what is the reason of this error: "package livekit-agents not found in any project files. Are you sure this is an agent?" I added livekit-agents to the requirements.txt and run the

lk agent create

from main directory. Tell me all the possible mistakes that I could make.

Thanks for reaching out, Berfin. I'm an AI assistant and I'm here to help. Give me a moment while I research this topic.

I am not using uv I use "python" command.

Thanks — good to know you’re using the plain

python

workflow. I’ll focus on what that means for the CLI error: "package livekit-agents not found in any project files. Are you sure this is an agent?" Short answer • The

lk

CLI does not detect Python agent projects from

requirements.txt

alone. You still need standard project metadata (a

pyproject.toml

in the project root) that lists

livekit-agents

as a dependency. Without that,

lk agent create

won’t recognize the project as an agent. What to check and fix (step-by-step) 1. Confirm you’re running the command from the project root ◦ Run

pwd

(or

cd

to the folder) and ensure the folder contains your agent code and any project files. 1. Ensure a

pyproject.toml

exists in the root ◦

requirements.txt

is not used by the CLI for detection. Create

pyproject.toml

if it’s missing. 1. Add

livekit-agents

to

pyproject.toml

dependencies ◦ Example minimal `pyproject.toml`:

[build-system]
     requires = ["hatchling"]
     build-backend = "hatchling.build"

     [project]
     name = "my-agent"
     version = "0.1.0"
     dependencies = [
       "livekit-agents>=1.0.0"
     ]

• Adjust the version and other dependencies as needed. 1. You can still use pip to install deps locally ◦ After adding

pyproject.toml

, run

pip install -r requirements.txt

or

pip install livekit-agents

as you prefer for local testing. The important part for

lk

is the

pyproject.toml

metadata. 1. Verify your agent entrypoint exists ◦ Ensure you have the agent server file (e.g.,

agent.py

) and an entry like:

from livekit.agents import AgentServer, cli

     server = AgentServer()
     # define handlers...
     if __name__ == "__main__":
         cli.run_app(server)

1. Retry

lk agent create

from the same directory ◦ Example:

lk agent create . --region us-west

Other things to double-check if it still fails • Filename typos: file must be exactly

pyproject.toml

. • Running

lk

from the wrong subdirectory. • If you have a

pyproject.toml

but didn’t list

livekit-agents

under

dependencies

, add it. • If everything looks right and detection still fails, share the directory listing (

ls

) and the contents of your

pyproject.toml

and

requirements.txt

and I’ll point to the exact issue. If you want, paste your

pyproject.toml

(or the directory listing) and I’ll review it and give the precise edits to make. Sources: Agents (Node.js) | livekit/livekit_composite | DeepWiki | SDKs | livekit/livekit_composite | DeepWiki | Build voice, video, and physical AI | LiveKit

[project] subdomain = "demo2-wkni8uu4" [agent] id = "CA_smefWJUPbxYg" this is an example livekit.toml file. How can I find my agent id. it is not in my livekit acount because I didn't deploy it I just started it.

Thanks — I see you have a

livekit.toml

with a

[agent] id = "..."

entry and you haven’t deployed the agent yet. Here’s exactly how agent IDs work and how you can find or get one. Short answer • The agent ID that appears in

livekit.toml

is created when an agent is registered (typically during

lk agent create

). If you never deployed or created the agent remotely, there will be no record of it in your LiveKit account. • If your

livekit.toml

already contains an

id

value, that value is the agent ID for that local configuration. It may have been generated earlier by a prior

lk agent create

(or copied from an example). But until you actually run

lk agent create

(or otherwise register the agent), that ID will not show up in your LiveKit dashboard. What you can do now • If you want to register/deploy and get a live agent record (so the ID appears in your account): a. From the project root (where

livekit.toml

lives) run:

lk agent create

1. After creation, run:

lk agent list

to confirm the agent appears and to see its ID in your account. • If you simply need an ID locally (for testing) and don’t want to deploy yet: ◦ You can keep a generated ID in

