LiveKit

LiveKit is an open-source platform for low-latency, bi-directional audio streaming and real-time media orchestration. With LiveKit Agents, developers can compose voice pipelines using modular components like speech-to-text (STT), large language models (LLMs), and text-to-speech (TTS).

Hume’s expressive TTS can be integrated into your LiveKit Agents pipelines using the Hume LiveKit Agents TTS plugin. This guide covers setup instructions, integration modes, and configuration best practices.

Authentication

To use the Hume TTS plugin with LiveKit Agents, you’ll need both Hume and LiveKit credentials. Follow these steps to obtain your credentials and set up environment variables.

HUME_API_KEY=...
LIVEKIT_URL=...
LIVEKIT_API_KEY=...
LIVEKIT_API_SECRET=...

Usage

The Hume TTS plugin for LiveKit Agents can be used for two use cases: Agent Sessions and Standalone TTS.

AgentSession

When using the Hume TTS plugin within an AgentSession, follow these guidelines to ensure responsive performance and consistent voice behavior throughout the session:

• Enable instant_mode: Reduces latency significantly. Note that enabling instant_mode requires explicitly specifying a voice.

• Specify a voice: Select from Hume’s extensive Voice Library or a custom voice for voice consistency.

• Omit crafting parameters: Parameters for crafting TTS output like description, speed, trailing_silence, and context are globally applied to all session responses. These parameters are best suited for standalone TTS.

Example implementation:

1
from livekit.agents import (
2
  Agent,
3
  AgentSession,
4
  JobContext,
5
  WorkerOptions,
6
  cli,
7
)
8
from livekit.plugins.hume import TTS, VoiceByName, VoiceProvider
9
10
class VoiceAssistant(Agent):
11
    def __init__(self):
12
        super().__init__(instructions="Your system prompt...")
13
14
async def entrypoint(ctx: JobContext) -> None:
15
    await ctx.connect()
16
17
    # 1. Configure the Hume TTS plugin
18
    tts = TTS(
19
        voice=VoiceByName(
20
            name="Male English Actor",
21
            provider=VoiceProvider.hume,
22
        ),
23
        instant_mode=True,
24
    )
25
26
    # 2. Create your AgentSession with STT/LLM as needed
27
    session = AgentSession(
28
        stt=..., # specify your STT config
29
        llm=..., # specify your LLM config
30
        tts=tts,
31
    )
32
33
    # 3. Start the session with a greeting
34
    await session.start(agent=VoiceAssistant(), room=ctx.room)
35
    await session.generate_reply(instructions=GREETING_INSTRUCTIONS)
36
37
if __name__ == "__main__":
38
    cli.run_app(
39
        WorkerOptions(entrypoint_fnc=entrypoint)
40
    )

Standalone TTS

The Hume TTS plugin can be used independently for direct text-to-speech synthesis, outside of an AgentSession. This is useful when you don’t need STT or LLM components and want full control over voice selection, expressiveness, and timing on a per-request basis.

When using the plugin this way, keep the following in mind:

• One utterance per request: LiveKit processes only a single utterance per request. Split multi-part dialogue into separate requests to control delivery for each line.

• Supply acting instructions: Use utterance options like description, speed, and trailing_silence to shape the delivery. See our acting instructions guide for best practices.

• Provide context: Use the context field to maintain continuity across requests. For more on how context influences output, see our continuation guide.

Example implementation:

1
import asyncio
2
from aiohttp import ClientSession
3
from livekit.plugins.hume import TTS
4
from simpleaudio import play_buffer
5
6
async def standalone_tts(text: str):
7
    async with ClientSession() as session:
8
        # 1. Configure the Hume TTS plugin
9
        tts = TTS(
10
            voice=VoiceByName(
11
                name="Male English Actor",
12
                provider=VoiceProvider.hume,
13
            ),
14
            description="calm, pedagogical",
15
            speed=0.65,
16
            trailing_silence=4,
17
            instant_mode=True,
18
            http_session=session,
19
        ),
20
21
        # 2. Collect PCM data
22
        pcm_buffer = bytearray()
23
        async for chunk in tts.synthesize(text):
24
            pcm_buffer.extend(chunk.frame.data)
25
26
    # 3. Play back the audio
27
    play_buffer(
28
        pcm,
29
        num_channels=1,     # mono
30
        bytes_per_sample=2, # 16-bit
31
        sample_rate=48000,  # 48000 Hz
32
    ).wait_done()
33
34
if __name__ == "__main__":
35
    asyncio.run(
36
        standalone_tts("Let us begin by taking a deep breath...")
37
    )

Constraints

• Audio format support: The Hume TTS plugin supports WAV, MP3, and PCM audio formats. If no audio format is specified, it will default to MP3.

• Fixed sample rate: The Hume TTS API outputs audio at a fixed sample rate of 48kHz. Ensure compatibility with your audio processing pipeline.

• Output data limitations: The plugin returns audio data with encoding details only. Additional Hume API response data (such as generation_id) is not included.

• Normalized TTS interface: Due to the LiveKit Agents SDK’s normalized interface, each request must contain a single utterance. Split multi-utterance text into separate requests.

• Plugin options persist: The configuration set when initializing the plugin is applied to each TTS request. To update these options during a session, use the plugin’s update_options method. See the LiveKit documentation for usage details.

Resources