LiveKit Integration

Build real-time voice agents with LiveKit Agents powered by 60db’s speech and language services — STT, TTS, and LLM all in one plugin.

Speech-to-Text

Real-time streaming transcription via WebSocket with interim results

Text-to-Speech

Low-latency streaming synthesis with chunked audio delivery

LLM Chat

OpenAI-compatible chat completions with tool-call support

Installation

Install the plugin

Requires Python 3.10+.

pip install livekit-plugins-60db

Set your API key

Choose one of the following methods:Option A — Environment variable (recommended):

export SIXTY_DB_API_KEY="your-api-key"

Option B — .env.local file:

SIXTY_DB_API_KEY=your-api-key

Option C — Pass it directly in code:

from livekit.plugins._60db import _60dbClient

client = _60dbClient("your-api-key")  # sets global default

Quick Start

Wire all three services together in a VoicePipelineAgent:

import asyncio
from livekit.agents import VoicePipelineAgent, cli, WorkerType
from livekit.plugins import silero
from livekit.plugins._60db import _60dbClient, STT, TTS, LLM

client = _60dbClient("your-api-key")  # sets global default


async def entrypoint(ctx):
    await ctx.connect()

    agent = VoicePipelineAgent(
        vad=silero.VAD.load(),   # voice activity detection
        stt=STT(),               # 60db speech-to-text
        llm=LLM(),               # 60db language model
        tts=TTS(),               # 60db text-to-speech
    )

    agent.start(ctx.room)


if __name__ == "__main__":
    cli.run_app(worker_type=WorkerType.ROOM, entrypoint_fnc=entrypoint)

Configuration

Environment Variables

All services read from the same environment variables by default. You only need to override them if you use a custom deployment.

Variable	Default	Description
`SIXTY_DB_API_KEY`	—	Your 60db API key (required)
`SIXTY_DB_STT_URL`	`wss://api.60db.ai/ws/stt`	STT WebSocket endpoint
`SIXTY_DB_TTS_URL`	`wss://api.60db.ai/ws/tts`	TTS WebSocket endpoint
`SIXTY_DB_LLM_URL`	`https://api.60db.ai/v1/chat/completions`	LLM HTTP endpoint

Each service also accepts a direct ws_url (or api_url) constructor argument which takes precedence over environment variables.

Services

Speech-to-Text

The STT service streams audio to 60db over WebSocket and returns transcriptions in real time — including interim (partial) results as the speaker is still talking.

Parameters

Name	Type	Default	Description
`api_key`	`str \| None`	global client / env var	Your 60db API key
`ws_url`	`str \| None`	env var	WebSocket endpoint URL
`languages`	`list[str] \| None`	`["en"]`	Language codes for recognition
`encoding`	`str`	`"mulaw"`	Audio encoding format
`sample_rate`	`int`	`8000`	Audio sample rate in Hz
`continuous_mode`	`bool`	`True`	Keep the session open for continuous recognition

Example

from livekit.plugins._60db import STT

stt = STT()  # picks up api_key from global client or env var

async with stt.stream() as stream:
    stream.push_frame(audio_frame)  # push raw audio frames

    async for event in stream:
        if event.type == stt.SpeechEventType.FINAL_TRANSCRIPT:
            print(event.alternatives[0].text)

Audio Formats

The plugin automatically handles audio conversion for you — no manual preprocessing needed.

Step	What happens
Stereo → Mono	Downmix via `audioop.tomono`
Resampling	Any input rate → target rate via `audioop.ratecv`
Encoding	LINEAR16 PCM → mulaw via `audioop.lin2ulaw` (when `encoding="mulaw"`)

Parameter	Default	Supported
Encoding	`mulaw`	`mulaw`, `LINEAR16`
Sample rate	`8000 Hz`	Any rate (auto-resampled)

Text-to-Speech

The TTS service converts text to speech over WebSocket. It supports both one-shot synthesis and streaming mode for low-latency incremental output.

Parameters

Name	Type	Default	Description
`api_key`	`str \| None`	global client / env var	Your 60db API key
`ws_url`	`str \| None`	env var	WebSocket endpoint URL
`voice_id`	`str`	`"fbb75ed2-975a-40c7-9e06-38e30524a9a1"`	Voice identifier
`encoding`	`str`	`"LINEAR16"`	Output audio encoding
`sample_rate`	`int`	`16000`	Output sample rate in Hz

Examples

One-shot synthesis — best for short, complete responses:

from livekit.plugins._60db import TTS

tts = TTS()

async for chunk in tts.synthesize("Hello, how can I help you?"):
    # chunk.data contains raw PCM audio bytes
    print(f"Received {len(chunk.data)} bytes")

Streaming synthesis — best for incremental LLM output:

async with tts.stream() as stream:
    stream.push_text("Hello, ")
    stream.push_text("how can I help you?")
    stream.end_input()

    async for chunk in stream:
        print(f"Received {len(chunk.data)} bytes")

Audio Format

Parameter	Default	Notes
Encoding	`LINEAR16`	Raw PCM
Sample rate	`16000 Hz`	Configurable via `sample_rate`

Audio is returned as base64-encoded PCM chunks by the server, decoded automatically by the plugin.

