python-agents-examples/docs/examples/changing_language at main

title

ElevenLabs Change Language

Prerequisites

Add a .env in this directory with your LiveKit and provider credentials:

LIVEKIT_URL=your_livekit_url
LIVEKIT_API_KEY=your_api_key
LIVEKIT_API_SECRET=your_api_secret
DEEPGRAM_API_KEY=your_deepgram_key
ELEVENLABS_API_KEY=your_elevenlabs_key

Install dependencies:

pip install python-dotenv "livekit-agents[silero,deepgram,elevenlabs]"

Load environment, logging, and define an AgentServer

Start by importing the necessary modules, loading your environment, and configuring logging for the agent.

import logging
from dotenv import load_dotenv
from livekit.agents import JobContext, JobProcess, Agent, AgentSession, AgentServer, cli, inference, function_tool
from livekit.plugins import deepgram, elevenlabs, silero

load_dotenv()

logger = logging.getLogger("language-switcher")
logger.setLevel(logging.INFO)

server = AgentServer()

Prewarm VAD and define the language-switcher agent

Preload VAD once per process to reduce connection latency. Configure the RTC session with Deepgram STT, ElevenLabs TTS, and an inference LLM.

import logging
from dotenv import load_dotenv
from livekit.agents import JobContext, JobProcess, Agent, AgentSession, AgentServer, cli, inference, function_tool
from livekit.plugins import deepgram, elevenlabs, silero

load_dotenv()

logger = logging.getLogger("language-switcher")
logger.setLevel(logging.INFO)

server = AgentServer()

def prewarm(proc: JobProcess):
    proc.userdata["vad"] = silero.VAD.load()

server.setup_fnc = prewarm

class LanguageSwitcherAgent(Agent):
    def __init__(self) -> None:
        super().__init__(
            instructions="""
                You are a helpful assistant communicating through voice.
                You can switch to a different language if asked.
                Don't use any unpronounceable characters.
            """
        )
        self.current_language = "en"

        self.language_names = {
            "en": "English",
            "es": "Spanish",
            "fr": "French",
            "de": "German",
            "it": "Italian",
        }

        self.deepgram_language_codes = {
            "en": "en",
            "es": "es",
            "fr": "fr-CA",
            "de": "de",
            "it": "it",
        }

        self.greetings = {
            "en": "Hello! I'm now speaking in English. How can I help you today?",
            "es": "¡Hola! Ahora estoy hablando en español. ¿Cómo puedo ayudarte hoy?",
            "fr": "Bonjour! Je parle maintenant en français. Comment puis-je vous aider aujourd'hui?",
            "de": "Hallo! Ich spreche jetzt Deutsch. Wie kann ich Ihnen heute helfen?",
            "it": "Ciao! Ora sto parlando in italiano. Come posso aiutarti oggi?",
        }

    async def on_enter(self):
        await self.session.say(
            "Hi there! I can speak in multiple languages including Spanish, French, German, and Italian. "
            "Just ask me to switch to any of these languages. How can I help you today?"
        )

@server.rtc_session()
async def entrypoint(ctx: JobContext):
    ctx.log_context_fields = {"room": ctx.room.name}

    session = AgentSession(
        stt=deepgram.STT(model="nova-2-general", language="en"),
        llm=inference.LLM(model="openai/gpt-4o"),
        tts=elevenlabs.TTS(model="eleven_turbo_v2_5", language="en"),
        vad=ctx.proc.userdata["vad"],
        preemptive_generation=True,
    )

    await session.start(agent=LanguageSwitcherAgent(), room=ctx.room)
    await ctx.connect()

Add the function tools to switch languages

Next we'll add a helper to swap STT/TTS languages, and function tools that let the LLM trigger language changes.

