Evan Mattson
d5e240b375
* Update github_copilot package for github-copilot-sdk>=0.1.32 (#4549) - Update requires-python from >=3.10 to >=3.11 - Remove Python 3.10 classifier - Update mypy python_version to 3.11 - Update dependency to github-copilot-sdk>=0.1.32 - Fix ToolResult API: use snake_case kwargs (text_result_for_llm, result_type) instead of camelCase (textResultForLlm, resultType) - Update test assertions to use attribute access on ToolResult - Add ToolResult type assertions to tool handler tests Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix tests to use ToolInvocation dataclass instead of plain dict (#4549) Update test_github_copilot_agent.py to pass ToolInvocation objects to tool handlers instead of plain dicts, matching the github-copilot-sdk>=0.1.32 API where ToolInvocation is a dataclass with an .arguments attribute. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Add regression tests for ToolInvocation contract (#4549) Add tests to lock in the new ToolInvocation-based calling convention: - test_tool_handler_rejects_raw_dict_invocation: verifies passing a raw dict (old calling convention) raises TypeError/AttributeError - test_tool_handler_with_empty_arguments: verifies ToolInvocation with empty arguments works correctly for no-arg tools Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Revert requires-python to >=3.10 to avoid breaking CI (#4549) The repo CI runs with Python 3.10 (uv sync --all-packages) and all other packages require >=3.10. Raising this package to >=3.11 would break the shared install flow. The SDK dependency version constraint (>=0.1.32) will enforce any Python version requirement from the SDK itself. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix min Python version for github_copilot package to >=3.11 github-copilot-sdk>=0.1.32 requires Python>=3.11, which conflicts with the package's declared >=3.10 minimum, breaking uv sync. * Bump py version for GH workflows to 3.11, exclude GHCP sdk from 3.10 items * Fix uv command * Fixes * Update samples --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Python Samples
This directory contains samples demonstrating the capabilities of Microsoft Agent Framework for Python.
Structure
| Folder | Description |
|---|---|
01-get-started/ |
Progressive tutorial: hello agent → hosting |
02-agents/ |
Deep-dive by concept: tools, middleware, providers, orchestrations |
03-workflows/ |
Workflow patterns: sequential, concurrent, state, declarative |
04-hosting/ |
Deployment: Azure Functions, Durable Tasks, A2A |
05-end-to-end/ |
Full applications, evaluation, demos |
Getting Started
Start with 01-get-started/ and work through the numbered files:
- 01_hello_agent.py — Create and run your first agent
- 02_add_tools.py — Add function tools with
@tool - 03_multi_turn.py — Multi-turn conversations with
AgentThread - 04_memory.py — Agent memory with
ContextProvider - 05_first_workflow.py — Build a workflow with executors and edges
- 06_host_your_agent.py — Host your agent via Azure Functions
Prerequisites
pip install agent-framework --pre
Environment Variables
Samples call load_dotenv() to automatically load environment variables from a .env file in the python/ directory. This is a convenience for local development and testing.
For local development, set up your environment using any of these methods:
Option 1: Using a .env file (recommended for local development):
- Copy
.env.exampleto.envin thepython/directory:cp .env.example .env - Edit
.envand set your values (API keys, endpoints, etc.)
Option 2: Export environment variables directly:
export AZURE_AI_PROJECT_ENDPOINT="your-foundry-project-endpoint"
export AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME="gpt-4o"
Option 3: Using env_file_path parameter (for per-client configuration):
All client classes (e.g., OpenAIChatClient, AzureOpenAIResponsesClient) support an env_file_path parameter to load environment variables from a specific file:
from agent_framework.openai import OpenAIChatClient
# Load from a custom .env file
client = OpenAIChatClient(env_file_path="path/to/custom.env")
This allows different clients to use different configuration files if needed.
For the getting-started samples, you'll need at minimum:
AZURE_AI_PROJECT_ENDPOINT="your-foundry-project-endpoint"
AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME="gpt-4o"
Note for production: In production environments, set environment variables through your deployment platform (e.g., Azure App Settings, Kubernetes ConfigMaps/Secrets) rather than using .env files. The load_dotenv() call in samples will have no effect when a .env file is not present, allowing environment variables to be loaded from the system.
For Azure authentication, run az login before running samples.
Note on XML tags
Some sample files include XML-style snippet tags (for example <snippet_name> and </snippet_name>). These are used by our documentation tooling and can be ignored or removed when you use the samples outside this repository.
Additional Resources
- Agent Framework Documentation
- AGENTS.md — Structure documentation for maintainers
- SAMPLE_GUIDELINES.md — Coding conventions for samples