HappyHorse-1.1-T2V is an Alibaba model for creating short video scenes from text. The prompt specifies characters, actions, surroundings and visual treatment; this mode does not require a source image. The model produces video and can generate accompanying audio.
The manufacturer highlights understanding of a scene's meaning, cinematic staging and expressive movement. Text can define the atmosphere, a character's actions, object behavior and physical dynamics. This makes it possible to build a scene around what should happen, then guide it through lighting, viewpoint and camera movement.
A prompt is required and may be in any language. It can contain up to 5000 non-Chinese or 2500 Chinese characters; any excess is truncated. The action, surroundings and important visual details need to be described within that limit. This approach leaves the model room to create a new scene rather than supplying it with a finished first frame.
In this mode, text is the main controlling input. The specific appearance of a character or object can be described in words; supplying separate images to establish that appearance belongs to another mode in the family. The result depends on the entire prompt, so the same random seed can help produce similar variations without guaranteeing an exact repeat.
For HappyHorse-1.1, video duration is selected as an integer from 3 to 15 seconds. Resolution levels of 480P, 720P and 1080P are supported. The finished file is MP4 at 24 frames per second. The model can generate audio alongside the visuals, connecting the soundtrack to what happens in the scene.
The frame shape can be specified in advance. Available ratios are 16:9, 9:16, 1:1, 4:3, 3:4, 4:5, 5:4, 9:21 and 21:9, ranging from a wide cinematic frame to an elongated portrait video. Resolution, format and duration determine the dimensions of the result; text defines its content and movement.
This variant is intended to create a new scene from a verbal concept. It is suited to a short episode, a visual idea or an atmospheric video whose staging needs to be expressed in text.
", "aboutText": "HappyHorse-1.1-T2V is an Alibaba model for creating short video scenes from text. The prompt specifies characters, actions, surroundings and visual treatment; this mode does not require a source image. The model produces video and can generate accompanying audio.\n\nThe manufacturer highlights understanding of a scene's meaning, cinematic staging and expressive movement. Text can define the atmosphere, a character's actions, object behavior and physical dynamics. This makes it possible to build a scene around what should happen, then guide it through lighting, viewpoint and camera movement.\n\n### Staging with words\n\nA prompt is required and may be in any language. It can contain up to 5000 non-Chinese or 2500 Chinese characters; any excess is truncated. The action, surroundings and important visual details need to be described within that limit. This approach leaves the model room to create a new scene rather than supplying it with a finished first frame.\n\nIn this mode, text is the main controlling input. The specific appearance of a character or object can be described in words; supplying separate images to establish that appearance belongs to another mode in the family. The result depends on the entire prompt, so the same random seed can help produce similar variations without guaranteeing an exact repeat.\n\n### Video and accompanying audio\n\nFor HappyHorse-1.1, video duration is selected as an integer from 3 to 15 seconds. Resolution levels of 480P, 720P and 1080P are supported. The finished file is MP4 at 24 frames per second. The model can generate audio alongside the visuals, connecting the soundtrack to what happens in the scene.\n\nThe frame shape can be specified in advance. Available ratios are 16:9, 9:16, 1:1, 4:3, 3:4, 4:5, 5:4, 9:21 and 21:9, ranging from a wide cinematic frame to an elongated portrait video. Resolution, format and duration determine the dimensions of the result; text defines its content and movement.\n\nThis variant is intended to create a new scene from a verbal concept. It is suited to a short episode, a visual idea or an atmospheric video whose staging needs to be expressed in text.", "editorialOverlay": { "copy_fields": null, "copy_sha256": null, "copy_source": null, "html_sha256": "5d78a51418db4fc5e8c048c1866009b8d1bc6d18598c398ed4cbc46b1f405433", "module_sha256": "ee9dc1c50b1e6a8fb7fa062030fcb4646b9aaaeb08be513b723a5a92a7290f06", "raw_model_unchanged": true, "schema": "ailoot-native-model-editorial-v1" }, "locale": "en", "methods": [ { "html": "happyhorse-1.1-t2vA model for creating short videos with audio from text descriptions. Suited to scenes whose movement, composition and visual style are specified in words.
This description covers the model’s capabilities. Available in Ailoot inputs, outputs and options are listed for the selected method below.