livekit.toml

and run the agent locally. That ID is just a local identifier until the agent is registered remotely. ◦ Note: a locally stored ID that was never registered won’t be visible in the LiveKit dashboard. • If you prefer a deterministic ID or want to re-use an ID: ◦ You can place the desired ID into

livekit.toml

manually before deploying. However, the canonical registration and authoritative record are created when you run `lk agent create`; the dashboard will reflect whatever agent was registered. How to verify what happened • If you think you might have previously run `lk agent create`: ◦ Run

lk agent list

to see registered agents. ◦ Check any CLI output from previous

lk agent create

runs — the command prints the created agent ID. If you’d like, tell me: • The contents of your

livekit.toml

(you already showed the relevant lines — that ID is the ID in that file), and • Whether you want to (A) deploy/register the agent now so the ID appears in your account, or (B) just run the agent locally for testing without registering. I can then give the exact

lk

commands and next steps for the option you choose. Sources: How to match the latency of the homepage agent | LiveKit | examples/drive-thru | livekit/livekit_composite | DeepWiki | Google AI and LiveKit | LiveKit Documentation | Where to find your Agent Logs | LiveKit

should I live livekit.toml file empty

Good question — don’t leave

livekit.toml

empty. It holds the agent configuration the CLI and LiveKit use to link your local project to a deployed agent. What to put in it depends on whether you plan to deploy or just run locally. What

livekit.toml

should contain • For deployment (recommended): include at least the

[agent]

id (if you already have one) and

[project]

subdomain or project details. Example minimal fields: ◦

[project]

with

subdomain = "your-subdomain"

◦

[agent]

with

id = "CA_..."

(this will be created when you run

lk agent create

if you don’t have one) • For local testing (no deploy): you can keep a minimal file with whichever values you need locally (subdomain or a locally chosen id). A locally set id is just a local identifier until you register the agent. When the agent id is created or required • The canonical agent id is created when you run

lk agent create

(which also registers/deploys the agent). After deployment the id in

livekit.toml

will match the agent record in your LiveKit account. • If you haven’t deployed, an id in

livekit.toml

is only local (it won’t appear in your dashboard). Recommended workflows • If you plan to deploy now: a. Ensure project files are present (including

pyproject.toml

for Python). b. Run

lk agent create

from the project root — this will register the agent and populate

livekit.toml

(or confirm the id). c. Run

lk agent list

to verify the agent appears in your account. • If you only want to run locally: ◦ Keep a minimal

livekit.toml

with any values you need. You can add or replace the real id later when you deploy. If you want, paste your current

livekit.toml

contents (or the directory listing) and tell me whether you want to deploy now or only test locally — I’ll tell you the exact edits or commands to run.

give me an example livekit.toml file. This should be exact file that I should add to my project

Thanks — below is an exact, ready-to-add

livekit.toml

you can drop into your project root. Replace the placeholder values with your real project subdomain and agent ID when you have them. Exact file content to add as

livekit.toml

[project]
subdomain = "your-project-subdomain"

[agent]
id = "your-agent-id"

What to replace • `your-project-subdomain`: the subdomain for your LiveKit Cloud project (example: the "myproject" from

<wss://myproject.livekit.cloud>

). • `your-agent-id`: the agent ID assigned when you register/deploy the agent. If you haven’t deployed yet, you can leave a placeholder; the

lk agent create

command will populate or confirm this value when you run it. If you want to create and register the agent now 1. Ensure your project root has

pyproject.toml

(so the CLI recognizes a Python agent). 2. From the project root run: ◦

lk agent create

1. After creation, run: ◦

lk agent list

The created agent ID will match the

id

field in your

livekit.toml

. If you’d like, paste your current

livekit.toml

(or tell me your project subdomain) and I’ll show the exact values you should put in. Sources: examples/drive-thru | livekit/livekit_composite | DeepWiki

I don't have an agent id, I just started my agent in another terminal but I didnt deploy is. After I start my agent from another terminal I run lk agent create but I am taking the errors. How will I take the agent id before deployment

