LiveKit Agent Deploy Error: Python 3.13 Incompatibility

Oct 11, 2025 by ADMIN 56 views

LiveKit Agent Deployment Failure: Python 3.13 and `av` Package Incompatibility

Hey guys! 👋 If you're diving into LiveKit and running into deployment snags, specifically with the av package, you're in the right place. This article breaks down a common issue where LiveKit agent deployment fails due to incompatibility between Python 3.13 and the av package. We'll explore the problem, understand why it happens, and provide you with a step-by-step guide to fix it. Let's get your agents up and running! 🚀

Understanding the Issue

So, what's the deal? You might encounter an error like this when trying to deploy a LiveKit agent:

error: Distribution `av==16.0.0 @ registry+https://pypi.org/simple` can't be installed because it doesn't have a source distribution or wheel for the current platform

hint: You're using CPython 3.13 (`cp313`), but `av` (v16.0.0) only has wheels with the following Python ABI tag: `cp310`

This error message is pretty clear: the av package (version 16.0.0) doesn't have pre-built wheels (compiled versions) that are compatible with Python 3.13 (cp313). It only has wheels for Python 3.10 (cp310).

But why does this happen? 🤔

The av package is a Python binding for FFmpeg, a powerful multimedia framework. It's used for tasks like encoding and decoding audio and video. Because it interacts with system-level libraries, av relies on compiled components called wheels. These wheels are specific to Python versions.

When you try to install av in an environment using Python 3.13, the package manager can't find a compatible wheel. This is because the av project hasn't yet built and released wheels that are specifically compiled for Python 3.13. It is very important to make sure each Python version has its version.

Why This Matters for LiveKit

LiveKit often uses packages like av for its real-time audio and video processing capabilities. If you're building LiveKit agents that depend on av, this incompatibility can halt your deployment process. You will need to find a way around this so that the application can work.

To understand the scope, let's break down the typical steps to reproduce this issue, as highlighted in the original problem:

Clone the Repository: Start by cloning the agent-starter-python repository from GitHub.

git clone https://github.com/livekit-examples/agent-starter-python
cd agent-starter-python-main

Set Up a Virtual Environment: Create and activate a virtual environment using Python 3.10.
```
uv venv --python 3.10 .venv
source .venv/bin/activate
```
A virtual environment is crucial here. It isolates your project's dependencies from the global Python installation, preventing conflicts. It's like having a separate little world for your project's requirements.
Sync Dependencies: Use uv sync to install the project's dependencies.
```
uv sync
```
This command reads your pyproject.toml file and installs all the necessary packages. It's the magic that brings in all the pieces your project needs to run smoothly.
Deploy the Agent: Attempt to deploy the LiveKit agent.
```
lk agent deploy
```
This is where the error typically surfaces. 💥

If you encounter this error, don't panic! We've got solutions coming up. 😉

Solutions to the Rescue!

Okay, so we know why the deployment is failing. Now, let's talk about how to fix it. Here are a couple of straightforward solutions you can try:

1. Use a Compatible Python Version

The most direct solution is to use a Python version that av does support. In this case, that means Python 3.10. This is mentioned in the error message itself:

hint: You're using CPython 3.13 (cp313), but av (v16.0.0) only has wheels with the following Python ABI tag: cp310

Here's how you can switch to Python 3.10:

Create a new virtual environment using Python 3.10 (if you haven't already).
```
uv venv --python 3.10 .venv
```
Activate the environment.
```
source .venv/bin/activate
```
Sync your dependencies.
```
uv sync
```
Try deploying again.
```
lk agent deploy
```

By using Python 3.10, you're providing a compatible environment for av to install and run without issues. Think of it as speaking the same language as the av package. 🗣️

2. Wait for `av` to Support Python 3.13 (or Later)

This is more of a long-term solution, but it's worth considering. The av project might release new versions with wheels compiled for Python 3.13 or later. Keep an eye on the av package's release notes or issue tracker. You can check their GitHub repository or PyPI page for updates.

Once a compatible version is released, you can upgrade the av package in your project and potentially use newer Python versions. 🎉

How to Check for Updates:

PyPI: Go to the av package page on PyPI (https://pypi.org/project/av/) and look for the latest releases.
GitHub: Check the av project's GitHub repository for releases and issues related to Python 3.13 support.