HappyHorse-1.1-T2V is an Alibaba model for creating short video scenes from text. The prompt specifies characters, actions, surroundings and visual treatment; this mode does not require a source image. The model produces video and can generate accompanying audio.
The manufacturer highlights understanding of a scene's meaning, cinematic staging and expressive movement. Text can define the atmosphere, a character's actions, object behavior and physical dynamics. This makes it possible to build a scene around what should happen, then guide it through lighting, viewpoint and camera movement.
A prompt is required and may be in any language. It can contain up to 5000 non-Chinese or 2500 Chinese characters; any excess is truncated. The action, surroundings and important visual details need to be described within that limit. This approach leaves the model room to create a new scene rather than supplying it with a finished first frame.
In this mode, text is the main controlling input. The specific appearance of a character or object can be described in words; supplying separate images to establish that appearance belongs to another mode in the family. The result depends on the entire prompt, so the same random seed can help produce similar variations without guaranteeing an exact repeat.
For HappyHorse-1.1, video duration is selected as an integer from 3 to 15 seconds. Resolution levels of 480P, 720P and 1080P are supported. The finished file is MP4 at 24 frames per second. The model can generate audio alongside the visuals, connecting the soundtrack to what happens in the scene.
The frame shape can be specified in advance. Available ratios are 16:9, 9:16, 1:1, 4:3, 3:4, 4:5, 5:4, 9:21 and 21:9, ranging from a wide cinematic frame to an elongated portrait video. Resolution, format and duration determine the dimensions of the result; text defines its content and movement.
This variant is intended to create a new scene from a verbal concept. It is suited to a short episode, a visual idea or an atmospheric video whose staging needs to be expressed in text.
POST /v1/videos/generationstextvideo| Field | Type | Requirement | Values & limits | Default |
|---|---|---|---|---|
Fieldmodel | Typestring | RequirementRequired | Values & limits happyhorse-1.1-t2v | Default— |
Fieldprompt | Typestring | RequirementRequired | Values & limits Minimum length: 1 | Default— |
Fieldduration | Typeinteger | RequirementOptional | Values & limits Minimum: 3 Maximum: 15 Unit: seconds | Default5 |
Fieldresolution | Typestring | RequirementOptional | Values & limits 480P, 720P, 1080P | Default720P |
Fieldratio | Typestring | RequirementOptional | Values & limits 16:9, 9:16, 1:1, 4:3, 3:4, 4:5, 5:4, 9:21, 21:9 | Default16:9 |
Fieldimage_urls | Typehttps_url|data_image_url[] | RequirementOptional | Values & limits Minimum items: 0 Maximum items: 0 Maximum decoded bytes: 20,971,520 MIME types: image/jpeg, image/png, image/webp | Default— |
Text to video · Required: prompt
| Parameter | Contract |
|---|---|
Parametercontent_type | Contractapplication/json |
Parameterrequired | Contractmodel, prompt |
Parametermaterial_types | Contracttext |
Parameteroptional | Contractduration, resolution, ratio |
Parameterduration_integer_range | Contract3, 15 |
Parameterdefault_duration | Contract5 |
Parameterresolution | Contract480P, 720P, 1080P |
Parameterdefault_resolution | Contract720P |
Parameterratio | Contract16:9, 9:16, 1:1, 4:3, 3:4, 4:5, 5:4, 9:21, 21:9 |
Parameterratio_must_omit | Contractfalse |
Parameterimage_urls | Contract{"max_count":0} |
Lifecycle: submit_once_poll_original
GET /v1/videos/{request_id}
GET /v1/videos/generations/{request_id}
GET /v1/videos/{request_id}/content
GET /v1/videos/generations/{request_id}/content
Method shapes and IDs are exact; supplier capability is separate from admission.
