mirror of
https://github.com/microsoft/agent-framework.git
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Eduard van Valkenburg
0521f5bed8
* [BREAKING] Rename ChatAgent -> Agent, ChatMessage -> Message, ChatClientProtocol -> SupportsChatGetResponse Simplify the public API by removing redundant 'Chat' prefix from core types: - ChatAgent -> Agent - RawChatAgent -> RawAgent - ChatMessage -> Message - ChatClientProtocol -> SupportsChatGetResponse Also renamed internal WorkflowMessage (was Message in _runner_context) to avoid collision. No backward compatibility aliases - this is a clean breaking change. * [BREAKING] Rename Agent chat_client parameter to client * Fix rebase issues: WorkflowMessage references and broken markdown links * Fix formatting and lint issues from code quality checks * Fix import ordering in workflow sample files * fixed rebase * Fix test failures: use WorkflowMessage and A2AMessage after ChatMessage→Message rename - Replace Message(data=..., source_id=...) with WorkflowMessage(...) in workflow tests - Fix isinstance check in A2A agent to use A2AMessage instead of Message - Fix import in test_workflow_observability.py (Message→WorkflowMessage) * Fix lint, fmt, and sample errors after ChatMessage→Message rename - Auto-fix 70+ ruff lint issues across samples (ChatMessage→Message refs) - Fix HostedVectorStoreContent→Content.from_hosted_vector_store in file search sample - Fix _normalize_messages→normalize_messages in custom agent sample - Fix context.terminate→raise MiddlewareTermination in middleware samples - Fix with_update_hook→with_transform_hook in override middleware sample - Add TOptions_co import back to custom_chat_client sample - Add noqa for FastAPI File() default in chatkit sample - Fix B023 loop variable capture in weather agent sample * fix: update Agent constructor calls from chat_client to client in declaration-only tool tests * fix: add register_cleanup to devui lazy-loading proxy and type stub * fixed tests and updated new pieces * fix agui typevar * fix merge errors * fix merge conflicts * fiux merge * Remove unused links --------- Co-authored-by: Evan Mattson <evan.mattson@microsoft.com>
76 lines
5.5 KiB
Markdown
76 lines
5.5 KiB
Markdown
# Semantic Kernel → Microsoft Agent Framework Migration Samples
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This gallery helps Semantic Kernel (SK) developers move to the Microsoft Agent Framework (AF) with minimal guesswork. Each script pairs SK code with its AF equivalent so you can compare primitives, tooling, and orchestration patterns side by side while you migrate production workloads.
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## What’s Included
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## What’s Included
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### Chat completion parity
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- [01_basic_chat_completion.py](chat_completion/01_basic_chat_completion.py) — Minimal SK `ChatCompletionAgent` and AF `Agent` conversation.
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- [02_chat_completion_with_tool.py](chat_completion/02_chat_completion_with_tool.py) — Adds a simple tool/function call in both SDKs.
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- [03_chat_completion_thread_and_stream.py](chat_completion/03_chat_completion_thread_and_stream.py) — Demonstrates thread reuse and streaming prompts.
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### Azure AI agent parity
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- [01_basic_azure_ai_agent.py](azure_ai_agent/01_basic_azure_ai_agent.py) — Create and run an Azure AI agent end to end.
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- [02_azure_ai_agent_with_code_interpreter.py](azure_ai_agent/02_azure_ai_agent_with_code_interpreter.py) — Enable hosted code interpreter/tool execution.
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- [03_azure_ai_agent_threads_and_followups.py](azure_ai_agent/03_azure_ai_agent_threads_and_followups.py) — Persist threads and follow-ups across invocations.
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### OpenAI Assistants API parity
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- [01_basic_openai_assistant.py](openai_assistant/01_basic_openai_assistant.py) — Baseline assistant comparison.
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- [02_openai_assistant_with_code_interpreter.py](openai_assistant/02_openai_assistant_with_code_interpreter.py) — Code interpreter tool usage.
