Python: [BREAKING] Python: Provider-leading client design & OpenAI package extraction (#4818)

* 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>
2026-06-16 21:04:09 +08:00 · 2026-03-25 10:56:29 +01:00
parent 4b533608b6
commit 5e056b672e
485 changed files with 9784 additions and 12084 deletions
@@ -3,7 +3,7 @@

 import asyncio

-from agent_framework import Message
+from agent_framework import Agent, Message
 from dotenv import load_dotenv

 """AutoGen RoundRobinGroupChat vs Agent Framework GroupChatBuilder/SequentialBuilder.
@@ -68,17 +68,20 @@ async def run_agent_framework() -> None:
    client = OpenAIChatClient(model_id="gpt-4.1-mini")

    # Create specialized agents
-    researcher = client.as_agent(
+    researcher = Agent(
+        client=client,
        name="researcher",
        instructions="You are a researcher. Provide facts and data about the topic.",
    )

-    writer = client.as_agent(
+    writer = Agent(
+        client=client,
        name="writer",
        instructions="You are a writer. Turn research into engaging content.",
    )

-    editor = client.as_agent(
+    editor = Agent(
+        client=client,
        name="editor",
        instructions="You are an editor. Review and finalize the content.",
    )
@@ -99,6 +102,7 @@ async def run_agent_framework() -> None:
 async def run_agent_framework_with_cycle() -> None:
    """Agent Framework's WorkflowBuilder with cyclic edges and conditional exit."""
    from agent_framework import (
+        Agent,
        AgentExecutorRequest,
        AgentExecutorResponse,
        AgentResponseUpdate,
@@ -111,17 +115,20 @@ async def run_agent_framework_with_cycle() -> None:
    client = OpenAIChatClient(model_id="gpt-4.1-mini")

    # Create specialized agents
-    researcher = client.as_agent(
+    researcher = Agent(
+        client=client,
        name="researcher",
        instructions="You are a researcher. Provide facts and data about the topic.",
    )

-    writer = client.as_agent(
+    writer = Agent(
+        client=client,
        name="writer",
        instructions="You are a writer. Turn research into engaging content.",
    )

-    editor = client.as_agent(
+    editor = Agent(
+        client=client,
        name="editor",
        instructions="You are an editor. Review and finalize the content. End with APPROVED if satisfied.",
    )
@@ -3,7 +3,7 @@

 import asyncio

-from agent_framework import Message
+from agent_framework import Agent, Message
 from dotenv import load_dotenv

 """AutoGen SelectorGroupChat vs Agent Framework GroupChatBuilder.
@@ -71,22 +71,22 @@ async def run_agent_framework() -> None:
    from agent_framework.openai import OpenAIChatClient
    from agent_framework.orchestrations import GroupChatBuilder

-    client = OpenAIChatClient(model_id="gpt-4.1-mini")
+    client = OpenAIChatClient(model="gpt-4.1-mini")

    # Create specialized agents
-    python_expert = client.as_agent(
+    python_expert = Agent(client=client,
        name="python_expert",
        instructions="You are a Python programming expert. Answer Python-related questions.",
        description="Expert in Python programming",
    )

-    javascript_expert = client.as_agent(
+    javascript_expert = Agent(client=client,
        name="javascript_expert",
        instructions="You are a JavaScript programming expert. Answer JavaScript-related questions.",
        description="Expert in JavaScript programming",
    )

-    database_expert = client.as_agent(
+    database_expert = Agent(client=client,
        name="database_expert",
        instructions="You are a database expert. Answer SQL and database-related questions.",
        description="Expert in databases and SQL",
@@ -95,7 +95,7 @@ async def run_agent_framework() -> None:
    workflow = GroupChatBuilder(
        participants=[python_expert, javascript_expert, database_expert],
        max_rounds=1,
-        orchestrator_agent=client.as_agent(
+        orchestrator_agent=Agent(client=client,
            name="selector_manager",
            instructions="Based on the conversation, select the most appropriate expert to respond next.",
        ),
@@ -3,7 +3,7 @@
 import asyncio
 from typing import Any

-from agent_framework import AgentResponseUpdate, WorkflowEvent
+from agent_framework import Agent, AgentResponseUpdate, WorkflowEvent
 from dotenv import load_dotenv

 """AutoGen Swarm pattern vs Agent Framework HandoffBuilder.
@@ -110,10 +110,10 @@ async def run_agent_framework() -> None:
    from agent_framework.openai import OpenAIChatClient
    from agent_framework.orchestrations import HandoffAgentUserRequest, HandoffBuilder

-    client = OpenAIChatClient(model_id="gpt-4.1-mini")
+    client = OpenAIChatClient(model="gpt-4.1-mini")

    # Create triage agent
-    triage_agent = client.as_agent(
+    triage_agent = Agent(client=client,
        name="triage",
        instructions=(
            "You are a triage agent. Analyze the user's request and route to the appropriate specialist:\n"
@@ -124,14 +124,14 @@ async def run_agent_framework() -> None:
    )

    # Create billing specialist
-    billing_agent = client.as_agent(
+    billing_agent = Agent(client=client,
        name="billing_agent",
        instructions="You are a billing specialist. Help with payment and billing questions. Provide clear assistance.",
        description="Handles billing and payment questions",
    )

    # Create technical support specialist
-    tech_support = client.as_agent(
+    tech_support = Agent(client=client,
        name="technical_support",
        instructions="You are technical support. Help with technical issues. Provide clear assistance.",
        description="Handles technical support questions",
@@ -5,6 +5,7 @@ import json
 from typing import cast

 from agent_framework import (
+    Agent,
    AgentResponseUpdate,
    Message,
    WorkflowEvent,
@@ -78,19 +79,22 @@ async def run_agent_framework() -> None:
    client = OpenAIChatClient(model_id="gpt-4.1-mini")