Thanks — I understand: you started the agent locally in one terminal, tried to run

lk agent create

in another, and want to know how to get the agent ID before deploying. Short answer: the canonical agent ID is created when you register/deploy the agent with

lk agent create

. You can’t obtain an official LiveKit agent ID from the cloud before that registration step — the ID in

livekit.toml

only becomes authoritative after a successful create/deploy. What this means for your workflow • A local agent process you run manually does not automatically create an agent record in the LiveKit Cloud or produce an official agent ID visible in your account. •

lk agent create

is the command that registers the agent with LiveKit Cloud and returns the agent ID. That same ID is written into

livekit.toml

. • If you have an

id

already in

livekit.toml

, that is just a local value until

lk agent create

registers it. If you want the agent to be registered (and get the cloud agent ID) 1. Ensure your project is detectable by the CLI (project root with

pyproject.toml

listing

livekit-agents

, correct agent entrypoint, etc.). 2. From the project root run: ◦ lk agent create 1. After it completes, run: ◦ lk agent list The created agent will appear and the ID will match

livekit.toml

. If

lk agent create

is failing (causing the error you mentioned), I can help fix that so you can register and get the ID. To diagnose the failure please share: • The exact error output you see when running

lk agent create

(copy-paste the whole message). • A directory listing from the project root (output of

ls -la

). • The contents of

pyproject.toml

(if present) and

livekit.toml

. • The command you used to start the agent locally (the exact

python ...

command). With those details I’ll point out the missing file or misconfiguration and give the exact steps to get

lk agent create

to succeed and produce your agent ID.

pyproject kullanmadan yapamaz mıyım ben ya. pyproject yapısı kullanmak istemiyorum.

Anlıyorum — pyproject.toml kullanmak istemiyorsunuz. Kısa cevap: maalesef

lk agent create

komutu Python agent projelerini otomatik olarak tespit etmek için proje metadata’sına ihtiyaç duyar ve CLI

requirements.txt

ya da sadece yerel

python

komutuyla başlatılmış bir süreçten agent ID’si üretmez. Yani pyproject.toml (veya

uv

akışıyla oluşturulan metadata/lock dosyası) olmadan CLI’nin agent olarak tanıması ve kaydetmesi mümkün değil. Neden pyproject.toml gerekiyor (kısa açıklama) •

lk

CLI, projenin bir Python agent olduğunu otomatik olarak anlamak için

pyproject.toml

gibi standart proje dosyalarına bakar.

requirements.txt

bu tespit için kullanılmaz. • Agent kaydı (ve dolayısıyla resmi agent ID’si) CLI üzerinden

lk agent create

ile yapılır; bu komut proje metadata’sına dayanır. Lokal olarak başlattığınız process bu kaydı otomatik oluşturmaz. Alternatifler ve ne yapabilirsiniz • Hızlı çözüm (en kolay, önerilen): a. Projenize minimal bir

pyproject.toml

ekleyin — çok basit bir dosya yeterli. Örnek:

[build-system]
     requires = ["hatchling"]
     build-backend = "hatchling.build"

     [project]
     name = "my-agent"
     version = "0.1.0"
     dependencies = ["livekit-agents>=1.0.0"]

1.

lk agent create

komutunu proje kökünden çalıştırın — böylece agent kaydı yapılır ve gerçek agent ID’sini alırsınız. Bu yol, CLI ile uyumlu ve en az uğraş gerektiren yöntemdir. • Eğer pyproject.toml kullanmak istemiyorsanız (ancak yine de agent ID’ye ihtiyaç varsa): ◦ Manuel bir kayıt/ID alma yöntemi yok. Agent ID yalnızca

lk agent create

çalıştırılarak LiveKit tarafında oluşturulur. ◦ Yani pyproject olmadan CLI’yi çalıştırmayı atlayıp “elle” agent kaydı yapamazsınız. • Sadece lokal test yapmak istiyorsanız: ◦

livekit.toml

içine geçici bir ID koyabilir ve agent’ı lokal olarak başlatabilirsiniz; fakat bu ID LiveKit hesabınızda görünmez ve resmi kayıt sağlamaz. Deploy/CLI işlemleri için yine pyproject gerekecek. Nasıl yardımcı olabilirim şimdi? • İsterseniz size tam olarak yapıştırıp kullanabileceğiniz minimal

pyproject.toml

dosyasını ve adım adım komutları vereyim (1–2 komutla hazır hale gelirsiniz). • Ya da eğer pyproject eklemek istemiyorsanız, lokal test için

livekit.toml

içeriğini nasıl ayarlayacağınızı ve hangi kısıtlarla çalışacağınızı açıklayayım. Hangi yolu tercih ediyorsunuz? Pyproject eklemeyi kabul ederseniz, hemen size hazır bir dosya ve kısa komut listesi veririm.

