Initial working
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Ben Cherry
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.env
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.env.*
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.DS_Store
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__pycache__
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.idea
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KMS
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uv.lock
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.venv
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.vscode
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*.egg-info
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.pytest_cache
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.ruff_cache
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MIT License
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Copyright (c) 2025 LiveKit, Inc.
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.
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<a href="https://livekit.io/">
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<img src="./.github/assets/livekit-mark.png" alt="LiveKit logo" width="100" height="100">
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</a>
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# Voice AI Assistant with LiveKit Agents
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<p>
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<a href="https://cloud.livekit.io/projects/p_/sandbox"><strong>Deploy a sandbox app</strong></a>
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•
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<a href="https://docs.livekit.io/agents/">LiveKit Agents Docs</a>
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•
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<a href="https://livekit.io/cloud">LiveKit Cloud</a>
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•
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<a href="https://blog.livekit.io/">Blog</a>
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</p>
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A simple voice AI assistant built with [LiveKit Agents for Python](https://github.com/livekit/agents).
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## Dev Setup
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Clone the repository and install dependencies to a virtual environment:
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```console
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cd agent-starter-python
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uv sync
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```
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Set up the environment by copying `.env.example` to `.env` and filling in the required values:
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- `LIVEKIT_URL`
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- `LIVEKIT_API_KEY`
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- `LIVEKIT_API_SECRET`
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- `OPENAI_API_KEY`
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- `DEEPGRAM_API_KEY`
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You can also do this automatically using the LiveKit CLI:
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```bash
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lk app env -w .env
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```
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Run the agent:
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```console
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uv run python src/agent.py dev
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```
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This agent requires a frontend application to communicate with. Use a [starter app](https://docs.livekit.io/agents/start/frontend/#starter-apps), our hosted [Sandbox](https://cloud.livekit.io/projects/p_/sandbox) frontends, or the [LiveKit Agents Playground](https://agents-playground.livekit.io/).
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import pytest
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from livekit.agents import AgentSession, llm
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from livekit.plugins import openai
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from agent import Assistant
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def _llm() -> llm.LLM:
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return openai.LLM(model="gpt-4o-mini", temperature=0.45)
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@pytest.mark.asyncio
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async def test_greeting() -> None:
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async with (
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_llm() as llm,
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AgentSession(llm=llm) as session,
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):
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await session.start(Assistant())
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result = await session.run(user_input="Hi there how are you?")
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await result.expect.message(role="assistant").judge(
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llm, intent="should offer a friendly greeting to the user"
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)
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result.expect.no_more_events()
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[build-system]
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requires = ["setuptools>=61.0", "wheel"]
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build-backend = "setuptools.build_meta"
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[project]
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name = "agent-starter-python"
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version = "0.1.0"
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description = "Simple voice AI assistant built with LiveKit Agents for Python"
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requires-python = ">=3.9"
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dependencies = [
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"livekit-agents",
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"livekit-plugins-openai",
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"livekit-plugins-turn-detector",
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"livekit-plugins-silero",
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"livekit-plugins-cartesia",
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"livekit-plugins-deepgram",
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"python-dotenv",
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"livekit-plugins-noise-cancellation~=0.2.1",
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]
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[dependency-groups]
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dev = [
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"pytest",
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"pytest-asyncio",
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]
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[tool.uv.sources]
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livekit-agents = { path = "../../livekit/agents/livekit-agents", editable = true }
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livekit-plugins-openai = { path = "../../livekit/agents/livekit-plugins/livekit-plugins-openai", editable = true }
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livekit-plugins-turn-detector = { path = "../../livekit/agents/livekit-plugins/livekit-plugins-turn-detector", editable = true }
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livekit-plugins-silero = { path = "../../livekit/agents/livekit-plugins/livekit-plugins-silero", editable = true }
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livekit-plugins-cartesia = { path = "../../livekit/agents/livekit-plugins/livekit-plugins-cartesia", editable = true }
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livekit-plugins-deepgram = { path = "../../livekit/agents/livekit-plugins/livekit-plugins-deepgram", editable = true }
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[tool.setuptools.packages.find]
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where = ["src"]
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[tool.setuptools.package-dir]
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"" = "src"
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[tool.pytest.ini_options]
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asyncio_mode = "auto"
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asyncio_default_fixture_loop_scope = "function"
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# This file makes the src directory a Python package
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@@ -0,0 +1,40 @@
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from dotenv import load_dotenv
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from livekit import agents
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from livekit.agents import AgentSession, Agent, RoomInputOptions
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from livekit.plugins import openai, noise_cancellation, silero, deepgram, cartesia
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from livekit.plugins.turn_detector.multilingual import MultilingualModel
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load_dotenv()
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class Assistant(Agent):
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def __init__(self) -> None:
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super().__init__(instructions="You are a helpful voice AI assistant.")
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async def entrypoint(ctx: agents.JobContext):
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session = AgentSession(
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stt=deepgram.STT(),
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llm=openai.LLM(model="gpt-4o-mini"),
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tts=cartesia.TTS(),
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vad=silero.VAD.load(),
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turn_detection=MultilingualModel(),
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)
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await session.start(
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room=ctx.room,
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agent=Assistant(),
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room_input_options=RoomInputOptions(
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# LiveKit Cloud enhanced noise cancellation
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# - If self-hosting, omit this parameter
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# - For telephony applications, use `BVCTelephony` for best results
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noise_cancellation=noise_cancellation.BVC(),
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),
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)
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await ctx.connect()
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if __name__ == "__main__":
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agents.cli.run_app(agents.WorkerOptions(entrypoint_fnc=entrypoint))
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