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1from livekit.agents import JobContext, WorkerOptions, cli, voice_assistant
2from livekit.plugins import openai, silero
3
4async def entrypoint(ctx: JobContext):
5 # Initialize the Voice Assistant
6 assistant = voice_assistant.VoiceAssistant(
7 vad=silero.VAD.load(),
8 stt=openai.STT(),
9 llm=openai.LLM(),
10 tts=openai.TTS(),
11 )
12
13 # Connect and start interaction
14 assistant.start(ctx.room)
15 await assistant.say("Hello! How can I help you today?")
16
17 # Listen for media tracks
18 @ctx.room.on("track_published")
19 def on_track(publication, participant):
20 if publication.track.kind == "video":
21 print(f"Processing video track from {participant.identity}")
22
23if __name__ == "__main__":
24 cli.run_app(WorkerOptions(entrypoint_fnc=entrypoint))
1from livekit.agents import JobContext, WorkerOptions, cli, voice_assistant
2from livekit.plugins import openai, silero
3
4async def entrypoint(ctx: JobContext):
5 # Initialize the Voice Assistant
6 assistant = voice_assistant.VoiceAssistant(
7 vad=silero.VAD.load(),
8 stt=openai.STT(),
9 llm=openai.LLM(),
10 tts=openai.TTS(),
11 )
12
13 # Connect and start interaction
14 assistant.start(ctx.room)
15 await assistant.say("Hello! How can I help you today?")
16
17 # Listen for media tracks
18 @ctx.room.on("track_published")
19 def on_track(publication, participant):
20 if publication.track.kind == "video":
21 print(f"Processing video track from {participant.identity}")
22
23if __name__ == "__main__":
24 cli.run_app(WorkerOptions(entrypoint_fnc=entrypoint))
1from livekit.agents import JobContext, WorkerOptions, cli, voice_assistant
2from livekit.plugins import openai, silero
3
4async def entrypoint(ctx: JobContext):
5 # Initialize the Voice Assistant
6 assistant = voice_assistant.VoiceAssistant(
7 vad=silero.VAD.load(),
8 stt=openai.STT(),
9 llm=openai.LLM(),
10 tts=openai.TTS(),
11 )
12
13 # Connect and start interaction
14 assistant.start(ctx.room)
15 await assistant.say("Hello! How can I help you today?")
16
17 # Listen for media tracks
18 @ctx.room.on("track_published")
19 def on_track(publication, participant):
20 if publication.track.kind == "video":
21 print(f"Processing video track from {participant.identity}")
22
23if __name__ == "__main__":
24 cli.run_app(WorkerOptions(entrypoint_fnc=entrypoint))
1from livekit.agents import JobContext, WorkerOptions, cli, voice_assistant
2from livekit.plugins import openai, silero
3
4async def entrypoint(ctx: JobContext):
5 # Initialize the Voice Assistant
6 assistant = voice_assistant.VoiceAssistant(
7 vad=silero.VAD.load(),
8 stt=openai.STT(),
9 llm=openai.LLM(),
10 tts=openai.TTS(),
11 )
12
13 # Connect and start interaction
14 assistant.start(ctx.room)
15 await assistant.say("Hello! How can I help you today?")
16
17 # Listen for media tracks
18 @ctx.room.on("track_published")
19 def on_track(publication, participant):
20 if publication.track.kind == "video":
21 print(f"Processing video track from {participant.identity}")
22
23if __name__ == "__main__":
24 cli.run_app(WorkerOptions(entrypoint_fnc=entrypoint))
1 cli.run_app(WorkerOptions(entrypoint_fnc=entrypoint))
2if __name__ == "__main__":
3
4 print(f"Processing video track from {participant.identity}")
5 if publication.track.kind == "video":
6 def on_track(publication, participant):
7 @ctx.room.on("track_published")
8 # Listen for media tracks
9
10 await assistant.say("Hello! How can I help you today?")
11 assistant.start(ctx.room)
12 # Connect and start interaction
13
14 )
15 tts=openai.TTS(),
16 llm=openai.LLM(),
17 stt=openai.STT(),
18 vad=silero.VAD.load(),
19 assistant = voice_assistant.VoiceAssistant(
20 # Initialize the Voice Assistant