    # Create specialized agents
-    researcher = client.as_agent(
+    researcher = Agent(
+        client=client,
        name="researcher",
        instructions="You are a research analyst. Gather and analyze information.",
        description="Research analyst for data gathering",
    )

-    coder = client.as_agent(
+    coder = Agent(
+        client=client,
        name="coder",
        instructions="You are a programmer. Write code based on requirements.",
        description="Software developer for implementation",
    )

-    reviewer = client.as_agent(
+    reviewer = Agent(
+        client=client,
        name="reviewer",
        instructions="You are a code reviewer. Review code for quality and correctness.",
        description="Code reviewer for quality assurance",
@@ -99,7 +103,8 @@ async def run_agent_framework() -> None:
    # Create Magentic workflow
    workflow = MagenticBuilder(
        participants=[researcher, coder, reviewer],
-        manager_agent=client.as_agent(
+        manager_agent=Agent(
+            client=client,
            name="magentic_manager",
            instructions="You coordinate a team to complete complex tasks efficiently.",
            description="Orchestrator for team coordination",
@@ -1,7 +1,18 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = [
+#     "autogen-agentchat",
+#     "autogen-ext[openai]",
+# ]
+# ///
+# Run with any PEP 723 compatible runner, e.g.:
+#   uv run samples/autogen-migration/single_agent/01_basic_assistant_agent.py
+
 # Copyright (c) Microsoft. All rights reserved.

 import asyncio

+from agent_framework import Agent
 from dotenv import load_dotenv

 """Basic AutoGen AssistantAgent vs Agent Framework Agent.
@@ -39,8 +50,9 @@ async def run_agent_framework() -> None:
    from agent_framework.openai import OpenAIChatClient

    # AF constructs a lightweight Agent backed by OpenAIChatClient
-    client = OpenAIChatClient(model_id="gpt-4.1-mini")
-    agent = client.as_agent(
+    client = OpenAIChatClient(model="gpt-4.1-mini")
+    agent = Agent(
+        client=client,
        name="assistant",
        instructions="You are a helpful assistant. Answer in one sentence.",
    )
@@ -54,11 +54,11 @@ async def run_autogen() -> None:

 async def run_agent_framework() -> None:
    """Agent Framework agent with @tool decorator."""
-    from agent_framework import tool
+    from agent_framework import Agent, tool
    from agent_framework.openai import OpenAIChatClient

    # Define tool with @tool decorator (automatic schema inference)
-    # NOTE: approval_mode="never_require" is for sample brevity. Use "always_require" in production; see samples/02-agents/tools/function_tool_with_approval.py and samples/02-agents/tools/function_tool_with_approval_and_sessions.py.
+    # NOTE: approval_mode="never_require" is for sample brevity.
    @tool(approval_mode="never_require")
    def get_weather(location: str) -> str:
        """Get the weather for a location.
@@ -72,8 +72,8 @@ async def run_agent_framework() -> None:
        return f"The weather in {location} is sunny and 72°F."

    # Create agent with tool
-    client = OpenAIChatClient(model_id="gpt-4.1-mini")
-    agent = client.as_agent(
+    client = OpenAIChatClient(model="gpt-4.1-mini")
+    agent = Agent(client=client,
        name="assistant",
        instructions="You are a helpful assistant. Use available tools to answer questions.",
        tools=[get_weather],
@@ -1,7 +1,18 @@
+# /// script
+# requires-python = ">=3.10"
+# dependencies = [
+#     "autogen-agentchat",
+#     "autogen-ext[openai]",
+# ]
+# ///
+# Run with any PEP 723 compatible runner, e.g.:
+#   uv run samples/autogen-migration/single_agent/03_assistant_agent_thread_and_stream.py
+
 # Copyright (c) Microsoft. All rights reserved.

 import asyncio

+from agent_framework import Agent
 from dotenv import load_dotenv

 """AutoGen vs Agent Framework: Thread management and streaming responses.
@@ -46,8 +57,9 @@ async def run_agent_framework() -> None:
    """Agent Framework agent with explicit session and streaming."""
    from agent_framework.openai import OpenAIChatClient

-    client = OpenAIChatClient(model_id="gpt-4.1-mini")
-    agent = client.as_agent(
+    client = OpenAIChatClient(model="gpt-4.1-mini")
+    agent = Agent(
+        client=client,
        name="assistant",
        instructions="You are a helpful math tutor.",
    )
@@ -55,13 +55,13 @@ async def run_autogen() -> None:

 async def run_agent_framework() -> None:
    """Agent Framework's as_tool() for hierarchical agents with streaming."""
-    from agent_framework import Content
+    from agent_framework import Agent, Content
    from agent_framework.openai import OpenAIChatClient

-    client = OpenAIChatClient(model_id="gpt-4.1-mini")
+    client = OpenAIChatClient(model="gpt-4.1-mini")

    # Create specialized writer agent
-    writer = client.as_agent(
+    writer = Agent(client=client,
        name="writer",
        instructions="You are a creative writer. Write short, engaging content.",
    )
@@ -75,7 +75,7 @@ async def run_agent_framework() -> None:
    )

    # Create coordinator agent with writer tool
-    coordinator = client.as_agent(
+    coordinator = Agent(client=client,
        name="coordinator",
        instructions="You coordinate with specialized agents. Delegate writing tasks to the writer agent.",
        tools=[writer_tool],