Digging Deeper: Why Virtual Environments Matter

We've mentioned virtual environments a couple of times, but let's really drill down on why they're so important in Python development, especially when you're dealing with dependencies like av.

A virtual environment is a self-contained directory that holds a specific Python interpreter and any packages you install for a particular project. It's like creating a little bubble 🫧 for your project where it can have its own private set of dependencies.

Here's why they're a lifesaver:

Dependency Isolation: Different projects often require different versions of the same package. Virtual environments prevent these versions from clashing. Imagine Project A needs requests==2.20.0, but Project B needs requests==2.28.1. Without virtual environments, you'd be in a dependency nightmare! 😱
Reproducibility: Virtual environments make your projects reproducible. By capturing the exact versions of your dependencies, you can ensure that your project works the same way on different machines and over time. This is critical for collaboration and deployment.
Cleanliness: Virtual environments keep your global Python installation clean. You won't clutter it with project-specific packages, which can lead to conflicts and unexpected behavior. A clean system is a happy system. 😊

Best Practices for Using Virtual Environments:

Create a virtual environment for every project. This is the golden rule. 🌟
Activate the environment before working on the project. This ensures you're using the correct Python interpreter and packages.
Use a dependency management tool like uv (as seen in the example) or pip with requirements.txt to track your project's dependencies.

Debugging Deployment Issues: A Pro's Toolkit

Even with the right solutions, deployment hiccups can still occur. Let's arm you with some debugging techniques to tackle those tricky situations. 💪

1. Reading Error Messages: Your First Clue

Error messages are your friends! They often contain valuable information about what went wrong. Don't just skim them; read them carefully. In the av incompatibility error, the message clearly states the issue:

error: Distribution `av==16.0.0` can't be installed because it doesn't have a source distribution or wheel for the current platform

hint: You're using CPython 3.13 (`cp313`), but `av` (v16.0.0) only has wheels with the following Python ABI tag: `cp310`

This message tells you:

The av package is the problem.
There's no compatible wheel for your Python version.
The supported Python ABI tag is cp310 (Python 3.10).

2. Checking Logs: The Detailed Story

Logs provide a more detailed view of what's happening during deployment. Look for log files in your project or deployment platform. They can reveal errors, warnings, and other helpful information that might not be visible on the command line.

In the original issue, the full log output was crucial for understanding the context:

% lk agent deploy

Using default project [monday-demo]
Using agent [agent]
Uploading 100% [==============================] (1.1 MB/s)
[+] Building 1.3s (12/15)
... (Docker build output) ...
0.212 error: Distribution `av==16.0.0 @ registry+https://pypi.org/simple` can't be installed because it doesn't have a source distribution or wheel for the current platform
...

The log showed that the error occurred during the uv sync --locked step within a Docker build, giving a clear indication of where to focus the troubleshooting efforts.

3. Isolating the Problem: Divide and Conquer

If you're facing a complex deployment issue, try to isolate the problem by breaking it down into smaller steps. For example:

Run commands locally: Try running the deployment commands locally within your virtual environment. This can help you identify if the issue is specific to the deployment environment or a general problem with your project.
Simplify your dependencies: Temporarily remove some dependencies to see if they're causing conflicts. This can help you narrow down the root cause.
Check your environment variables: Ensure that all required environment variables are set correctly in your deployment environment.

4. Seeking Help: Don't Be Afraid to Ask

If you're stuck, don't hesitate to seek help from the LiveKit community, online forums, or the av project's issue tracker. Often, someone else has encountered a similar issue and can offer guidance.

When asking for help, provide as much detail as possible:

Your project setup (LiveKit version, Python version, operating system).
The exact error message you're seeing.
The steps you've taken to try to resolve the issue.
Any relevant log output.

Wrapping Up: Smooth Deployments Ahead! 🚀

Alright, guys! We've covered a lot of ground in this article. You now understand the Python 3.13 and av incompatibility issue, know how to fix it by using a compatible Python version, and have some killer debugging techniques in your toolkit. 🛠️

Remember, deploying software can sometimes feel like navigating a maze, but with the right knowledge and approach, you can conquer any challenge. Keep experimenting, keep learning, and keep building awesome LiveKit applications! 🥳

If you have any questions or run into other deployment snags, don't hesitate to reach out. Happy coding! 🎉