Files
meet/src/agents/multi-user-transcriber.py
T
Ghislain LE MEUR 9f9cef7e2a (agents) add multilingual support for real-time subtitles
Add dynamic configuration for Deepgram STT via environment variables,
enabling multilingual real-time subtitles with automatic language
detection.

Changes:
- Add DEEPGRAM_STT_* environment variables pattern for configuration
- Implement _build_deepgram_stt_kwargs() to dynamically build STT
  parameters from environment variables
- Add whitelist of supported parameters (model, language) for LiveKit
  Deepgram plugin
- Log warnings for unsupported parameters (diarize, smart_format, etc)
- Set default configuration: model=nova-3, language=multi
- Document supported parameters in Helm values.yaml

Configuration:
- DEEPGRAM_STT_MODEL: Deepgram model (default: nova-3)
- DEEPGRAM_STT_LANGUAGE: Language or 'multi' for automatic detection
  of 10 languages (en, es, fr, de, hi, ru, pt, ja, it, nl)

Note: Advanced features like diarization and smart_format are not
supported by the LiveKit Deepgram plugin in streaming mode.
2025-11-12 11:45:08 +01:00

247 lines
8.0 KiB
Python

"""Multi user transcription agent."""
import asyncio
import logging
import os
from dotenv import load_dotenv
from livekit import api, rtc
from livekit.agents import (
Agent,
AgentSession,
AutoSubscribe,
JobContext,
JobProcess,
JobRequest,
RoomInputOptions,
RoomIO,
RoomOutputOptions,
WorkerOptions,
WorkerPermissions,
cli,
utils,
)
from livekit.plugins import deepgram, silero
load_dotenv()
logger = logging.getLogger("transcriber")
TRANSCRIBER_AGENT_NAME = os.getenv("TRANSCRIBER_AGENT_NAME", "multi-user-transcriber")
# Default Deepgram STT configuration
DEEPGRAM_STT_DEFAULTS = {
"model": "nova-3",
"language": "multi",
}
# Supported parameters for LiveKit's deepgram.STT() in streaming mode
# Note: Not all Deepgram API parameters are supported by the LiveKit plugin
# detect_language is NOT supported for real-time streaming
# Use language="multi" instead for automatic multilingual support
DEEPGRAM_STT_SUPPORTED_PARAMS = {
"model",
"language",
}
def _build_deepgram_stt_kwargs():
"""Build Deepgram STT kwargs from DEEPGRAM_STT_* environment variables.
Only parameters supported by LiveKit's deepgram.STT() are included.
Unsupported parameters are logged as warnings.
"""
stt_kwargs = DEEPGRAM_STT_DEFAULTS.copy()
# Scan environment variables for DEEPGRAM_STT_* pattern
for key, value in os.environ.items():
if key.startswith("DEEPGRAM_STT_"):
# Extract parameter name and convert to lowercase
param_name = key.replace("DEEPGRAM_STT_", "", 1).lower()
# Check if parameter is supported by LiveKit plugin
if param_name not in DEEPGRAM_STT_SUPPORTED_PARAMS:
supported = ", ".join(sorted(DEEPGRAM_STT_SUPPORTED_PARAMS))
logger.warning(
f"Ignoring unsupported Deepgram STT parameter: {param_name}. "
f"Supported parameters: {supported}"
)
continue
# Parse value type
value_lower = value.lower()
if value_lower in ("true", "false"):
# Boolean values
stt_kwargs[param_name] = value_lower == "true"
elif value.isdigit():
# Integer values
stt_kwargs[param_name] = int(value)
else:
# String values
stt_kwargs[param_name] = value
logger.info(f"Deepgram STT configuration: {stt_kwargs}")
return stt_kwargs
class Transcriber(Agent):
"""Create a transcription agent for a specific participant."""
def __init__(self, *, participant_identity: str):
"""Init transcription agent."""
# Build STT configuration from environment variables
stt_kwargs = _build_deepgram_stt_kwargs()
super().__init__(
instructions="not-needed",
stt=deepgram.STT(**stt_kwargs),
)
self.participant_identity = participant_identity
class MultiUserTranscriber:
"""Manage transcription sessions for multiple room participants."""
def __init__(self, ctx: JobContext):
"""Init multi user transcription agent."""
self.ctx = ctx
self._sessions: dict[str, AgentSession] = {}
self._tasks: set[asyncio.Task] = set()