livekit-agents azure-functions openai python-dotenv requests aiohttp pydantic PyYAML imageio-ffmpeg livekit-agents[azure,silero,openai,turn-detector]~=1.3 livekit-plugins-noise-cancellation~=0.2 azure-search-documents azure-cognitiveservices-speech azure-monitor-opentelemetry bunlara göre bana bir pyproject.toml hazırla

Thanks — below is a ready-to-add

pyproject.toml

you can drop into your project root. It includes the dependencies you listed (consolidated and deduplicated) and minimal metadata so the LiveKit CLI will recognize the project as a Python agent. Paste this exact content into a file named

pyproject.toml

in your project root:

[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"

[project]
name = "my-livekit-agent"
version = "0.1.0"
description = "LiveKit agent project"
readme = "README.md"
license = { text = "MIT" }
authors = [{ name = "Your Name", email = "<mailto:you@example.com|you@example.com>" }]
requires-python = ">=3.9"

dependencies = [
  "livekit-agents[azure,silero,openai,turn-detector]~=1.3",
  "livekit-agents",
  "livekit-plugins-noise-cancellation~=0.2",
  "azure-functions",
  "azure-search-documents",
  "azure-cognitiveservices-speech",
  "azure-monitor-opentelemetry",
  "openai",
  "python-dotenv",
  "requests",
  "aiohttp",
  "pydantic",
  "PyYAML",
  "imageio-ffmpeg"
]

[tool.hatch.build]
# Optional: include package discovery if you package this project
include = ["**/*.py", "pyproject.toml", "livekit.toml"]

Notes and small adjustments • I left

requires-python

as ">=3.9". Change this if your runtime differs. • The dependency list includes

livekit-agents[azure,silero,openai,turn-detector]~=1.3

as you requested. I also included a plain

"livekit-agents"

entry to ensure the core package is recognized; you can remove the plain entry if you prefer the extras-only notation. • If you maintain a

requirements.txt

for local installs, you can still use

pip install -r requirements.txt

. This

pyproject.toml

is used by the CLI to detect the project, not to replace pip for local installs. • After adding this file, run from the project root: a. (Optional) create/activate your virtual environment b. pip install -r requirements.txt OR pip install -e . (or pip install livekit-agents etc.) c. lk agent create If you want, tell me: • Your Python version and whether you want the project packaged (so I can tweak

requires-python

or packaging settings), and • Any extra metadata (author/company) to fill into the file.

sadece gerekli kısımlar kalsın sadeleştir:

[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"

[project]
name = "my-livekit-agent"
version = "0.1.0"
description = "LiveKit agent project"
readme = "README.md"
license = { text = "MIT" }
authors = [{ name = "Your Name", email = "<mailto:you@example.com|you@example.com>" }]
requires-python = ">=3.9"

dependencies = [
  "livekit-agents[azure,silero,openai,turn-detector]~=1.3",
  "livekit-agents",
  "livekit-plugins-noise-cancellation~=0.2",
  "azure-functions",
  "azure-search-documents",
  "azure-cognitiveservices-speech",
  "azure-monitor-opentelemetry",
  "openai",
  "python-dotenv",
  "requests",
  "aiohttp",
  "pydantic",
  "PyYAML",
  "imageio-ffmpeg"
]

[tool.hatch.build]
# Optional: include package discovery if you package this project
include = ["**/*.py", "pyproject.toml", "livekit.toml"]