Language Model

The LLM service provides OpenAI-compatible chat completions with SSE streaming and tool-call support.

Parameters

Name	Type	Default	Description
`api_key`	`str \| None`	global client / env var	Your 60db API key
`api_url`	`str \| None`	env var	Chat completions endpoint URL
`model`	`str`	`"qcall/slm-3b-int4"`	Model identifier
`temperature`	`float \| None`	`None`	Sampling temperature (0–2)
`top_p`	`float \| None`	`None`	Nucleus sampling probability
`top_k`	`int \| None`	`None`	Top-K sampling parameter
`max_tokens`	`int \| None`	`None`	Maximum tokens in the response
`chat_template_kwargs`	`dict \| None`	`None`	Extra template kwargs for the model

Example

from livekit.plugins._60db import LLM
from livekit.agents import llm

model = LLM(temperature=0.7)

chat_ctx = llm.ChatContext()
chat_ctx.append(role="system", text="You are a helpful voice assistant.")
chat_ctx.append(role="user", text="What is the capital of France?")

async for chunk in model.chat(chat_ctx=chat_ctx):
    print(chunk.choices[0].delta.content, end="")

Tool Calls

The LLM supports OpenAI-style function tool calls. When the model calls a tool, the plugin accumulates the streamed argument fragments and emits a complete FunctionToolCall once the stream finishes.

Timeouts

Control timeouts per-request by passing APIConnectOptions:

from livekit.agents import APIConnectOptions

opts = APIConnectOptions(timeout=30.0)

# STT
async with stt.stream(conn_options=opts) as s:
    ...

# TTS
async for chunk in tts.synthesize("Hello", conn_options=opts):
    ...

# LLM
async for chunk in model.chat(chat_ctx=ctx, conn_options=opts):
    ...

Error Handling

All three services raise standard LiveKit Agents exceptions:

Exception	When it’s raised
`APIConnectionError`	WebSocket handshake failure, HTTP error, or unexpected protocol message
`APITimeoutError`	Request exceeds the configured timeout
`ValueError`	Missing API key or service URL at construction time

Common HTTP Error Codes (LLM)

Status	Meaning
`401`	Invalid or missing API key
`429`	Rate limit exceeded
`500`	Server error
`503`	Service unavailable

Retry Tips

STT: If you receive an error message during the handshake, reconnect with a short delay. A connecting status before connection_established is normal.
TTS: Retry connection failures with exponential backoff.
LLM: httpx.TimeoutException → APITimeoutError; httpx.HTTPStatusError → APIConnectionError.

WebSocket Protocol Reference

STT WebSocket Protocol

Connect:

wss://api.60db.ai/ws/stt?apiKey={API_KEY}

Handshake:Server → {"connection_established": true}Client → start command:

{
  "type": "start",
  "languages": ["en"],
  "config": {
    "encoding": "mulaw",
    "sample_rate": 8000,
    "continuous_mode": true
  }
}

Server → {"type": "connected"}Audio: Send raw audio as binary WebSocket frames.Transcription response:

{
  "type": "transcription",
  "text": "Hello, world",
  "is_final": false,
  "language": "en"
}

Stop:Client → {"type": "stop"}Server →

{
  "type": "session_stopped",
  "billing_summary": { "total_cost": "..." }
}

TTS WebSocket Protocol

Connect:

wss://api.60db.ai/ws/tts?apiKey={API_KEY}

Create context:

{
  "create_context": {
    "context_id": "unique-id",
    "voice_id": "fbb75ed2-975a-40c7-9e06-38e30524a9a1",
    "audio_config": {
      "audio_encoding": "LINEAR16",
      "sample_rate_hertz": 16000
    }
  }
}

Send text:

{ "send_text": { "context_id": "unique-id", "text": "Hello!" } }

Flush (trigger audio generation):

{ "flush_context": { "context_id": "unique-id" } }

Audio response:

{ "audio_chunk": { "audioContent": "<base64 PCM>" } }

Followed by {"flush_completed": true} when all audio has been delivered.Close context:

{ "close_context": { "context_id": "unique-id" } }

​LiveKit Integration

Speech-to-Text

Text-to-Speech

LLM Chat

​Installation

​Quick Start

​Configuration

​Environment Variables

​Services

​Speech-to-Text

​Parameters

​Example

​Audio Formats

​Text-to-Speech

​Parameters

​Examples

​Audio Format

​Language Model

​Parameters

​Example

​Tool Calls

​Timeouts

​Error Handling

​Common HTTP Error Codes (LLM)

​Retry Tips

​WebSocket Protocol Reference

LiveKit Integration

Installation

Quick Start

Configuration

Environment Variables

Services

Speech-to-Text

Parameters

Example

Audio Formats

Text-to-Speech

Parameters

Examples

Audio Format

Language Model

Parameters

Example

Tool Calls

Timeouts

Error Handling

Common HTTP Error Codes (LLM)

Retry Tips

WebSocket Protocol Reference