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This experiment demonstrates how to deploy and use a text-to-speech model (Kokoro) 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
  • The flexai CLI installed and configured

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Start the FlexAI Inference Endpoint

Start the FlexAI endpoint for the Kokoro text-to-speech model: 
INFERENCE_NAME=text-to-speech
flexai inference serve $INFERENCE_NAME --runtime flexserve -- --model hexgrad/Kokoro-82M --task text-to-speech --lang-code a
This command will:
  • Create an inference endpoint named text-to-speech
  • Use the flexserve runtime optimized for text-to-speech tasks
  • Load the Kokoro model for natural voice synthesis
  • Configure it for English language text-to-speech 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 Speech

Now you can generate speech by making HTTP POST requests to your endpoint. Here is an example: 
curl -X POST \
  -H "Authorization: Bearer $INFERENCE_API_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
    "inputs": "Welcome to FlexAI! Produce lifelike speech and spin up production inference endpoints in seconds.",
    "parameters": {
      "voice": "af_heart"
    }
  }' \
  -o welcome.wav \
  "$INFERENCE_URL/v1/speeches/generations"

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Parameters Explanation

The API accepts the following parameters:
  • inputs: The text you want to convert to speech
  • voice: The voice model to use for synthesis

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Supported Languages

You can configure different languages by changing the --lang-code parameter when starting the inference endpoint. The voice model to use is specified in the voice parameter of your request. For a complete list of supported languages and available voices, check the Kokoro GitHub repository