Higgs Audio
Generates speech from text with advanced, expressive audio quality.
api reference
about
generates speech from text with advanced, expressive audio quality.
1. calling the api
install the client
the client provides a convenient way to interact with the api.
1pip install inferenceshsetup your api key
set INFERENCE_API_KEY as an environment variable. get your key from settings → api keys.
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.
1import os2from inferencesh import inference34client = inference(api_key=os.environ["INFERENCE_API_KEY"])567result = client.run({8 "app": "infsh/higgs-audio",9 "input": {10 "transcript": "transcript"11 }12 })1314print(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.
1import os2from inferencesh import inference34client = inference(api_key=os.environ["INFERENCE_API_KEY"])567# stream=True yields updates as they arrive8for update in client.run({9 "app": "infsh/higgs-audio",10 "input": {11 "transcript": "transcript"12 }13 }, stream=True):14 if update.get("progress"):15 print(f"progress: {update['progress']}%")16 if update.get("output"):17 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.
1# local file paths are automatically uploaded2result = client.run({3 "app": "infsh/higgs-audio",4 "input": {5 "image": "/path/to/local/image.png", # detected & uploaded6 "audio": "https://example.com/audio.mp3", # url passed through7 }8})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.
1result = client.run({2 "app": "infsh/higgs-audio",3 "input": {4 "transcript": "transcript"5 },6 "webhook": "https://your-server.com/webhook"7}, wait=False)webhook payload
your endpoint receives a JSON POST with the task result:
1{2 "event": "task.completed",3 "timestamp": "2024-01-15T10:30:05Z",4 "data": {5 "id": "task_abc123",6 "short_id": "abc123",7 "status": 10,8 "status_text": "completed",9 "output": { ... },10 "created_at": "2024-01-15T10:30:00Z",11 "updated_at": "2024-01-15T10:30:05Z"12 }13}5. schema
input
the text to convert to speech
the value used to module the next token probabilities
the number of highest probability vocabulary tokens to keep for top-k-filtering
top-p sampling parameter
the maximum number of new tokens to generate
random seed for generation
voice reference audio name (e.g., 'belinda', 'broom_salesman') or comma-separated for multi-speaker
scene description prompt for context
chunking method: 'speaker', 'word', or none
maximum words per chunk when using word chunking
maximum turns per chunk when using speaker chunking
maximum chunks to keep in buffer
ras sampling window length (0 to disable)
maximum ras window repeats
include reference audio description in system message
ready to run Higgs Audio?
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