POST /v1/videos/generationsAiloot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. How reservation and settlement work →
set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_PROMPT_FILE:?Set your actual UTF-8 scene brief}"\nexport AILOOT_PROMPT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"model": "happyhorse-1.1-t2v", "prompt": "", "duration": 5, "resolution": "720P", "ratio": "16:9"}')\nf=Path(os.environ["AILOOT_PROMPT_FILE"])\nif not f.is_file():raise SystemExit("Choose your actual UTF-8 brief")\np['prompt']=f.read_text(encoding="utf-8")\nif not p['prompt'].strip():raise SystemExit("Brief must contain text")\nPath("request.json").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/videos/generations \\\n -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path("result.json").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\nmp4
GET /v1/videos/{request_id}GET /v1/videos/generations/{request_id}GET /v1/videos/{request_id}/contentGET /v1/videos/generations/{request_id}/contentset -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_OPERATION_ID:?Set the actual Ailoot operation ID returned by creation}"\nexport AILOOT_OPERATION_ID\noperation_id=$(python3 -c 'import os,urllib.parse;print(urllib.parse.quote(os.environ["AILOOT_OPERATION_ID"],safe=""))')\ncurl --fail-with-body --silent --show-error "https://api.ailoot.ai/v1/videos/generations/$operation_id" \\\n -H "Authorization: Bearer $AILOOT_API_KEY" -o status.json\npython3 - <<'PY_STATUS'\nimport json\nfrom pathlib import Path\nr=json.loads(Path("status.json").read_text())\nprint(json.dumps(r))\nif r.get("status")=="completed":\n for x in r.get("data",[]):print(x)\nPY_STATUS\nset -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_STATUS_FILE:?Set the actual completed status JSON file}"\nexport AILOOT_STATUS_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\nfrom urllib.parse import urlsplit,urljoin\nf=Path(os.environ["AILOOT_STATUS_FILE"])\nif not f.is_file():raise SystemExit("Choose the actual completed status file")\nr=json.loads(f.read_text())\nif r.get("status")!="completed" or not isinstance(r.get("data"),list) or not r["data"]:raise SystemExit("Wait for a completed status with asset paths")\nurls=[]\nfor x in r["data"]:\n if not isinstance(x,str) or "\\n" in x or "\\r" in x:raise SystemExit("Invalid asset path")\n u=urljoin("https://api.ailoot.ai",x)\n z=urlsplit(u)\n if z.scheme!="https" or z.netloc!="api.ailoot.ai" or z.username or z.password:raise SystemExit("Use the actual Ailoot asset paths from status")\n urls.append(u)\nPath("asset-urls.txt").write_text("\\n".join(urls)+"\\n")\nPY_REQUEST\nindex=0\nwhile IFS= read -r asset_url; do\n curl --fail-with-body --silent --show-error "$asset_url" \\\n -H "Authorization: Bearer $AILOOT_API_KEY" -o "video-${index}.mp4"\n index=$((index + 1))\ndone < asset-urls.txt\nset -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_OPERATION_ID:?Set the actual Ailoot operation ID returned by creation}"\nexport AILOOT_OPERATION_ID\noperation_id=$(python3 -c 'import os,urllib.parse;print(urllib.parse.quote(os.environ["AILOOT_OPERATION_ID"],safe=""))')\ncurl --fail-with-body --silent --show-error "https://api.ailoot.ai/v1/videos/generations/$operation_id/content" \\\n -H "Authorization: Bearer $AILOOT_API_KEY" -o video.mp4\nSave every completed video or returned file; retrieve every actual returned asset URL.
Preserve every returned data item/output index. content_url is first only; fetch every actual content path/asset. GETcontentwithoutindex isnotalloutputs.
Read existing original job; never resubmit unknown send.
| Field | Type |
|---|---|
Fieldid | Typestring |
Fieldobject | Typestring |
Fieldmodel | Typestring |
Fieldstatus | Typestring |
Fieldcontent_url | Typesigned URL |
Fielddata[] | Typesigned URL |
Fieldusage | Typeobject |
Fieldresult_pending_check | Typeboolean |
| Response | Condition | Next step |
|---|---|---|
Response400 · invalid_request_error | ConditionInvalid required fields, material representation or parameter value | Next stepCorrect the indicated fields before a new creation request. |
Response409 · video_not_ready | ConditionOriginal result content is not yet available | Next stepPoll the original returned ID and respect Retry-After. |
Responseserver_error | ConditionThe returned response says the operation or result requires a check | Next stepKeep the original returned operation/task ID, request headers and response; continue supported reads of that original operation. Do not resubmit the creation request. |
Ailoot happyhorse-1.1-t2v, happyhorse-t2v, happyhorse-t2v-latest
Use the method paths shown above.
happyhorse-t2vA model for creating short videos with audio from text descriptions. Suited to scenes whose movement, composition and visual style are specified in words.