import logging
from dotenv import load_dotenv
from livekit.agents import JobContext, JobProcess, Agent, AgentSession, AgentServer, cli, inference, function_tool
from livekit.plugins import deepgram, elevenlabs, silero

load_dotenv()

logger = logging.getLogger("language-switcher")
logger.setLevel(logging.INFO)

server = AgentServer()

def prewarm(proc: JobProcess):
    proc.userdata["vad"] = silero.VAD.load()

server.setup_fnc = prewarm

class LanguageSwitcherAgent(Agent):
    def __init__(self) -> None:
        super().__init__(
            instructions="""
                You are a helpful assistant communicating through voice.
                You can switch to a different language if asked.
                Don't use any unpronounceable characters.
            """
        )
        self.current_language = "en"

        self.language_names = {
            "en": "English",
            "es": "Spanish",
            "fr": "French",
            "de": "German",
            "it": "Italian",
        }

        self.deepgram_language_codes = {
            "en": "en",
            "es": "es",
            "fr": "fr-CA",
            "de": "de",
            "it": "it",
        }

        self.greetings = {
            "en": "Hello! I'm now speaking in English. How can I help you today?",
            "es": "¡Hola! Ahora estoy hablando en español. ¿Cómo puedo ayudarte hoy?",
            "fr": "Bonjour! Je parle maintenant en français. Comment puis-je vous aider aujourd'hui?",
            "de": "Hallo! Ich spreche jetzt Deutsch. Wie kann ich Ihnen heute helfen?",
            "it": "Ciao! Ora sto parlando in italiano. Come posso aiutarti oggi?",
        }

    async def on_enter(self):
        await self.session.say(
            "Hi there! I can speak in multiple languages including Spanish, French, German, and Italian. "
            "Just ask me to switch to any of these languages. How can I help you today?"
        )

    async def _switch_language(self, language_code: str) -> None:
        """Helper method to switch the language"""
        if language_code == self.current_language:
            await self.session.say(f"I'm already speaking in {self.language_names[language_code]}.")
            return

        if self.session.tts is not None:
            self.session.tts.update_options(language=language_code)

        if self.session.stt is not None:
            deepgram_language = self.deepgram_language_codes.get(language_code, language_code)
            self.session.stt.update_options(language=deepgram_language)

        self.current_language = language_code

        await self.session.say(self.greetings[language_code])

    @function_tool
    async def switch_to_english(self):
        """Switch to speaking English"""
        await self._switch_language("en")

    @function_tool
    async def switch_to_spanish(self):
        """Switch to speaking Spanish"""
        await self._switch_language("es")

    @function_tool
    async def switch_to_french(self):
        """Switch to speaking French"""
        await self._switch_language("fr")

    @function_tool
    async def switch_to_german(self):
        """Switch to speaking German"""
        await self._switch_language("de")

    @function_tool
    async def switch_to_italian(self):
        """Switch to speaking Italian"""
        await self._switch_language("it")

@server.rtc_session()
async def entrypoint(ctx: JobContext):
    ctx.log_context_fields = {"room": ctx.room.name}

    session = AgentSession(
        stt=deepgram.STT(model="nova-2-general", language="en"),
        llm=inference.LLM(model="openai/gpt-4o"),
        tts=elevenlabs.TTS(model="eleven_turbo_v2_5", language="en"),
        vad=ctx.proc.userdata["vad"],
        preemptive_generation=True,
    )

    await session.start(agent=LanguageSwitcherAgent(), room=ctx.room)
    await ctx.connect()

Run the server

Use the CLI runner to start the agent server so it can respond to language-change requests.