def start(self):
"""Start listening for participant connection events."""
self.ctx.room.on("participant_connected", self.on_participant_connected)
self.ctx.room.on("participant_disconnected", self.on_participant_disconnected)
async def aclose(self):
"""Close all sessions and cleanup resources."""
await utils.aio.cancel_and_wait(*self._tasks)
await asyncio.gather(
*[self._close_session(session) for session in self._sessions.values()]
)
self.ctx.room.off("participant_connected", self.on_participant_connected)
self.ctx.room.off("participant_disconnected", self.on_participant_disconnected)
def on_participant_connected(self, participant: rtc.RemoteParticipant):
"""Handle new participant connection by starting transcription session."""
if participant.identity in self._sessions:
return
logger.info(f"starting session for {participant.identity}")
task = asyncio.create_task(self._start_session(participant))
self._tasks.add(task)
def on_task_done(task: asyncio.Task):
try:
self._sessions[participant.identity] = task.result()
finally:
self._tasks.discard(task)
task.add_done_callback(on_task_done)
def on_participant_disconnected(self, participant: rtc.RemoteParticipant):
"""Handle participant disconnection by closing transcription session."""
if (session := self._sessions.pop(participant.identity)) is None:
return
logger.info(f"closing session for {participant.identity}")
task = asyncio.create_task(self._close_session(session))
self._tasks.add(task)
task.add_done_callback(lambda _: self._tasks.discard(task))
async def _start_session(self, participant: rtc.RemoteParticipant) -> AgentSession:
"""Create and start transcription session for participant."""
if participant.identity in self._sessions:
return self._sessions[participant.identity]
session = AgentSession(
vad=self.ctx.proc.userdata["vad"],
)
room_io = RoomIO(
agent_session=session,
room=self.ctx.room,
participant=participant,
input_options=RoomInputOptions(
text_enabled=False,
),
output_options=RoomOutputOptions(
transcription_enabled=True,
audio_enabled=False,
),
)
await room_io.start()
await session.start(
agent=Transcriber(
participant_identity=participant.identity,
)
)
return session
async def _close_session(self, sess: AgentSession) -> None:
"""Close and cleanup transcription session."""
await sess.drain()
await sess.aclose()
async def entrypoint(ctx: JobContext):
"""Initialize and run the multi-user transcriber."""
transcriber = MultiUserTranscriber(ctx)
transcriber.start()
await ctx.connect(auto_subscribe=AutoSubscribe.AUDIO_ONLY)
for participant in ctx.room.remote_participants.values():
transcriber.on_participant_connected(participant)
async def cleanup():
await transcriber.aclose()
ctx.add_shutdown_callback(cleanup)
async def handle_transcriber_job_request(job_req: JobRequest) -> None:
"""Accept job if no transcriber exists in room, otherwise reject."""
room_name = job_req.room.name
transcriber_id = f"{TRANSCRIBER_AGENT_NAME}-{room_name}"
async with api.LiveKitAPI() as lkapi:
try:
response = await lkapi.room.list_participants(
list=api.ListParticipantsRequest(room=room_name)
)
transcriber_exists = any(
p.kind == rtc.ParticipantKind.PARTICIPANT_KIND_AGENT
and p.identity == transcriber_id
for p in response.participants
)
if transcriber_exists:
logger.info(f"Transcriber exists in {room_name} - rejecting")
await job_req.reject()
else:
logger.info(f"Accepting job for {room_name}")
await job_req.accept(identity=transcriber_id)
except Exception:
logger.exception(f"Error processing job for {room_name}")
await job_req.reject()
def prewarm(proc: JobProcess):
"""Preload voice activity detection model."""
proc.userdata["vad"] = silero.VAD.load()
if __name__ == "__main__":
cli.run_app(
WorkerOptions(
entrypoint_fnc=entrypoint,
request_fnc=handle_transcriber_job_request,
prewarm_fnc=prewarm,
agent_name=TRANSCRIBER_AGENT_NAME,
permissions=WorkerPermissions(hidden=True),
)
)