This description covers the model’s capabilities. Available in Ailoot inputs, outputs and options are listed for the selected method below.
HappyHorse-1.1-T2V is an Alibaba model for creating short video scenes from text. The prompt specifies characters, actions, surroundings and visual treatment; this mode does not require a source image. The model produces video and can generate accompanying audio.
The manufacturer highlights understanding of a scene's meaning, cinematic staging and expressive movement. Text can define the atmosphere, a character's actions, object behavior and physical dynamics. This makes it possible to build a scene around what should happen, then guide it through lighting, viewpoint and camera movement.
A prompt is required and may be in any language. It can contain up to 5000 non-Chinese or 2500 Chinese characters; any excess is truncated. The action, surroundings and important visual details need to be described within that limit. This approach leaves the model room to create a new scene rather than supplying it with a finished first frame.
In this mode, text is the main controlling input. The specific appearance of a character or object can be described in words; supplying separate images to establish that appearance belongs to another mode in the family. The result depends on the entire prompt, so the same random seed can help produce similar variations without guaranteeing an exact repeat.
For HappyHorse-1.1, video duration is selected as an integer from 3 to 15 seconds. Resolution levels of 480P, 720P and 1080P are supported. The finished file is MP4 at 24 frames per second. The model can generate audio alongside the visuals, connecting the soundtrack to what happens in the scene.
The frame shape can be specified in advance. Available ratios are 16:9, 9:16, 1:1, 4:3, 3:4, 4:5, 5:4, 9:21 and 21:9, ranging from a wide cinematic frame to an elongated portrait video. Resolution, format and duration determine the dimensions of the result; text defines its content and movement.
This variant is intended to create a new scene from a verbal concept. It is suited to a short episode, a visual idea or an atmospheric video whose staging needs to be expressed in text.
POST /v1/videos/generationstextvideo| Field | Type | Requirement | Values & limits | Default |
|---|---|---|---|---|
Fieldmodel | Typestring | RequirementRequired | Values & limits happyhorse-t2v | Default— |
Fieldprompt | Typestring | RequirementRequired | Values & limits Minimum length: 1 | Default— |
Fieldduration | Typeinteger | RequirementOptional | Values & limits Minimum: 3 Maximum: 15 Unit: seconds | Default5 |
Fieldresolution | Typestring | RequirementOptional | Values & limits 480P, 720P, 1080P | Default720P |
Fieldratio | Typestring | RequirementOptional | Values & limits 16:9, 9:16, 1:1, 4:3, 3:4, 4:5, 5:4, 9:21, 21:9 | Default16:9 |
Fieldimage_urls | Typehttps_url|data_image_url[] | RequirementOptional | Values & limits Minimum items: 0 Maximum items: 0 Maximum decoded bytes: 20,971,520 MIME types: image/jpeg, image/png, image/webp | Default— |
Text to video · Required: prompt
| Parameter | Contract |
|---|---|
Parametermaterial_types | Contracttext |
Parameterrequired | Contractnull |
Parameteroptional_controls | Contractnull |
Lifecycle: submit_once_poll_original
GET /v1/videos/{request_id}
GET /v1/videos/generations/{request_id}
GET /v1/videos/{request_id}/content
GET /v1/videos/generations/{request_id}/content
Method shapes and IDs are exact; supplier capability is separate from admission.
