apps/heygen/photo-video

photo-video

Animate portrait photos into talking videos using HeyGen. Upload a face image and add speech with configurable voice, motion prompts, and expressiveness.

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 heygen/photo-video

# run

$belt app run heygen/photo-video

api reference

about

animate portrait photos into talking videos using heygen. upload a face image and add speech with configurable voice, motion prompts, and expressiveness.

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": "heygen/photo-video",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": "heygen/photo-video",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": "heygen/photo-video",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": "heygen/photo-video",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

imagestring(file)*

portrait image to animate. should be a clear face photo.

scriptstring

text for the animated image to speak.

example: "Hi there! Thanks for checking out this demo."

voice_idstring

voice id for speech. required if script is provided.

audio_urlstring

url to an audio file for the avatar to lip-sync to. alternative to script+voice_id.

titlestring

title for the video.

resolutionstring

video resolution.

default: "1080p"

options:"720p""1080p""4k"

aspect_ratiostring

video aspect ratio.

default: "16:9"

options:"16:9""9:16"

expressivenessstring

expressiveness of the animated image.

default: "high"

options:"high""medium""low"

motion_promptstring

natural language description of desired motion (e.g., 'nodding slowly').

remove_backgroundboolean

remove the video background.

output_formatstring

output video format.

default: "mp4"

options:"mp4""webm"

output

videostring(file)*

the generated video from the photo.

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