agent-framework/python/DEV_SETUP.md

Dev Setup

This document describes how to setup your environment with Python and uv, if you're working on new features or a bug fix for Agent Framework, or simply want to run the tests included.

For coding standards and conventions, see CODING_STANDARD.md.

System setup

We are using a tool called poethepoet for task management and uv for dependency management. At the end of this document, you will find the available Poe tasks.

If you're on WSL

Check that you've cloned the repository to ~/workspace or a similar folder. Avoid /mnt/c/ and prefer using your WSL user's home directory.

Ensure you have the WSL extension for VSCode installed.

Using uv

uv allows us to use AF from the local files, without worrying about paths, as if you had AF pip package installed.

To install AF and all the required tools in your system, first, navigate to the directory containing this DEV_SETUP using your chosen shell.

For windows (non-WSL)

Check the uv documentation for the installation instructions. At the time of writing this is the command to install uv:

powershell -c "irm https://astral.sh/uv/install.ps1 | iex"

For WSL, Linux or MacOS

Check the uv documentation for the installation instructions. At the time of writing this is the command to install uv:

curl -LsSf https://astral.sh/uv/install.sh | sh

Alternative for MacOS

For MacOS users, Homebrew provides an easy installation of uv with the uv Formulae

brew install uv

After installing uv

You can then run the following commands manually:

# Install Python 3.10, 3.11, 3.12, and 3.13
uv python install 3.10 3.11 3.12 3.13
# Create a virtual environment with Python 3.10 (you can change this to 3.11, 3.12 or 3.13)
$PYTHON_VERSION = "3.10"
uv venv --python $PYTHON_VERSION
# Install AF and all dependencies
uv sync --dev
# Install all the tools and dependencies
uv run poe install
# Install prek hooks
uv run poe prek-install

Alternatively, you can reinstall the venv, pacakges, dependencies and prek hooks with a single command (but this requires poe in the current env), this is especially useful if you want to switch python versions:

uv run poe setup -p 3.13

You can then run different commands through Poe the Poet, use uv run poe to discover which ones.

VSCode Setup

Install the Python extension for VSCode.

Open the python folder in VSCode.

The workspace for python should be rooted in the ./python folder.

Open any of the .py files in the project and run the Python: Select Interpreter command from the command palette. Make sure the virtual env (default path is .venv) created by uv is selected.

LLM setup

Make sure you have an OpenAI API Key or Azure OpenAI service key

There are two methods to manage keys, secrets, and endpoints:

1. Store them in environment variables. AF Python leverages pydantic settings to load keys, secrets, and endpoints from the environment.

   When you are using VSCode and have the python extension setup, it automatically loads environment variables from a .env file, so you don't have to manually set them in the terminal. During runtime on different platforms, environment settings set as part of the deployments should be used.

2. Store them in a separate .env file, like dev.env, you can then pass that name into the constructor for most services, to the env_file_path parameter, see below.

   Make sure to add *.env to your .gitignore file.

Example for file-based setup with OpenAI Chat Completions

To configure a .env file with just the keys needed for OpenAI Chat Completions, you can create a openai.env (this name is just as an example, a single .env with all required keys is more common) file in the root of the python folder with the following content:

Content of .env or openai.env:

OPENAI_API_KEY=""
OPENAI_CHAT_MODEL_ID="gpt-4o-mini"

You will then configure the ChatClient class with the keyword argument env_file_path:

from agent_framework.openai import OpenAIChatClient

chat_client = OpenAIChatClient(env_file_path="openai.env")

Tests

All the tests are located in the tests folder of each package. There are tests that are marked with a @skip_if_..._integration_tests_disabled decorator, these are integration tests that require an external service to be running, like OpenAI or Azure OpenAI.

If you want to run these tests, you need to set the environment variable RUN_INTEGRATION_TESTS to true and have the appropriate key per services set in your environment or in a .env file.

Alternatively, you can run them using VSCode Tasks. Open the command palette (Ctrl+Shift+P) and type Tasks: Run Task. Select Test from the list.