POST /v1/videos/generationsAiloot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. How reservation and settlement work →
set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_PROMPT_FILE:?Set your actual UTF-8 scene brief}"\nexport AILOOT_PROMPT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"model": "happyhorse-t2v", "prompt": "", "duration": 5, "resolution": "720P", "ratio": "16:9"}')\nf=Path(os.environ["AILOOT_PROMPT_FILE"])\nif not f.is_file():raise SystemExit("Choose your actual UTF-8 brief")\np['prompt']=f.read_text(encoding="utf-8")\nif not p['prompt'].strip():raise SystemExit("Brief must contain text")\nPath("request.json").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/videos/generations \\\n -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path("result.json").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\nmp4
GET /v1/videos/{request_id}GET /v1/videos/generations/{request_id}GET /v1/videos/{request_id}/contentGET /v1/videos/generations/{request_id}/contentset -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_OPERATION_ID:?Set the actual Ailoot operation ID returned by creation}"\nexport AILOOT_OPERATION_ID\noperation_id=$(python3 -c 'import os,urllib.parse;print(urllib.parse.quote(os.environ["AILOOT_OPERATION_ID"],safe=""))')\ncurl --fail-with-body --silent --show-error "https://api.ailoot.ai/v1/videos/generations/$operation_id" \\\n -H "Authorization: Bearer $AILOOT_API_KEY" -o status.json\npython3 - <<'PY_STATUS'\nimport json\nfrom pathlib import Path\nr=json.loads(Path("status.json").read_text())\nprint(json.dumps(r))\nif r.get("status")=="completed":\n for x in r.get("data",[]):print(x)\nPY_STATUS\nset -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_STATUS_FILE:?Set the actual completed status JSON file}"\nexport AILOOT_STATUS_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\nfrom urllib.parse import urlsplit,urljoin\nf=Path(os.environ["AILOOT_STATUS_FILE"])\nif not f.is_file():raise SystemExit("Choose the actual completed status file")\nr=json.loads(f.read_text())\nif r.get("status")!="completed" or not isinstance(r.get("data"),list) or not r["data"]:raise SystemExit("Wait for a completed status with asset paths")\nurls=[]\nfor x in r["data"]:\n if not isinstance(x,str) or "\\n" in x or "\\r" in x:raise SystemExit("Invalid asset path")\n u=urljoin("https://api.ailoot.ai",x)\n z=urlsplit(u)\n if z.scheme!="https" or z.netloc!="api.ailoot.ai" or z.username or z.password:raise SystemExit("Use the actual Ailoot asset paths from status")\n urls.append(u)\nPath("asset-urls.txt").write_text("\\n".join(urls)+"\\n")\nPY_REQUEST\nindex=0\nwhile IFS= read -r asset_url; do\n curl --fail-with-body --silent --show-error "$asset_url" \\\n -H "Authorization: Bearer $AILOOT_API_KEY" -o "video-${index}.mp4"\n index=$((index + 1))\ndone < asset-urls.txt\nset -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_OPERATION_ID:?Set the actual Ailoot operation ID returned by creation}"\nexport AILOOT_OPERATION_ID\noperation_id=$(python3 -c 'import os,urllib.parse;print(urllib.parse.quote(os.environ["AILOOT_OPERATION_ID"],safe=""))')\ncurl --fail-with-body --silent --show-error "https://api.ailoot.ai/v1/videos/generations/$operation_id/content" \\\n -H "Authorization: Bearer $AILOOT_API_KEY" -o video.mp4\nSave every completed video or returned file; retrieve every actual returned asset URL.
Preserve every returned data item/output index. content_url is first only; fetch every actual content path/asset. GETcontentwithoutindex isnotalloutputs.
Read existing original job; never resubmit unknown send.
| Field | Type |
|---|---|
Fieldid | Typestring |
Fieldobject | Typestring |
Fieldmodel | Typestring |
Fieldstatus | Typestring |
Fieldcontent_url | Typesigned URL |
Fielddata[] | Typesigned URL |
Fieldusage | Typeobject |
Fieldresult_pending_check | Typeboolean |
| Response | Condition | Next step |
|---|---|---|
Response400 · invalid_request_error | ConditionInvalid required fields, material representation or parameter value | Next stepCorrect the indicated fields before a new creation request. |
Response409 · video_not_ready | ConditionOriginal result content is not yet available | Next stepPoll the original returned ID and respect Retry-After. |
Responseserver_error | ConditionThe returned response says the operation or result requires a check | Next stepKeep the original returned operation/task ID, request headers and response; continue supported reads of that original operation. Do not resubmit the creation request. |
Ailoot happyhorse-1.1-t2v, happyhorse-t2v, happyhorse-t2v-latest
Use the method paths shown above.
happyhorse-t2v-latestA model for creating short videos with audio from text descriptions. Suited to scenes whose movement, composition and visual style are specified in words.
This description covers the model’s capabilities. Available in Ailoot inputs, outputs and options are listed for the selected method below.
