happyhorse-1.0-r2v
happyhorse-1.0-r2v is available through TTAPI. Text- and image-to-video generation with clear per-second billing.
Same input, two HappyHorse generations
Classroom momentum chain

【Core Logic: Cause & Effect Chain】 1. Initiation: Protagonist (Female Student) is cornered. Opponent 1 lunges with a right punch. 2. Reaction & Momentum: Protagonist does NOT just dodge; she uses the opponent's momentum. She sidesteps left, grabbing Opponent 1's wrist to pull him off-balance. Her body rotates with the pull, using centrifugal force. 3. Environmental Interaction: As she spins, her foot kicks a loose chair leg. The chair slides across the floor (friction visible), tripping Opponent 2 who was rushing in. 4. Flow Transition: The spin continues. She releases Opponent 1, who crashes into a desk (wood splinters, papers fly). Her momentum carries her forward over the desk surface (parkour vault). 5. Landing & Reset: She lands on the other side of the desk in a crouch, absorbing impact. Opponent 3 hesitates. She rises smoothly, ready for the next engagement. Note: Every movement must have a clear physical cause. No floating, no sudden stops without deceleration. 【Visual Style & Camera Sync】Style: Gritty Realism, High-Budget Action Cinema. Natural light, dust motes, sweat, worn textures. Camera: "Physical Participant" perspective. ● When she pulls Opponent 1, camera whips LEFT to follow the rotation. ● When the chair slides, camera tilts DOWN to track the obstacle. ● When she vaults, camera BOOMS UP rapidly to match her vertical leap. ● Handheld shake matches the intensity of impacts. ● Foreground obstruction: Desks and arms frequently block the lens briefly to enhance depth and chaos. 【Character & Environment Details】Protagonist: Agile, wearing standard Japanese high school uniform (blazer/skirt or tracksuit), hair tied back but loosening. Movements are grounded, feet always interacting with floor friction. Opponents: Three aggressive males, reacting realistically to pain and balance loss (stumbling, flailing arms). Environment: Cluttered classroom. Desks are heavy (don't fly like cardboard). Papers swirl in turbulent air currents caused by movement. Sunlight creates dynamic shadows that move with the characters. 【Negative Prompts - Logic Specific】No teleporting, no instant direction changes without weight shift, no floating limbs, no enemies standing still after being hit, no magical effects, no slow-motion unless specified, no static background, no repetitive loops, no distorted anatomy during rapid motion, no clipping through objects.
Princess and dragon-man dialogue


The princess [Image 2] was imprisoned in bedroom and be threatened by the dragon man [Image 1]. They had a long dialogue.
Livestream apparel demo




A female livestream host sells products from home [Image 4], using the livestream shopping scene as reference [Image 1]. The host speaks in an excited and energetic tone, holding up the pants from [Image 3] with her left hand. [0-4s] “Okay, be honest... how many sweatpants do you own that actually make you feel put-together?” After this line, the camera pushes in to a close-up of her fingers stretching the fabric, with a hook-like questioning tone. [5-9s] Cut to the host at home [Image 4], already changed into the outfit shown in [Image 2]. The camera pulls back to a half-body shot as she touches the fabric around her waist to demonstrate the material, speaking in an expressive tone. Line: “This isn't just loungewear. It's butter-soft ribbed knit, four-way stretch, high-waisted, stays put, and never rolls down.” [10-12s] Full-body shot showing the fit. Line: “Watch this. From a grocery run to a coffee date.” [12-15s] With a confident tone: “Link in bio. Grab yours before it sells out again.”
Neon apartment dialogue



A modern minimalist living room at dusk, with a blurred city night view and neon bokeh outside the floor-to-ceiling window. In front of a dark gray fabric sofa is a low wooden coffee table with two glasses of water, a phone placed screen-down, and an open magazine. The woman from [Image 1], [Image 3], gently pushes a glass of water with her fingertips and says softly, “That day, when you told me to wait until the wind stopped, I believed you.” Cut to a close-up of the man from [Image 2]. His gaze darkens slightly: “I was the one who let go first.” The woman raises her eyes and looks straight ahead, her tone softening: “So you even skipped the apology?” The two never make eye contact. The camera pushes in to an over-the-shoulder side profile of Lin Wan. The corner of her mouth lifts slightly, but the smile never reaches her eyes: “Leave? You taught me how to leave, but never gave me the address of the door.” The woman walks to the floor-to-ceiling window, while the man remains seated on the sofa, head lowered in silence. The cool blue neon outside blends naturally with the warm interior light. The scene maintains cinematic shallow depth of field and subtle film grain in a 16:9 frame, with lip sync aligned to dialogue, restrained pacing, and a realistic short-drama look.
Cowboys at the bar


Two cowboys, [Image 1] and [Image 2], are drinking in a bar and talking about their future. The two have an extended dialogue.
What you can build with happyhorse-1.0-r2v
Prompt driven generation
Submit a concise prompt and get production-ready video output through one TTAPI job.
Core controls only
Keep integration simple with prompt, model, output settings, and callback handling.
Async result flow
Use polling or webhook callbacks so long-running generations do not block your UI.
Ready for product UI
Return HappyHorse results that can be displayed, stored, or passed into downstream workflows.
Per-action, in quota
Usage is metered in quota by model, action, and output settings.
Headers and submit parameters
Use the endpoint below with your TTAPI key and the request fields shown.
/happyhorse/api/v1/services/aigc/video-generation/reference-to-videoSubmit a HappyHorse R2V task.
Official reference/happyhorse/api/v1/tasks/{task_id}Retrieve a HappyHorse task result.
Official referenceHeaders
TT-API-KEYstringrequiredYour TTAPI API key.
Content-TypestringrequiredUse application/json.
Body
modelstringrequiredHappyHorse task model such as happyhorse-1.1-t2v.
input.promptstringconditionalText prompt for generation or editing.
input.mediaobject[]conditionalFirst-frame image, reference images, or source video for the selected workflow.
parameters.resolutionenumoptional720P or 1080P output.
parameters.durationintegeroptionalClip duration in seconds.
parameters.ratioenumoptionalOutput aspect ratio for supported workflows.
parameters.watermarkbooleanoptionalWhether to include the HappyHorse watermark.
parameters.seedintegeroptionalRandom seed from 0 to 2147483647.
From key to first result
Copy the resolved endpoint, authentication headers, and request body for this model.
curl --request POST \
--url https://api.ttapi.io/happyhorse/api/v1/services/aigc/video-generation/reference-to-video \
--header 'TT-API-KEY: $TTAPI_KEY' \
--header 'Content-Type: application/json' \
--data '{"model":"happyhorse-1.0-r2v","input":{"prompt":"slow dolly shot through a lantern-lit alley","media":[{"type":"reference_image","url":"https://example.com/reference.jpg"}]},"parameters":{"resolution":"720P","duration":5,"watermark":false}}'