If you want to run the tests for a single package, you can use the uv run poe test command with the package name as an argument. For example, to run the tests for the agent_framework package, you can use:

uv run poe --directory packages/core test

These commands also output the coverage report.

Code quality checks

To run the same checks that run during a commit and the GitHub Action Python Code Quality, you can use this command, from the python folder:

    uv run poe check

Ideally you should run these checks before committing any changes, when you install using the instructions above the prek hooks should be installed already.

Code Coverage

We try to maintain a high code coverage for the project. To run the code coverage on the unit tests, you can use the following command:

    uv run poe test

This will show you which files are not covered by the tests, including the specific lines not covered. Make sure to consider the untested lines from the code you are working on, but feel free to add other tests as well, that is always welcome!

Catching up with the latest changes

There are many people committing to Semantic Kernel, so it is important to keep your local repository up to date. To do this, you can run the following commands:

    git fetch upstream main
    git rebase upstream/main
    git push --force-with-lease

or:

    git fetch upstream main
    git merge upstream/main
    git push

This is assuming the upstream branch refers to the main repository. If you have a different name for the upstream branch, you can replace upstream with the name of your upstream branch.

After running the rebase command, you may need to resolve any conflicts that arise. If you are unsure how to resolve a conflict, please refer to the GitHub's documentation on resolving conflicts, or for VSCode.

Task automation

Available Poe Tasks

This project uses poethepoet for task management and uv for dependency management.

Setup and Installation

Once uv is installed, and you do not yet have a virtual environment setup:

uv venv

and then you can run the following tasks:

uv sync --all-extras --dev

After this initial setup, you can use the following tasks to manage your development environment. It is advised to use the following setup command since that also installs the prek hooks.

setup

Set up the development environment with a virtual environment, install dependencies and prek hooks:

uv run poe setup
# or with specific Python version
uv run poe setup --python 3.12

install

Install all dependencies including extras and dev dependencies, including updates:

uv run poe install

venv

Create a virtual environment with specified Python version or switch python version:

uv run poe venv
# or with specific Python version
uv run poe venv --python 3.12

prek-install

Install prek hooks:

uv run poe prek-install

Code Quality and Formatting

Each of the following tasks run against both the main agent-framework package and the extension packages in parallel, ensuring consistent code quality across the project.

fmt (format)

Format code using ruff (runs in parallel across all packages):

uv run poe fmt

lint

Run linting checks and fix issues (runs in parallel across all packages):

uv run poe lint

pyright

Run Pyright type checking (runs in parallel across all packages):

uv run poe pyright

mypy

Run MyPy type checking (runs in parallel across all packages):

uv run poe mypy

typing

Run both Pyright and MyPy type checking:

uv run poe typing

Code Validation

markdown-code-lint

Lint markdown code blocks:

uv run poe markdown-code-lint

Comprehensive Checks

check-packages

Run all package-level quality checks (format, lint, pyright, mypy) in parallel across all packages. This runs the full cross-product of (package × check) concurrently:

uv run poe check-packages

check

Run all quality checks including package checks, samples, tests and markdown lint:

uv run poe check

Testing

test

Run unit tests with coverage by invoking the test task in each package in parallel:

uv run poe test

To run tests for a specific package only, use the --directory flag:

# Run tests for the core package
uv run --directory packages/core poe test

# Run tests for the azure-ai package
uv run --directory packages/azure-ai poe test

all-tests

Run all tests in a single pytest invocation across all packages in parallel (excluding lab and devui). This is faster than test as it uses pytest's parallel execution:

uv run poe all-tests

all-tests-cov

Same as all-tests but with coverage reporting enabled:

uv run poe all-tests-cov

Building and Publishing

build

Build all packages:

uv run poe build

clean-dist

Clean the dist directories:

uv run poe clean-dist

publish

Publish packages to PyPI:

uv run poe publish

Prek Hooks

Prek hooks run automatically on commit and execute a subset of the checks on changed files only. Package-level checks (fmt, lint, pyright) run in parallel but only for packages with changed files. Markdown and sample checks are skipped when no relevant files were changed. If the core package is changed, all packages are checked. You can also run all checks using prek directly:

uv run prek run -a