HappyHorse-1.1-T2V is an Alibaba model for creating short video scenes from text. The prompt specifies characters, actions, surroundings and visual treatment; this mode does not require a source image. The model produces video and can generate accompanying audio.
The manufacturer highlights understanding of a scene's meaning, cinematic staging and expressive movement. Text can define the atmosphere, a character's actions, object behavior and physical dynamics. This makes it possible to build a scene around what should happen, then guide it through lighting, viewpoint and camera movement.
A prompt is required and may be in any language. It can contain up to 5000 non-Chinese or 2500 Chinese characters; any excess is truncated. The action, surroundings and important visual details need to be described within that limit. This approach leaves the model room to create a new scene rather than supplying it with a finished first frame.
In this mode, text is the main controlling input. The specific appearance of a character or object can be described in words; supplying separate images to establish that appearance belongs to another mode in the family. The result depends on the entire prompt, so the same random seed can help produce similar variations without guaranteeing an exact repeat.
For HappyHorse-1.1, video duration is selected as an integer from 3 to 15 seconds. Resolution levels of 480P, 720P and 1080P are supported. The finished file is MP4 at 24 frames per second. The model can generate audio alongside the visuals, connecting the soundtrack to what happens in the scene.
The frame shape can be specified in advance. Available ratios are 16:9, 9:16, 1:1, 4:3, 3:4, 4:5, 5:4, 9:21 and 21:9, ranging from a wide cinematic frame to an elongated portrait video. Resolution, format and duration determine the dimensions of the result; text defines its content and movement.
This variant is intended to create a new scene from a verbal concept. It is suited to a short episode, a visual idea or an atmospheric video whose staging needs to be expressed in text.
POST /v1/videos/generationstextvideo| Field | Type | Requirement | Values & limits | Default |
|---|---|---|---|---|
Fieldmodel | Typestring | RequirementRequired | Values & limits happyhorse-t2v-latest | Default— |
Fieldprompt | Typestring | RequirementRequired | Values & limits Minimum length: 1 | Default— |
Fieldduration | Typeinteger | RequirementOptional | Values & limits Minimum: 3 Maximum: 15 Unit: seconds | Default5 |
Fieldresolution | Typestring | RequirementOptional | Values & limits 480P, 720P, 1080P | Default720P |
Fieldratio | Typestring | RequirementOptional | Values & limits 16:9, 9:16, 1:1, 4:3, 3:4, 4:5, 5:4, 9:21, 21:9 | Default16:9 |
Fieldimage_urls | Typehttps_url|data_image_url[] | RequirementOptional | Values & limits Minimum items: 0 Maximum items: 0 Maximum decoded bytes: 20,971,520 MIME types: image/jpeg, image/png, image/webp | Default— |
Text to video · Required: prompt
| Parameter | Contract |
|---|---|
Parametermaterial_types | Contracttext |
Parameterrequired | Contractnull |
Parameteroptional_controls | Contractnull |
Lifecycle: submit_once_poll_original
GET /v1/videos/{request_id}
GET /v1/videos/generations/{request_id}
GET /v1/videos/{request_id}/content
GET /v1/videos/generations/{request_id}/content
Method shapes and IDs are exact; supplier capability is separate from admission.