import logging
from dotenv import load_dotenv
from livekit.agents import JobContext, JobProcess, Agent, AgentSession, AgentServer, cli, inference, function_tool
from livekit.plugins import deepgram, elevenlabs, silero

load_dotenv()

logger = logging.getLogger("language-switcher")
logger.setLevel(logging.INFO)

server = AgentServer()


def prewarm(proc: JobProcess):
    proc.userdata["vad"] = silero.VAD.load()


server.setup_fnc = prewarm


class LanguageSwitcherAgent(Agent):
    def __init__(self) -> None:
        super().__init__(
            instructions="""
                You are a helpful assistant communicating through voice.
                You can switch to a different language if asked.
                Don't use any unpronounceable characters.
            """
        )
        self.current_language = "en"

        self.language_names = {
            "en": "English",
            "es": "Spanish",
            "fr": "French",
            "de": "German",
            "it": "Italian",
        }

        self.deepgram_language_codes = {
            "en": "en",
            "es": "es",
            "fr": "fr-CA",
            "de": "de",
            "it": "it",
        }

        self.greetings = {
            "en": "Hello! I'm now speaking in English. How can I help you today?",
            "es": "¡Hola! Ahora estoy hablando en español. ¿Cómo puedo ayudarte hoy?",
            "fr": "Bonjour! Je parle maintenant en français. Comment puis-je vous aider aujourd'hui?",
            "de": "Hallo! Ich spreche jetzt Deutsch. Wie kann ich Ihnen heute helfen?",
            "it": "Ciao! Ora sto parlando in italiano. Come posso aiutarti oggi?",
        }

    async def on_enter(self):
        await self.session.say(
            "Hi there! I can speak in multiple languages including Spanish, French, German, and Italian. "
            "Just ask me to switch to any of these languages. How can I help you today?"
        )

    async def _switch_language(self, language_code: str) -> None:
        """Helper method to switch the language"""
        if language_code == self.current_language:
            await self.session.say(f"I'm already speaking in {self.language_names[language_code]}.")
            return

        if self.session.tts is not None:
            self.session.tts.update_options(language=language_code)

        if self.session.stt is not None:
            deepgram_language = self.deepgram_language_codes.get(language_code, language_code)
            self.session.stt.update_options(language=deepgram_language)

        self.current_language = language_code

        await self.session.say(self.greetings[language_code])

    @function_tool
    async def switch_to_english(self):
        """Switch to speaking English"""
        await self._switch_language("en")

    @function_tool
    async def switch_to_spanish(self):
        """Switch to speaking Spanish"""
        await self._switch_language("es")

    @function_tool
    async def switch_to_french(self):
        """Switch to speaking French"""
        await self._switch_language("fr")

    @function_tool
    async def switch_to_german(self):
        """Switch to speaking German"""
        await self._switch_language("de")

    @function_tool
    async def switch_to_italian(self):
        """Switch to speaking Italian"""
        await self._switch_language("it")


@server.rtc_session()
async def entrypoint(ctx: JobContext):
    ctx.log_context_fields = {"room": ctx.room.name}

    session = AgentSession(
        stt=deepgram.STT(model="nova-2-general", language="en"),
        llm=inference.LLM(model="openai/gpt-4o"),
        tts=elevenlabs.TTS(model="eleven_turbo_v2_5", language="en"),
        vad=ctx.proc.userdata["vad"],
        preemptive_generation=True,
    )

    await session.start(agent=LanguageSwitcherAgent(), room=ctx.room)
    await ctx.connect()

if __name__ == "__main__":
    cli.run_app(server)

Run it

python elevenlabs_change_language.py console

Try saying:

"Switch to Spanish"
"Can you speak French?"
"Let's talk in German"
"Change to Italian"

Supported languages

Language	Code	Deepgram Code	Example Phrase
English	en	en	"Hello! How can I help you?"
Spanish	es	es	"¡Hola! ¿Cómo puedo ayudarte?"
French	fr	fr-CA	"Bonjour! Comment puis-je vous aider?"
German	de	de	"Hallo! Wie kann ich Ihnen helfen?"
Italian	it	it	"Ciao! Come posso aiutarti?"

How it works

The agent greets in English and waits for a language change request.
A function tool routes to _switch_language(), which updates both TTS and STT via update_options().
The agent tracks the current language to avoid redundant switches.
A native greeting confirms the change, and the rest of the conversation stays in the selected language until switched again.

