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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file with only comment path updates (100 files) - One import-fix diff (workflow_as_agent_human_in_the_loop.py) - One superseded minimal_sample.py Resource files (sample.pdf, countries.json, employees.pdf, weather.json) copied to 02-agents/sample_assets/ and 02-agents/resources/ since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
This commit is contained in:
Eduard van Valkenburg
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# Copyright (c) Microsoft. All rights reserved.
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import asyncio
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import random
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import sys
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from collections.abc import AsyncIterable, Awaitable, Mapping, Sequence
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from typing import Any, ClassVar, Generic
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from agent_framework import (
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BaseChatClient,
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ChatMiddlewareLayer,
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ChatResponse,
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ChatResponseUpdate,
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Content,
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FunctionInvocationLayer,
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Message,
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ResponseStream,
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Role,
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)
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from agent_framework._clients import OptionsCoT
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from agent_framework.observability import ChatTelemetryLayer
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if sys.version_info >= (3, 13):
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pass
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else:
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pass
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if sys.version_info >= (3, 12):
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from typing import override # type: ignore # pragma: no cover
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else:
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from typing_extensions import override # type: ignore[import] # pragma: no cover
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"""
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Custom Chat Client Implementation Example
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This sample demonstrates implementing a custom chat client and optionally composing
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middleware, telemetry, and function invocation layers explicitly.
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"""
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class EchoingChatClient(BaseChatClient[OptionsCoT], Generic[OptionsCoT]):
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"""A custom chat client that echoes messages back with modifications.
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This demonstrates how to implement a custom chat client by extending BaseChatClient
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and implementing the required _inner_get_response() method.
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"""
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OTEL_PROVIDER_NAME: ClassVar[str] = "EchoingChatClient"
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def __init__(self, *, prefix: str = "Echo:", **kwargs: Any) -> None:
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"""Initialize the EchoingChatClient.
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Args:
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prefix: Prefix to add to echoed messages.
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**kwargs: Additional keyword arguments passed to BaseChatClient.
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"""
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super().__init__(**kwargs)
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self.prefix = prefix
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@override
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def _inner_get_response(
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self,
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*,
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messages: Sequence[Message],
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stream: bool = False,
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options: Mapping[str, Any],
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**kwargs: Any,
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) -> Awaitable[ChatResponse] | ResponseStream[ChatResponseUpdate, ChatResponse]:
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"""Echo back the user's message with a prefix."""
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if not messages:
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response_text = "No messages to echo!"
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else:
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# Echo the last user message
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last_user_message = None
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for message in reversed(messages):
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if message.role == Role.USER:
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last_user_message = message
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break
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if last_user_message and last_user_message.text:
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response_text = f"{self.prefix} {last_user_message.text}"
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else:
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response_text = f"{self.prefix} [No text message found]"
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response_message = Message(role=Role.ASSISTANT, contents=[Content.from_text(response_text)])
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response = ChatResponse(
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messages=[response_message],
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model_id="echo-model-v1",
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response_id=f"echo-resp-{random.randint(1000, 9999)}",
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)
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if not stream:
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async def _get_response() -> ChatResponse:
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return response
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return _get_response()
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async def _stream() -> AsyncIterable[ChatResponseUpdate]:
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response_text_local = response_message.text or ""
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for char in response_text_local:
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yield ChatResponseUpdate(
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contents=[Content.from_text(char)],
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role=Role.ASSISTANT,
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response_id=f"echo-stream-resp-{random.randint(1000, 9999)}",
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model_id="echo-model-v1",
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)
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await asyncio.sleep(0.05)
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return ResponseStream(_stream(), finalizer=lambda updates: response)
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class EchoingChatClientWithLayers( # type: ignore[misc,type-var]
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ChatMiddlewareLayer[OptionsCoT],
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ChatTelemetryLayer[OptionsCoT],
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FunctionInvocationLayer[OptionsCoT],
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EchoingChatClient[OptionsCoT],
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Generic[OptionsCoT],
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):
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"""Echoing chat client that explicitly composes middleware, telemetry, and function layers."""
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OTEL_PROVIDER_NAME: ClassVar[str] = "EchoingChatClientWithLayers"
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async def main() -> None:
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"""Demonstrates how to implement and use a custom chat client with Agent."""
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print("=== Custom Chat Client Example ===\n")
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# Create the custom chat client
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print("--- EchoingChatClient Example ---")
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echo_client = EchoingChatClientWithLayers(prefix="🔊 Echo:")
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# Use the chat client directly
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print("Using chat client directly:")
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direct_response = await echo_client.get_response("Hello, custom chat client!")
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print(f"Direct response: {direct_response.messages[0].text}")
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# Create an agent using the custom chat client
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echo_agent = echo_client.as_agent(
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name="EchoAgent",
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instructions="You are a helpful assistant that echoes back what users say.",
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)
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print(f"\nAgent Name: {echo_agent.name}")
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# Test non-streaming with agent
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query = "This is a test message"
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print(f"\nUser: {query}")
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result = await echo_agent.run(query)
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print(f"Agent: {result.messages[0].text}")
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# Test streaming with agent
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query2 = "Stream this message back to me"
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print(f"\nUser: {query2}")
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print("Agent: ", end="", flush=True)
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async for chunk in echo_agent.run(query2, stream=True):
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if chunk.text:
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print(chunk.text, end="", flush=True)
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print()
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# Example: Using with threads and conversation history
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print("\n--- Using Custom Chat Client with Thread ---")
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thread = echo_agent.get_new_thread()
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# Multiple messages in conversation
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messages = [
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"Hello, I'm starting a conversation",
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"How are you doing?",
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"Thanks for chatting!",
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]
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for msg in messages:
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result = await echo_agent.run(msg, thread=thread)
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print(f"User: {msg}")
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print(f"Agent: {result.messages[0].text}\n")
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# Check conversation history
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if thread.message_store:
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thread_messages = await thread.message_store.list_messages()
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print(f"Thread contains {len(thread_messages)} messages")
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else:
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print("Thread has no message store configured")
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if __name__ == "__main__":
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asyncio.run(main())
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