POST /v1/videos/generationsAiloot reserves an estimated amount before a request. After the result, it settles the final charge from measured usage. Streaming settlement uses the final usage record. How reservation and settlement work →
set -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_PROMPT_FILE:?Set your actual UTF-8 scene brief}"\nexport AILOOT_PROMPT_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{"model": "happyhorse-t2v-latest", "prompt": "", "duration": 5, "resolution": "720P", "ratio": "16:9"}')\nf=Path(os.environ["AILOOT_PROMPT_FILE"])\nif not f.is_file():raise SystemExit("Choose your actual UTF-8 brief")\np['prompt']=f.read_text(encoding="utf-8")\nif not p['prompt'].strip():raise SystemExit("Brief must contain text")\nPath("request.json").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/videos/generations \\\n -H "Authorization: Bearer $AILOOT_API_KEY" -H 'Content-Type: application/json' \\\n --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nprint(json.dumps(json.loads(Path("result.json").read_text()),ensure_ascii=False,indent=2))\nPY_RESULT\nmp4
GET /v1/videos/{request_id}GET /v1/videos/generations/{request_id}GET /v1/videos/{request_id}/contentGET /v1/videos/generations/{request_id}/contentset -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_OPERATION_ID:?Set the actual Ailoot operation ID returned by creation}"\nexport AILOOT_OPERATION_ID\noperation_id=$(python3 -c 'import os,urllib.parse;print(urllib.parse.quote(os.environ["AILOOT_OPERATION_ID"],safe=""))')\ncurl --fail-with-body --silent --show-error "https://api.ailoot.ai/v1/videos/generations/$operation_id" \\\n -H "Authorization: Bearer $AILOOT_API_KEY" -o status.json\npython3 - <<'PY_STATUS'\nimport json\nfrom pathlib import Path\nr=json.loads(Path("status.json").read_text())\nprint(json.dumps(r))\nif r.get("status")=="completed":\n for x in r.get("data",[]):print(x)\nPY_STATUS\nset -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_STATUS_FILE:?Set the actual completed status JSON file}"\nexport AILOOT_STATUS_FILE\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\nfrom urllib.parse import urlsplit,urljoin\nf=Path(os.environ["AILOOT_STATUS_FILE"])\nif not f.is_file():raise SystemExit("Choose the actual completed status file")\nr=json.loads(f.read_text())\nif r.get("status")!="completed" or not isinstance(r.get("data"),list) or not r["data"]:raise SystemExit("Wait for a completed status with asset paths")\nurls=[]\nfor x in r["data"]:\n if not isinstance(x,str) or "\\n" in x or "\\r" in x:raise SystemExit("Invalid asset path")\n u=urljoin("https://api.ailoot.ai",x)\n z=urlsplit(u)\n if z.scheme!="https" or z.netloc!="api.ailoot.ai" or z.username or z.password:raise SystemExit("Use the actual Ailoot asset paths from status")\n urls.append(u)\nPath("asset-urls.txt").write_text("\\n".join(urls)+"\\n")\nPY_REQUEST\nindex=0\nwhile IFS= read -r asset_url; do\n curl --fail-with-body --silent --show-error "$asset_url" \\\n -H "Authorization: Bearer $AILOOT_API_KEY" -o "video-${index}.mp4"\n index=$((index + 1))\ndone < asset-urls.txt\nset -eu\n: "${AILOOT_API_KEY:?Set your Ailoot API key}"\n: "${AILOOT_OPERATION_ID:?Set the actual Ailoot operation ID returned by creation}"\nexport AILOOT_OPERATION_ID\noperation_id=$(python3 -c 'import os,urllib.parse;print(urllib.parse.quote(os.environ["AILOOT_OPERATION_ID"],safe=""))')\ncurl --fail-with-body --silent --show-error "https://api.ailoot.ai/v1/videos/generations/$operation_id/content" \\\n -H "Authorization: Bearer $AILOOT_API_KEY" -o video.mp4\nSave every completed video or returned file; retrieve every actual returned asset URL.
Preserve every returned data item/output index. content_url is first only; fetch every actual content path/asset. GETcontentwithoutindex isnotalloutputs.
Read existing original job; never resubmit unknown send.
| Field | Type |
|---|---|
Fieldid | Typestring |
Fieldobject | Typestring |
Fieldmodel | Typestring |
Fieldstatus | Typestring |
Fieldcontent_url | Typesigned URL |
Fielddata[] | Typesigned URL |
Fieldusage | Typeobject |
Fieldresult_pending_check | Typeboolean |
| Response | Condition | Next step |
|---|---|---|
Response400 · invalid_request_error | ConditionInvalid required fields, material representation or parameter value | Next stepCorrect the indicated fields before a new creation request. |
Response409 · video_not_ready | ConditionOriginal result content is not yet available | Next stepPoll the original returned ID and respect Retry-After. |
Responseserver_error | ConditionThe returned response says the operation or result requires a check | Next stepKeep the original returned operation/task ID, request headers and response; continue supported reads of that original operation. Do not resubmit the creation request. |
Ailoot happyhorse-1.1-t2v, happyhorse-t2v, happyhorse-t2v-latest
Use the method paths shown above.