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This experiment demonstrates how to deploy and use a text-to-audio model (Stable Audio Open 1.0) using Flexai’s inference serving capabilities.

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Prerequisites

Before starting, make sure you have:
  • A Flexai account with access to the platform
  • A Hugging Face token with access to the stabilityai/stable-audio-open-1.0 model
  • The flexai CLI installed and configured

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Setup FlexAI Secret for Hugging Face Token

First, create a FlexAI secret that contains your Hugging Face token to access the inference model: 
# Enter your HF token value when prompted
flexai secret create MY_HF_TOKEN
Make sure your Hugging Face token has access to the stabilityai/stable-audio-open-1.0 model. You may need to accept the model’s license terms on Hugging Face first.

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Start the FlexAI Inference Endpoint

Start the FlexAI endpoint for the Stable Audio Open 1.0 model: 
INFERENCE_NAME=stable-audio-open
flexai inference serve $INFERENCE_NAME --runtime flexserve --hf-token-secret MY_HF_TOKEN -- --task text-to-audio --model stabilityai/stable-audio-open-1.0
This command will:
  • Create an inference endpoint named stable-audio-open
  • Use the flexserve runtime optimized for text-to-audio tasks
  • Load the Stable Audio Open 1.0 model from Hugging Face
  • Configure it for text-to-audio generation

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Get Endpoint Information

Once the endpoint is deployed, you’ll see the API key displayed in the output. Store it in an environment variable: 
export INFERENCE_API_KEY=<API_KEY_FROM_ENDPOINT_CREATION_OUTPUT>
Then retrieve the endpoint URL: 
export INFERENCE_URL=$(flexai inference inspect $INFERENCE_NAME -j | jq .config.endpointUrl -r)
You’ll notice these export lines use the jq tool to extract values from the JSON output of the inspect command.If you don’t have it already, you can get jq from its official website: https://jqlang.org/

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Generate Audio

Now you can generate audio by making HTTP POST requests to your endpoint. Here are some examples:

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Example 1: Relaxing Music

curl -X POST \
  -H "Authorization: Bearer $INFERENCE_API_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
    "inputs": "Relaxing piano music with soft ambient sounds, calm and peaceful",
    "parameters": {
      "audio_end_in_s": 10.0,
      "num_inference_steps": 200,
      "guidance_scale": 7.0,
      "seed": 42
    }
  }' \
  -o relaxing_music.wav \
  "$INFERENCE_URL/v1/audios/generations"

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Example 2: Nature Soundscape

curl -X POST \
  -H "Authorization: Bearer $INFERENCE_API_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
    "inputs": "Forest ambience with birds chirping and a gentle stream flowing",
    "parameters": {
      "audio_end_in_s": 15.0,
      "num_inference_steps": 200,
      "guidance_scale": 7.0,
      "negative_prompt": "distorted, low quality, muffled",
      "seed": 123
    }
  }' \
  -o nature_sounds.wav \
  "$INFERENCE_URL/v1/audios/generations"

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Example 3: Electronic Beat

curl -X POST \
  -H "Authorization: Bearer $INFERENCE_API_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
    "inputs": "Upbeat electronic music with synthesizers and energetic drums, 128 bpm",
    "parameters": {
      "audio_end_in_s": 20.0,
      "num_inference_steps": 200,
      "guidance_scale": 7.0,
      "seed": 456
    }
  }' \
  -o electronic_beat.wav \
  "$INFERENCE_URL/v1/audios/generations"
These will save the generated audio files in your current directory.

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Parameters Explanation

The API accepts the following parameters:
  • inputs: The text prompt describing the audio you want to generate
  • audio_length_in_s: Output audio duration in seconds (typically up to 47 seconds for Stable Audio Open)
  • num_inference_steps: Number of denoising steps (higher = better quality but slower, recommended: 100-200)
  • guidance_scale: As you increase the value, the model tries harder to match your prompt.
  • negative_prompt: Description of what you don’t want in the audio (helps improve quality)
  • seed: Random seed for reproducible results