Inference Logoinference.sh
apps/infsh/magi-1

magi-1

Generates high-quality videos from text descriptions, ensuring smooth, consistent motion across the video, and supports real-time streaming.

run in browser run via API
run with your agent
# install belt
$curl -fsSL https://cli.inference.sh | sh
# view schema & details
$belt app get infsh/magi-1
# run
$belt app run infsh/magi-1

api reference

about

generates high-quality videos from text descriptions, ensuring smooth, consistent motion across the video, and supports real-time streaming.

1. calling the api

install the client

the client provides a convenient way to interact with the api.

bash
1pip install inferencesh

setup your api key

set INFERENCE_API_KEY as an environment variable. get your key from settings → api keys.

bash
1export INFERENCE_API_KEY="inf_your_key"

run and get result

submit a request and wait for the final result. best for batch processing or when you don't need progress updates.

python
1from inferencesh import inference23client = inference()456result = client.run({7        "app": "infsh/magi-1",8        "input": {}9    })1011print(result["output"])

stream live updates

get real-time progress updates as the task runs. ideal for showing progress bars, partial results, or long-running tasks.

python
1from inferencesh import inference23client = inference()456# stream=True yields updates as they arrive7for update in client.run({8        "app": "infsh/magi-1",9        "input": {}10    }, stream=True):11    if update.get("progress"):12        print(f"progress: {update['progress']}%")13    if update.get("output"):14        print(f"output: {update['output']}")

2. authentication

the api uses api keys for authentication. see the authentication docs for detailed setup instructions.

3. files

file inputs are automatically handled by the sdk. you can pass local paths, urls, or base64 data.

automatic upload

the python sdk automatically detects local file paths and uploads them. urls are passed through as-is.

python
1# local file paths are automatically uploaded2result = client.run({3    "app": "infsh/magi-1",4    "input": {5        "image": "/path/to/local/image.png",  # detected & uploaded6        "audio": "https://example.com/audio.mp3",  # url passed through7    }8})

manual upload

you can also upload files manually and use the returned url.

python
1# upload and get a hosted URL2file = client.files.upload("/path/to/file.png")3print(file.uri)  # https://cloud.inference.sh/...

4. webhooks

get notified when a task completes by providing a webhook url. when the task reaches a terminal state (completed, failed, or cancelled), a POST request is sent to your url with the task result.

python
1result = client.run({2    "app": "infsh/magi-1",3    "input": {},4    "webhook": "https://your-server.com/webhook"5}, wait=False)

webhook payload

your endpoint receives a JSON POST with the task result:

json
1{2  "id": "task_abc123",3  "status": 9,4  "output": { ... },5  "error": "",6  "session_id": null,7  "created_at": "2024-01-15T10:30:00Z",8  "updated_at": "2024-01-15T10:30:05Z"9}
idstring— task id
statusnumber— terminal status (9=completed, 10=failed, 11=cancelled)
outputobject— task output (when completed)
errorstring— error message (when failed)
session_idstring— session id (if using sessions)
created_atstring— iso timestamp
updated_atstring— iso timestamp

5. schema

input

modestring*

the mode of the pipeline

options:"t2v""i2v""v2v"
promptstring*

the prompt for the pipeline. used for all modes.

imagestring(file)

for i2v mode, the source image path

prefix_videostring(file)

for v2v mode, the source video path

seedinteger

random seed. -1 means random.

default: -1
num_framesinteger

number of frames in the output video.

default: 96
num_stepsinteger

number of inference steps.

default: 8
window_sizeinteger

window size for inference.

default: 4
fpsinteger

frames per second.

default: 24
chunk_widthinteger

chunk width for inference.

default: 6
widthinteger

width of the output video. must be multiple of 8.

default: 1280
heightinteger

height of the output video. must be multiple of 8.

default: 720

output

videostring(file)*

video

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