mirror of https://github.com/microsoft/agent-framework.git synced 2026-06-16 21:04:09 +08:00

Files

T

Eduard van Valkenburg a2856d3b92 Python: restructure: Python samples into progressive 01-05 layout (#3862 )

* restructure: Python samples into progressive 01-05 layout

- 01-get-started/: 6 numbered steps (hello agent → hosting)
- 02-agents/: all agent concept samples (tools, middleware, providers, etc.)
- 03-workflows/: ALL existing workflow samples preserved as-is
- 04-hosting/: azure-functions, durabletask, a2a
- 05-end-to-end/: demos, evaluation, hosted agents
- Old files moved to _to_delete/ for review
- Added AGENTS.md with structure documentation
- autogen-migration/ and semantic-kernel-migration/ preserved at root

* fix: switch to AzureOpenAI Foundry, fix CI failures

- Switch all 01-get-started samples to AzureOpenAIResponsesClient with
  Azure AI Foundry project endpoint (AZURE_AI_PROJECT_ENDPOINT +
  AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME + AzureCliCredential)
- Add _to_delete/ and 05-end-to-end/ to pyrightconfig.samples.json excludes
- Fix test paths in packages/ that referenced old getting_started/ dirs:
  durabletask conftest + streaming test, azurefunctions conftest,
  devui conftest + capture_messages + openai_sdk_integration
- Fix workflow_as_agent_human_in_the_loop.py import (sibling import)
- Update hosting READMEs and tool comment paths
- Replace root README.md with new structure overview
- Update AGENTS.md to document Azure OpenAI Foundry as default provider

* cleanup: remove _to_delete folder, copy resource files to active dirs

All files in _to_delete/ were either:
- Exact duplicates of files in the new structure (240 files)
- Same file with only comment path updates (100 files)
- One import-fix diff (workflow_as_agent_human_in_the_loop.py)
- One superseded minimal_sample.py

Resource files (sample.pdf, countries.json, employees.pdf, weather.json)
copied to 02-agents/sample_assets/ and 02-agents/resources/ since active
samples reference them.

* fix: address PR review comments, centralize resources, remove root duplicates

- Fix type annotation in 04_memory.py (string union -> proper types)
- Fix old sample paths in observability files
- Fix grammar/spelling in observability samples
- Move sample_assets/ and resources/ to shared/ folder
- Remove 8 duplicate observability files from 02-agents root
- Update resource path references in multimodal_input and provider samples

* fix: update broken links from old getting_started paths to new structure

- Update relative paths in READMEs: getting_started/ → 01-get-started/,
  02-agents/, 03-workflows/, 04-hosting/, 05-end-to-end/
- Fix absolute GitHub URLs in package READMEs
- Fix broken link in ollama package README

* fix: convert absolute GitHub URLs to relative paths for link checker

Absolute URLs to python/samples/ on main branch 404 until PR merges.
Converted to relative paths that linkspector can verify locally.

* fix: update link for handoff sample moved to orchestrations/

* fix: update chatkit-integration README path from demos/ to 05-end-to-end/

* fix: update broken links in orchestrations README to match flat directory structure

a2856d3b92 · 2026-02-12 17:36:36 +00:00

History

orchestrations

Python: [BREAKING] Simplify API: ChatAgent -> Agent, ChatMessage -> Message (#3747 )

2026-02-10 23:04:32 +00:00

single_agent

Python: restructure: Python samples into progressive 01-05 layout (#3862 )

2026-02-12 17:36:36 +00:00

.gitignore

Python: AutoGen migration samples (#1738 )

2025-10-28 00:47:31 +00:00

pyrightconfig.json

Python: AutoGen migration samples (#1738 )

2025-10-28 00:47:31 +00:00

README.md

Python: [BREAKING] Simplify API: ChatAgent -> Agent, ChatMessage -> Message (#3747 )

2026-02-10 23:04:32 +00:00

README.md

AutoGen → Microsoft Agent Framework Migration Samples

This gallery helps AutoGen developers move to the Microsoft Agent Framework (AF) with minimal guesswork. Each script pairs AutoGen code with its AF equivalent so you can compare primitives, tooling, and orchestration patterns side by side while you migrate production workloads.

What's Included

Single-Agent Parity

01_basic_assistant_agent.py — Minimal AutoGen AssistantAgent and AF Agent comparison.
02_assistant_agent_with_tool.py — Function tool integration in both SDKs.
03_assistant_agent_thread_and_stream.py — Thread management and streaming responses.
04_agent_as_tool.py — Using agents as tools (hierarchical agent pattern) and streaming with tools.

Multi-Agent Orchestration

01_round_robin_group_chat.py — AutoGen RoundRobinGroupChat → AF GroupChatBuilder/SequentialBuilder.
02_selector_group_chat.py — AutoGen SelectorGroupChat → AF GroupChatBuilder.
03_swarm.py — AutoGen Swarm pattern → AF HandoffBuilder.
04_magentic_one.py — AutoGen MagenticOneGroupChat → AF MagenticBuilder.

Each script is fully async and the main() routine runs both implementations back to back so you can observe their outputs in a single execution.

Prerequisites

Python 3.10 or later.
Access to the necessary model endpoints (Azure OpenAI, OpenAI, etc.).
Installed SDKs: Install AutoGen and the Microsoft Agent Framework with:
```
pip install "autogen-agentchat autogen-ext[openai] agent-framework"
```
Service credentials exposed through environment variables (e.g., OPENAI_API_KEY).

Running Single-Agent Samples

From the repository root:

python samples/autogen-migration/single_agent/01_basic_assistant_agent.py

Every script accepts no CLI arguments and will first call the AutoGen implementation, followed by the AF version. Adjust the prompt or credentials inside the file as necessary before running.

Running Orchestration Samples

Advanced comparisons are in autogen-migration/orchestrations (RoundRobin, Selector, Swarm, Magentic). You can run them directly:

python samples/autogen-migration/orchestrations/01_round_robin_group_chat.py
python samples/autogen-migration/orchestrations/04_magentic_one.py

Tips for Migration

Default behavior differences: AutoGen's AssistantAgent is single-turn by default (max_tool_iterations=1), while AF's Agent is multi-turn and continues tool execution automatically.
Thread management: AF agents are stateless by default. Use agent.get_new_thread() and pass it to run() to maintain conversation state, similar to AutoGen's conversation context.
Tools: AutoGen uses FunctionTool wrappers; AF uses @tool decorators with automatic schema inference.
Orchestration patterns:
- RoundRobinGroupChat → SequentialBuilder or WorkflowBuilder
- SelectorGroupChat → GroupChatBuilder with LLM-based speaker selection
- Swarm → HandoffBuilder for agent handoff coordination
- MagenticOneGroupChat → MagenticBuilder for orchestrated multi-agent workflows