Tamam — aşağıda yalnızca gerekli, sade ve doğrudan kullanılabilir bir

pyproject.toml

örneği var. Bu dosyayı proje köküne yapıştırın; LiveKit CLI projenizi Python agent olarak tanıyacaktır. pyproject.toml (sade)

[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"

[project]
name = "my-livekit-agent"
version = "0.1.0"
requires-python = ">=3.9"
dependencies = [
  "livekit-agents[azure,silero,openai,turn-detector]~=1.3",
  "livekit-plugins-noise-cancellation~=0.2",
  "azure-functions",
  "azure-search-documents",
  "azure-cognitiveservices-speech",
  "azure-monitor-opentelemetry",
  "openai",
  "python-dotenv",
  "requests",
  "aiohttp",
  "pydantic",
  "PyYAML",
  "imageio-ffmpeg"
]

Kısa notlar •

livekit-agents

paketini extras ile birlikte tek satırda belirttim; ayrıca ayrı bir

livekit-agents

girmeye gerek yok. •

requires-python

değerini kullandığınız Python sürümüne göre değiştirin (ör.

>=3.10

). • Bu dosya CLI’nin proje tipini tespit etmesi için yeterlidir. Lokal test için yine

pip install -r requirements.txt

veya

pip install .

kullanabilirsiniz. • Dosyayı ekledikten sonra proje kökünden çalıştırın: a. (opsiyonel) virtualenv aktif edin b. pip ile bağımlılıkları kurun (isteğe bağlı):

pip install -r requirements.txt

veya

pip install .

c.

lk agent create

İsterseniz şimdi: •

livekit.toml

içeriğinizi paylaşın; birlikte minimal hâlini de doğrularız, veya •

lk agent create

hata çıktısını atın; hangi eksik/yanlış satır olduğunu söyleyeyim.

unable to create agent: build failed for fra.ocir.io/axyci3pr8vxm/production-cloud-agents:p-2it6jaqrdw8-ca-drcmqxxuqfcp-v20260304200944: failed to solve: process "/bin/sh -c python \"LiveKit/agent_ticket.py\" download-files" did not complete successfully: exit code: 1

Anladım — build sırasında şu hata alıyorsunuz: "process "/bin/sh -c python \"LiveKit/agent_ticket.py\" download-files" did not complete successfully: exit code: 1 Bu, Docker build aşamasında

python LiveKit/agent_ticket.py download-files

komutunun başarısız olduğunu gösteriyor. Aşağıda adım adım olası nedenler ve hızlı çözümler var. Terminal çıktısını paylaşırsanız daha kesin yönlendirme yaparım. 1) Hemen kontrol etmeniz gerekenler • Dosya yolu ve isim ◦ Proje kökünde

LiveKit/agent_ticket.py

gerçekten var mı? (küçük/büyük harf duyarlılığına dikkat) ◦

.dockerignore

içinde

LiveKit/

veya

*.py

gibi dosyaları dışarıya atmamış mısınız? • Docker build komutundaki tırnak/kaçış sorunları ◦ Dockerfile içinde komut şu şekilde daha güvenli olmalı: python LiveKit/agent_ticket.py download-files • Çift tırnak ya da kaçışlar yanlış argüman oluşturuyor olabilir. 2) Script çalıştırılamıyorsa nedenleri • Script bağımlılıkları yüklenmemiş olabilir. Build sırasında gerekli paketler kuruluyor mu? (

pyproject.toml

içindeki bağımlılıklar doğru mı ve kurulum başarılı mı) • Script çalıştırıldığında eksik bir dosya veya network isteği hatası veriyor olabilir (ör. model dosyası indirme sırasında hata). 3) Lokal olarak test edin (hata ayıklama) • Aynı komutu yerelde çalıştırarak çıkışı görün: ◦ virtualenv açın, bağımlılıkları yükleyin (

pip install -r requirements.txt

veya

pip install .