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- [03_openai_assistant_function_tool.py](openai_assistant/03_openai_assistant_function_tool.py) — Custom function tooling.
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### OpenAI Responses API parity
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- [01_basic_responses_agent.py](openai_responses/01_basic_responses_agent.py) — Basic responses agent migration.
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- [02_responses_agent_with_tool.py](openai_responses/02_responses_agent_with_tool.py) — Tool-augmented responses workflows.
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- [03_responses_agent_structured_output.py](openai_responses/03_responses_agent_structured_output.py) — Structured JSON output alignment.
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### Copilot Studio parity
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- [01_basic_copilot_studio_agent.py](copilot_studio/01_basic_copilot_studio_agent.py) — Minimal Copilot Studio agent invocation.
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- [02_copilot_studio_streaming.py](copilot_studio/02_copilot_studio_streaming.py) — Streaming responses from Copilot Studio agents.
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### Orchestrations
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- [sequential.py](orchestrations/sequential.py) — Step-by-step SK Team → AF `SequentialBuilder` migration.
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- [concurrent_basic.py](orchestrations/concurrent_basic.py) — Concurrent orchestration parity.
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- [group_chat.py](orchestrations/group_chat.py) — Group chat coordination with an LLM-backed manager in both SDKs.
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- [handoff.py](orchestrations/handoff.py) - Handoff coordination between agents.
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- [magentic.py](orchestrations/magentic.py) — Magentic Team orchestration vs. AF builder wiring.
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### Processes
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- [fan_out_fan_in_process.py](processes/fan_out_fan_in_process.py) — Fan-out/fan-in comparison between SK Process Framework and AF workflows.
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- [nested_process.py](processes/nested_process.py) — Nested process orchestration vs. AF sub-workflows.
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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.
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## Prerequisites
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- Python 3.10 or later.
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- Access to the necessary model endpoints (Azure OpenAI, OpenAI, Azure AI, Copilot Studio, etc.).
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- Installed SDKs: `semantic-kernel` and the Microsoft Agent Framework (`pip install semantic-kernel agent-framework`), or the repo’s editable packages if you are developing locally.
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- Service credentials exposed through environment variables (for example `OPENAI_API_KEY`, `AZURE_OPENAI_ENDPOINT`, `AZURE_OPENAI_KEY`, or Copilot Studio auth settings).
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## Running Single-Agent Samples
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From the repository root:
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```
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python samples/semantic-kernel-migration/chat_completion/01_basic_chat_completion.py
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```
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Every script accepts no CLI arguments and will first call the SK implementation, followed by the AF version. Adjust the prompt or credentials inside the file as necessary before running.
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## Running Orchestration & Workflow Samples
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Advanced comparisons are split between `samantic-kernel-migration/orchestrations` (Sequential, Concurrent, Magentic) and `samantic-kernel-migration/processes` (fan-out/fan-in, nested). You can run them directly, or isolate dependencies in a throwaway virtual environment:
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```
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cd samples/semantic-kernel-migration
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uv venv --python 3.10 .venv-migration
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source .venv-migration/bin/activate
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uv pip install semantic-kernel agent-framework
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uv run python orchestrations/sequential.py
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uv run python processes/fan_out_fan_in_process.py
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```
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Swap the script path for any other workflow or process sample. Deactivate the sandbox with `deactivate` when you are finished.
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## Tips for Migration
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- Keep the original SK sample open while iterating on the AF equivalent; the code is intentionally formatted so you can copy/paste across SDKs.
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- Threads/conversation state are explicit in AF. When porting SK code that relies on implicit thread reuse, call `agent.get_new_thread()` and pass it into each `run` call.
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- Tools map cleanly: SK `@kernel_function` plugins translate to AF `@tool` callables. Hosted tools (code interpreter, web search, MCP) are available only in AF—introduce them once parity is achieved.
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- For multi-agent orchestration, AF workflows expose checkpoints and resume capabilities that SK Process/Team abstractions do not. Use the workflow samples as a blueprint when modernizing complex agent graphs.
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