Speechify
Speechify is a service that provides high quality, low latency Text-to-Speech (TTS). It's a great fit for real-time voice applications such as voice AI agents and conversational interfaces.
The Speechify plugin for the Stream Python AI SDK allows you to add TTS functionality to your project.
Installation
Install the Stream Speechify plugin with
uv add "vision-agents[speechify]"
# or directly
uv add vision-agents-plugins-speechify
Examples
Read on for some key details and check out our Speechify example to see working code:
- in main.py we see a voice bot that uses Speechify TTS in a Stream call
Initialisation
The Speechify plugin for Stream exposes a TTS class:
from vision_agents.plugins import speechify
tts = speechify.TTS()
To initialise without passing in the API key, make sure the `SPEECHIFY_API_KEY` is available as an environment variable.
You can do this either by defining it in a `.env` file or exporting it directly in your terminal.
Parameters
These are the parameters available in the Speechify TTS plugin for you to customise:
| Name | Type | Default | Description |
|---|---|---|---|
api_key |
str or None |
None |
Your Speechify API key. If not provided, the plugin will look for the SPEECHIFY_API_KEY environment variable. |
voice_id |
str |
"geffen_32" |
ID of the voice to use for TTS responses. See the voices endpoint for options. |
model |
str |
"simba-3.2" |
ID of the Speechify model to use. |
language |
str or None |
None |
Optional ISO 639-1 + ISO 3166-1 language tag (e.g. en-US). When omitted the language is auto-detected. |
Functionality
Send text to convert to speech
The send_iter() method sends the text passed in for the service to synthesize
and yields TTSOutputChunks containing the produced PCM audio.
async for chunk in tts.send_iter("Demo text you want AI voice to say"):
pass
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