21async def entrypoint(ctx: JobContext):
22
23from livekit.plugins import openai, silero
24from livekit.agents import JobContext, WorkerOptions, cli, voice_assistant
1 cli.run_app(WorkerOptions(entrypoint_fnc=entrypoint))
2if __name__ == "__main__":
3
4 print(f"Processing video track from {participant.identity}")
5 if publication.track.kind == "video":
6 def on_track(publication, participant):
7 @ctx.room.on("track_published")
8 # Listen for media tracks
9
10 await assistant.say("Hello! How can I help you today?")
11 assistant.start(ctx.room)
12 # Connect and start interaction
13
14 )
15 tts=openai.TTS(),
16 llm=openai.LLM(),
17 stt=openai.STT(),
18 vad=silero.VAD.load(),
19 assistant = voice_assistant.VoiceAssistant(
20 # Initialize the Voice Assistant
21async def entrypoint(ctx: JobContext):
22
23from livekit.plugins import openai, silero
24from livekit.agents import JobContext, WorkerOptions, cli, voice_assistant
1 cli.run_app(WorkerOptions(entrypoint_fnc=entrypoint))
2if __name__ == "__main__":
3
4 print(f"Processing video track from {participant.identity}")
5 if publication.track.kind == "video":
6 def on_track(publication, participant):
7 @ctx.room.on("track_published")
8 # Listen for media tracks
9
10 await assistant.say("Hello! How can I help you today?")
11 assistant.start(ctx.room)
12 # Connect and start interaction
13
14 )
15 tts=openai.TTS(),
16 llm=openai.LLM(),
17 stt=openai.STT(),
18 vad=silero.VAD.load(),
19 assistant = voice_assistant.VoiceAssistant(
20 # Initialize the Voice Assistant
21async def entrypoint(ctx: JobContext):
22
23from livekit.plugins import openai, silero
24from livekit.agents import JobContext, WorkerOptions, cli, voice_assistant
1 cli.run_app(WorkerOptions(entrypoint_fnc=entrypoint))
2if __name__ == "__main__":
3
4 print(f"Processing video track from {participant.identity}")
5 if publication.track.kind == "video":
6 def on_track(publication, participant):
7 @ctx.room.on("track_published")
8 # Listen for media tracks
9
10 await assistant.say("Hello! How can I help you today?")
11 assistant.start(ctx.room)
12 # Connect and start interaction
13
14 )
15 tts=openai.TTS(),
16 llm=openai.LLM(),
17 stt=openai.STT(),
18 vad=silero.VAD.load(),
19 assistant = voice_assistant.VoiceAssistant(
20 # Initialize the Voice Assistant
21async def entrypoint(ctx: JobContext):
22
23from livekit.plugins import openai, silero
24from livekit.agents import JobContext, WorkerOptions, cli, voice_assistant
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About RTC LEAGUE

We builds real-time applications using amodular, production-proven architecturethat connects WebRTC

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Our platforms support HTTP, WebSocket, and WebRTC transport layers, allowing low-latency communication across browsers, mobile apps, and enterprise systems. We work with Swift, Flutter, React, and Python SDKs, enabling teams to ship WebRTC applications across iOS, Android, web, and backend services.

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RTC League empowers businesses with real-time communication, cloud infrastructure, and AI solutions designed for performance, security, and long-term scalability.

With global delivery experience and a deep focus on WebRTC technology, we help organizations move beyond prototypes and deploy real-world systems that handle thousands of concurrent sessions, AI-driven conversations, and mission-critical workflows.

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RTC League designs WebRTC and AI systems that meet global compliance and security standards for enterprise Grade Infrastructure You Can Trust

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