mirror of
https://github.com/microsoft/agent-framework.git
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Eduard van Valkenburg
5e056b672e
* Python: Provider-leading client design & OpenAI package extraction Major refactoring of the Python Agent Framework client architecture: - Extract OpenAI clients into new `agent-framework-openai` package - Core package no longer depends on openai, azure-identity, azure-ai-projects - Rename clients for discoverability: OpenAIResponsesClient → OpenAIChatClient, OpenAIChatClient → OpenAIChatCompletionClient - Unify `model_id`/`deployment_name`/`model_deployment_name` → `model` param - New FoundryChatClient for Azure AI Foundry Responses API - New FoundryAgent/FoundryAgentClient for connecting to pre-configured Foundry agents - Remove OpenAIBase/OpenAIConfigMixin from non-deprecated client MRO - Deprecate AzureOpenAI* clients, AzureAIClient, OpenAIAssistantsClient - Reorganize samples: azure_openai+azure_ai+azure_ai_agent → azure/ - ADR-0020: Provider-Leading Client Design Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: missing Agent imports in samples, .model_id → .model in foundry_local sample Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: CI failures — mypy errors, coverage targets, sample imports - azure-ai mypy: add type ignores for TypedDict total=, model arg, forward ref - Coverage: replace core.azure/openai targets with openai package target - project_provider: add type annotation for opts dict Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix: populate openai .pyi stub, fix broken README links, coverage targets Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fixes * updated observabilitty * reset azure init.pyi * fix errors * updated adr number * fix foundry local * fixed not renamed docstrings and comments, and added deprecated markers to old classes * fix tests and pyprojects * fix test vars * updated function tests * update durable * updated test setup for functions * Fix Foundry auth in workflow samples Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Stabilize Python integration workflows Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Update hosting samples for Foundry Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Trigger full CI rerun Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Trigger CI rerun again Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * trigger rerun * trigger rerun * fix for litellm * undo durabletask changes * Move Foundry APIs into foundry namespace Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Fix Foundry pyproject formatting Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Split provider samples by Foundry surface Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * Restore hosting sample requirements Also fix the Foundry Local sample link after the provider sample move. Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * updated tests * udpated foundry integration tests * removed dist from azurefunctions tests * Use separate Foundry clients for concurrent agents Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com> * fix client setup in azfunc and durable * disabled two tests * updated setup for some function and durable tests * improved azure openai setup with new clients * ignore deprecated * fixes * skip 11 * remove openai assistants int tests --------- Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
73 lines
5.1 KiB
Markdown
73 lines
5.1 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 session reuse and streaming prompts.
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### Azure AI agent parity
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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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- Sessions/conversation state are explicit in AF. When porting SK code that relies on implicit session reuse, call `agent.create_session()` 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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