per-family rewrite rules (this model's family isn't one of the 12, so only general enhancement applies) shape how a rough prompt gets rewritten.
- The per-provider speech guide — for TTS scripts, the agent follows a provider-specific tag scheme — not relevant to this model, but it's why voiceover scripts come out marked up correctly.
expand_movie_scene— in movie flows, brief scene ideas are rewritten into detailed cinematic descriptions before generation.
Mistakes that waste generations
- Writing a multi-beat script (three different actions or cuts) into one generation call on a model capped well under 15s — VEO tops out at 8s per call, Sora 2's kie variant only offers 10 or 15 frames — and the model compresses everything into a blur or drops the later beats rather than pacing through your scenes.
- Describing aspect ratio or resolution in prose ('shot in glorious 4K widescreen') instead of setting the actual aspect_ratio/resolution enum — the text has no effect on frame shape or output resolution, only the parameter does, and on Sora 2 the valid values are the words 'portrait'/'landscape', not a ratio string at all.
- Using one family's register on another: a dense Kling-style shot list ('slow pan, then a hard cut to a tracking shot') fights a Wan model's 'straightforward... style keywords' tip, and a plain narrative sentence undersells VEO or Sora's named-camera-movement tip.
Frequently asked questions
How long can a Happy Horse 1.0 Text to Video prompt be?+
Happy Horse 1.0 Text to Video's schema caps the prompt at 2,500 characters. Spend them on the subject, motion, and the register its family rewards rather than restating parameters the schema already controls.
Does Happy Horse 1.0 Text to Video support negative prompts?+
No — Happy Horse 1.0 Text to Video's published schema has no negative_prompt parameter. Exclusions have to be phrased positively inside the main prompt, or dropped.
Which aspect ratios does Happy Horse 1.0 Text to Video support?+
The aspect_ratio parameter is an enum: 16:9, 9:16, 1:1, 4:3, 3:4. Set the parameter — describing the frame shape in prose does nothing on its own.
How long can a Happy Horse 1.0 Text to Video generation be?+
Duration is a hard enum: 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15. Write one continuous beat sized to the window you pick, not a script the model will compress.
How does the Versely agent know Happy Horse 1.0 Text to Video's parameters?+
Before generating, the agent calls its get_model_input_schema tool, which looks up the exact input fields, required fields, allowed values, defaults, and min/max bounds for the model. Nothing on this page is guessed — it is the same schema surface those tools read.
Related prompting guides
Generate with Happy Horse 1.0 Text to Video
Happy Horse 1.0 Text to Video is live in Versely — paste a template above, or just describe what you want and let the agent map it onto the schema for you.