) ◦ Çalıştırın: python LiveKit/agent_ticket.py download-files ◦ Hata mesajı burada daha okunaklı olur ve hangi dosya/istek hata veriyor gösterir. 4) Docker build bağlamı ve proje yapısı kontrolü • Proje kök dizini örneği: project-root/ • LiveKit/agent_ticket.py • pyproject.toml • livekit.toml • .dockerignore •

.dockerignore

içinde yanlışlıkla LiveKit/ veya agent_ticket.py engellenmediğinden emin olun. 5) Önerilen kısa düzeltmeler • Dockerfile veya build aşamasındaki satırı tırnaksız çalıştırın: RUN python LiveKit/agent_ticket.py download-files • Eğer script network veya kimlik doğrulama gerektiriyorsa build zamanı ortam değişkenleri veya creds eksik olabilir; indirme adımını container çalışırken değil, image içinde derleme öncesinde yapıyorsanız gerekli erişim sağlanmalı. 6) Paylaşırsanız doğrudan bakabilirim Lütfen aşağıdakileri gönderin; bunlara bakıp kesin çözümü söyleyeyim: •

Dockerfile

veya

lk

tarafından oluşturulan build aşamasını içeren logların tam kısmı (hata ile birlikte birkaç satır). •

LiveKit/agent_ticket.py

dosyasının ilk ~30 satırı (veya download kısmını gösteren fonksiyon). •

.dockerignore

içeriği. • Proje kökünün

ls -la

çıktısı. Özet: Hata büyük ihtimalle ya dosya yolunun build bağlamında bulunamamasından/çıkarılmasından ya da scriptin çalışması için gerekli bağımlılık/erişim eksikliğinden kaynaklanıyor. Lokal olarak aynı komutu çalıştırıp çıkan hatayı paylaşın — doğru düzeltmeyi birlikte yapalım. Sources: Introducing the Grok Voice Agent API in partnership with xAI | Introducing the Grok Voice Agent API in partnership with xAI

pyproject içine dowload files ekle

I don't have the answer you're looking for. You could also try asking your question: • in one of the other Slack channels or • to https://deepwiki.com/livekit/livekit_composite which is trained on all LiveKit source code If you find the answer, please post it here to help others!

=> ERROR [9/9] RUN python "LiveKit/agent_ticket.py" download- 0.4s ------ > [9/9] RUN python "LiveKit/agent_ticket.py" download-files: 0.348 Traceback (most recent call last): 0.349 File "/app/LiveKit/agent_ticket.py", line 13, in <module> 0.349 from azure.monitor.opentelemetry import configure_azure_monitor 0.349 File "/usr/local/lib/python3.13/site-packages/azure/monitor/opentelemetry/__init__.py", line 7, in <module> e_azure_monitor 0.349 File "/usr/local/lib/python3.13/site-packages/azure/monitor/opentelemetry/_configure.py", line 27, in <module> 0.349 from azure.monitor.opentelemetry._constants import ( 0.349 ...<15 lines>... 0.349 ) 0.349 File "/usr/local/lib/python3.13/site-packages/azure/monitor/opentelemetry/_constants.py", line 7, in <module> 0.349 from azure.monitor.opentelemetry.exporter._constants import ( # pylint: disable=import-error,no-name-in-module 0.349 _AZURE_MONITOR_DISTRO_VERSION_ARG, 0.349 ) 0.349 File "/usr/local/lib/python3.13/site-packages/azure/monitor/opentelemetry/exporter/__init__.py", line 7, in <module> 0.349 from azure.monitor.opentelemetry.exporter.export.logs._exporter import AzureMonitorLogExporter 0.349 File "/usr/local/lib/python3.13/site-packages/azure/monitor/opentelemetry/exporter/export/logs/_exporter.py", line 14, in <module>0.349 from opentelemetry.sdk._logs import LogData 0.349 ImportError: cannot import name 'LogData' from 'opentelemetry.sdk._logs' (/usr/local/lib/python3.13/site-packages/opentelemetry/sdk/_logs/__init__.py) ------ unable to create agent: build failed for fra.ocir.io/axyci3pr8vxm/production-cloud-agents:p-2it6jaqrdw8-ca-drcmqxxuqfcp-v20260304200944: failed to solve: process "/bin/sh -c python \"LiveKit/agent_ticket.py\" download-files" did not complete successfully: exit code: 1