Full example

import logging
from dotenv import load_dotenv
from livekit.agents import JobContext, JobProcess, Agent, AgentSession, AgentServer, cli, inference, function_tool
from livekit.plugins import deepgram, elevenlabs, silero

load_dotenv()

logger = logging.getLogger("language-switcher")
logger.setLevel(logging.INFO)

server = AgentServer()


class LanguageSwitcherAgent(Agent):
    def __init__(self) -> None:
        super().__init__(
            instructions="""
                You are a helpful assistant communicating through voice.
                You can switch to a different language if asked.
                Don't use any unpronounceable characters.
            """
        )
        self.current_language = "en"

        self.language_names = {
            "en": "English",
            "es": "Spanish",
            "fr": "French",
            "de": "German",
            "it": "Italian",
        }

        self.deepgram_language_codes = {
            "en": "en",
            "es": "es",
            "fr": "fr-CA",
            "de": "de",
            "it": "it",
        }

        self.greetings = {
            "en": "Hello! I'm now speaking in English. How can I help you today?",
            "es": "¡Hola! Ahora estoy hablando en español. ¿Cómo puedo ayudarte hoy?",
            "fr": "Bonjour! Je parle maintenant en français. Comment puis-je vous aider aujourd'hui?",
            "de": "Hallo! Ich spreche jetzt Deutsch. Wie kann ich Ihnen heute helfen?",
            "it": "Ciao! Ora sto parlando in italiano. Come posso aiutarti oggi?",
        }

    async def on_enter(self):
        await self.session.say(
            "Hi there! I can speak in multiple languages including Spanish, French, German, and Italian. "
            "Just ask me to switch to any of these languages. How can I help you today?"
        )

    async def _switch_language(self, language_code: str) -> None:
        """Helper method to switch the language"""
        if language_code == self.current_language:
            await self.session.say(f"I'm already speaking in {self.language_names[language_code]}.")
            return

        if self.session.tts is not None:
            self.session.tts.update_options(language=language_code)

        if self.session.stt is not None:
            deepgram_language = self.deepgram_language_codes.get(language_code, language_code)
            self.session.stt.update_options(language=deepgram_language)

        self.current_language = language_code

        await self.session.say(self.greetings[language_code])

    @function_tool
    async def switch_to_english(self):
        """Switch to speaking English"""
        await self._switch_language("en")

    @function_tool
    async def switch_to_spanish(self):
        """Switch to speaking Spanish"""
        await self._switch_language("es")

    @function_tool
    async def switch_to_french(self):
        """Switch to speaking French"""
        await self._switch_language("fr")

    @function_tool
    async def switch_to_german(self):
        """Switch to speaking German"""
        await self._switch_language("de")

    @function_tool
    async def switch_to_italian(self):
        """Switch to speaking Italian"""
        await self._switch_language("it")


def prewarm(proc: JobProcess):
    proc.userdata["vad"] = silero.VAD.load()


server.setup_fnc = prewarm


@server.rtc_session()
async def entrypoint(ctx: JobContext):
    ctx.log_context_fields = {"room": ctx.room.name}

    session = AgentSession(
        stt=deepgram.STT(model="nova-2-general", language="en"),
        llm=inference.LLM(model="openai/gpt-4o"),
        tts=elevenlabs.TTS(model="eleven_turbo_v2_5", language="en"),
        vad=ctx.proc.userdata["vad"],
        preemptive_generation=True,
    )

    await session.start(agent=LanguageSwitcherAgent(), room=ctx.room)
    await ctx.connect()


if __name__ == "__main__":
    cli.run_app(server)

Example conversation

Agent: "Hi there! I can speak in multiple languages..."
User: "Can you speak Spanish?"
Agent: "¡Hola! Ahora estoy hablando en español. ¿Cómo puedo ayudarte hoy?"
User: "¿Cuál es el clima?"
Agent: [Responds in Spanish about the weather]
User: "Now switch to French"
Agent: "Bonjour! Je parle maintenant en français. Comment puis-je vous aider aujourd'hui?"